by Jeffrey A. Glassman, PhD

Revised 7/10/07



Classical and advanced signal analysis techniques applied to the climate data of global temperature, solar wind, and El Niño/Southern Oscillation (ENSO) reveal new events and correlations in graphical form. The results include:

1.         Major state changes appear in the global temperature record around 1934.4 and 1979.5.

2.         A major state change occurred in the solar wind index around 1937 to 1939, and a secondary state change occurred in the 1970s.

3.         Major state changes occurred in the Southern Oscillation Index beginning about 1919.3 and 1979.4. A large state change occurred during the brief period of 1940.2 to 1942.0.

4.         The state changes are real in the records, but may be due either to data acquisition artifacts or to real physical phenomena.

5.         The Southern Oscillation Index has a weak cyclic behavior with a period of 3.38 years.

6.         Global temperature lags the Southern Oscillation Index by about 5 months.

7.         The global temperature record appears to suffer from excessive processing.

8.         High correlations found by other investigators may be the result of prior data smoothing.

9.         The low level of correlation between temperature and other parameters may be due to excessive noise, equivalently due to low signal to noise ratio. More importantly, it may be due to the closed loop gain of a mechanism in the climate, unknown to the Consensus on Climate, that regulates global surface temperature.

10.       Global temperature is weakly correlated with ENSO. The SOI could account for 4.6% of the measured variation in global temperature.

11.       Global temperature and the solar wind index are correlated. The solar wind index may contribute as much as 8.9% of the processed global temperature variations.

12.       Global temperature lags the solar wind index by about two to five years.

13.       ENSO and the Southern Oscillation affect the global surface temperature. The reverse, that temperature might affect either, is not true.

ENSO may, as the Consensus says, devastate, but it has only half the capacity of the solar wind to warm the planet. By omitting the solar wind, the Consensus underestimates the natural causes of global warming, simultaneously overestimating the anthropogenic sources by the equivalent of two ENSOs, assigning the error to carbon dioxide emissions.

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Global surface temperature is the essence of global climate, and by definition the only sensible measure of Global Warming. Global temperature is influenced in part by the solar wind, according to a chain of connections admitted by the IPCC in its Third Assessment Report (TAR). The Consensus on Climate, which finds its voice in the IPCC reports, recognizes (1) a dependence of global temperature on clouds, (2) a positive correlation between clouds and galactic cosmic rays, and (3) the physics of cosmic ray flux modulation by the solar wind. Nonetheless, the Consensus refuses to adopt this three part model into its climate models for lack of evidence. Climate Change 2001, ¶, pp. 384-385. More importantly, the TAR never uses the record of solar wind measurements, a record longer than the record of temperature from thermometers.

According to the Consensus, Earth’s surface temperature is strongly affected by the El Niño/Southern Oscillation (ENSO), so named because of the strong indication of El Niño events in the Southern Oscillation Index (SOI), a continuous variable. The Consensus is convinced that ENSO causes human suffering, and that on some time scales it is the cause of the strongest natural fluctuations in the climate. Climate Change 2001, Box 4, p. 52. However, the Global Circulation Models, formerly known as Global Climate Models but more aptly named Global Catastrophe Models, (GCMs), have yet to demonstrate sufficient accuracy in replicating ENSO to even answer the pointed question posed by the Consensus: whether anthropogenic greenhouse gases cause a positive feedback by precipitating warming El Niño events. Climate Change 2001, p. 151; ¶7.6.5, pp. 453-455. The SOI sample record is substantial, but the TAR uses it merely to remark on its variability and to label the El Niño events for qualitative discussion.

These issues are well-suited to ordinary signal analysis of the three time series because the method can recognize signals at the threshold of detectability. It can, among other things, locate events in the record, and measure the correlation and lead or lag between temperature and the other parameters, all key to model building. That analysis, not reported in the IPCC and apparently never addressed by the Consensus, is initiated here for what it reveals, and as background for upcoming climate studies.


Records are available on-line of monthly measurements of the Temperature anomaly, the Southern Oscillation Index, and Solar Wind Index.

Temperature anomaly

The Temperature anomaly is the subject of several reductions by the IPCC (e.g., Fourth Assessment Report, Summary for Policy Makers, p. 14, Fig. 5; Climate Change 2001, Fig. 2.7c, p. 114. See also http://svs.gsfc.nasa.gov/vis/a000000/a001000/a001008/a001008_pre.jpg), including the infamous reduction for the Northern Hemisphere (Climate Change 2001, Fig. 2.20, p. 134) known derisively outside the IPCC reports as the Hockey Stick reconstruction. The phrase solar wind appears just once in the TAR, and that is in the title of a reference about cloud creation. However, the TAR uses not a single datum from the solar wind database. The Fourth Assessment Report also mentions the solar wind, but again just once, and that is to say that the effects of solar wind fluctuations are ambiguous. Id., ¶, p. 192.

Global temperature data are available from January, 1880. http://data.giss.nasa.gov/gistemp/tabledata/GLB.Ts.txt. (see also ftp://ftp.ncdc.noaa.gov/pub/data/anomalies/monthly.land_and_ocean.90S.90N.df_1901-2000mean.dat.) The global temperature as reported by the IPCC extracted from Figure 2.7(c) is shown in Figure 1. The report states without elaboration that the data are an “optimum average”.

Figure 2.7: …[C]ombined land-surface air and sea surface temperatures (ºC), 1861 to 2000, relative to 1961 to 1990, for … (c) Globe. …[S]hown are the unsmoothed optimum averages – red bars… . Climate Change 2001, p. 114. [Click figures to enlarge.]

Figure 1

IPCC Data Distribution Center

Although not stated in the Third or Fourth Assessment Report, the IPCC maintains a separate Data Distribution Center. It includes information on the Temperature anomaly but not on the solar wind.

The Temperature anomaly is an IPCC-calculated global figure based on a grid of temperature differences spanning the globe and recorded by the Climate Research Unit (CRU), School of Environmental Sciences, University of East Anglia (UEA). The CRU provides additional information on-line about the Temperature anomaly and its treatment by the IPCC, however its key records exceed the number of rows permitted in Microsoft Excel.

The CRU data are the differences between a calculated mean temperature for each grid section and its average from 1961 to 1990. The IPCC interpolates for missing data points, and its final temperature anomaly is a weighted average over the globe and over an unspecified time interval. In the processing, adjustments are included for station altitude, and to convert sea surface temperature to local atmospheric temperature.

In spite of these complications, the National Oceanic and Atmospheric Administration (NOAA) says,

By adding the long-term monthly mean temperature for the Earth to each anomaly value, one can create a time series that approximates the temperature of the Earth and how it has been changing through time. National Climatic Data Center, Global Surface Temperature Anomalies, 2/6/06. http://www.ncdc.noaa.gov/oa/climate/research/anomalies/anomalies.html

According to the Consensus, the long-term mean surface temperature is 14ºC. Climate Change 2001, p. 89.

Southern Oscillation Index

The available Southern Oscillation Index (SOI) data, designated “aa”, begin January, 1876. ftp://ftp.bom.gov.au/anon/home/ncc/www/sco/soi/soiplaintext.html. {Begin rev. 7/10/07} The Third Assessment Report charts them in Figure 7.9 after subtracting the average for the first 100 years. A copy is Figure 2, below. The offset by the average has little effect; it is trivial because by design, the Index is nominally zero. {End rev. 7/10/07}

Figure 7.9: Darwin Southern Oscillation Index (SOI) represented as monthly surface pressure anomalies in hPa. Data cover the period from January 1882 to December 1998. Base period climatology computed from the period January 1882 to December 1981. The step function fit is illustrative only, to highlight a possible shift around 1976 to 1977. Climate Change 2001, p. 455.

Figure 2

Solar Wind Index

{Begin rev. 7/10/07} Solar Wind Index (“aa”) data start January, 1868. ftp.ngdc.noaa.gov/STP/SOLAR_DATA/RELATED_INDICES/AA_INDEX/ [rev. 7/10/07].{End rev. 7/10/07} The Third Assessment Report refers to Tinsley, B.A., 1996, Correlations of atmospheric dynamics with solar wind-induced changes of air-earth current density into cloud top, J. Geophys. Res., 101, 29701-29714 ($9) in its discussion of a correlation between galactic cosmic rays and clouds. Climate Change 2001, ¶, pp. 384-385. The Consensus summaries a mechanism proposed by Tinsley to link cosmic rays and clouds, but without mentioning the solar wind at that point or anywhere else in the Report.


Referring to these three records as raw data, the objective now is to mine them for correlations and abrupt changes in statistics. These changes delineate changes in state of the data. They might signify data acquisition artifacts, or actual climate events or patterns. The techniques rely on numerical analysis, witnessed by graphs, and employ ordinary techniques used in engineering signal analysis.

Data Reduction.

Data reduction may employ advanced techniques, but if any part of those techniques is kept hidden, the method is secret and beyond mere esotericism. An example is the application of Principle Component analysis where the principle components are not fully disclosed. Principle Component analysis is esoteric, not wrong. However discarding components or keeping the selection method secret violates scientific principles, and is sufficient to invalidate the results.

The objective of data reduction is to reveal features in the underlying physical processes, uncovering any artifacts caused by faulty data acquisition along the way. It is to unveil real events and patterns with which to perfect models, and from those models to make predictions.

Data reduction used to support a subjective conclusion is for the movies. Data reduction to make the data better looking, or trendy, or to create correlations in support of conjectures is for the advertising business.

In science, where a method fails to produce a useful result for a model, the application fails. The method is not discarded merely for being instantaneously inapplicable.

On the other hand, where a method does produce a useful result, it is successful even if the method may be deemed heuristic for lack of theoretical exposition. Here applied is a technique that reveals profound changes in the statistics of the data, changes which could be artifacts of the record preparation, but which are reproducible and which could not have been produced by the data reduction technique.

Temperature and the Solar Wind.

The signal analysis begins with a co-plot of the Solar Wind Index, aa, and the so-called global “Temperature anomaly”. Plotting both records along the same time scale creates a parametric view of the data, with time the parameter. This is Figure 3.

Figure 3

In this chart, the solar wind rises slowly over its history, marked by decadal clumping. Temperature has a lazy-w shape. The solar wind starts relatively well organized, and later diffuses. The temperature history starts disorganized and later coalesces. Stated another way, the variability of the Solar Wind Index increases over its record, and the variability of the Temperature anomaly decreases. No rationale is known for this organizational behavior, nor for its complementary appearance.

Solar Wind Trend

Filtering helps measure the rise in the solar wind record. Figure 4 shows four overlaid, low pass filter reductions, with time constants of one, two, three and five decades. At the shortest time constant, the solar wind reveals a step-ramp-step shape, with breaks around 1920 and 1960.

Figure 4

The long term, steady rise in both the Solar Wind Index and the Temperature anomaly suggest a correlation between the two traces.

Temperature & Solar Wind Events

Independent, best fit, three-step fits to Temperature and the Solar Wind, beginning in common from 1880, reveal no particular relationship. Figure 5.

Figure 5

In the legend, the numbers in parenthesis are one standard deviation error between the best fit and the data over the full record, expressed in the units of the ordinate. The digit preceding the standard deviation is the number of segments in the mathematical model. Best fit modeling characterizes the data objectively. The dates and step magnitudes are determined mathematically, once the investigator selects the number of segments. The fits are arithmetically best in that they minimize the sum squared error for the model type, and as is evident, not necessarily the best shape subjectively. For example, Temperature appears as though it would be better modeled with a step-step-ramp shape.

Cumulative Signal Analysis.

Numerical analysis of cumulative data reveals characteristics of the physics hidden by noise in the raw data. An illustration applied to the Temperature anomaly and the Solar Wind Index is in Figure 6.

Figure 6

The segmented, best fit curves comprise straight lines between the end points and the labeled graph markers on or near the cumulative curve. The best fit endpoints in this analysis lie on the cumulative data, and were not subject to optimization. The slope of each segment is the height of step in the corresponding best fit to the raw data. The step height approximates the mean value of the raw data in the segment interval span. The curves have the smallest Root Mean Square (RMS) error between the raw data, not the cumulative data, and the stairstep fits, as finally determined by the Excel 2004 solver routine, for the operator-selected number of segments.

The Temperature record contains a state change beginning at about 1934.4 and 1979.5, with second order state changes at about 1918.2, 1946.5, and 1997.4. Any of these may be data acquisition artifacts, as when instrumentation technology, standards, or the set of measuring stations changed. For example, new standards for thermometer measurements became effective circa 1920, and satellite measurements were added in the ’70s. No discrete, climate event appears in these data from 1880 to the present which suggests an anthropogenic source or event.

Masking Effects of Scaling

Cumulative analysis removes noise from the measurements, much as do its cousin, the running-average, pass band filters, and other classes of filters. Noise is the variation in the data from any source other than the parameter under examination. The cumulative technique has the advantage of lack of subjectivity, the bane of science. The analysis is immediately applicable to the Temperature anomaly because the original investigators reduced that record to approximately zero mean. If a constant 14ºC had not been subtracted from the Temperature, its cumulative graph would be the ramp in Figure 7.

Figure 7

The plot in Figure 7 comprises individual, unconnected dots for each data point. The state change information is still in the data, but it is no longer resolvable to the unaided eye. The state structure might be visible with a magnifying glass on a graph rendered at upwards of 600 dots per inch. Greater resolution would be required had the temperature been recorded in total degrees Kelvin. This demonstrates the masking effects of merely an unfortunate choice of units. The technique of offsetting a bias or mean is common in signal analysis, and, in some circumstances, necessary. It is the creation of an arbitrary zero point, as commonplace as using the Fahrenheit and centigrade scales. It causes no loss of information so long as the offset is stated. That is, the raw record can be restored exactly by calculating sample by sample differences in a cumulative history, and restoring the offset.

The Solar Wind Index retains a large average value. So in the cumulative, its signal changes ride masked atop a strong ramp. Figure 6. Another operation is necessary to prepare this raw record for cumulative analysis.

Raw Solar Wind vs. Cumulative Temperature anomaly

A comparison of Temperature with its seven-segment fit to the raw Solar Wind Index with its three-step fit is shown in Figure 8. The coincidental break around 1934 is suggestive of an actual climatic event. This coincidence is a form of correlation, and like correlation does not prove a cause and effect, but suggests where a causative event might lie. On the other hand, its absence is convincing evidence against a cause and effect.

Figure 8

The step models fitted to the Solar Wind Index and Temperature in Figures 5 and 8 could be fanciful. The fitting of a step function yields steps even if the record is a pure ramp or other kind of smooth curve. The fact that the steps are unequal may be due to noise, or to an acceleration in the record. No such choice occurs with the cumulative technique, next applied to the Solar Wind Index by offsetting the raw data by the full record mean.

Solar Wind Events

The Solar Wind Index contains changes, including one profound change, previously unknown at least to the Consensus on climate. A primary state change occurred around 1937-1939, and a secondary state change around 1980. These are revealed in Figures 9 through 12 with progressively increasing numbers of segments, 3, 4, 7, and 9, respectively. Since the RMS error to the raw data is already on these charts, the standard deviations referenced to the cumulative data are the RMS error between the segmented ramps and the cumulative curves.

Figure 9

Figure 10

Figure 11

Figure 12

Cumulative Solar Wind vs. Cumulative Temperature anomaly

The next three charts show a cumulative analysis of the offset Solar Wind Index parametrically with that of the Temperature anomaly. The best fits are independent, and for 3, 4, and 7 segments, with the RMS errors referenced to the raw data. Increasing the number of segments has a relatively minor effect on the accuracy (mathematically the accuracy cannot decrease), and quickly produces diminishing returns.

Figure 13

Figure 14

Figure 15

A reasonable conclusion is that the evident Solar Wind events did not precipitate the evident global temperature events.

Autocorrelation Functions of Solar Wind & Temperature anomaly

Next in Figure 16 are the autocorrelation functions for the Solar Wind Index and Global Temperature.

Figure 16

The well-known 11 year solar cycle appears in the Solar Wind Index, but not in the Temperature record. (Compare with “The surface temperature response to the 11-year cycle is found to be small (citations).” Climate Change 2001, p. 708.) The breadth and shape of the Temperature autocorrelation function suggests weighted filtering over a window of about 20 years. Such filtering can distort signal analysis, requiring special considerations. All the correlation function calculations here employ the tape-loop algorithm.

While global temperature is correlated with the solar wind, the cyclic behavior of the solar wind is not evident in the temperature. One reason might be heavy temporal smoothing of the Temperature anomaly record.

Cross Correlation of Solar Wind & Temperature anomaly

Next is the cross correlation function between Temperature and Solar Wind Index. Figure 17.

Figure 17

This curve is not sharp enough to yield a conclusive lead/lag relationship, perhaps again because of temperature processing. Physically, global temperature should not lead the Solar Wind Index. The data suggest that the Temperature lags the Solar Wind Index by about two to five years.

Temperature anomaly vs. Solar Wind Scatter Diagram

The most significant relationship between Temperature and the Solar Wind appears in the cross-plot scatter diagram with the linear fits. These are in Figure 18 with zero time offset between the traces.

Figure 18

The pair of lines are the result of simply changing which variable is assigned as the dependent variable, and it illustrates the centroid of the scatter, and the correlation between the variables. The legend includes the slope of each straight line fit, where the product of the slopes is the coefficient of determination, r2, the square of the correlation coefficient, r. The smaller the acute angle between the lines, the greater the correlation, and the lines cross at the means of the two variables. (If the lines are perpendicular, the traces are called orthogonal. Only if the lines are perpendicular and cross at (0,0), are they strictly called uncorrelated.) The line T(aa) is bold to emphasize the feasibility of temperature depending, in part, on the Solar Wind, while the reverse, aa(T), is not possible.

In signal analysis terms, the coefficient of determination is a measure of the mutual power between the normalized variables. In statistical terms, the coefficient represents the variability in a given observation due to an explanatory variable. The solar wind could account for 8.9% of global temperature in a linear regression.

On the Low Coefficient of Determination, r2.

Another investigator came to quite different conclusions about the relationship between the solar wind and global temperature. This investigator, obviously outside the Consensus (the Consensus did not analyze the solar wind), wrote:

Abstract. Near-Earth variations in the solar wind, measured by the geomagnetic aa index since 1868, are closely correlated with global temperature (r = 0.96; P < 10-7). Geomagnetic activity leads temperature by 4 to 8 years. Allowing for this temperature lag, an outstanding aa peak around 1990 could explain the high global temperature in 1998. After 1990 the geomagnetic aa data show a steep decline comparable to the decrease between 1955 and 1967, followed by falling temperatures from 1961 through 1973 in spite of growing anthropogenic CO2 emissions. This points to decreasing global temperature during the next 10 years. Landscheidt, T., Solar wind near earth: indicator of variations in global temperature, Proceedings of 1st Solar & Space Weather Euro Conference, 9/29/00, p. 1. http://www.mitosyfraudes.org/Calen/SolarWind.html.

Smoothed yearly aa index [ordinate]. Smoothed yearly Northern Hemisphere temperature anomalies [abscissa]. Figure 1. Scatter plot of yearly means of the geomagnetic aa index and Northern Hemisphere land air and sea surface temperature anomalies 1868 -1998. The aa data are shifted to offset a 6-year lag of temperature. The slope of the regression line and the aggregation of the slightly smoothed data around the straight line fit indicate a close correlation (r = 0.75) which is highly significant ( P < 10-7). Id., p. 2.

A scatter plot of the raw yearly data shows a promising positive correlation between aa and temperature (r = 0.48). Id., p. 3. The data were subjected to three-point smoothing. The least-squares linear fit line indicates a strong correlation ( r = 0.75) which explains 56% of the variance. This correlation is highly significant. After the shift, the record of yearly means is reduced from 131 to 125 data points as the data lost by shifting cannot be replaced. [¶] Three-point smoothing, applied once, reduces the number of independent data to 42. Id., p. 3.

Regardless of statistical rationale, the yearly averaging at the outset produces additional correlation out of whole cloth, exacerbated by the additional three-point smoothing. Amplified correlation attained by smoothing is a mathematical recreation, but is less likely to lead to a physical model with predictive power than working from raw data.


Still another investigator on a related subject followed a similar course, writing

A linear fit of daily solar wind parameters todaily sunspot numbers does not lead to very useful results. The residual scatter is simply too high. If, however, the plasma- and sunspot data are smoothed beforehand by an averaging procedure, then structures show up which are persistent in each of the last two sunspot cycles. This averaging procedure can either be accomplished by running means over, say, 3 years or by the lower terms of a Fourier analysis. Both versions lead to the same results. Köhnlein, W. Cross-correlation of solar wind parameters with sunspots (‘long-term variations’) at 1 AU during cycles 21 and 22, Astrophysics and Space Science, v. 245: 81-88. 11/13/96. p. 83. www.springerlink.com/index/N675G9N846K16722.pdf

Indeed, it is the so-called scatter (noise) that causes decorrelation. Smoothing removes noise, and thereby increases correlation mathematically, but it is no part of the underlying physics. Alternatively stated, smoothing is a regression process that progressively reduces data toward a curve. Two data streams similarly filtered appear correlated. Two straight lines are perfectly correlated, even though the sources were independent.

A strong r-squared, that is, one near unity, is excellent support for a cause and effect model between the dependent variable and the predictor, or explanatory, variable. Conversely, a small value may be due to noise alone, indicating that the independent variable has little predictive power, if any. A weak value might be a masking by noise. It can be an indication of a poor signal-to-noise ratio, a common challenge in communications, astronomy, and climatology. The noise can be an additive interference, contributions from multiple sources, or limitations in the instrumentation and data reduction. An example of a noisy source is the algorithm to reckon a global temperature from widely scattered measurements, over land and sea, and complicated by weather phenomena, altitude, seasonal and diurnal effects, measurement complexities, estimations and arbitrary weightings.

Open Loop Inferences from Closed Loop Measurements

Yet another cause of poor correlation, one not recognized by the Consensus, is the phenomenon of closed loop behavior. During the time that a separate phenomenon regulates the dependent variable, the closed loop response to a predictor variable can be sharply attenuated. The response is reduced by the closed loop gain. Earth’s global temperature is likely just such a variable. The mean temperature around 14ºC is not just some accidental, instantaneous value as the climate slowly wanders between the temperature of Venus and that of Neptune.

Current Global Catastrophe Models force greenhouse gas accumulation to drive the climate to end life-as-we-know-it – except for the dominant greenhouse gas, water vapor. And except for clouds, which have yet to be modeled successfully. And except for albedo, which the Consensus treats as a constant known to one significant figure.

Why Is Earth’s Climate so Stable?

The notion of a Delicate Blue Planet is romantic and juvenile. The idea of a tipping point is a manifestation of paranoia if believed, or mischief if not. Round boulders do not perch on the sides of hills, and cones are not found standing on their tips. Minute disturbances quickly produce a new, quasi-stable state. Global Climate Models are not designed with any stable state. They are as chaotic as the weather. They tip over in a random direction due to one disturbance or another, hence Global Catastrophe Models. At the start of a run, the GCM stands on its tip. The Consensus computes the average cause and effect from runs with a number of these unstable Global Conical Models. See especially Climate Change 2001, Chapter 8, Model Evaluation, pp. 471-512. Catastrophe is certain. The only questions by this paradigm is how fast, how far, which direction, and from which causes.

A rational approach to Earth’s climate begins with the observation that it is in a conditionally stable state, and the scientific challenge is first to model the variables that regulate that state. The global temperature does not move much with changes in the solar wind or ENSO. In part, that is because the temperature is regulated, and measurements can only be made in closed loop.

The next task for climatology is to determine the margin for closed loop control. The atmosphere has lots of room for more water vapor, more clouds, and a greater albedo, or the reverse, thanks to the immense reservoir of liquid water and its heat capacity.

Still, comparing cumulative temperature to the raw solar wind index as done for Figure 8 but with four segments for each trace instead of three, results in a weak and somewhat subjective support for a model for temperature dependence on the solar wind. It is shown in Figure 19.

Figure 19

The correlation in Figure 18 supports a dependence of global temperature on solar wind, and is an important conclusion of this signal analysis. Figure 19 suggests the dependence does not strongly arise from a state change in the solar wind. It shows the effects of constraining the breaks in the temperature model to coincide with those in the solar wind. The constraint increases the standard deviation of the error by more than 50% (4.8 to 7.5). Experimentation by lagging the temperature breaks might produce a better fit.

Regardless, the correlation need not be strong because the solar wind is not a direct source of warming. Instead the theory of cloud formation makes the solar wind a gate to admit greater solar radiation through reduction in cloud cover and hence reduction in Earth’s albedo.

Temperature and ENSO.

Third for signal analysis is the Southern Oscillation Index (SOI), a strong, climate measure over the South Pacific, well‑established as an indicator of Los Niños (the harmful El Niño and his amiable sister, La Niña) events. Sir Gilbert Walker, the discoverer, apparently was responsible for setting the Index to be neutral at zero, and negative toward an El Niño event. A sustained, strong excursion in negative or positive territory of the SOI invariably indicates such events, so climatologists give the phenomenon the name ENSO for El Niño/Southern Oscillation. See Figure 2, above.

ENSO Events

Raw SOI data are featureless compared to its colorful behavior in the cumulative. The comparison is shown in Figures 20 and 21 along with three- and five-piece linear fits, respectively. As before, the standard deviations given are for the respective fits.

Figure 20

Figure 21

The cumulative curves are surprising. Nothing in the cumulative signal analysis could have caused these statistical changes. The analysis proceeds mechanically without regard to the time coordinate.

When the Consensus analyzed the variability of ENSO, it divided the instrument record into four main epochs: the first 40 to 50 years, the period of 1920 to 1960, an intervening period, and the last 40 to 50 years, with special remarks for the period of low SOI from 1990 to 1995. Climate Change 2001, p. 151. The data are more precisely characterized by three first order epochs, separated at 1916 and 1977, with a brief, strong retrace in the middle epoch between 1940 and 1942.

ENSO vs. Temperature anomaly Events

Parametric comparisons of ENSO and the Temperature anomaly are in Figures 22 and 23, the cumulative first, yielding the dates demarking the first order events, and second in raw data form, providing the best fits.

Figure 22

Figure 23

At the opening of the record in 1880, SOI is slightly negative, during which time the climate is dominantly below average 0.3 ºC. This lasts until 1918 when ENSO enters a 60 year cooling state, interrupted for just two years beginning in 1940 by a sharp warming signal. Meanwhile, global temperature is within ± 0.1ºC of its long term average. In the middle of 1977, ENSO turned sharply toward El Niño by 4.2 units. During this time until the present, global temperature accelerated an average of over 0.4 ºC.

ENSO Effects

The Consensus claims that ENSO has global implications, and that its contribution to global temperature is probable.

Warm episodes of the El Niño-Southern Oscillation (ENSO) phenomenon (which consistently affects regional variations of precipitation and temperature over much of the tropics, sub-tropics and some mid-latitude areas) have been more frequent, persistent and intense since the mid-1970s, compared with the previous 100 years. Climate Change 2001, Summary for Policy Makers, p. 5.

Warm phase ENSO episodes have been relatively more frequent, persistent, or intense than the opposite cold phase during this period. [¶] This recent behavior of ENSO is related to variations in precipitation and temperature over much of the global tropics and subtropics and some mid-latitude areas. The overall effect is likely to have made a small contribution to the increase in global surface temperature during the last few decades. Climate Change 2001, p. 103.

Thus, cooler nutrient-rich waters upwell from below along the equator and western coasts of the Americas, favouring development of phytoplankton, zooplankton, and hence fish. Climate Change 2001, Technical Summary of the Working Group I Report, p. 52.

By cumulative analysis, the change attributed to the “mid-1970s” can be objectively set to the period of 1977.5 to 1979.4. The quantification of the ENSO signal to Los Niños events alone by the Consensus obscures indications of major shifts and trends in Pacific circulations.

In the upwelling discussion, the Technical Summary omits the coincident CO2 increases observed by Keeling and Revelle:

During “normal” years the partial pressure of carbon dioxide in surface ocean waters near the equator in the Eastern Tropical Pacific is 60 to 80 parts per million higher than in the atmosphere, and there is a flux of about 0.6 gigatons of carbon from the sea to the air. During these years the Southern Oscillation Index is positive, that is, the air pressure off the coast of South America is higher than in the far western Pacific. The excess CO2 is carried to the surface by water upwelling from depths of between 50 and 150 meters. These upwelling waters are also rich in plant nutrients, resulting in intense biological production and the settling out from the surface layers into deep waters of particulate organic matter containing nearly 1 gigaton of carbon.

During “El Nino” years, when the Southern Oscillation Index is negative, upwelling and biological productivity virtually cease, the surface waters are depleted in nutrients, and the carbon dioxide partial pressure in the sea is about the same as in the atmosphere. Consequently there is no appreciable flux of CO2 from tropical waters into the air. Bold added, Keeling, C.D. and R. Revelle, Effects of El Nino/Southern Oscillation on the Atmospheric Content of Carbon Dioxide, Meteoritics, Vol. 20, No.2, Part 2, June 30, 1985. P. 437.

These El Niño factors are discussed in the main body of the TAR, but in the context of “CO2 variability” and a “reduced upwelling of CO2-rich waters”. Climate Change 2001 in ¶3.5.2, pp. 208-209. Regardless, the Consensus concludes with a contrary observation:

In any case, the slowdown (of the early 1990s) proved to be temporary, and the El Niño of 1998 was marked by the highest rate of CO2 increase on record, 6.0 PgC/yr. Id., p. 210.

Signal analysis supports a different view of the relationship between ENSO and global temperature.

ENSO & Temperature anomaly Relationship

First is the autocorrelation function of the Southern Oscillation Index. Figure 24.

Figure 24

This figure shows that the well-known cyclic behavior of ENSO has a period of 3.38 years (“preferred period of about three to six years”, Climate Change 2001>, Technical Summary, p. 52), and again no evidence of the solar 11-year cycle.

Next is the cross correlation function between Temperature and the negative of the Southern Oscillation Index. Figure 25.

Figure 25

Because a negative going SOI is a warming trend, the cross-correlation calculation includes a sign change to preserve the usual orientation of the function. A well-defined peak in correlation of 0.46 occurs at a five month lag in the temperature record.

The TAR says,

Whether global warming is influencing El Niño… is a key question, especially as El Niño affects global temperature itself. Citations omitted, Climate Change 2001, p. 151.

The five month lag in temperature suggests the answer is no. Surface temperature is a weak, lagging indicator of ENSO, not a predictor.

Next is the scatter diagram of Temperature lagged by five months and the Southern Oscillation Index for the period of 1880 to 2007. Figure 26.

Figure 26

The chart shows the small but significant relationship that global temperature tends to increase with decreasing SOI. In a linear regression, the SOI could account for 4.6% of the variability (power) in the temperature anomaly.

The Measured Correlations Are Not Likely Due to Noise

Finally as a demonstration and validation of the conclusions, examine the correlation between the Solar Wind Index and the Southern Oscillation Index in a scatter diagram. The two should be orthogonal (r2=0). As shown in Figure 27, r2 = 0.0015.

Figure 27

An elementary simulation shows the probability of r2 being at least this large due to noise alone is a weak but not improbable 10%. Accepting the hypothesis that the traces are orthogonal is bolstered by the facts that r-squared for temperature and solar wind is 60 times larger, and for temperature and the southern oscillation it is 31 times larger.

These results support a model in which global temperature does not affect ENSO. Because the solar wind affects global temperature, if the temperature in turn influenced ENSO, the solar wind and ENSO would be correlated. They are not measurably correlated. This conclusion is supported by the fact that temperature lags ENSO.


According to the Consensus, “ENSO … play[s] a fundamental role in global climate” (Climate Change 2001, Technical Summary, p. 51) The Consensus on Climate said of its destructive power,

Changes associated with ENSO produce large variations in weather and climate around the world from year to year. These often have a profound impact on humanity and society because of associated droughts, floods, heat waves and other changes that can severely disrupt agriculture, fisheries, the environment, health, energy demand, air quality and also change the risks of fire. ENSO also plays a prominent role in modulating exchanges of CO2 with the atmosphere. The normal upwelling of cold nutrient-rich and CO2-rich waters in the tropical Pacific is suppressed during El Niño. Id., p. 52.

although the ENSO correlation with carbon dioxide proved fleeting:

In any case, the slowdown (of the early 1990s) proved to be temporary, and the El Niño of 1998 was marked by the highest rate of CO2 increase on record, 6.0 PgC/yr. Climate Change 2001, p. 210.

The Consensus accounts for the various natural sources for climate variability, and the remainder it must attribute to man:

Any human-induced changes in climate will be embedded in a background of natural climatic variations that occur on a whole range of time- and space-scales. Climate variability can occur as a result of natural changes in the forcing of the climate system, for example variations in the strength of the incoming solar radiation and changes in the concentrations of aerosols arising from volcanic eruptions. Natural climate variations can also occur in the absence of a change in external forcing, as a result of complex interactions between components of the climate system, such as the coupling between the atmosphere and ocean. The El Niño-Southern Oscillation (ENSO) phenomenon is an example of such natural “internal” variability on interannual time-scales. To distinguish anthropogenic climate changes from natural variations, it is necessary to identify the anthropogenic “signal” against the background “noise” of natural climate variability. Climate Change 2001, Technical Summary, p. 25.

In this accounting, the Consensus places ENSO third on its list after solar radiation and volcanoes. It excluded the solar wind, arguing

We conclude that mechanisms for the amplification of solar forcing are not well established. … At present there is insufficient evidence to confirm that cloud cover responds to solar variability.Climate Change 2001, ¶ Cosmic Rays and Clouds, p. 385

The evidence has been hidden in the climate records for decades. It was not just that the solar activity was linked to cloud cover, but that it was linked to global surface temperature. The solar wind could account for 8.9% of the variation in the Temperature anomaly, 1.93 times the power of ENSO, which accounts for 4.6% of the surface temperature.

Climate signal analysis establishes the following:

1.         Major state changes appear in the global temperature record around 1934.4 and 1979.5.

2.         A major state change occurred in the solar wind index around 1937 to 1939, and a secondary state change occurred in the 1970s.

3.         Major state changes occurred in the Southern Oscillation Index beginning about 1919.3 and 1979.4. A large state change occurred during the brief period of 1940.2 to 1942.0.

4.         The state changes are real in the records, but may be due either to data acquisition artifacts or to real physical phenomena.

5.         The Southern Oscillation Index has a weak cyclic behavior with a period of 3.38 years.

6.         Global temperature lags the Southern Oscillation Index by about 5 months.

7.         The global temperature record appears to suffer from excessive processing.

8.         High correlations found by other investigators may be the result of prior data smoothing.

9.         The low level of correlation between temperature and other parameters may be due to excessive noise, equivalently due to low signal to noise ratio. More importantly, it may be due to the closed loop gain of a mechanism in the climate, unknown to the Consensus, that regulates global surface temperature.

10.       Global temperature is weakly correlated with ENSO. The SOI could account for 4.6% of the measured variation in global temperature.

11.       Global temperature and the solar wind index are correlated. The solar wind index may contribute as much as 8.9% of the processed global temperature variations.

12.       Global temperature lags the solar wind index by about two to five years.

13.       ENSO and the Southern Oscillation affect the global surface temperature. The reverse, that temperature might affect either, is not true.

ENSO may devastate, but it has only half the capacity of the solar wind to warm the planet. By omitting the solar wind, the Consensus underestimates the natural causes of global warming, simultaneously overestimating the anthropogenic sources by the equivalent of two ENSOs, assigning the error to carbon dioxide emissions.


IPCC, Fourth Assessment Report (4AR), 2007

IPCC, Third Assessment Report (TAR), Climate Change 2001

Keeling, C.D. and R. Revelle, Effects of El Nino/Southern Oscillation on the Atmospheric Content of Carbon Dioxide, Meteoritics, Vol. 20, No.2, Part 2, June 30, 1985

Köhnlein, W. Cross-correlation of solar wind parameters with sunspots ('long-term variations') at 1 AU during cycles 21 and 22, Astrophysics and Space Science, v. 245: 81-88. 11/13/96

Landscheidt, T., Solar wind near earth: indicator of variations in global temperature, Proceedings of 1st Solar & Space Weather Euro Conference, 9/29/00

National Oceanic and Atmospheric Administration (NOAA), National Climatic Data Center, Global Surface Temperature Anomalies, 2/6/06

National Oceanic and Atmospheric Administration (NOAA), National Climatic Data Center, Southern Oscillation Index (aa)

Tinsley, B.A., 1996, Correlations of atmospheric dynamics with solar wind-induced changes of air-earth current density into cloud top, J. Geophys. Res., 101, 29701-29714 ($9)

© 2007 JAGlassman. All rights reserved.


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Comments (28)

Murray duffin wrote:

Dr. Glassman,

Your solar wind comments are intriguing. We have several imperfect solar correlations with climate change. The roughly 11 year cycle is clearly correlated. Long term irradiance seems to be correlated, but is taken to have a very weak forcing effect. The solar magnetic field and solar wind modulation of incoming cosmic rays seems to be a fair correlation, but with some obvious recent problems. Svensmark's 1998 paper shows a pretty good correlation of sunspot cycle length with temperature up to about 1970, that has been contested for recent decades. Rise time from sunspot min to max also seems to correlate - shorter rise times of successive cycles = more warming. (same as cycle length??). The recent decline in sunspot max and cycle lengthening (cycles 22 and 23) do not seem to correlate well with temp. for the last 2 decades, but solar prominences and CMEs remained very active at least through 2005 (related to Atlantic hurricanes??). Is it possible to come up with a "solar index" that combines these effects with appropriate weighting that gives an undeniable correlation? I lack the analytic talent to undertake such an analysis, but it might be right up your alley.

The theory of solar activity driven by planetary motion seems highly likely, and the 60 to 80 year Gleissberg cycle is evident in almost all climate records. (It may well be that the sun also drives ENSO/SOI). However there may have to be a solar index composed of sunspot level, cycle length, solar wind, CME activity, etc that gives a best correlation, and that accounts for all or most of global warming/cooling.

Regards, Murray Duffin

[RSJ:Correlation is a mathematical measure of the similarity between two data streams. The quality of being perfect or imperfect has no meaning. The values measured depend largely on the signal to noise ratio in the data streams, which is typically quite low in climatology. Often a useful scientific model follows from discovery of a barely detectable peak in the correlation function compared to the background noise. Svensmark's and Gleissberg's contributions are examples.

[Be aware, though, that the IPCC mentions neither Gleissberg nor his cycle. While Gleissberg phenomena may be relevant to a climate model someday, they need not concern us here because they are not relevant to the anthropogenic global warming conjecture.

[You note that the "11 year cycles [are] clearly correlated", but you don't say to what. Some sources for your views about "long term irradiance" and the solar magnetic field would have been helpful in promoting a dialog. Nonetheless, the Consensus on Climate seems at odds with what you report. It says,

The absolute value of the spectrally integrated total solar irradiance (TSI) incident on the Earth is not known to better than about 4 W/m^2, but satellite observations since the late 1970s show relative variations over the past two solar 11-year activity cycles of about 0.1%, which is equivalent to a variation in radiative forcing of about 0.2 W/m^2. Prior to these satellite observations, reliable direct measurements of solar irradiance are not available. Variations over longer periods may have been larger, but the techniques used to reconstruct historical values of TSI from proxy observations (e.g., sunspots) have not been adequately verified. Bold added, IPCC, Third Assessment Report (TAR), Technical Summary, p. 45.

[You need to read Section, Cosmic rays and clouds, TAR, pp. 384-385. This section, except for two speculatively citations in one paragraph on p. 709, contains the entire IPCC discussion of Svensmark, and of his model relating surface temperature to cloudiness through Galactic Cosmic Rays. It expressly cites Svensmark, H., Influence of Cosmic Rays on Earth's Climate, Physical Review Letters, Vol. 81, No. 22, pp. 5027-5030, 11/18/98, but for a different proposition than yours:

[Svensmark (1998) showed that, at least for the limited period of this study, total cloud varies more closely with GCRs than with the 10.7 cm solar activity index over the past solar cycle. Id.

[In that paper, Svensmark says,

[clouds are clearly linked with cosmic rays rather than with other solar phenomena such as sunspots or the emission of visible light, ultraviolet and X-rays. Id., unpaginated.

[which overall doesn't support your "pretty good correlation of sunspot cycle length with temperature". Moreover, Svensmark's 1998 paper say nothing with respect to 1970.

[The Consensus makes clear that it is looking to cloudiness for the greenhouse effect:

[Even if high cloud[s] did respond to cosmic rays, it is not clear that this would cause global cooling as for thin high cloud the long-wave warming effects dominate the short-wave cooling effect. … Thus the evidence for a cosmic ray impact on cloudiness remains unproven. Id., p. 384.

[And lastly, dismisses Svensmark:

[We conclude that mechanisms for the amplification of solar forcing are not well established. … At present there is insufficient evidence to confirm that cloud cover responds to solar variability. Id., p. 385.

[The Consensus here errs twice. First, it should have been looking not to the greenhouse effects of clouds but to the cloud albedo effect. Second, it should have checked the correlation not between solar activity and cloud cover, but between solar activity and global temperature. This paper, Solar Wind, El Niño/Southern Oscillation, & Global Temperature: Events & Correlations, addresses the latter using the aa geomagnetic index (see TAR, ¶, p. 381-382), but not the sunspot number. The other error will be addressed in an upcoming paper now in review.]

Dan Pangburn wrote:


I am convinced that CO2 is not a significant factor in the planet getting warmer. This is apparent by plotting the carbon level and temperature level vs time since 1860.


[RSJ: This chart shows the estimate for global carbon emissions since 1750 in metric tons. A search for this type of chart in the TAR and AR4 was not productive. IPCC puts cumulative global emissions since 1850 at 156 GtC (AR4, p. 139), which is about 20 times the maximum scale of the CDIAC chart! (1 Pg = 103 Tg = 103 Mt = 1 Gt, Peta = 1015, Tera=1012, Giga=109, Mega=106. For more on relevant units, see TAR, p. 869.) Global emissions rate in GtC/yr is in Figure 2.3(b), AR4, p. 138. Atmospheric concentrations of CO2 in ppm from year 0 to 2000 are shown in FAQ 2.1, Figure 1 (unpaginated). Similar concentrations for the past 10,000 years are in Figure SPM.1, p. 3, with insets for the period since 1750. The caption says the Consensus attributes the increases since about 1750 "to human activities in the industrial era."]

and http://www.ncdc.noaa.gov/oa/climate/research/anomalies/anomalies.html

[RSJ: This chart from the National Climatic Data Center is a slight revision and seven year update of data presented by the IPCC in TAR, p. 107, Figure 2.1(a). The NCDC provides links to the data in tabular form, including monthly beginning January, 1880 and current through September, 2007.]

Also from 440 mya when temperature was the same as now but CO2 level was 10 times the present http://mysite.verizon.net/mhieb/WVFossils/Carboniferous_climate.html.

[RSJ: This page, dating from 1996 and last updated 9/19/06 was posted by AGW skeptic Monte Hieb, Chief Engineer, West Virginia Office of Miners Health Safety and Training. Monte Hieb has been well excoriated by the AGW folks. When someone criticized an article by Ray Pierrehumbert wearing his RealClimate hat, suggesting the group might read Hieb, Gavin Schmidt replied,

[[Response: Far be it for me to start the whole engineers vs. scientists thing again, but Monte Hieb's calculations are, to quote Senator Dirksen, "hogwash" and are almost as wrong as it is possible to be! - see: http://www.realclimate.org/index.php/archives/2006/01/calculating-the-greenhouse-effect/ . I hope that the rigour he applies to his mine safety calculations is significantly higher. - gavin].

[Part II: What Angstrom didn't know, Comment 77. http://www.realclimate.org/index.php/archives/2007/06/a-saturated-gassy-argument-part-ii/. The paper, Calculating the greenhouse effect, is by Schmidt to criticize "an Australian climate 'contrarian'", perhaps the late John L. Daly, Still Waiting for Greenhouse, http://www.john-daly.com/, a valuable site. Schmidt's reference says nothing about Hieb or his writings.

[Pointing to a merely different calculation in no way demonstrates a challenged calculation is wrong. Whichever calculation is correct, the error is RealClimate's for failure to engage in a rational argument.

[Similarly, the first rounds of the debate against Monte Hieb are won by the defendant. He is accused of being an engineer and not a climatologist, of being biased and a tool of the coal industry, of being uncredentialed, of not publishing in peer reviewed journals, and of getting (unspecified) facts wrong. Except for the one blank, it's a firing squad with the man at the post, not his arguments.

[Back to Pangburn, what he cites is a graph by Monte Hieb containing two traces, Atmospheric CO2 and Ave. Global Temp, over a range of the last 600 million years. Hieb attributes his data to fully qualified climatologists, or better. His AGW prosecutors say nothing about the reliability of any of Hieb's data, much less these two records. For the purposes here, we must accept the data as valid, and Pangburn's datum extract is correct, if understated.

Correlation does not prove causation but lack of correlation proves lack of causation. The irradiance data is not completely satisfactory. This analysis helps.

[RSJ: Pangburn's observation at 440 mya coincides with the minor ice age called the Andean-Saharan. Between about 330 and 260 mya, the Karoo Ice Age, Hieb shows atmospheric CO2 was also comparable to the modern levels. However, Hieb's data show a hot climate, about eight degrees hotter than the present for the first quarter of the epoch, even while CO2 concentration was falling. If the CO2 concentration were predictive of the temperature changes, the lags were in the millions of years.

[The disconnect between the Consensus and responsible critics lies in just such simple observations. What is not brought to the surface is that the GCMs, once meaning Global Climate Models, and now Global Circulation Models, cannot predict climate, and cannot even reproduce the climate over the 430,000 to 600,000 years of the Vostok record or the 600 million years shown by Hieb's sources. The models are initialized in an equilibrium state for modern climate, and then tipped over by the addition of some anthropogenic CO2. They're still GCMs -- Global Catastrophe Models.

[Observations like Pangburn's and Hieb's are telling, but the Consensus remains undeterred. Notwithstanding the imperatives of science, climatologists are not trying to replicate the time before the present. Their models only look forward. At least if they offered a defense other than ad hominem attacks, that's what they would say. They don't what happened before the Big Bang, either.

[And so, the objective of the Rocket Scientist's Journal on climate is not to offer contesting theories to that of the Consensus. It is to expose the errors in the AGW conjecture as set forth in the IPCC Reports.

[Pangburn's closing observation about causation and correlation is often repeated, and true. Most often, correlation requires fine mathematical computations. In this case of the two records over-plotted by Hieb, the lack of correlation between CO2 concentration and global temperature is abundantly obvious. Clearly the AGW conjecture that CO2 drives the climate doesn't hold on the scale of the ice ages any more than it did on the scale of the glacial epochs. See The Acquittal of Carbon Dioxide.

[Pangburn's last two observation about irradiance and an analysis that helps seemed out of place and ambiguous. Perhaps he will elucidate.]

dan pangburn wrote:

Climate obviously has changed and will continue to change. The observation that ice is melting does not show that human activity is the cause. The assertion that humans have or ever can have a significant influence on climate by limiting the use of fossil fuel (a.k.a. limiting human production of carbon dioxide) is not supported by any historical record. Avoid the group-think and de facto censorship by Climate Scientists. Directly interrogate official government data that taxpayers have paid for from ORNL and NOAA as follows: If the carbon dioxide level from Law Dome, Antarctica http://cdiac.ornl.gov/ftp/trends/co2/lawdome.combined.dat is graphed on the same time scale as fossil fuel usage from http://cdiac.ornl.gov/trends/emis/tre_glob.htm it is discovered that the current carbon dioxide level increase started about 1750, a century before any significant fossil fuel use. If average earth temperature since 1880 from http://www.ncdc.noaa.gov/oa/climate/research/anomalies/anomalies.html is graphed on the same time scale as fossil fuel use it is discovered that there is no correlation between rising fossil fuel use and average global temperature to 1976. The asserted hypothesis that, since 1976, increasing carbon dioxide level has caused the temperature to rise is refuted by the carbon dioxide level from http://cdiac.ornl.gov/trends/co2/vostok.html and earth temperature from http://cdiac.ornl.gov/ftp/trends/temp/vostok/vostok.1999.temp.dat determined from the Vostok, Antarctica ice cores. If these are graphed on a higher resolution time scale it is discovered that the change in atmospheric carbon dioxide level lags earth temperature change by hundreds of years. If Law Dome carbon dioxide data and Vostok temperature are plotted on the same graph since 1000 AD (or before) it is observed that temperature oscillates up to ±1.5ºC (half pitch about 100 yr) while carbon dioxide level remains essentially unchanged (between 9000BC and 1750AD). The conclusion from all this is that carbon dioxide change does not cause significant climate change.

Regarding the irradiance data being not completely satisfactory. IMO irradiance, solar wind, cosmic rays, local relative humidity (propensity to form clouds) and possibly as yet undiscovered factors appear to all interact and have not yet been completely sorted out. The Glassman analysis is at least a start but most of temperature change remains uncorrelated.

[RSJ: 1. Instead, what ought to be demanded of the Federal government is that every paper supported by Federal money be made freely available to the public. In addition every paper or data source on which the IPCC relied for its reports should be made freely available, on line, personal computer-compatible before any decisions are made with respect to making the IPCC results any part of public policy.

[2. The technique of co-plotting records and by eye determining correlation and lead/lag relationships is a start, but the method is subjective and unscientific. To make matters worse, the records for plotting are regularly smoothed and partial. Smoothing even properly done falsely magnifies correlation. Leads and lags and correlation are mathematical relationships, and are calculable. Once those computations are made over the full range of the data, then science can discover and affirm cause and effect relationships in models.

[3. In the current paper, "Solar Wind Has Twice the Global Warming Effect of El Niño", you will find the following. The IPCC proclaims El Niño to have a "profound impact on humanity and society". And evidence that the Solar Wind has twice the power of El Niño in its likely effect on global surface temperature. You'll find that the IPCC is aware of the positive correlation between clouds and temperature, between cloud formation and galactic cosmic rays, and between cosmic rays and the solar wind. Nonetheless, the Consensus rejected the model that solar wind affects temperature for lack of evidence. A strong case exists for a model that cloud albedo regulates warming, minimizing any greenhouse effect, and modified by the sun, not through changes in its radiant power, but through the solar wind and dwarfing the El Niño effect.

Dan Pangburn wrote:

The ORNL and NOAA references appear to be unsmoothed data. However, since the conclusion is based on lack of correlation, any unidentified smoothing would make the conclusion more secure. The Vostok carbon dioxide data is at much greater time spacing than the temperature data. Graphics reveal locations where subjective interpretation may cause one to avoid certain data. For example, there is a point for carbon dioxide at 17695 ybp. A subjective assessment from observing the totality of information is that a point 17000 ybp would probably result in a significantly different 'curve' than a straight line from the point at 17695 ybp to the next point at 13989 ybp. Although a specific defined mathematic process will produce repeatable values, I found the subjective graphic determination of the definite lag of CO2 change to temperature change during transition from glacial to interglacial to be a compelling discovery. An objective, mathematically precise assessment would be welcome.

[RSJ: First, two points of order: By "the ORNL and NOAA" data, I presume you mean your references in your comment of 12/4/07 relative to Law Dome data vs. carbon emission history, and Vostok CO2 data vs. Vostok temperature. Also, by "the conclusion" you would mean your conclusions in that same comment.

[The subjective assessment is invaluable in science. It provides an intuitive check on any objective measurements and conclusions. However, the subjective has no part to play in the process model itself.

[Subjective conclusions can lead to a world of trouble and error. Climatologists were enthralled with their first look at the Vostok record. It appeared to corroborate the long held model of the greenhouse effect and the role of CO2. A little numerical analysis showed that conclusion perversely wrong. CO2 follows temperature, not the reverse. At least it did on the paleontological record. No reason exists for the reverse to be true, yet that is exactly what the IPCC and the Consensus persist in doing with their GCMs. As their story goes, manmade CO2 in the future will cause temperatures to rise while the natural CO2, 16 times as intense, will have no effect.

[Mathematical tests exists to accomplish two important tasks. One is to test for smoothing in the data. Natural smoothing needs to be accommodated in the model. Data reduction smoothing needs to be discounted. The other task for the math is to investigate small signals and relationships buried in the noise. After all, climatology is about detecting small signals in extreme noise limited by the state of the art in measuring.

[Even though lack of correlation in measurements supports lack of correlation in models, that does not extend to lack of subjective correlation in the data. Science does more than just welcome the mathematical results. It requires that one do the math.

matt vooro wrote:


Since 1990's there has been a continuous increase in global average temperatures .prime cause may not be greenhouse gases but rather the increase in Stratospheric joule heating caused by the increase in solar wind intensity. …

[RSJ: Matt Vooro brings up a real physical process, stratospheric joule heating coupled with the solar wind. But it is not part of the IPCC GCMs, and its strength is unquantified. It would not be, as he suggests, a competitor with greenhouse gases, which are not a source of energy. It would add to solar shortwave radiation. The addition, though, should prove negligible, because just a few percent change in solar radiation is sufficient to shift Earth's climate from ice age to arid.

[Vooro's lengthy post (about 1500 words) is a new subject, and neither a comment on any RSJ papers nor a contribution to the discussions. It is sorely in need of editing for typos and dangling references, and appears to be a disjointed conglomeration of several different writings. The RSJ policy is to accept all comments, and to provide thoughtful responses. This one was not junk, but too rough to post in its entirety.]

matt vooro wrote:


Dear sir

I think you have completely misdescribed [sic] my material and electrical joule heatig [sic]. It is not just solar short wave radiation.

[RSJ: There is no connection made in our dialog between joule heating and shortwave radiation.]

Did you really read the reference papers at the back ?. [sic] I enclose the conclusions of that paper on what joule heating is about. Also the joule heating concept is not unquantified if you read the number of papers in the various scientific journals since 2004. Why it was omitted By IPCC has been questioned by others as well. [sic]

[RSJ: No, I didn't read your references. You shouldn't expect anyone to undertake such a task. You give references like a required reading list for a course. You should state all the needed facts in your argument, with citations to the page in your references for fact checking. That may be the only purpose of references in scientific writing.

[You have failed to quantify joule heating and to show how it compares to solar shortwave heating. Don't expect your readers to substantiate your qualitative claims by searching through vague "various scientific journals since 2004."

[You questioned the omission from the IPCC reports? Where is the authority for this claim?]

To only quote one paragraph of mine yet take two to find faults seems kind of one sided and clearly biased.Also [sic] my material although not agreeing with your views is related [sic] to solar heating. Your very negative comments seem extreme and puzzling.Other [sic] bloggers have entered into an healthy dialoge [sic] with me including major scientific organizations .They [sic] may not agree with everything but they respect disenting [sic] opinions equally

[RSJ:Your writing was too burdensome to repair for posting. It contained misspellings, extra periods, run-on sentences, sentences without capital letters, references to "above" and "below" that couldn't be located, and citations not linked to your argument. You should use a spell checker and a grammar checker before submitting.

[Your material was not rejected for disagreeing with my papers. In fact, a major purpose of the blog is to seek such commentary. The web is the last refuge for legitimate peer review.

[Where might one find these "other bloggers" and what are the "major scientific organizations" that have responded to you? Where is the end to your last sentence above?]

Numerical estimations presented in this study show that the energy of the solar wind could be transferred into the Earth atmosphere through the electric fields induced by the solar wind disturbances. This process could be effective up to stratospheric altitudes 20–25 km where the ionized layer produced by the galactic cosmic rays and by some other sources exists. The electric currents induced by the electric fields are able to heat the atmosphere at altitude 25 km up to 5×10−2 K/h (1–2 K/day). It means that the stratospheric warming could be produced not only by dynamical factors but also by a local heating of the atmosphere by electric current. The latter phenomenon could be especially effective in high-latitude region. Several rough approximations have been made in the above calculations, which nevertheless did not prevent to get realistic results. The aim of the further studies is to elaborate more accurate values of the parameters involved in these calculations.

[RSJ:To what does "this study" and "further studies" refer? Is this a clipping from some article? Why are you writing in incomplete conditionals ("could be" if what?) instead of the definitive ("is")? Why do we care about the altitudes at which induction occurs and not care about the power induced? The last two sentences read like a poor translation from a foreign language, but regardless contain nothing of substance worth translating. The next two paragraphs suffer the same problems. They read like gobbledegook.]

The preliminary calculation of the global Joule heating fields allows to conclude [sic] that the proposed method of the Joule heating rate parameterization is physically correct and meaningful. The obtained magnitude of the Joule heating is comparable with atmospheric heating rate due to even solar UV radiation and should be taken into account in climate models.

The direct consequences of such warming could be the changes in dynamics of the stratospheric polar vortex, global ozone concentration and also climate/weather pattern. All these processes could only be accurately evaluated using a global scale 3D chemistry–climate model and the parameterization for the additional heating presented and explained here.

matt vooro wrote:


Dear Sir

I have removed all graphs from my previous material to make it read more clearly.It would appear that the graphs did not come through in my previous post. If it is too long , please remove the references If this material is still unsatisfactory, I would sincerely ask you to remove all my material from this web page.


[RSJ:Your submission on 1/22/08 didn't contain graphs, nor did it appear to have missing graphs. The problem with your submissions is not length, but typography and relevance.

[I am posting your comments, annotated, and provisionally. I have deleted only your references because they are not linked to your comments, they include abstracts and without free links to the papers. They are merely additional clutter. The rest of your comments, warts and all, are posted in full plus criticism for the tutorial value on how to participate in scientific dialog.]


Since 1990's there has been a continuous increase in global average temperatures .The prime cause may not be greenhouse gases but rather the increase in Stratospheric joule heating [electrical heating ]caused by the increase in solar wind intensity. "Sprites" and jets have been found to transfer electricity between the ionosphere and storm clouds. So electricity is known to be transferred 65 km directly to our atmosphere. This joule heating may extend all the way to our lower atmosphere and possibly to the very surface of the planet. Here we define the increased solar wind intensity as increased number of days per year with high solar wind velocity of 500 km/sec or more. .Quiet wind is closer to 275 -350 km/s.

[RSJ:Global average temperature has been flat for the last five years or so. Smoothed over a sufficient length of time, the data do show a long term rise. The cause is not greenhouse gas, so we need to look elsewhere. If joule heating is a candidate cause, then your argument needs to show as the first order of business how much energy it could couple into the atmosphere. Solar shortwave radiation is more than ample to account for the most extreme climates. Instead, your argument wanders disconnectly into the altitude at which joule heating induction occurs and the frequency of occurrence of high solar winds. ]

Solar wind dynamic pressure and the Joule heating are directly related. Solar dynamic pressure or pulse is directly proportional to the density of the wind times the wind velocity squared. Thus doubling the solar wind velocity [which is what happens during these solar wind peaks of 500-1000 km/s and more] increases the dynamic pressure pulse four fold, increases the electrical field-aligned currents, which then increases ionospheric Joule heating which contribute to global warming. The magnitude of electric field in the atmosphere is proportional to the nearness of Magnetopause to the Earth.

[RSJ:How many watts? What is your authority for the physics connecting solar wind velocity, solar wind dynamic pressure, and electric field currents? And for the physics of ionospheric joule heating and global warming? And for the physics connecting the electric field in the atmosphere and the distance to the magnetopause?]

Data supplied by the University of Maryland and SOHO shows a very recent solar wind velocity spike during December 2007. It is no wonder that the year 2007 was tied with1998 as the second warmest global year. There were 93 days of high solar wind during 2007, the 4th highest on record1995-2007]. Already during January 2008 we have had 14.5 high velocity solar wind days. The average number of solar wind days per month is 6.3

[RSJ:How many watts? Your treatment of solar wind and global temperature is not valid; it is subjective correlation and has no scientific basis. You have set arbitrary measures and thresholds, removed the noise, and compared your private view of the results to proclaim discoveries. Expressions like "It is no wonder" are purely subjective and have no place in scientific dialog.

[You need to measure the crosscorrelation and the coefficient of determination over the entire records. This has been done for you on this site, above, using the geomagnetic aa index. If you don't like the aa index, then the paper is a model for what you need to do with your record of choice. You might want to crosscorrelate the aa index with the short SOHO proton flux record to test the surrogate value of the aa index that extends back well into the 19th Century.]

The high velocity solar wind days are analogous to the number of days in a year that our planet's furnace and fan were on and set on HIGH. The global temperature anomaly is what your thermostat reads as the actual temperature.

The average number of high solar wind days per year for the three years [1995-1997] around the last solar minimum was 42. The average number of high solar wind days 10 years later at the current solar minimum for the three years [2005-2007] is 92 , more than double .This may account for why temperature anomalies have also gone up from those around 0 .30 to 0.60 due to joule heating.

Solar wind data only goes back to November 1994 otherwise I would go back earlier to the 1980's when the so called "manmade global warming" started. I continue to state that in my personal opinion, the prime cause [80%] of global warming is the sun. Man made greenhouse gases contribute to the warming but only about 20%.

[RSJ:The geomagnetic aa index is a reasonable surrogate for the solar wind. "[T]he aa-index is highly controlled by the solar wind velocity". http://www.dsri.dk/showpage.php3?id=191. That cite then reports on an examination of empirical probability densities [a far better practice is to estimate probability distributions] of the aa index and the solar wind velocity. The reader might want to Google for combinations of various geomagnetic indices, e.g., aa index, Ap index, Kp index, PC index, Dst index, AE index, with or without the solar wind.

[The aa index starts in 1868. The IPCC uses 1750 as a baseline year to begin the industrial era and man's influence. Why would a reader care about your personal opinion? Science is not about beliefs, it's about models with predictive power, and your model of greenhouse gases fails. GHGs are passive; they insulate. They store heat acquired from the sun and Earth, which like all warm bodies they lose by the usual methods of heat transfer.]

Some scientists have commented that there has been no change to the sun since the 1950's. This may not be true as per the quote below taken from a 1999 technical paper noted at the end of this article. As the magnetic fields of the sun increase, so do the electrical fields and associated joule heating.

[RSJ:You need to supply the comments and not leave it to your readers to search for what you found worthwhile. Name the sources on which you rely or wish to criticize. Quote them and cite to the page where the quote can be found.]

Here we report that the measurements of the near-Earth interplanetary magnetic field reveal that the total magnetic field leaving the sun has risen by a factor 1.4 since 1964. Using surrogate interplanetary measurements, we find that the rise since 1901 is by a factor of 2.3. This change may be related to chaotic changes in the dynamo that generates the solar magnetic field. We do not yet know quantitatively how such changes will influence the global environment.

[RSJ:Is this a clipping from an abstract? It jumps in disconnected fashion from concept to concept. In the end "we" can't quantify the effects. That is the transcendent problem with your discussion. Solar radiation imparts 8.2 million quads per year of energy on Earth. Man consumes just under 500 quads per year. According to Vooro, joule heating contributes an unknown number of quads per year, which may or may not be part of the 8.2 million quads from the sun.

[Next you provide three rambling, useless paragraphs on alternative conjectures for global warming.]

If the magnetic fields leaving the sun increased 40% during the period 1964 to 1999, then by 2008 the increase could be up by another 10%, assuming the same rate of change.

There may also be another source of global warming since about 1988, namely weather modification experiments and techniques as explained as per the following web page. http://www.globalresearch.ca/index.php?context=va&aid=7561

The unusual hot weather of 1998 could come from these weather modification sources as there were no unusual solar events or sudden rise in greenhouse gas levels in the atmosphere. An El Nino existed but past similar strong El Nino's like 1972/1973 and again 1982/1983 showed no such temperature increases. The writer has no other evidence to confirm whether and when any weather modifications took place.

I applaud and support all the efforts to reduce the use of fossil fuels and when this is not possible, the use of latest and cleanest fossil fuel technologies capture] to clean up the pollution associated with greenhouse gases.

[RSJ:Why would your readers care about your personal likes and support? Are you in a position to award grants? ]

It is very odd and very noticeable that the issue of pollution as opposed to global warming is rarely now mentioned by all the scientific bodies engaged in the climate change debate. If everyone is focused on CO2 reductions only and climate change, cleaning up the pollution is conveniently forgotten.

[RSJ:The Supreme Court recently ruled that the EPA may treat CO2 emissions as a pollutant. That, too, has zero scientific validity. CO2 is benign and beneficial. It is an optimum effluent. It is a greening agent. One man's meat is another man's poison.]

I merely wish to point out that manmade greenhouse gases may not be the prime cause behind global climate change. The facts of this will become apparent in the near future. The sun and our planet are changing due to causes that are not all of man's making but we can reduce the pollution that we are causing.

[RSJ:"References" deleted. They included links to web pages and reproduced abstracts.]

Barry Cooper wrote:



Please let me know if this is accurate: since the relative importance of CO2 as a forcing increases as you go up in the atmosphere, then logically if CO2 is a principle forcing in our current time, the temperature increases will be measurably higher in the upper troposphere and stratosphere. Christopher Monckton made this point, and it appears to me to be a predictive hypothesis that could bring the process of falsification into the short term.

Is this accurate? Strategically, it seems to me, there is a pronounced need to force them into specific predictions that can be verified and this one seems relatively easy.

[RSJ: Barry, your question touches on a few important and complicated facets of climate modeling.

[Point of Order. Forcing is a nickname for radiative forcing, the modeling paradigm for global climate models (in the broadest sense), selected and defended by the IPCC. That puts your question in the domain of the IPCC and its GCMs. Regardless, the only models worth falsifying, as you would like, are those models. That is because no reasonable climate crisis or threat would exist but for the IPCC. And with regard to forcing, the IPCC says,

In the context of climate change, the term forcing is restricted to changes in the radiation balance of the surface-troposphere system imposed by external factors, with no changes stratospheric dynamics, without any surface and tropospheric feedbacks in operation (i.e., no secondary effects induced because of changes in tropospheric motions or its thermodynamic state), and with no dynamically-induced changes in the amount and distribution of atmospheric water (vapour, liquid, and solid forms). Bold added, Third Assessment Report (TAR), ¶6.1 Radiative Forcing (¶6.1.1 Definition), p. 353.

[That definition of forcing might resolve your question because forcing doesn't apply in the stratosphere, and the stratosphere is not allowed to change dynamically. But that is a narrow, legalistic answer I won't make.

[The IPCC defines forcings to be external factors, so the natural CO2 circulating through the ocean and atmosphere, 60 times that produced by man, is not a forcing. While the TAR (2001) defined radiative forcing to exclude any feedbacks, especially of water vapor (as quoted above), by the Fourth Assessment Report (AR4) (2007) GCMs included water vapor feedback. Nevertheless, the IPCC didn't bother changing its definition. Except to interpret your question to be about extra CO2 added to the climate, the following response does not rely on the technical scope of forcing.

[Is Lord Monckton your source for the notion that "the relative importance of CO2 as a forcing increases as you go up in the atmosphere"? You could be referring to his August 2007 paper, "Greenhouse Warming, What Greenhouse Warming". http://scienceandpublicpolicy.org/images/stories/papers/monckton/whatgreenhouse/moncktongreenhousewarming.pdf. Regardless, your "relative importance" model does not appear to be an IPCC concept.

[To the IPCC, by far the dominant effect of CO2 on the climate is its greenhouse effect, and the greenhouse effect is a phenomenon of the troposphere. Moreover the IPCC treats CO2 as well-mixed throughout the troposphere. While that is not true on a small scale, particularly where the IPCC can resolve CO2 measurements, the well-mixed assumption should be satisfactory on the scale of the atmospheric layers, i.e., troposphere, stratosphere, mesosphere, and thermosphere. Therefore, the relative importance of CO2 doesn't change through the troposphere, which is up to about 11 km, the bottom of the stratosphere.

[Point of Order: "Temperature increases" can mean warming such as caused by forcings, or it can mean the changes in temperature with altitude caused by gas and radiative thermodynamics. Technically, the latter sense is known as the temperature lapse rate, which varies with altitude. So by asking whether the "temperature increases will be measurably higher in the upper troposphere and stratosphere" you might mean higher than temperature increases at the surface, or higher than normal in that region. Viewed either way, the answer is the same and it rests on an understanding of lapse rate, which is in a state of great confusion within the IPCC.

[Regardless that small amounts of CO2 are found in the stratosphere, the stratosphere exhibits no blanket or insulating effect. The IPCC now recognizes that the greenhouse effect is a blanket effect (AR4, FAQ 1.1, p. 97, but the word blanket is not found in the TAR), and nowhere does the IPCC model or calculate a blanket effect. The blanket model may be incompatible with the radiative forcing paradigm.

[A blanket supports a temperature drop through its interior proportional to the heat flowing through it. The blanket or greenhouse resistance is proportional to the ratio of the lapse rate to the heat through the blanket.

[In the US Standard Atmosphere the tropospheric lapse rate is -6.5ºC/km. For insight into temperature lapse rate, look at a graph of the temperature of a Standard Atmosphere, such as the US Standard Atmosphere at http://www.aerospaceweb.org/question/atmosphere/q0112.shtml . (In case you have relied on Lord Monckton's paper cited above, he explains his model with a pair of lapse rate profile charts across the troposphere and into the lower stratosphere.) The Standard is a piecewise linear model, discontinuous in lapse rate (the slope), which is most obvious in its tabular form. See, for example, http://mtp.jpl.nasa.gov/notes/altitude/StdAtmos1976.html . There is also an International Standard Atmosphere which differs only slightly from the US. These Standards are idealized averages representing the globe for a middling moisture content, and use a geopotential height, that is, a pressure altitude, instead of actual altitude for the independent variable to make the data latitude-independent. Regional or local lapse rates will be different, and they change with moisture content, convection, and much more. The GCMs appear to start with a Standard Atmosphere and then calculate a new lapse rate in search of a radiation equilibrium cell by cell.

[Point of Order: The lapse rate in the Standard Atmosphere is negative through the troposphere, but the IPCC (and others) define lapse rate as the rate of decrease of temperature, thus reversing the sign. AR4, Glossary, p. 948. The IPCC also defines lapse rate in general, making it applicable not just to temperature, but to other variables, such as gas concentration. In its Reports, the IPCC often discusses lapse rate ambiguously, not specifying whether it is temperature. This response uses the Standard Atmosphere sign convention, and uses lapse rate only with respect to temperature. There is also a scaling problem, which this response ignores. Lapse rate might be defined locally, such as within a GCM grid; regionally, such as an average for the tropics; or globally.

[GCMs calculate a new lapse rate during runs using a process called parametrization (UK) or parameterization (US). Parameterization is a universal method, and it can produce valid equations when based on sound scientific theories or laws. However, in IPCC parlance, it is a mathematical model based on some degree of curve fitting, used for phenomena where the physics could not be simulated. Reasons for parameterizing include that the physics doesn't fit the GCM scale, is too complex to run in affordable time, or is unknown. Whether parameterized variables, like lapse rate, track the real world is a matter of luck or skill on the part of the modeler. Also a parameterized variable is limited by the quality of the underlying data.

[Radiosonde and satellite data are the two primary sources for lapse rate data, but the IPCC has not been able to reconcile them. As a result, a wide discrepancy exists between GCMs in what is called the lapse rate feedback. More about feedback below, but first the IPCC says,

[There remains substantial disagreement between different observational estimates of lapse rate changes over recent decades, but some of these are consistent with GCM simulations (see Sections 3.4.1 and 9.4.4). Bold added, 4AR, Box 8.1: Upper-Tropospheric Humidity and Water Vapour Feedback, p. 632.

[Section 9.4.4 refers back to section 3.4.1, where the IPCC says,

[Within the community that constructs and actively analyses satellite- and radiosonde-based temperature records there is agreement that the uncertainties about long-term change are substantial. Changes in instrumentation and protocols pervade both sonde and satellite records, obfuscating the modest long-term trends. Historically there is no reference network to anchor the record and establish the uncertainties arising from these changes – many of which are both barely documented and poorly understood. Therefore, investigators have to make seemingly reasonable choices of how to handle these sometimes known but often unknown influences. It is difficult to make quantitatively defensible judgments as to which, if any, of the multiple, independently derived estimates is closer to the true climate evolution. This reflects almost entirely upon the inadequacies of the historical observing network and points to the need for future network design that provides the reference sonde-based ground truth. Bold added, AR4, ¶3.4.1 Temperature of the Upper Air: Troposphere and Stratosphere, p. 265.

[Point of Order: The IPCC defines the term feedback well enough (see climate feedback, AR4, Glossary, p. 943), but uses it in two other unique and misleading ways. For the most part, and especially with regard to lapse rate feedback, the IPCC uses feedback to mean simply that the GCM calculates the parameter value at run time. As of the TAR, the feedback by its definition did not apply to radiative forcing by its definition. The definitions haven't been updated, but as of AR4 the IPCC has relaxed the restriction against feedback in its models.

[Parameterization likely accounts for the tendancy of GCMs to drift slowly from their initial conditions into unrealistic states, a situation the IPCC finds baffling. It also causes a great discrepancy to exist between the output of different or even identical GCMs, exacerbating a chronic problem of poor quality observations. As a result, the IPCC and its GCMs have not settled on a consistent, much less validated, model for temperature lapse rate.

[With increasing altitude, the Standard atmosphere temperature of the stratosphere is initially constant (isothermal), and then increases (a positive lapse rate). By the Standard, the stratosphere is a negative blanket; it cools by carrying heat away from the troposphere. Thus, the dominant effect of CO2, to be a greenhouse gas, is precluded in the Standard stratosphere, and, of course, its secondary effect as a greening agent for the biosphere doesn't apply above the surface.

[Climate effects of the stratosphere are dominantly its cooling, aerosol effects, ozone layer absorption, and ice clouds. These are all larger than any speculated stratospheric CO2 effect.

[So the dominant effect of CO2 is constant with altitude through the troposphere, and has no effect above that.

[Your hypothesis that "CO2 is a principal forcing in our current time" and your conclusion that "temperature increases will be measurably higher in the upper troposphere and stratosphere" form a false cause and effect relationship. First, the hypothesis is false. See The Acquittal of Carbon Dioxide on this blog. CO2 concentration growth is an effect of global warming, not a cause of it. So we might rephrase the conclusion to ask the whether CO2 increases are positively correlated with temperature increases at altitude. They are not.

[Lest your model be a straw man, you need a reference that postulates your model.

[The IPCC Fourth Assessment Report, Technical Summary, has a set of four charts on temperature anomalies from the surface to the lower stratosphere for the period of 1958 to 2005. AR4, Figure TS.7, p. 38. Being anomalies, though, the IPCC has discarded any altitude discrimination, and with it any information about the temperature lapse rate. Still, the set shows the lower stratosphere baseline temperature dropping continuously over the period (punctuated with warming bursts coincident with volcanic eruptions) while since the mid 60s, the surface temperature rose (mostly immune to the eruptions). Elsewhere, the IPCC reports show the CO2 concentration rising continuously over the period. See TAR, Figure 3.2a, p. 201 (1958 to 1998), updated with the AR4, Figure 2.3(a), p. 138 (1970 to 2006).

[So the temperature at the tropopause, adjacent to the lower stratosphere, has been dropping while the global CO2 concentration has been increasing. If your conclusion is about CO2 causing higher temperatures around the tropopause, then it hasn't been happening. A model that predicts a rise in temperature at the tropopause caused by increases in CO2 concentration at the surface is falsified (in Popperese) or simply invalidated.

[A plausible conclusion for the greenhouse warming hypothesis begins with the recognition that the lapse rate in the troposphere must increase in magnitude. This follows from the thickening of the blanket. That can be accommodated with an increase in lapse rate such that the temperature at the top of the troposphere doesn't change. Instead of the Standard lapse rate of -6.5ºC/km, a rate of -6.591ºC/km will account for a 1ºC temperature rise at the surface and no change at the stratosphere. In this model, the tropospheric branch of the Standard Atmosphere pivots about the 11 km point at its top, shifting the bottom +1ºC, and is different than Monckton's before and after graphs. It is a minute change in lapse rate, well masked by the IPCC ability to measure or calculate the global mean lapse rate, but still a plausible scenario.

[A major activity in science is the discovery of hidden relationships implied by a model. If the conditions of the relationship are met but the conclusions are not, the model is invalid. It must be discarded or repaired, and the usual method of repair is to add conditions or exclude parts of the domain of the model. In any case, the invalidation must be based on a provable relationship. Proof that such a relationship exists would be "to force them into specific predictions" as you suggest. Your conjecture doesn't fill the bill. Your model hypothesizes that CO2 importance increases with altitude, and then extrapolates that to the region around the tropopause. Neither the basis for the argument nor its extrapolation is valid.]

Barry Cooper wrote:


Thanks for the response. I think I need to format my question somewhat differently.

What concrete predictions do the IPCC models make, which can be tested over a relatively short period of time?

The climate is of course in constant flux, and long term patterns not always immediately obvious, but my intent was to find something which we could measure accurately, and which we could compare to the models.

If I understood your response correctly, at least some of the models have already been falsified, based on logical scenarios which are inferred by their assumptions.

Strategically, it seems to me, the goal is to bring them into the realm of science. Tactically, the aim is to force them into hypotheses which they agree to consider binding. If their predictions cannot be verified, they will agree that something--maybe everything--is wrong with their models. That's what I'm looking for.

What do you suggest?


[Your core question looking for short term predictions in the IPCC GCMs is spot-on. Before a hypothesis can advance to a theory, it must have made some non-trivial predictions which have been validated by observations. Only then, at the model quality level of a theory, may the model be used ethically for public policy.

[The IPCC has failed this requirement, and is acting unethically. It has urged governments and industry to act now based on a prediction of catastrophe a century hence, a prediction made by an unvalidated model. (The fact that the model is a set of models, a collection of GCMs, and the fact that they may be in agreement are well-touted by the IPCC, but each fact is irrelevant.)

[The responsibility to develop a model in keeping with scientific principles is solely the responsibility of the modeler, in this case, the IPCC. This is not the duty of anyone else. The duty of the public, specifically government and industry leaders, is to hold the IPCC to its duty. The scientific literacy to do so is sorely lacking in our leaders, and this is a sad reflection on our public education system.

[The requirement to postulate validating predictions before scaring the public is not the total of the prerequisites for the IPCC. It must also demonstrate that its model fits all the data in its domain. It fails this duty as well, but demonstrating this failure is concrete and easier to grasp. How the IPCC might repair its models to fit all the data is the difficult part, but that is not up to the public to solve.

[The GCMs need repair to fit the dominant feature of Earth's climate: the temperature extremes demarked by the ice ages. The ice ages are sometimes distinguished as four major ice ages, plus the interleaving glacial epochs. Repair comes in two forms. Either the GCMs can replicate the historical record, or the IPCC can define the parameters comprising the domain of the GCMs objectively so that the domain excludes the paleo record.

[The IPCC asks just the right question as FAQ 6.1 in AR4: What Caused the Ice Ages and Other Important Climate Changes Before the Industrial Era? FAQ 6.1 begins,

[Climate on Earth has changed on all time scales, including long before human activity could have played a role. Great progress has been made in understanding the causes and mechanisms of these climate changes. Changes in Earth's radiation balance were the principal driver of past climate changes, but the causes of such changes are varied. For each case - be it the Ice Ages, the warmth at the time of the dinosaurs or the fluctuations of the past millennium - the specific causes must be established individually. In many cases, this can now be done with good confidence, and many past climate changes can be reproduced with quantitative models. Italics in original. AR4, id., p. 449.

[Imbedded in this paragraph is a multi-pronged confession that some major climatic events are unexplained, and only some models can reproduce some events. It implies that the IPCC models are not sufficient, and require some other undetermined causative agents to work. The paragraph falls quite short of saying that the GCMs reproduce every hot or cold epoch even coarsely. Furthermore, the IPCC shows no results even for those models for which it claims some success.

[FAQ 6.1 says,

[Starting with the ice ages that have come and gone in regular cycles for the past nearly three million years, there is strong evidence that these are linked to regular variations in the Earth's orbit around the Sun, the so-called Milankovitch cycles (Figure 1). These cycles change the amount of solar radiation received at each latitude in each season (but hardly affect the global annual mean), and they can be calculated with astronomical precision. There is still some discussion about how exactly this starts and ends ice ages, but many studies suggest that the amount of summer sunshine on northern continents is crucial: if it drops below a critical value, snow from the past winter does not melt away in summer and an ice sheet starts to grow as more and more snow accumulates. Climate model simulations confirm that an Ice Age can indeed be started in this way, while simple conceptual models have been used to successfully 'hindcast' the onset of past glaciations based on the orbital changes. The next large reduction in northern summer insolation, similar to those that started past Ice Ages, is due to begin in 30,000 years. [¶] Although it is not their primary cause, atmospheric carbon dioxide (CO2) also plays an important role in the ice ages. AR4, FAQ 6.1, p. 449.

[So the GCMs, which predict a catastrophe of about 2ºC to 3ºC from a doubling of atmospheric CO2, have no mechanism by which to account for the estimated, natural excursions of 11ºC to 12ºC, peak to peak, occurring just in the last 400,000 years. The IPCC hypothesizes that the doubling of CO2 will be produced by man, and relates it to the warming observed through the 20th Century. But the modeling has no way to exclude the overwhelming natural background of warming and cooling that characterize Earth's climate.

[The IPCC initializes its models based on a radiation equilibrium budget attributed to the 1750, a point in the pre-industrial era. See AR4, FAQ 1.1, p. 96. The modelers presume that this era was also in thermodynamic equilibrium, but it was not. Earth is supposed to be in radiation equilibrium while it is warming in recovery from the Little Ice Age.

[The IPCC puts little effort into justifying the Milankovitch theory, possibly because it is no part of its models. It damns the theory with faint praise. The theory is far less than suggested. Ray Pierrehumbert, an often quoted lead author for parts of the TAR, says,

[The gaping hole in Milankovic's theory is that it predicts that ice ages should follow the precessional cycle. In particular, the Northern Hemisphere and Southern Hemisphere should have ice ages in alternation every 10,000 years, with the severity of the ice ages modulated by the eccentricity cycle. This is not at all what is observed. Pierrehumbert, R. T., Principles of Planetary Climate", 7/31/07, ¶8.5, p. 253.

[He explains,

[The problem is not that the amplitude of radiative forcing associated with Milankovitch cycles is small: it amounts to an enormous 100W/m2, with the amplitude determined by the eccentricity cycle. The problem is that the forcing occurs on the fast precessional time scale, whereas the climate response is predominately on a much slower 100,000 year time scale.

[Gaping hole indeed! The IPCC GCMs are based on the radiative forcing paradigm. The Milankovitch theory relates to a forcing of 100 W/m2, while the CO2 radiative forcing in 2005 was 1.66 W/m2,. AR4, ¶2.3.1, p. 140. This is not to say that Milankovitch swamps CO2, but instead casts doubt on the radiative forcing paradigm. A forcing 60 times as great as CO2, modeled by its radiative forcing, is not evident in the climate.

[In a discussion on other effects, the IPCC suggests a waning confidence in its chosen paradigm:

[Irrigation affects the temperature, humidity, clouds and precipitation as well as the natural evaporation through changes in the surface temperature, raising questions about the strict use of RF in this case. Bold added, AR4, ¶2.5.5 Other Effects of Anthropogenic Changes in Land Cover, p. 185.

[FAQ 6.1 tells us what does affect the climate.

[There are three fundamental ways the Earth's radiation balance can change, thereby causing a climate change: (1) changing the incoming solar radiation (e.g., by changes in the Earth's orbit or in the Sun itself), (2) changing the fraction of solar radiation that is reflected (this fraction is called the albedo - it can be changed, for example, by changes in cloud cover, small particles called aerosols or land cover), and (3) altering the longwave energy radiated back to space (e.g., by changes in greenhouse gas concentrations). Bold added, FAQ 6.1

[Here are some frank comments by the IPCC on cloud modeling:

[In spite of this undeniable progress, the amplitude and even the sign of cloud feedbacks was noted in the TAR as highly uncertain, and this uncertainty was cited as one of the key factors explaining the spread in model simulations of future climate for a given emission scenario. This cannot be regarded as a surprise: that the sensitivity of the Earth's climate to changing atmospheric greenhouse gas concentrations must depend strongly on cloud feedbacks can be illustrated on the simplest theoretical grounds, using data that have been available for a long time. 4AR, ¶1.5.2, p. 114.

[The importance of simulated cloud feedbacks was revealed by the analysis of model results, and the first extensive model intercomparisons also showed a substantial model dependency. The strong effect of cloud processes on climate model sensitivities to greenhouse gases was emphasized further through a now-classic set of General Circulation Model (GCM) experiments. They produced global average surface temperature changes (due to doubled atmospheric CO2 concentration) ranging from 1.9°C to 5.4°C, simply by altering the way that cloud radiative properties were treated in the model. It is somewhat unsettling that the results of a complex climate model can be so drastically altered by substituting one reasonable cloud parametrization for another, thereby approximately replicating the overall intermodel range of sensitivities. Citations omitted, bold added, 4AR, ¶1.5.2, p. 114.

[In spite of this undeniable progress, the amplitude and even the sign of cloud feedbacks was noted in the TAR as highly uncertain, and this uncertainty was cited as one of the key factors explaining the spread in model simulations of future climate for a given emission scenario. This cannot be regarded as a surprise: that the sensitivity of the Earth's climate to changing atmospheric greenhouse gas concentrations must depend strongly on cloud feedbacks can be illustrated on the simplest theoretical grounds, using data that have been available for a long time. 4AR, ¶1.5.2, p. 114.

[[C]loud feedbacks remain the largest source of uncertainty in climate sensitivity estimates. AR4, ¶ Clouds, p. 636.

[So the IPCC AGW model fails to account for three million years of profound climate variations. It does not replicate the dominant features. The IPCC hints at studies linking these features to the Milankovitch cycles, but instead those cycles challenge the essence of the IPCC modeling paradigm. The IPCC lists cloud cover among causes of major climate change, but fails to model it successfully.

[So the answer to your question,

[What concrete predictions do the IPCC models make, which can be tested over a relatively short period of time?

[is none, and the IPCC has the duty to provide such predictions after fixing their AGW conjecture for its problems accounting for the most significant climate data.

[These modeling inadequacies should be sufficient for any leader to relegate Anthropogenic Global Warming to the bin of discarded scientific conjectures.]


Dear Jeff

Thank you for your high quality work to ensure that pressure, temperature and the weight of evidence (all puns intended) are kept on the global warming pseudo-consensus.

As a geochemist of long standing, with lots of exposure to profound biochemical effects on basic chemothermodynamics in the most unlikely or surprising of environments I must admit to not being entirely convinced by your reply to David Ellard to the effect that biological effects on the Oceanic CO2 Conveyor are strictly 2nd order.

[RSJ: Here's what was actually said in response to Ellard:

[However, those chemical reactions should not have any first order effects on the net rate of CO2 flux between atmosphere and ocean. Bold added. The Acquittal of Carbon Dioxide, on this blog, comment dated January 17, 2008.

[The restriction is neither "strictly" nor is it to a "biological effect". It's an observation about the thermomechanical solubility effect. Solubility of gases in water is well-characterized. The first order parameters are temperature and pressure. A second order parameter is salinity. The IPCC, though, has oceanic biological processes causing a bottleneck to solubility.

[In a one-dimensional model, biological processes might draw CO2 ions from the aqueous CO2 reservoir, and that might be detectable from atmospheric measurements. Its solubility might appear greater than temperature, say, would indicate. This columnar model is stagnant compared to the three dimensional thermohaline circulation. According to the IPCC's figures, 90 GtC/yr outgases from the ocean, the great abundance from the Eastern Equatorial Pacific. The ocean uptakes 92 GtC/yr in the form of CO2 in the high latitudes. The hypothesis here is that the THC accounts for this flux, dominantly according to the first order causes of temperature and pressure. The RSJ response to Ellard was that the biological effects are less than first order with respect to the flux, and now might be said to be third order, if measurable at all.]

While I agree with you that IPCC struggle when they claim that past temperature excursions can be explained by GCMs there is one simple fact that is hard to gainsay.

The very zones of the Oceanic CO2 Conveyor where atmospheric CO2 'hops on' are the cold circumpolar oceanic bands which support the bulk of the phototrophic cyanobacteria that in turn constitutes the bulk of the biomass on this planet.

[RSJ: The RSJ model doesn't suggest that CO2 boards the conveyor belt at the poles. Instead, the THC has a large NH and a weak SH poleward surface current, each of which absorbs CO2 all along the path to the points of descent. The circulation descends in part to feed the two deep water, circumpolar currents, and in part to continue to the points of outgassing in the Pacific and Western Indian Oceans.]

Alive, cyanobacteria absorb dissolved CO2 and bicarbonate and respire O2 (and are eaten by zooplankton, krill etc). Dead, their sinking cells are also subject to aerobic decomposition which returns some CO2 to the gaseous and aqueous phases. Because this looks roughly like a closed cycle there is a tendency to think that the net loss of sinking carbon to the ocean's depth is minor.

However, it is surely incontestable that at a certain phase of Earth's history this process took an atmosphere with at least several tens of percent of CO2 and converted it relatively quickly (in geological terms) into one with a modern steady state of 21% O2 and less than 1% CO2.

How can we reconcile this fact with a view that this process is 2nd order by comparison with the solubility + temperature + density driven thermodynamics of the Oceanic CO2 Conveyor? Would we have to conclude that the planet's cyanobacterial biomass was once far, far larger than it is today? I have the impression there is no unambiguous geological evidence that this was the case.

[RSJ: You set up a straw man that the cyanobacterial biomass process is rather decoupled from the THC, but don't actually disprove it. Regardless, no claim is made here comparing the magnitude of the biological process to the magnitude of the THC/solubility flux. The THC is at present a powerful, thermomechanical process exchanging CO2 with the atmosphere and the biospheres, but adding nothing to the reservoirs apart from that caused by changing ocean temperature. A common theme among climatologists, and supported in the IPCC reports, is that the THC may have been quite different, even non-existent at times in the past, and that might happen again.]

Analogously, this issue reminds me that over the last decade, atmospheric methane levels have been slowly declining even though we are frequently told that the Siberian permafrost is warming, the oceans are warming and hence increasing tonnages of methane are now entering the atmosphere.

We have plenty of evidence that the ocean has no trouble biologically rapidly removing large localized fluxes of methane directly into it over very short distances as the attached web reference shows:


Given that methane is also a gas subject to solubility + temperature + density driven thermodynamics, just another 2nd order effect?

[RSJ: The issues need to be set in perspective. Methane is a second order climate effect because the IPCC chose to make it so. Since there would be no climate crisis but for the IPCC, CO2 alone is the first order cause of the upcoming climate catastrophe. The conclusion reached here is that CO2, much less CH4, has a negligible effect on Earth's climate.

[Furthermore, neither gas affects the THC, nor is much of an influence on the physics of solubility. The THC, though, is important because it accounts for the shape of the paleo concentration of CO2 relative to global temperature. The record supports the model that atmospheric CO2 is global-temperature sensitive. Especially because the ocean emits 15 times as much man, CO2 must be modeled not as the IPCC models it, as a forcing, but as a feedback. The same might be true of CH4, if it were deemed important.

[The IPCC notion that natural CO2 is in equilibrium and anthropogenic CO2 accumulates in the atmosphere ignores its own residency time model, and assumes without support that the ocean discriminates between nCO2 and ACO2, necessarily by fractionation. Barring some evidence to the contrary, the THC will remove ACO2 as rapidly as it does nCO2. Biological effects, whether they might cause an increase or a decrease in CO2, help decrease the residency time to about a year and a half compared to the IPCC biologically-limited estimate of centuries to millennia.

[The IPCC declares ACO2 a "Long Lived Greenhouse Gas" (LLGHG) to support two claims. First, long residency time makes atmospheric CO2 well-mixed, so the concentration measured at Mauna Loa represents global increases instead of regional phenomena. Second, because man's CO2 emissions stay in the atmosphere, a greenhouse catastrophe within the Century is unavoidable. Neither is true because the premise is false. The premise is false because biological processes are not a bottleneck to the dissolution of either species of CO2 in the ocean.]

Clothcap wrote:


Acquittal is not accessible, if you are updating, could you be kind enough to let me know when it is available again.

[RSJ: While updating on number 2 computer, the hard drive failed catastrophically, 3 months post-warranty, leaving The Acquittal half in bit heaven. I removed the file with number 1 computer, replaced the hard drive, and while restoring the files from mirrored volumes on number 1, its power supply failed catastrophically. What are the odds! Sorry for the inconvenience.]

On climate, as the temperature incline achieved its steepness pre 1850 and would seem to follow deforestation, forests playing a large part in the water vapour cycle, is it possible for you to apply your skills to the stats and perhaps arrive at a conclusion regarding relevance to current warming. I feel that a person with an understanding of the complicated cycle of GHGs, convection, evaporation, etc., would arrive at a more reliable determination than I could ever hope to achieve.

[RSJ: So much (poor) data and so little time! Besides, the only model worth debunking is that of the IPCC. The evil genie needs to be stuffed back in her bottle, so science can get back to its natural, academic, peer-reviewed journal pace, and leave Congress and Parliament to their own mischief. So instead of speculating about data (which you haven't provided), I believe I can arrive at a reliable determination from the standpoint of what the IPCC says and has done.

[The steepness of the temperature record at some point and the concept of deforestation are vague and too qualitative for scientific analysis. One would need to quantify both ideas into measurable epochs, each in a background about ten times as long as the subject epoch. You would need to define "steepness", and exactly what constitutes deforestation. You would also need to be aware of the scale of the model. Climate is global phenomenon, expressed in estimable but unmeasurable thermodynamic concepts. Deforestation evokes politically-charged, regional ideas, like clearing rain forests and species destruction, but ignoring gains in re-forestation elsewhere.

[IPCC Reports touch on deforestation in all its aspects, including surface albedo, aerosols, and the hydrological cycle with respect to precipitation and regional cloudiness, but primarily and most quantitatively for its different effects on the carbon cycle. However, the IPCC admits its treatment of the hydrological and carbon cycles are the greatest sources of error and uncertainty in its collective global climate model. The situation is much worse than the IPCC admits. Both of its cycle models contain technical errors and omissions which are fatal to its AGW concept. As a result, the context is missing in which to analyze deforestation as it relates to global warming via the water cycle.

[First, the fatal flaw: In the IPCC's treatment of water vapor, and hence the hydrological cycle, it omits global cloud albedo feedback. A paper is in the final throes of editing for the Journal with a model that shows that control of Earth's climate is dominated by cloud albedo, and not the greenhouse effect. The IPCC models the greenhouse effect as an open loop phenomenon, when it is actually governed by the powerful negative feedback of cloud albedo. The closed loop gain can reduce the greenhouse effect by an order of magnitude and be undetectable within today's state of the art in measuring albedo.

[The IPCC makes the problem more complicated by using the terms "cloud albedo" and "feedback" ambiguously. Furthermore, the IPCC simulates water vapor feedback and cloud albedo with parameterizations, which produce representative statistics instead of replicating physical processes with their essential dependencies. The following assumptions about global average parameters in the GCMs cannot be refuted from the IPCC reports: (1) atmospheric specific humidity (again as modeled, not as proclaimed) is independent of temperature, (2) the cloud coverage, and hence the total cloud albedo, is independent of the specific humidity, and (3) Earth's albedo is independent of cloud albedo. Should any of these assumptions be false, one would expect the IPCC to provide accuracies with which these processes are simulated. It does not. These appear to be three broken links in the essential process by which cloud cover adjusts to moderate Earth's climate.

[To the extent that deforestation affected the water cycle, it would be important to global warming. An essential part of that determination involves relative contribution of water vapor to the total flux that feeds the atmosphere. To this end, a hydrological budget is needed, but which the IPCC omits. An authoritative source is available as Figure 1 in Trenberth, K.E., L. Smith, T. Qian, A. Dai, and J. Fasullo, Estimates of the global water budget and its annual cycle using observational and model data, National Center for Atmospheric Research, J. Hydrometeor., November, 2006. http://www.cgd.ucar.edu/~tqian/papers/gewexJHM3607.pdf. According to this paper, the ocean provides 413 K km^3/yr into the air, almost six times that from land sources (73 K km^3/yr). Deforestation must be a small fraction of the total land mass, and insignificant to the global specific humidity.]

I feel CO2 has been grossly overplayed and it is time for other factors of possibly greater influence be brought more to the forefront of this (IMO) farcical political game.

[RSJ: Agreed. We need to put the CO2 question to bed politically. However, we don't want to shift gears into hypothetical alternative greenhouse gases. The greenhouse effect is regulated by the negative feedback of cloud albedo. Climatologists need to cast new models in which the Earth slowly switches between at least two states: a cloudless frozen ball, and a cloud-controlled habitat where animals flourish.]

Have you seen Lombert's length of day did it theory hosted on icecap?

[RSJ: Your reference is a bit garbled. With a little research, I uncovered the recent paper, Löbert, G., A Compilation of the Arguments that Irrefutably Prove that Climate Change is driven by Solar Activity and not by CO2 Emission, 3/6/08. http://icecap.us/images/uploads/Lobert_on_CO2.pdf. I assume this is what you intended.

[Löbert's reliance on cloud cover supports my conclusions, and I agree that man can have little influence on climate with today's technology. Varying CO2 emissions will do nothing. We might want to try to cover the sky with contrails when it gets hot enough.

[I am new to this model where the length of earth's day cycles, and appears to correlate with and lead Earth's temperature. I'd like to see a technical paper on the subject instead of what is little more than a promotional abstract. The claim that the time of day vs. temperature graph is "irrefutable evidence" is over the top for science. It might be evidence for a physical model, but that model needs to be developed. What is the thermodynamic argument for the length of the day affecting global average temperature?

[To rely on just a data examination, we should see perhaps ten or so cycles, not just two.]

[I also object to correlation assessed by eye, especially from graphs adjusted to give the appearance of correlation.

[A couple of searches more and I discovered Löbert's graphs in Climate Change and Long-Term Fluctuations of Commercial Catches - The Possibility of Forecasting. http://www.fao.org/docrep/005/Y2787E/y2787e00.htm#Contents;. That paper links me to a popular article on the debunking of General Relativity, and a new model called the Seaon Theory. These two are apparently the creation of Löbert himself! http://www.zpenergy.com/modules.php?name=News&file=article&sid=1683. The connection between these budding models and the variation of the length of the day has yet to emerge. This was an interesting and circular excursion, but way too much to research for no payoff with respect to debunking the IPCC AGW conjecture.

[To rely on alternative models to the IPCC model is argumentative, and gives too much credence to the latter, a boat that won't float.]

I enjoy your writings greatly.


CC :-)


I have computed monthly deviations between CO2 level at each of the seven southern stations lying from 40 deg S to the Pole obtained from the NOAA record of monthly averages for ALL Southern Hemisphere stations and the NOAA (monthly) average global CO2 levels for the period 1982 through 2006.

I then computed the average annual deviations for all southern stations from the global annual mean CO2 levels. Note I used strictly ONLY complete year records for each station and dumped any year if it had missed a single month or more. Seasonal effects invalidate computation of an annual mean wherever data for any month is missing.

[RSJ: Handbook algorithms for spectral and correlation measurements respond quite poorly to irregular sampling intervals, including missing data. However, minimum mean square error estimating of means, trends, seasonal effects, forming cross correlations and autocorrelations, and in general MMSSE estimating records by arbitrary functions, using first principles are not terribly complex tasks so long as the data have reliable time tags. Discarding data is unnecessary, suspect for bias, and a poor technique that reduces accuracy.

[When using NOAA and other data, be sure you allow for damage done by processing. Some records may have El Niño or volcano eruptions removed. Some have been regionally calibrated to make records from different sites agree. See RSJ, Gavin Schmidt's Response to the Acquittal of CO2 Should Sound the Death Knell for AGW, comment dated 10/13/07.]

[RSJ: Much of Stephen Short's comment below is lifted from his article on Jennifer Marohasy's fine blog, linked above. That article includes an important chart that illuminates this post. Also, it contains a dialog of comments and criticism, with further explanation from Stephen.

[Stephen Short's post relates to his previous comments. See above at 3/30/08.]

Slight revision of this data has refined the cubic spline R^2 value to 0.6992 for the 1982 - 2006 period. Note the inflection commencing around 1991 (Pinatubo load?).

Northern Hemisphere CO2 levels undoubtedly continued to climb monotonically on an annual scale over the period 1982 – 2006 and we can reasonably presume was accompanied by no significant attendant global warming since about 2000.

However, it appears that after a hiatus in the 1990s, Southern Ocean and Antarctic CO2 levels continue to deviate increasingly, in the negative sense, in relation to the global CO2 average (dominated by data from Northern Hemisphere and Tropical Zone monitoring stations).

[RSJ: The overarching problem of the AGW conjecture is in the domain of thermodynamics. As such, the parameters are macroparameters at the highest level. Some of these are not measurable, such as the primary parameter of interest, the surface temperature, the concept of a planetary albedo, known as the Bond albedo, the insolation, greenhouse gases, and the outgoing longwave radiation. Nonetheless, these parameters, which are all long term, global averages, are estimable and the laws of thermodynamics apply to the estimation and prediction processes.

[Short term variations are the temporal noise of the climate system. Regional variations are spatial climate noise. These are unavoidable in measuring, but by the very intent of thermodynamic modeling, they are below the resolution of a global climate model.

[Even such a coarse partitioning into hemispheres, much less concern about regional pools and gyres of water, are climate relevant only in the context of a set of measurements which span the time and space of the modeling.]

In my view, this southern offset from the global average CO2 level should be getting smaller, not larger, worldwide due to increasing global circulation to accord with present GCM theory.

[RSJ: Global circulation in IPCC terminology is, in general, advection. See the definition at AR4, Glossary, p. 941. Advection is poorly represented, if at all, in the present GCM "theory". For example, read between the lines, paying particular attention to the "cans" and "mays", in TAR at ¶2.6.6, p. 154; ¶, p. 314; ¶, p. 426; ¶7.3.4, p. 438 (re parameterization); ¶7.6.4, p. 452 (THC role not established); ¶8.9, p. 510; ¶14.2.3, p. 775 (ill-understood); and ¶14.2.6, p. 781.

Zones of blooming cyanobacteria directly back-scatter solar radiation due to calcite-producing coccolithophores, which are found everywhere but especially in subpolar regions (Coccolithus pelagicus), thereby decreasing ocean heat retention and cooling the underlying water column.

[RSJ: The biochemistry discussion here appears restricted to the water column, which is the lower section of a GCM cell. These cells span the globe in the simulation, but are poorly connected horizontally. That is, they don't represent advection well at all. This has led the IPCC climatologists to represent the ocean as stagnant pools. Their models ignore the dynamic surface circulation where CO2 is absorbed over most of the globe, fed into the THC circulation, and then outgassed centuries to a millennium later in hot, tropical zones. See previous response at 3/30/08.]

The presence of lipid monolayers due to predation by zooplankton and lysis by cyanobacteriophages enhances the positive effect on albedo.

[RSJ: "Enhances the positive effect on albedo" is redundant and confusing. An increase in ocean albedo would make it less a sink for insolation. Planetary albedo is a dominating negative feedback to global warming, which is not, and cannot be, represented in the GCMs.]

Cyanobacteria also produce the sulfur compound dimethylsulfoniopropionate, which decomposes in sea water into dimethylsulfide, diffuses into the atmosphere, and is oxidized, leading to acidic aerosols that function as efficient cloud condensation nuclei. This also increases albedo over the ocean.

[RSJ:How significant is dimethlysulfide aerosol as condensation nuclei compared to cosmic rays? If the albedo increases over the ocean, then all other things being equal, the planetary albedo would increase. If the dimethlysulfide aerosol formation is temperature dependent, then it would be another cause, in addition to the increase in specific humidity, of the albedo being a temperature feedback. The dominant source of the planetary albedo apparently is cloud albedo, which is temperature dependent. None of this is represented in the GCMs.]

The net effect of these phenomena is to lower surface water temperature and enhance CO2 solubility wherever cyanobacteria occur in high numbers.

[RSJ:The ocean surface currents may be locally cooled (or warmed), increasing (or decreasing) CO2 solubility, but the water continues poleward where at present it is in equilibrium with ice. The THC begins its plunge saturated with CO2 at about 0ºC, regardless of the temperature path by which it arrived.]

It is speculated that cyanobacteria in the Great Southern Ocean entered a phase of higher blooming rates in the early part of the millennium, thereby consuming CO2, increasing oceanic albedo and cloud cover (via dimethylsulfide emissions) and likely significantly cooling the surface of the southern ocean.

Current GCMs tend to demonstrably:

1. overestimate the positive feedback from water vapour over the Pacific in El Niño warming; and

2. underestimate the negative feedback from cloud albedo in El Niño warming - particularly with respect to low altitude cloud.


However, both of these 'offsets' are precisely those one would expect from a warm sea surface with a significant near-surface population of 'blooming' cyanobacteria producing:

• increased low level cloudiness due to enhanced nucleation by (oxidized) dimethyl sulfide emitted by cyanobacteria; and

• increased ocean surface reflectivity (= less sub-surface warming) and reduced evaporation (i.e. effect on the wet adiabatic lapse rate) as a consequence of the presence of calcareous cyanobacteria (coccolithophores) and/or monolayers of lipids, sterols etc at the surface resulting from zooplankton predation and lysis by cyanobacteriophages within and around areas of increased primary productivity.

A good analogy for the latter is the well known use of organic monolayers e.g. using octanol to reduce evaporation off reservoirs and dams.

[RSJ: El Niño is singularly important to weather and has a "profound impact on humanity". But in terms of climate, it is rather unimportant. It causes regional redistributions of heat and humidity, but it is climate noise. What is singularly important to Earth's climate is global cloud albedo. To the extent that the total albedo increases with temperature, it is a negative feedback that regulates global warming as would be caused by greenhouse gases. GHGs hold in the puny longwave radiation from the Earth; albedo holds back the powerful solar radiation. Cloud albedo reduces the closed loop gain of GHGs by about an order of magnitude compared to the open loop greenhouse effect. The GCMs model GHGs open loop.]

Barry Cooper wrote:

[RSJ: Thanks, Barry, I hadn't seen it.

[The book is The Deniers: The World Renowned Scientists Who Stood Up Against Global Warming Hysteria, Political Persecution, and Fraud**And those who are too fearful to do so, written by Lawrence Solomon. He bills himself as "world-renowned environmentalist author and activist", "one of Canada's leading environmentalists", with all that that label entails. He says he "has been at the forefront of movements to … stop nuclear power".

[I am torn between publicizing such a book and ignoring it. I suppose it should be recommended to legislators or Presidential candidates who have been influenced by the claims that a consensus exists in support of AGW, and that the matter is scientifically settled. This scientific fraud is gaining a dangerous and costly momentum.

[The problem with these government figures is action in the face of an abysmal science literacy. They need to be educated in the principles of science. It is never about voting or consensus forming. Such claims are evidence of belief systems and fraud, not science. The IPCC claims should be dismissed on their face.

[Promoting the book, though, gives credence to subjective, unscientific methods. We don't want to contradict the IPCC and Al Gore by mustering a bigger vote. We don't want to contradict a belief system, we want it dismissed. Deny can have either meaning. We want to disprove (invalidate) the IPCC climate model, and in the process lay a foundation for a valid model.

[I am guilty of judging the book by its cover. I did check the index, and fortunately did not find my name.]

Barry Cooper wrote:

It appears to be a compilation of a number of articles published for Canada's National Post. The term Deniers is of course used ironically, since that is the label attached to anyone not on board with "The Consensus".

I understand your points with respect to, in effect, not resorting to the method of demoting the scientific method to vulgar populism, with all the potential for abuse that entails. At the same time, sooner or later, to a greater or lesser extent, the importance of "preventing climate change" will come to a literal vote. People will put in office and keep in office those they feel are best responding either to the "emergency", or the abuse of science by the IPCC, depending on where they come down on the issue.

For this reason, books like this are useful. Yes, he does compile a long list. But he also includes the detailed views of the scientists on the list, and where they believe the IPCC has been sloppy or corrupt, and why.

The number count and the content both go towards a serious effort to correct the effectiveness of the propaganda most Americans--most industrialized nations--have been exposed to for 15 years.

RodD wrote:

Move over IPCC and pay close attention to what the sun has to show about global warming. See the warning of impending catastrophic long term cooling by the Space and Science Research Center in it's letter to world leaders.


[RSJ: This comment could qualify as spam, especially because it's merely an advertisement for a source which is, alas, scientific junk. However, an objective of RSJ is to take on all comers. Further, both the data and the conclusions of the source have a certain validity, so some explanation is needed.

[At the outset, the link, which is to the Space and Science Research Center and there from to a paper called RC Theory by John L. Casey, Director of SSRC, didn't pass the sniff test. It included a link to a presumptuous open letter to the four candidates for the presidency, warning of an impending solar minimum, and intended to counteract the IPCC's prediction of a warming catastrophe.

[The flaws include that the name of the organization was too high falutin' not to have been a part of something recognizably significant. Second, both RC Theory and Casey are unknowns. Third, while a solar minimum is a strong and distinct possibility and would have a huge impact on humans, a theory predicting such an event in any meaningful way would in itself be a spectacular scientific achievement. And fourth, while warning the four candidates off support for the AGW fraud would be also be spectacular achievement on political, social, and economic fronts, unwarranted counter alarms are counterproductive. They bury legitimate criticism in noise.

[The paper, RC Theory, contains some decent graphs from various well-cited sources on solar cycles and Earth temperature. The paper fails, though, to diagram its predictions, overlaid on the data charts. Casey makes the same error the IPCC makes by relying on visual correlations of co-plotted data records. This is deceptive, and produces erroneous results. Correlation is a mathematical relationship between records, and needs to be treated with precision. This paper on Solar Wind, El Niño/Southern Oscillation, & Global Temperature: Events & Correlations demonstrates the proper handling of data and correlation. It is an example of how correct data processing can reveal previously undiscovered events and correlations.

[Casey claims to have found a number of solar periodicities or cycles based on sun spot cycles. His sources are well-labeled with events, including the major Maunder Minimum and the minor Dalton Minimum. From these, he claims to have predicted another, imminent minimum. The presence of a single minimum or two is far from sufficient to establish a cycle of minimums. A rule of thumb is that he would need ten minima. More important than a mathematical prediction though, he needs a physical model for solar activity which can be validated by Earthly observations, and then use that model to predict the time and intensity of the next minimum. He fails these modeling prerequisites of science.

[Furthermore, Earth's climate is stabilized by the hydrological cycle through the negative feedback of cloud albedo. It substantially mitigates the warming predicted by the IPCC and will have the reverse effect of counteracting a decline in solar radiation. Casey and the IPCC have ignored this effect, even to show that it might be negligible, and so both fail to predict climate.

[In the oft-repeated opinion of RSJ, no climate crisis would exist but for the IPCC. To pose alternative climate models, or to rely on data not used by the IPCC, both of which Casey does, is merely argumentative. These approaches to legitimizing the climate story are profuse, and quickly get reduced to unscientific battles of credentials and votes. The RSJ is dedicated instead to debunking the IPCC reports on their specific modeling errors.]

Dan Pangburn wrote:

There is only one complete and exact computer of global climate and that is the planet itself. By definition it complies with all laws of nature including physics and quantum mechanics. Einstein said "no number of tests can prove I'm right but only one is needed to prove I'm wrong". There have been many tests that prove to be wrong the theory that added atmospheric carbon dioxide causes significant global warming. They were run on the planet computer and the results are archived in the Vostok and EPICA ice cores and other proxies. They show that, repeatedly, a temperature increasing trend changed to a decreasing trend and vice versa. For those who understand how feedback works, this temperature trend direction change proves that there is no significant net positive feedback. All that is needed to determine if there is net positive feedback is a temperature trace for a long enough time to average out cyclic variation from random noise and other factors, ENSO, etc. The temperature trace does not even need to be correct in absolute terms just reasonably accurate in relative terms time-wise.

While determination of the magnitude and even the sign of feedback in climate is difficult using climatology, it is trivial, as described above, for someone who understands feedback to deduce from the temperature record that significant net positive feedback does not exist. Many climatologists apparently don't know how feedback works so they don't realize this. Unaware of their ignorance, they impose significant net positive feedback in their GCMs which causes them to predict substantial warming from carbon dioxide increase. Without significant net positive feedback, the GCMs do not predict significant Global Warming.

[RSJ: Your comments go to the core of what science is. It is all about building models of the real world with predictive power. Those models are scale dependent, from the macro level of thermodynamics down to the micro level of atoms and molecules. In between is the sensible level, involving things that man can see and feel and smell. We use technology to extend the boundaries of these three regions, converting observations into measurements and facts, which are the domain of the models. And by this extension of senses, science strives to create unifying models that bridge the boundaries, that mend the seams.

[For the portion of the real world known as Earth's climate, an observation has been overlooked in the state-of-the-art climate modeling, one that ranks observations about feedback. That is the observation that Earth is in a (conditionally) stable climate state, and that it has resided in other such states quite different from the conditions today. A model that denies quasi stable states, that says we are in chaos, in the midst of a climate explosion or implosion, seems to deny the possibility of successful science - to make reliable, significant predictions. A model that says Earth is in an unstable state, that it is at one of Hansen's "tipping points", an allusion to a cone found standing on its point, is an initial condition of probability zero, unobservable and unworthy of perfecting.

[IPCC models have only state. They don't replicate ice ages. Its modeling begins and ends with a state of instability. In its model, a tiny disturbance by man will push the Delicate Blue Planet over the edge. These investigators intentionally initialize their GCMs, as you have observed, with a net positive feedback. By design, they balance their climate models on knife edges, today leaning hot.

[Instead, the modelers should try to discover what causes Earth's climate to be as stable as it is. The scientific question is, how deep is the negative feedback that holds back the conditions on Mars or Venus, on the one hand, or a snow ball Earth, on the other?

[But this powerful school of IPCC climatology doesn't even understand the concept of feedback, at least as it has been defined, developed, and recognized in systems science. It models feedback loops as relations between merely correlated signals, in flow models with neither an input nor an output. See TAR, Figures 7.4 (p. 439), 7.6 (p. 445), 7.7 (p. 448), and 7.8 (p. 454).





[Feedback is a sample of energy, displacement, rates or information from within a system that adds to the driving signal. It is a signal flow, and requires flow variables in the model. System theory defines a closed loop gain by which to assess the strength and nature of a feedback. In spite of extensive discussion of feedback in IPCC Reports, they address none of these concepts from the theory, and indeed its selected paradigm of radiative forcing may be compatible with signal flow. Again as you have observed, IPCC does not understand feedback.

[The net feedback to temperature in the real world is, as it must be, negative. In the present state, the only viable candidate for the controlling negative feedback is cloud albedo, which GCMs model as a fixed fraction. The effect is that GCMs model climate around an open loop greenhouse effect. QED.]

Dan Pangburn wrote:

A strong negative feedback, called the 'iris effect' was discovered by Dr. Richard Lindzen et al. It is described at http://www-eaps.mit.edu/faculty/lindzen/adinfriris.pdf and was referred to in a peer reviewed article, available at http://www.weatherquestions.com/Spencer_07GRL.pdf, published in Geophysical Research Letters, on 9 August 2007. The phenomenon is also described in another peer reviewed article by Dr. Spencer and W. D. Braswell available at http://landshape.org/stats/wp-content/uploads/2008/07/potential_biases_in_cloud_feedback_diagnosis.doc which will be published November 2008 in Journal of Climate. Further study of satellite data on clouds and water vapor is presented in a new article titled "On the Overestimation of Climate Sensitivity Caused by Internal Radiative Forcing by Clouds", by R.W. Spencer & W.D. Braswell, scheduled to be submitted to Geophysical Research Letters by mid-August, 2008. This article addresses new satellite and modeling evidence that previous satellite diagnoses of high climate sensitivity--which directly translate into predictions of dangerous levels of global warming--contain a large spurious bias. It is shown that those exaggerated estimates were the result of faulty assumptions regarding clouds when analyzing variations in average global temperature and average reflected sunlight off of the Earth. A new method to diagnose the total radiative feedback parameter (the inverse of climate sensitivity) called "local slopes analysis", is introduced. A more detailed (yet simplified) explanation can be seen at http://www.weatherquestions.com/Climate-Sensitivity-Holy-Grail.htm. Corrected analysis will result in low climate sensitivity, that is, corrected GCMs would predict that increased atmospheric carbon dioxide does not produce significant global warming. This assessment is described at http://www.weatherquestions.com/Roy-Spencer-on-global-warming.htm .

A completely independent assessment gives an estimate of what the effect on future temperature is for various feedback assumptions. It also determines that there is no significant net positive feedback. It can be seen in a You Tube presentation at http://www.climate-skeptic.com/2008/01/index.html.

Another completely independent assessment argues that "the IPCC's estimates of climate sensitivity must have been very much exaggerated". It can be seen at http://www.aps.org/units/fps/newsletters/200807/monckton.cfm.

[RSJ: Lindzen and Spencer doubt IPCC modeling results showing strong positive feedback resulting from ACO2. Perhaps a fair characterization of their approach is that they seek to discover why Earth is in a stable (or conditionally stable or quasi-stable) state instead of an unstable state. IPCC directs its modeling toward establishing that Earth's climate is unstable. This is a state of probability zero, a statement in the vernacular of system science but with a clear meaning. The view that the climate is conditionally stable is philosophically superior, and should lead to a scientific assessment of what processes effect that stability and what their dynamic ranges (the quantitative limits of control) are.

[Tom Nelson writing in Climate Skeptic at the citation you gave shows that he understands this difference where he discusses stability and feedback.

[Lindzen and Spencer also recognize the powerful effects of clouds as a controlling process, and a process not correctly treated by IPCC. Unfortunately their papers lack the bottom line: how Earth's albedo varies with surface temperature. Also some ambiguity exists with regard to the climate sensitivity parameter among the references you cite and in IPCC reports as well.

[IPCC implies that climate sensitivity is a parameter set for some models (e.g., "climate sensitivity used in the simple model", TAR, p. 13, fn. 10), and that it is a parameter measured as the response within other models (e.g., "factors determining the simulated amplitude of the response, such as the climate sensitivity of the model, TAR, Tech.Sum., ¶E.6, p. 59). Spencer and Monckton describe IPCC climate sensitivity estimates as exaggerated, which is not quite the appropriate word. IPCC did not determine a low value for climate sensitivity, and then overstate it. The intention of IPCC was to produce a high value, one that was not demonstrably false nor beyond the realm of possibilities, but sufficient to destroy life on Earth as we know it at a time just beyond our horizon of credulity or understanding.

[In systems theory, a model will exhibit gain, an increase or decrease in a signal between two reference points. Routinely and where appropriate, gain is modeled as open loop gain and closed loop gain. Climate sensitivity is such a parameter. The system is a model of the climate and the sensitivity is the ratio of the reference temperature increase to an increase in radiative forcing. This sensitivity is affected by a number of loops, principally increased greenhouse gas concentration, namely water vapor and CO2, and albedo. These are loops because the parameters change with temperature to add to the initial cause for the temperature change. If all such loops were left open, meaning that the temperature did not cause the respective changes, then the resulting climate sensitivity would be the open loop gain or open loop climate sensitivity. And if all the loops were closed, the climate sensitivity would be the closed loop value. IPCC closed some loops and ignored others to leave them open.

[For a different introduction along the same lines, see Lindzen, id., p. 425.

[Cloud albedo has a high loop gain, much greater than all the others. A change in albedo as small as the state-of-the-art accuracy with which albedo can be estimated, can, all by itself, have an order of magnitude effect on climate sensitivity. This is due to the fact that it modulates the intense radiation from the sun. IPCC does not model this effect, so for all practical purposes both its climate sensitivity and its greenhouse effect are open loop.

[So IPCC didn't so much exaggerate the climate sensitivity as it allowed its models do so, whether it be an error of omission or commission.

[As discussed here recently, models are scale dependent and perform quite differently at various scales. Sometimes introducing parameters from a finer scale are disruptive and distracting. Macroparameters suitable for thermodynamic models don't mix well with parameters from sensible or microscopic scales. In a global model, regional effects in any of three dimensions may not be appropriate. Yet that is how GCMs work. Global average surface temperature is extracted from a two dimensional network of partially coupled one dimensional (vertical) ocean and air models.

[The climate question is how does the global average surface temperature depend on man's activities. This is a macroparameter question, involving global average albedo, the global average greenhouse effect, and global heat sinks. Conceptually such a model produces a climate sensitivity, another macroparameter.

[Lindzen's analysis is thorough, and includes a representation of the global albedo in terms of many regional parameters. But his paper and the study he describes have a distinctly regional flavor. For another discussion of his iris effect, see the two part paper and especially the rebuttal, "Evidence Against the Iris Hypothesis", beginning at


[The rebuttal is based on discrepancies in tropical results, underscoring the regional flavor of the iris hypothesis. Putting aside all the regional modeling, the problem reduces to the global question, what is the relation between Earth albedo and global average surface temperature?

[IPCC admits that specific humidity increases with increasing surface temperature. That the cloud albedo might at the same time decrease is counterintuitive. The Iris Hypothesis on the global scale is difficult to refute.]

Dr. Gerhard Loebert wrote:


After three decades of continual increase, the mean Earth temperature has been decreasing steadily since 2002, as precise satellite measurements show. World climate is a regular quasi-periodic phenomenon [driven by solar activity with a period of 70 - 80 years (Gleissberg cycle)] that lags the mean Earth rotational velocity by 6 years. Because of this regularity, it can be stated with absolute certainty that the mean Earth temperature will continue to decrease until 2040. (Bold added.)

[RSJ: Absolute certainty is a state of knowledge outside the realm of science. It could be poetic, perhaps even romantic, assuredly philosophical gum-chewing, but always subjective. It is a mental awareness found in both consciousness and a hallucinatory state. Other than as a medical symptom, absolute certainty is not part of the vernacular of science, and applied to climate, it raises an alarm about the speaker. All views on climate are welcome here, but we dice the spam.

[The ellipsis replaces 2000 words Dr. Loebert (Löbert) has splashed as comments across a dozen or two web sites. Some of them, e.g., Free Republic, Canada Free Press, pulled his writing. The reception has not always been kind, e.g., "quack", "nutter". RSJ investigates the merit of those reactions.

[In January of '08, Dr. Loebert discussed his cosmological model with Mitch Battros on a pair of internet broadcasts. Now Battros also runs a high-sounding blog called Earth Changes Media, which publishes Loebert's work. Battros, though, provides no scientific criticism, nor in its stead, credentials that might support his scientific opinions (he has an MS in psychology). To make matters worse, Battros, who is in the business of selling blog subscriptions, salts his science with snippet's of conspiracy theories, embedded in the most radical of anti-Bush shibboleths.

[Regardless, and in response to the broadcasts, Dr. Paul LaViolette addressed Loebert's model:


[For background on LaViolette and his ample credentials, see


[LaViolette, who, it must be admitted, also appears on Mitch Battros' broadcasts, is kind to Loebert, in a way. He gives some credence to Loebert's model. However where he does, he claims Loebert relies on LaViolette's work but without citation.

[Actually, part of Loebert's model might resonate favorably here. Skepticism about the Big Bang and about Einsteinian geometry could be healthy in a scientific argument. But that would be limited to skepticism, to doubt not irrefutability. And that sympathy certainly does not include Loebert's sketchy, naive connection of gravity waves to climate.

[Much of Loebert's deleted comment is found in an article he published on the web, entitled "A Compilation of the Arguments that Irrefutably Prove that Climate Change Is Driven by Solar Activity and Not by CO2 Emission", bold added, dated 3/6/08:


[In Loebert's paper is the following paragraph occuring intact in the deleted portion of his post urging that gravity waves drive the climate:

Irrefutable evidence for the existence of this new, super-Einsteinian wave type is provided by the extremely close correlation between changes of the mean temperature and fluctuations of the mean rotational velocity of the Earth. (see Fig. 2.2 of www.fao.org). Einsteinian theory cannot explain this amazing correlation between two physical quantities that seem to be completely unrelated. Bold added, Loebert.

[The cited figure number 2.2, actually the first and only figure in the paper, bears the following caption:

Dynamics of the detrended global temperature anomaly (dT) and detrended negative Length of Day (-LOD). The ACI ("zonal" form) [RSJ: Atmospheric Circulation Index] has practically no pronounced general trend. Comparison of dT and ACI (Figure 2.2A) shows their close similarity in shape, but ACI runs several years ahead of dT. Shifting the ACI curve by 4 years [RSJ: actually six years in the chart] to the right (Fig 2.2B) results in almost complete coincidence of the curve maximums of the early 1870s, late 1930s, and middle 1990s. Bold added, Loebert.

[To his credit, Loebert knew to rely on detrended data, but his "almost complete coincidence", based on arbitrarily scaling and overlaying two ragged, foreshortened (perhaps 66 years) of Gleissberg cycles (around 87 years) of data, and with no correlation measurement, is preposterous.

[Preposterous, too, are Loebert's subjective phrases "extreme close correlation", "amazing correlation", and "completely unrelated". These show a lack of respect for the correlation statistic and its principles. Without more, his expressions would be unacceptable in a scientific paper. Loebert does go further, saying,

The extremely close correlation between the changes in the mean global temperature and the small changes in the rotational velocity of the Earth in the past 150 years which has been ignored by the mainstream climatologists, leaves little room for a human influence on climate. This close correlation results from the action of galactic vacuum density waves on the Sun and on the Earth. Citations deleted, Loebert.

[But how in Loebert's model do the galactic vacuum density waves cause Earth's rotation alternately to advance and retard? Does he suggest that Earth has a clockwork torsion pendulum, timed by a synchronous gravitational coupling to the cyclical galactic vacuum density waves? When the gravity wave relaxes, what causes Earth to accelerate, to gain angular momentum? Is rotational energy stored somewhere? Or, is his gravity bipolar? Alas, Loebert provides no data on the waves by which one might test the physics of his cause and effect conjecture.

[Contrary to Loebert's claim in his article, Earth's mean temperature and rate of rotation are anything but "completely unrelated". When the atmosphere warms, it expands, increasing Earth's angular moment of inertia. Conserving angular momentum, the rate of rotation should then decrease and the length of the day (LOD) should increase. And when climate cools, the reverse should occur. In this model, temperature would lead LOD. Looking at Loebert's figure, one might imagine not –LOD advanced 6 years, but LOD lagged 27 years. The cross-correlation function should be computed. A dynamic mass model should be constructed to test the contradictory hypothesis to Loebert's model that warming is causing the length of day variations, a reasonable alternative to gravitational waves changing solar radiation and pumping Earth's rotation.

[Speaking of rotation, Battros likes to spin conspiracies, such as,

[Was the Bush Administration Behind Benazir Bhutto Assassination? Battros, 12/29/07


[2nd Gulf of Tonkin Incident Attempted by US Navy

[BAHRAIN - Several reports from highly placed sources in the Pentagon have whispered the Bush administration is provoking Iran to react prior to the end of Bush's term. Battros, undated.

[Shh! All the more believable if whispered! Battros also spins economic waves into Earth physics:

[As predicted by Mayan Elder 'Carlos Barrios' and Mayan Scholar Carl Johan Calleman, author of "The Mayan Calendar", all major networks including the right wing Fox News, are reporting a very serious instability in US financial standings.

[Just this morning on MSNBC, one financial commentator stated "in some circles, there are serious rumors of the US dollar falling to 51% of the Euro-dollar." They went on to say Japan may be next to follow in the devaluation of US currency. It appears the Bush Administration's propaganda of pretending to have a strong economy is in the process of a rapid "implosion".

[It was just a few months ago when I posted highlights from my interview with Carl Johan Calleman who clearly stated "everyone in the world will no longer be able to deny the signs of an economic collapse beginning in November of this year". You can hear this interview by going to our "Audio Archive" page to find our August 26th interview.

[Yes, it does appear highly placed signs are being broadcast by the mainstream media of which "no one can deny".

[I have arranged an interview with Mayan Elder 'Carlos Barrios' for December 7th. Lets hear first hand from those who know as it pertains to predicted escalation of earth changes, and perhaps to some, even more importantly what is in store for our "way of life" as it relates to the US economy. Bold added, Battros.

[Note the wingedness of only Fox News. Note the "clearly stated" economic collapse of 2004, due to currency devaluation, which will unmask the pretenses of the Bush Administration. Focusing on the effect and not the cause, Battros would be omniscient, like a stopped clock, correct twice a day. And on point, note how earth changes might connect to the US economy.

[Battros knows AGW to be false because its revelation parallels the deceit of the Bush Administration:

[Just five short years ago, the world witnessed a scam played on its own people right here in the United States of America. We were sold a pack of lies by the Bush regime based on a true-and-tested method of "scaring you into submission".

[You were told Saddam Hussein and Iraq tried to purchase "yellow cake" uranium from Niger to complete their nuclear weapon. It was a LIE. [RSJ: Actually, it was true.] You were told Hussein had weapons of mass destruction WMD --- it was a LIE. [RSJ: He actually used them.] You were told 9/11 = Iraq --- it was a LIE. [RSJ: Not by the Administration.] Now you are told Iran will have nuclear weapons any day [RSJ: No. Any year.] --- it is a LIE.

[The global warming regime is using the very same formula the Bush regime used with Iraq. Create an 'evil doer', demonize and create false scenarios, scare the public, then come forward as the 'white knight' to save the day, but with a martyrs slant.

[Instead of Saddam Hussein (evil doer), we have human polluters (evil doers). Instead of Weapons of Mass Destruction, we have Global Warming. Instead of the (mushroom cloud), we have the world ice shelves melting. Battros.

[Ignore the politics, but just consider the rhetoric. A tin foil hat makes a mighty big tent. Even in publishing Dr. Loebert's work, Battros inserted his bitty Bush barb into his rave review:

[I am humbled and most grateful for the opportunity to present you with an "exclusive" four part interview with one of the most leading research scientists in "skunk works" technology. This is one of those occasions, when for whatever reason, I was chosen to be the presenter of what is about to be revealed publicly for the first time ever.

[Quite honestly, it is a bit frightening. It is events like what you are about to read which puts me on every SyOPs (security operating procedures) radar screen in the world. But I can't help myself … literally. I am sitting here typing as if I am not attached to my fingers. It is either Divine Intervention, or remote mind control. How's that for woo-woo. But seriously folks, this a bit unsettling, but somehow I know it is my journey to continue.

[Why Dr. Löbert chose me for this project is still not clear. He tells me it because of my stand-alone research with the Sun. I vacillate between this being the greatest honor I have ever experienced in my entire life as a result of my in-depth research for "Solar Rain", to thinking I may be the biggest ego driven fool since Bubba Bush. Whichever way this goes, I am compelled to see it through. If you could see me right now, you would see me shaking my head from side to side thinking "why would a person of Dr. Löbert's caliber choose me to disclose what could be acknowledged as the "next generation of gravitational, quantum, and magnetic physics". Bold added, Battros.

[Woo-woo, indeed! Not research with the Sun; research in the Sun. It's not SyOPs at the door, it's Psy-cho-OPs.

[Nonetheless, the Battros/Loebert admiration is mutual. Apparently fact-less thought attracts fact-less thought. Undaunted, Loebert writes,

[I have been reading the earth changes newsletter of Mr. Mitch Battros, in which he addresses all aspects of the Sun-Earth connection as well as other important humanitarian issues, for a number of years and I have been impressed by the scientific competence of Mr. Battros and by his high ethical standards. I also admire his broad knowledge, dedicated commitment and unusually high diligence. I agree with his views on the physics underlying the Sun to Earth influence. (Of course, I am convinced that one day science will speak of a Galactic Center - Sun - Earth connection.) I wish Mr. Battros the continued professional success that his admirable and exemplary work deserves. Loebert.]

[Battros's question is answered. We see why Dr. Löbert chose him. Why they chose one another. Irrefutability.

[One man's guilt by association is another man's peer review, and vice versa. RSJ wishes them both the continued professional success that their work deserves.

[Gradually the public is becoming aware that AGW is a fraud. It is a black eye for science, with immense economic and humanitarian consequences for no positive gain in any quarter. CO2, once an optimum effluent sought from energy use, has irrationally become a toxicant in the public eye. The cause in debunking AGW isn't helped by counterbalancing with Loebertian or Battrosian nonsense.]

Dr. Gerhard Loebert wrote:


[RSJ: Without addressing the comments on his post from two weeks ago, Dr. Loebert repeats his model, this time more succinctly, but adding a headline, byline, and unexplained six month old date:]


Dr. Gerhard Löbert, Munich. April 24, 2008

[His conjecture that gravity waves are a primary cause of climate change is without merit, as explained with comparable succinctness below.]

In my opinion the researchers in climatology should put aside their present work for a moment and focus their attention on the central and decisive subject of climatology. This is the extremely close correlation between the changes in the mean surface temperature and the small changes in the rotational velocity of the Earth in the past 150 years (see Fig. 2.2 of www.fao.org/DOCREP/005/Y2787E/y2787e03.htm), which has been ignored by the mainstream climatologists. Everything else in climatology follows from this one central theme.

Note that temperature lags rotation by about 6 years.

[RSJ: What Dr. Loebert refers to as "extremely close correlation" is the subjective similarity of two co-plotted records. This is the same highly objectionable practice employed by IPCC, which they use as a substitute for a model encompassing a cause and effect according to principles of physics. Loebert's model has gravity waves alternatively increasing and decreasing the angular momentum of Earth with no supporting physics. Is he perhaps suggesting that because of Earth's eccentricity it is synchronously pumped by gravity waves? The implications seem rather incredible.]

Since temperature is lagging rotation it cannot be influencing the latter. On the other hand, it cannot be envisaged how rotation should influence temperature. Hence, a third agent must be driving the two. The solution is given in www.icecap.us/images/uploads/Lobert_on_CO2.pdf . There it is shown that small-amplitude vacuum density waves generated by the motion of the supermassive objects located in the center of the Galaxy are constantly acting on the Sun and the Earth and are thereby producing a series of physical reactions within these celestial bodies.

[Especially in view of the fact that each of the records, the mean surface temperature and LOD (Length of Day), has a major cyclical component of about 65 years, the lag is the author's arbitrary choice. Loebert should have computed the cross-correlation function between his two records. If he had, he would have had a quantitative correlation at specific leads and lags. More importantly, he might have found the equally strong correlation between +LOD and Temperature, with Temperature leading by about 27 years. This contradicts the position he adopts for his model.

[As noted in response to his previous post, physics provides a temperature cause for the LOD effect. Warming increases Earth's angular moment of inertia by expanding the atmosphere. Conservation of angular momentum then produces a slower rate of rotation, and an increased LOD, with the reverse holding for cooling. This is analogous to the spinning skater extending her arms to slow the spin, and retracting them to accelerate it. With respect to climate, this model needs to be quantified to create a prediction for validation. Regardless, and while it does not begin to solve the riddle of the climate, it does contradict Loebert's model.]

Remember: Everything in climatology follows from this one central theme.

[RSJ. Disagree. Little of import in science is so pat.

[Perhaps Dr. Loebert will engage in a dialog by posting a categorical reply.]

Dr. Gerhard Loebert wrote:


[RSJ: Except for three inserted words and a hyphen ("so-called anomalous"), plus caps, Dr. Loebert's post appears in its entirety as his comment to another blog (http://tomnelson.blogspot.com/2008/06/stephen-wilde-sixth-article-death-blow.html) on 6/7/08. Whole paragraphs of this post can be found on a half-dozen to a dozen web sites. His "Seaon Theory", actually a conjecture, has a possible link to Earth's climate through modulation of the solar wind, but Loebert skips over the evidence and analysis presented on that subject in the Journal.

[Dr. Loebert refuses to engage in a dialog following the responses here to his two previous posts. He may not realize that his cut and paste posts amount to nothing more than spam.

[The policy of RSJ is to respond to all sincere, topical comments, but that does not include cosmological musings. Future submittals by Dr. Loebert will be treated as spam unless they contain either original commentary on climate, or a rebuttal to the RSJ conclusion that his model connecting gravitational waves to climate is without merit.]

Dr. Gerhard Loebert wrote:

Dear Editor,

I kindly ask you to remove my posts of October 14, 27, and 29 with the corresponding RSJ-comments from your website.

Thank you very much.

[RSJ: In exasperation at Dr. Loebert's non-responsive, cut-and-paste posts, the response to his last post included,

[Future submittals by Dr. Loebert will be treated as spam unless they contain either original commentary on climate, or a rebuttal to the RSJ conclusion that his model connecting gravitational waves to climate is without merit.

[Regardless that his most recent post still does not respond to my previous invitation,

[Perhaps Dr. Loebert will engage in a dialog by posting a categorical reply.

[but in recognition of the courtesy expressed in his request I respond in kind.

[Dr. Loebert, not I, introduced the topic of his gravitational wave conjecture. It is relevant to the Journal not just because it relates to climate, but because it urges that previous climate modeling is invalid for omitting gravity wave effects. The responses here comprise responsible scientific criticism of his model, and show that it his conclusions that are not valid.

[Indeed, Dr. Loebert's model led to a positive contribution to climate modeling by his linking of the Length of the Day (LOD) to the global mean temperature. He claimed that the complement of the LOD leads temperature, and therefore modeled LOD as a cause of temperature change. Instead, and as shown in the responses, LOD lags temperature, and that is as expected by the conservation of angular momentum during temperature change. This finding has the potential to improve climate modeling in general.

[Dr. Loebert gives no reason for removing either his posts or my responses. In light of the relevance of the topic, the demonstrated pedagogy of scientific criticism, and the resulting affirmative application to climate modeling, the material should remain on site.

[PS. Dr. Loebert submitted his request a second time 20 hours later. It will not be posted separately.]

Dr. Gerhard Loebert wrote:

The New is always the enemy of the Old. In the last century it was scientific consensus for 50 years that continental drift does not exist. Alfred Wegener received a hostile treatment until the end of his life. Today, he is highly honored.

[RSJ: Dr. Loebert would imply that fault was found for his gravitational wave model for climate change because of its novelty. The reasons instead were based on problems with the physics of his model, as shown in response to his posts.

[Wegener is remembered, among other things, for his 1912 contribution to the theory of continental drift. However, his model attributed the drift to centrifugal force and tidal drag, which could not be supported by physics. Discoveries through the next five decades led to plate tectonics based on convection currents in the mantle. This theory was based on Wegener's sound observations about continental drift. For Wegener, too, Error was the enemy of his New. He is honored more for his observations than for his theories.]

Dan Pangburn wrote:

Those who understand Control Theory (CT) have the tool to recognize that earth's climate can be evaluated as a dynamic system with feedback. Since the sun is the only significant energy source, the model is quite simple. The input (to the transfer function) is the insolation (energy from the sun) combined with feedback from average global temperature (agt). The transfer function includes all factors that contribute to agt. That is part of why it is so simple. An understanding of the science of CT may help to grasp how this works.

[RSJ: Surely the AGW community would deny your claims, point to what they have written on feedback systems, and castigate your brief comments as arrogant, inaccurate, and incomplete. In particular, you discuss a model without providing it. You give no results for the climate in response to CO2 emissions in the industrial era, and rely solely on the paleo record.

[You will find citations and a discussion of IPCC's misunderstanding of feedback loops in the RSJ response to Earl Stone, 12/12/07, Acquittal of Carbon Dioxide. Just Google for "correlation vectors" on this site.

[Even if what you have concluded were true, at the best you have only suggested an alternative model to IPCC's radiative forcing model. The success of the AGW scare and protocol demand that we show more than an alternative model. We need to show that IPCC GCMs are wrong, and why, as is being done here on the RSJ site. When that is done, then you need to show your results.

[You are correct in the sense that a simple heat flow model is quite valuable in understanding Earth's climate. IPCC models have no flow variable, so are far from the mark of an engineering thermodynamic model. IPCC is forced to redefine feedback. In control system theory, feedback is a signal from a response of the system that flows forward to combine with and alter the input signal. Lacking flow variables, IPCC uses feedback to mean a model calculation made at run time. In its reports, it defines feedback loops as closed paths of correlation between elements of its models. IPCC is unable within its paradigm to compute closed-loop feedback gain.

[IPCC asserts repeatedly that the climate is "highly nonlinear", exposing its lack of understanding of linear systems. Linearity is a property of a mathematical representation, not of nature, and it is not a measure for quantifying degrees of nonlinearity. At best, IPCC means that its models of the climate are non-linear. That implies that the responses of the climate to its inputs are not additive. But that is precisely what IPCC's radiative forcing model does. It is initialized in an equilibrium state circa 1750, to which it adds a response due to added CO2. Just considering the nonlinearity in the physics of solubility of CO2 is sufficient to show IPCC's error as an emulation.

[IPCC errs to assume that Earth was in equilibrium at the beginning of the Industrial Era. The ice core data show that it was in a state of rapid warming. The equilibrium assumption has the effect of wrongly attributing background warming to anthropogenic CO2.

[IPCC skirts around solubility, causing the effect to be accounted for partially in the Revelle buffer factor, disagreeing amongst themselves whether the Revelle factor is temperature dependent. The GCMs model the response to CO2 by dumping a slug of it into the atmosphere, assuming it is long lasting. GCMs model neither the ACO2 being absorbed by the ocean, nor the ocean outgassing at 15 times the rate of the ACO2 emissions, nor the temperature dependence of oceanic outgassing and uptake. As a result, IPCC gets the climate wrong by getting the carbon cycle wrong.

[IPCC does not model dynamic cloud formation and the varying albedo, which is the most powerful feedback in the climate system, and it is negative. As a result, IPCC gets the hydrological cycle wrong, and the climate as well.

[Your description of a suitable climate model from control theory is far too brief to have any persuasive power. You have identified the dominating heat source, but none of the heat sinks that would be required in a model. Earth's surface temperature, agt as you call it, needs to be added as a node in your model, connected to deep space and an effective deep ocean by two key transfer functions. The ocean has a highly significant heat capacity, and the path to space includes the greenhouse gases, which contain the variables of concern in the problem.

[Earth transitions endlessly over its history between two states, a warm, wet state regulated by cloud albedo, and a dry cold state regulated by surface albedo. IPCC erred not to make such a model, and you should show in your CT model how that would be the case. To correct IPCC errors, you need to modulate insolation and to have a path for Earth's shortwave reflection. You would want to modulate insolation by both cloud albedo and by orbital mechanics. As you say, this is simple, so when you have something to show, please share it.

[I also have a mass balance model for CO2, which is necessary to support any model for the accumulation of CO2 in the atmosphere. IPCC gives all indications that it relied on a mass balance calculation, but gives no details. The mass balance model shows that the increase in CO2 seen at MLO is dominantly due to natural effects, with a small contribution by man. At the same time, it also shows that the measured isotopic ratio δ13C can be attributed to ACO2 emissions over a wide range of values set for its parameters. The integration of the mass balance model into the climate circuit model has lost significance because of the small contribution of man to the CO2 accumulation and because any increase in greenhouse gas is mitigated by cloud albedo.]

The factors do not need to be explicitly defined. All of the minutia of weather and climate whether known or not get lumped together (in the transfer function). The output is agt. It is not necessary to explicitly describe any of the factors in the transfer function to determine, using the climate record archived in the Vostok ice cores, whether net feedback, if significant, is positive or negative.

[RSJ: Feedback requires a physical signal, which could be in the form of mass flow or heat, that adds algebraically to the input flow variable. Your transfer function modeling implies flow variables, and your reference to net feedback implies multiple feedback paths. But you don't indicate what is fed back or what is modulated.]

As observed on graphs showing temperature trends during the last and previous glacial periods, repeatedly, a temperature increasing trend changed to a decreasing trend. This is not possible if there is significant net positive feedback from temperature.

[RSJ: The Vostok record shows that the climate is stable in the region of record, meaning that the temperature feedback was less than one, but not the polarity.]

Climate alarmists are apparently unaware of the science of Control Theory with which it is trivial to prove, using these ice core records, that there is no net positive feedback in earth's climate. They incorporate features in their atmosphere/ocean global climate models (AOGCMs) that result in significant net positive feedback. This causes the AOGCMs to erroneously predict substantial global warming. Without significant net positive feedback AOGCMs do not predict significant global warming. (Zero feedback results in 1.2°C which is still high because of faulty cloud parameterization etc from doubling of atmospheric carbon dioxide per p631 of ch8 of IPCC AR4.).

Most climate scientists are unaware of the science of Control Theory which helps explain why they made such an egregious mistake. There is no academic requirement for climate scientists to learn about CT. As a result, many climatologists are unaware of that part of science which proves that net positive feedback from temperature does not exist in earth's climate.

[RSJ: The leading climate alarmist has to be Dr. James Hansen. He along with seven other climate scientists are on record relying substantially on control system theory for climate modeling. See Hansen, et al., Climate Sensitivity: Analysis of Feedback Mechanisms, Climate Processes and Climate Sensitivity Geophysical Monograph 29, Maurice Ewing Volume 5, 1984. Follow the download link at http://pubs.giss.nasa.gov/abstracts/1984/Hansen_etal_1.html. The authors rely on a respected if dated source in the field, Bode, H.W., Network Analysis and Feedback Amplifier Design, Van Nostrand, New York, 1945, for "procedures and terminology of feedback".

[Whatever value Hansen's paper might have had, it had no effect on the direction that AGW took, or on the IPCC, regardless that IPCC cited it seven times in References between the Third and Fourth Assessment Reports. Hansen, et al. wrote,

[Clearly, assessment of the cloud contribution to climate sensitivity depends crucially upon development of more realistic representation of cloud formation processes in climate models, as verified by an accurate global cloud climatology. Id., p. 141.

[IPCC has failed this crucial requirement in its entirety. Cloud albedo feedback too small to be measured within the current state-of-the-art estimate of about 0.3 is sufficient to overwhelm warming or cooling from any of the modeled forces, including in particular the greenhouse effect. Earth's climate is not controlled by the greenhouse effect; it is controlled by the albedo.]

[I have a mature, working draft of a thermodynamic heat model that I call a climate circuit model, more or less along the lines that you have suggested and containing many features also found in Hansen's 1984 paper. It has a parametric formula for cloud albedo to evaluate its closed loop and open loop (IPCC) effects. It has a heat capacitance for the ocean which has not been quantified or tested. Without that capacitance, the model replicates the steady state response of the climate, instantly reproducing a climate sensitivity in the IPCC range of estimates. It reproduces IPCC results, which are all open loop with respect to albedo, and shows that closing the cloud albedo loop reduces the greenhouse effect by about a factor of 10.

[The climate circuit model has no provision as yet to replicate Earth's cold state. I need to develop a model for average water vapor concentration, the dominant greenhouse gas, which I expect to be zero in the cold state.

[The long promised publication of this modeling effort has been delayed in part for lack of a good break point. More important has been the discovery and focus on the errors in IPCC modeling, which are fatal in themselves without any reliance on alternative models. These are:

[1. By virtue of the radiative forcing paradigm, IPCC wrongly makes the background of natural climate and the manmade climate change additive in a necessarily non-linear climate model.

[2. IPCC wrongly initializes its GCMs in a state of equilibrium, causing the background of natural warming, which it does not take into account, to be falsely attributed to man.

[3. IPCC wrongly models the surface layer of the ocean to be in equilibrium. This has the effects of causing CO2, contrary to the laws of solubility, to accumulate in the atmosphere, ACO2 to increase the greenhouse effect, the rate of CO2 dissolution to depend on the rate of sequestration in the ocean with time constants into a millennium, and atmospheric CO2 to be well-mixed. The latter has the effect of making the MLO record represent global CO2, and covertly to justify unwarranted calibration of the various CO2 measurements to make them all agree.

[4. IPCC admits that substantial CO2 gradients exist across the globe, but wrongly models the MLO record as global data, ignoring that MLO lies in the plume of the massive Eastern Equatorial Pacific outgassing. At the same time, IPCC ignores that ice core data are collected inside the polar sinks of oceanic uptake of CO2. The concentration of CO2 should be maximal at MLO, and minimal at the poles, but IPCC makes them contiguous or overlapping through arbitrary calibrations.

[5. IPCC wrongly ignores the great planetary flows of CO2 through the atmosphere and across and through the surface layer of the ocean, and then into the Thermohaline Circulation.

[6. For these reasons, IPCC gets the carbon cycle wrong.

[7. IPCC rejects the Svensmark cosmic ray model for cloud cover, then wrongly models no dynamic cloud effect at all. It does so in spite of the strong correlation of cloud cover to cosmic ray intensity, and the correlation of cosmic ray intensity to global surface temperature. Consequently, IPCC does not model the overwhelming feedback in climate, the negative feedback of cloud albedo.

[8. For this reason, IPCC gets the hydrological cycle wrong.

[Another factor in the delay in publishing my models is a pair of effects caused by the on-going, worldwide economic collapse. First, it is changing public priorities away from the phantom global warming scare and onto the real threat of Depression 2.0. Second, it is draining capital from national treasuries and credit that would have been spent on carbon and other green measures.]

Dan Pangburn wrote:

The Climate Science community appears to be unaware of the science that proves that added atmospheric carbon dioxide has no significant effect on average global temperature. See the pdf links at http://climaterealists.com/index.php?tid=145&linkbox=true to discover what really caused the temperature run up in the 20th century and the proof that it wasn't atmospheric carbon dioxide.

[RSJ: I accepted Dan Pangburn's invitation to learn about the true effects of CO2 from his article The AGW Mistake.pdf. He has some good ideas, but without follow-through they are mere speculations. His writing adds nothing quantitative to climate modeling, and he commits a few scientific errors, as shown next.

[He says,

[To effectively use the ice core data it is helpful to define what is meant by a trend. Trends must be for a long enough time to average out cyclic variation from random noise and other factors such as the El Niño southern oscillation (ENSO), Atlantic Multidecadal Oscillation (AMO), and the Pacific decadal oscillation (PDO). To avoid question they should also be substantially longer than any smoothing period that was employed in generating the data set. Thus a trend would be for many hundreds or even thousands of years.

[This is not true at all. The concept of a trend is so elementary that it's definition doesn't cross the threshold to be included in many math books or treatises, in fact, none of which I am aware. A trend is mathematical. It is a line fit to data under some criterion, usually least sum square error, and it promises nothing. It is not a forecast, though it may lead to one, depending on the investigator's modeling skills. A forecast is what must overcome random noise and disturbing events such as Pangburn lists, and that is the engineering subject of detection and estimation theory.

[For an excellent introduction to trend approximations, try the built-in Add Trendline … command in Excel. Build a table of data and graph it with data points but no line. Then select the series by clicking on one point, followed by selecting Chart>Add Trendline …. You will be given a choice of six contours, some with selectable parameters, and some with the option of showing the equation for the line on the chart. Experiment with them all, and try both positive and mixed polarity data. You will learn, for example, that it takes only two points to create a trend line, whether disturbed by noise or not. Try using the Vostok temperature anomalies and try adding 14ºC to change from anomalies back to temperature, and check the difference in trend line options available.

[Unfortunately, the choices provided by Excel don't include the crucially important sinusoids by which one uncovers and estimates cycles in data. Nor do they perform piecewise linear fits to the data, such as one might like to do considering disruptions like El Niño or eruptions. The concept of a trend line arises out of regression analysis, and in general the trend line can be any shape whatsoever. The Acquittal of Carbon Dioxide shows how the relationship between CO2 and Temperature in the Vostok record fits Henry's law of solubility. Excel is still a fine application for finding other trend lines, for which the Solver Add-in, temporarily dropped by Microsoft, is nearly indispensable.

[Pangburn is correct that the data set should be long. A trend always exists in data, even if it's the zero straight line fit. But when Pangburn applied the Vostok record, he only used a third of it, about 140 Kyrs out of 422. The full data set has lots of character, showing unsymmetrical excursions in both temperature and CO2, vacillating together between two extreme states (not modeled by IPCC, by the way). Pangburn erased these properties by abbreviating his set.

[Some texts, especially in economics or business, define trend in the language of time series, where time invariably becomes the independent variable. The mathematical concept of trend knows nothing about dimensions. A good example was available to Pangburn, but he didn't discover it. He should have cross-plotted CO2 and Temperature, as shown in The Acquittal. Then he could have investigated trends in CO2 as a function of Temperature, (CO2(T) in mathematical function notation) and the reverse (T(CO2)). Here he could have modeled CO2 and Temperature independent of any cyclical or unsymmetrical properties by various trend lines.

[Pangburn doesn't cross-plot CO2 and Temperature, but co-plots them with time the independent parameter. This is a good and important technique, especially for investigating the unsymmetric nature of these two time series: quick to warm and quick to increase CO2, and slow in the reverse direction. (A most interesting physical model can account for this dissymmetry.) Pangburn makes some subjective observations from the co-plot, especially suggesting a correlation between the records. He should have quantified what he thinks he sees, making supporting measurements from the data. Whether investigating the dissymmetry or the correlation, he should have used all the available data, especially in consideration of how sparse the data are.

[Subjective correlation is an especially poor technique, and in fact is a red flag for an unscientific analysis. Correlation is over-played with regularity anyway, and the error should not be compounded by subjective correlation. IPCC commits both these rank and unscientific errors, as in its demonstration that the increase in atmospheric CO2 is anthropogenic based reached by co-plotting ACO2 emissions and the atmospheric carbon isotopic fraction. AR4, Figure 2.3(b), p. 138.

[Whether analyzing the dissymmetry, which he didn't catch, or correlation, Pangburn should have used the full, 422 Kyr record.

[Pangburn relies on the theory that CO2 causes warming in proportion to the logarithm of its concentration. He says,

[However, it is well known that added increments of carbon dioxide have less influence than previous increments (logarithmic decline in effect). Since there is more carbon dioxide in the atmosphere today than during the glacial periods, added increments of carbon dioxide today have even less influence than the same size increments did during the glacial periods when they did not drive temperature. Thus added atmospheric carbon dioxide today does not drive temperature. Anthropogenic (human caused) global warming, AGW, which is based on increased atmospheric carbon dioxide, is a mistake.

[This is a good idea. He should have backed it up with the Vostok data showing that the logarithmic model is actually evident in the data. As it stands, the notion is speculation. To make matters worse, his comparison between CO2 levels today and in the glacial period is erroneous (and another error made by IPCC). The levels are not measured by the same techniques, and the glacial set comes from inside a polar CO2 sink while the modern set comes from Mauna Loa, which sits in the plume of massive oceanic outgassing. IPCC calibrates these data to make them agree and appear contiguous when they are not.

[Regardless, even if the records were of the same species and the logarithm theory held, Pangburn has not developed any evidence to conclude that IPCC's model in which CO2 drives temperature is "a mistake". His conclusion is correct, but he arrived at it by leaps. He implies that because added CO2 has a lesser effect than a previous addition (the logarithm model) that it therefore has no effect. From his analysis, it should have a lesser effect, not none.

[Pangburn says,

[Those who understand Control Theory (CT) have the tool to recognize that earth's climate can be evaluated as a dynamic system with feedback. Since the sun is the only significant energy source, the model is quite simple. The input (to the control/plant) is the insolation (energy from the sun) combined with feedback from average global temperature (agt). The control/plant includes all factors that influence agt [average global temperature].

[That's a good idea, but the devil is in the details. James Hansen and IPCC feature feedback in their analyses, but they use the term incorrectly. Hansen co-authored a paper called Climate Sensitivity: Analysis of Feedback Mechanisms published in 1984. In this work, he relies on Network Analysis and Feedback Amplifier Design,, a respected and valuable text by H. W. Bode from 1945. He introduces the concept of feedback gain, but it goes no further in the field. Neither Hansen nor IPCC compute a feedback gain. In fact, the IPCC radiative forcing model is not a flow model, has no flow variable which a gain might multiply. IPCC provides diagrams of climatic feedback loops which include neither a flow variable nor a physical loop, and feedback becomes a correlation between signals. Feedback in control system theory requires a displacement, or a transfer of energy or material, and is not a result of correlation. For discussion, see Solar Wind, El Niño/Southern Oscillation, & Global Temperature: Events & Correlations, RSJ response to Pangburn, 10/2/08.

[If the model is as simple as Pangburn claims, he should publish it. In needs a flow diagram showing the boxes in his model and the flow variables. Will he have a carbon cycle or a hydrological cycle, where the flow variable is CO2 or H2O? Will he include heat or radiation? How will the average global temperature modulate a flow variable as he suggests?

[Pangburn's paper hints at some of the fundamentals of climate modeling, but it does not put the ideas to work. He has not provided the necessary models. The "climate science community" has a vested interest in a most complex model, and is not all likely to give such shallow, qualitative observations any credence. Before the community could be receptive to an alternative model, it has to come to grips with the structural flaws well-hidden within its own narrative. For these, see Fatal Errors in IPCC's Global Climate Models in this Journal.

[Pangburn quotes from Einstein: "No number of tests can prove I'm right but only one is needed to prove I'm wrong." Bold added. Perhaps something got lost in the translation, because he also wrote, "Physical concepts are free creations of the human mind, and are not, however it may seem, uniquely determined by the external world." Evolution of Physics, 1938.

[The problem arises not in the fact that a single experiment can invalidate a model. Instead it is his use of the word prove. Proof is for mathematics and logic, not science. A proof in these domains is conclusive, based on the complete set of theorems and axioms known. (Proof in law is made subjective.) Validation is the test in science. Experiments refine the accuracy and sharpen the domain of a model. A model is a creation of man. It is always an approximation to the Real World, one that is scale dependent, and limited to what can be measured, i.e., reduced to fact.]

Dan Pangburn wrote:

Perhaps it would have been less contentious if I had said 'meant HERE by a trend' instead of 'meant by a trend'. You can't seriously think that I am unfamiliar with the mathematical meaning of trend or the trend line features (and limitations) in EXCEL.

[RSJ: I didn't find your article at all contentious, but rather pedagogical. I thought it important to respond in that vein to help those perhaps mislead by your words or unfamiliar with trend analysis. I was pleased to suggest Excel as both a tutorial and as an analysis aid because of its rapid production of a variety of trend lines.]

I unfortunately occasionally forget to include the word 'significant' when talking about the effect of CO2 on average global temperature. The finding is that there can be no significant positive feedback (engineering usage) from average global temperature.

[RSJ: Misuse, coupled with overuse, of the words significant and exponential is one of my red flags for poor writing. Each has a strong, quantifiable meaning in science and mathematics, and I suggest they be reserved for those meanings. Why raise a ruckus, though, when we turn out classes of high school graduates who can't choose the proper case for pronouns, distinguish between science and a variety of junk like environmentalism, and the list goes on.]

I was wondering if you were aware of the graphic shown at http://chriscolose.wordpress.com/2008/12/10/an-update-to-kiehl-and-trenberth-1997/#comment-902 .

This is an update of the graphic that they produced in 1997 that appears to be widely used (I have seen it in at least one book). I made a simple energy balance model of the processes depicted on the graphics. This (my) work, and other knowledge, revealed at least three misleading things on the graphic. They are described at my June 18 post to that site.

[RSJ: The diagram in its earlier form, and of two slightly different versions, is the core of the IPCC radiative forcing paradigm. TAR, Figure 1.2, p. 90, and AR4, Figure FAQ 1.1, p. 96. One cannot fully appreciate what IPCC has done, or its errors along the way, without knowledge of this diagram. The original paper by Kiehl and Trenberth in 1997 has important, additional information relevant to this diagram that is not reported by IPCC.

[No climate crisis would exist but for IPCC, and because of its size, power, and position, the only debunking worthwhile is its specific work. The fact that updated data are available for the Kiehl and Trenberth model is unimportant and a diversion. No one is going to stop IPCC's massive fraud by publishing corrections to its data, what amounts to weather data in place of climate data, or alternative models that suddenly (in the time frame of more than a century, from Chamberlin, Arrhenius, and Callendar, through Revelle and C. D. Keeling, and on to the IPCC) arrive at different conclusions.

[If you want to be a climatologist, explore where the wind might take you. It's a fertile field to plow. If you want to stop the train wreck of Anthropogenic Global Warming, which poses as science, you should develop such a familiarity with IPCC's Third and Fourth Assessment Reports that you use them, or their references, as the source for information wherever possible. They are available on line, and searchable with Google. Those reports derive and present the upcoming catastrophe, and those reports need to be put on trial. The runaway greenhouse effect arises out of (the ashes of the) original K&T paper.]

Also, I found it interesting to read the Hansen et al 1984 paper where it appears that the mistake got imbedded.

[RSJ: I don't exactly follow what you have in mind as being embedded. Hansen et al. found a legitimate source for control system theory and vernacular, and attempted to apply it to climate modeling. What survives of that effort is little more than the word feedback, worked to death but supplied an altogether different meaning. What has evolved is the AGW community, deserving of the label Cargo Cult.

[For a quick introduction to Cargo Cults as popularized by Richard Feynman in his 1974 Cal Tech commence address, see Huber, P. W., "Galileo's Revenge, Junk Science in the Courtroom", 1991, chapter 10, "The Cargo Cult", pp. 171-2. For a far more extensive and entertaining treatment of the phenomenon going back to missionary days, see Worsley, P. M., "Cargo Cults of Melanesia", 5/57, reprinted on its 50th anniversary in Scientific American, 5/09. All three sources (Worsley, Feynman, and Huber) are available on line.]

Dan Pangburn wrote:

Nicol, http://www.ruralsoft.com.au/ClimateChange.doc, Barrett, http://www.warwickhughes.com/papers/barrett_ee05.pdf, and Hug, http://www.john-daly.com/artifact.htm present calculations showing absorption by the atmosphere of radiation from earth's surface. They do not, however, address thermalization. It appears that they assume that all absorption is thermalized. This does not appear to be compatible with the necessary radiation from the atmosphere back to the surface to comply with conservation of energy.

My energy balance model uses an average surface emissivity of 0.98 for a total radiation from the surface of 382.3 W/m^2. Accepting K&T's value of 40 W/m^2 going through the 'window' leaves 342.3 being absorbed by the atmosphere. Of this, 287.5 must be radiated back to the surface by the atmosphere to meet conservation of energy which leaves 54.7 W/m^2 or 15.98 % of the absorbed energy getting thermalized. This leads to the speculation that on average in earth's atmosphere 15.98 % of earth's LW radiation at any point in the atmosphere close to the surface is always thermalized.

If the above is true then it is straight forward to calculate that LW radiation is reduced by half of the previous level about every 154 meters instead of every 24 meters or so from Barrett's paper and less from the others.

Dan Pangburn wrote:

During further research on the issue of thermalization I discovered an error in my calculation of the distance above the emitting surface of absorption of half of the surface radiation based on Barrett's paper. The residual radiation fraction for 285 ppmv is very nearly exp^(n*X) where n is -0.01306 and X is the distance above the surface in meters (inexact because of 'wings' and pressure broadening). After correction the last paragraph should read:

If the above is true then it is straight forward to calculate that LW radiation is reduced by half of the previous level about every 345 meters instead of every 53 meters or so from Barrett's paper and less from the others.

Dan Pangburn wrote:


Anthropogenic Global Warming (AGW) (and therefore ACC) is a mistake. All of the global average temperatures are readily calculated for the entire 20th century and until the present with no consideration whatsoever of atmospheric carbon dioxide at http://climaterealists.com/index.php?tid=145&linkbox=true . (New analysis (10/16/09) with graph)

The sun has been very quiet for over 32 months. It has not been this quiet (daily average sunspot count less than 4 for the period) this long since the low around 1913 (41 months). 86 of the last 99 days (as of Oct 17, 2009) have been sunspot free. August had no sunspots. The last time there was a sunspot-free month was in 1913. Numerical data for the last 30 days are provided at http://www.swpc.noaa.gov/ftpdir/latest/DSD.txt . SESC sunspot number is calculated the same way as Wolf number. The Little Ice Age and other periods of reduced average global temperature coincide with few sunspots. Sunspot changes appear to be a 'catalyst' for cloud changes and therefore have much greater influence on average earth temperature than total solar irradiance (TSI).

[RSJ: Svensmark's model linking solar activity to climate is far more direct than the "'catalyst'" you suggest. He postulates that Global Cosmic Rays are condensation nuclei, and that they are modulated by solar activity. During periods of high sunspot activity, the greater solar wind sweeps the GCRs past Earth, reducing cloud cover, reducing cloud albedo, and causing climate warming. This is supported by the correlation of cloud cover with the solar wind, but IPCC summarily rejected the model. A change in cloud albedo too small to be measured in today's state-of-the-art is sufficient to change cloud albedo, which, coupled with the temperature dependence of water vapor, creates the strongest feedback in the climate system. It is negative, and it is not represented in IPCC's models. IPCC recites disputes about whether water vapor feedback is positive or negative, comprising the greenhouse effect and including the greenhouse effect in clouds, but excluding cloud cover albedo. With cloud albedo, water vapor dominates and controls Earth's climate. Changes in radiative forcing caused by cloud albedo can exceed observed and projected variations in TSI. During this period of low solar activity that you discuss, we should look for increased cloud cover, greater tropical rainfall, lower specific humidity, and lower temperatures.

[The humidity-temperature relationship is modeled in the GCMs, but it only increases water vapor and its greenhouse effect. The dynamic cloud albedo is missing. That omission makes IPCC's simulated greenhouse effect dominantly open loop. Closing the loop can be shown (model to be published) to reduce the climate sensitivity by an order of magnitude. IPCC's conclusion that the greenhouse effect regulates climate is wrong. The regulating mechanism is albedo, cloud albedo in the warm state, and surface albedo in the cold state.

[We need to focus on the errors in the AGW model, and that was made obvious a second time this week when I sat through "Not Evil, Just Wrong".

[Not Evil, Just Wrong

["Not Evil, Just Wrong" is a tedious, 85 minute film by Phelim McAleer, director, and Ann McElhinney, claiming to show "the real world consequences of acting on global warming fears" (Wall Street Journal) and to be "a devastating account … of Mr. Gore's brand of self-interest and hypocritical alarmism" (National Post (Canada)). Those featured endorsements draw immediate suspicion because Bret Stephens, columnist for the WSJ, and the Canadian debunker team of Stephen McIntyre and Ross McKitrick appear prominently in the film, taking nothing from their individual contributions.

[Phelim McAleer, by the way, was the journalist at a press conference whose microphone was turned off when he asked Gore one embarrassing question too many. He was probing what Gore was going to do about the nine errors a UK court found in his multiple prize winning An Inconvenient Truth. "Not Evil…" shows the cover page of Mr. Justice Burton's decision, but does not examine each his nine errors.

[Those media endorsements are unfortunately accurate. "An Inconvenient Truth" relates the AGW threat with some fidelity, repeating fatal errors in IPCC's conjecture and its Global Climate Models. However, "Not Evil…" scarcely lays a glove on Gore in debunking the climate story he parrots, the "Wrong" part. Long segments of the film are dedicated to reviewing the well-known disaster visited on humans by the ban on DDT, endorsed ex post facto by Gore, and on anecdotal stories of people along the Indiana-Kentucky border who will lose their livelihood when the moratorium Gore endorses is placed on coal fired electric power generation, the "Evil" parts. The link between Gore and the gore of the DDT ban was too flimsy to support the time spent on the unintended and irresponsible costs in lives and the health of indigenous people in Asia and Africa (30 million killed; a few hundred millions debilitated). "Not Evil …" features Gore's endorsement of the 1994 edition of Rachel Carson's Silent Spring, but it needed strengthening with quotations from, or better reenactments of, his endorsement to hoist him by his own words. Not evil? That might depend on one's religious views, but surely mass homicide by reckless disregard for human life.

[If Gore's awards were still in doubt, he could have said about the DDT that that was a different matter, and while it might have been handled better, it did prevent an ecological tragedy. He would say of the 7 million jobs to be lost in the coal industry, that it can be handled by the usual retraining, and that it's necessary to save the lives and property of "a hundred million or more" residing along coastlines from Manhattan to Bangladesh.

["Not Evil …" also uses skillful editing to ridicule actor Ed Begley, Jr., and climatologists Dr. Stephen Schneider and Dr. James Hansen – deserving characters to be sure, but it does diminish the documentary.

[The movie reports on McIntyre, especially, and McKitrick debunking Mann's Hockey Stick, IPCC's acceptance of it in its Third Report, and its dropping the idea in its Fourth Report. "Not Evil…" also tells how McIntyre uncovered an error in recent temperature records that debunked Gore's and Hansen's claim that the climate in recent years reached record high temperatures. Better, it could have said a lot more, such as IPCC rehabilitating the Medieval Warm Period and Little Ice Age instead of erasing the Hockey Stick with little fanfare. Best, "Not Evil …" might have underscored the issue by being more obvious that Gore's movie relied on the discredited Hockey Stick as fact.

[In "An Inconvenient Truth", Gore talks about a thousand years of temperature and CO2 records that "closely fit together." Then he says,

[Now, a thousand years of CO2 data in the mountain glacier. That is one thing. But in Antarctica, they can go back 650,000 years. This incidentally is the first time anybody outside of a small group of scientists have seen this image. [Chart 00_23_53] …

[Now an important point: In all of this time, 650,000 years, the CO2 level has never gone above 300 parts per million. Now, as I said, they can also measure temperature. Here is what the temperature has been on our earth. … The relationship is very complicated. But there is one relationship that is more powerful than all the others and it is this. When there is more carbon dioxide, the temperature gets warmer, because it traps more heat from the sun inside.

[Sources: A unofficial transcript of "An Inconvenient Truth" is available at http://forumpolitics.com/blogs/2007/03/17/an-inconvient-truth-transcript/ , complete with embedded charts. A more legible copy in two parts is at http://global-warming-truth.com/environmental-tv-movies/unofficial-transcription-of-an-inconvenient-truth-1.html . However, in neither transcript are the charts the same as those used in the movie. The charts can be seen separately at http://web.ncf.ca/jim/ref/inconvenientTruth/index.html , where the quality is poor. Gore's charts are neither numbered nor attributed. The key chart discussed below is shown partially at time 00_22_49 and more completely but still badly keystoned at 00_23_53. A better view of 00_23_53, annotated where the text is unclear, is available on http://www.flickr.com/photos/80992994@N00/380193705/sizes/o/ , along with two other charts not on web.ncf.ca. Gore's data in chart 00_23_53 appears to be taken in part from IPCC'S Fourth Assessment Report, Figure 6.3. It can be viewed on p. 444 at http://ipcc-wg1.ucar.edu/wg1/Report/AR4WG1_Print_Ch06.pdf . Note: Figure 6.3 is missing the units, kyr, on the abscissa scale.

[Let's count some errors by Gore just in this snippet on ice core data from the transcript.

[Gore's First Mistake: Gore's 00_23_53 chart is an extraction of two traces from IPCC's Figure 6.3, to which he has added a vertical tail to the CO2 curve for the future, and changed the name of the deuterium curve, δD (‰), to "Temp. in F" with no discernable scale. Gore's "small group of scientists" responsible for this chart doctored it, though not in any particularly unique way, but nevertheless in a manner specifically rejected by IPCC. The panel said,

[The main reason for the current concern about climate change is the rise in atmospheric carbon dioxide (CO2) concentration (and some other greenhouse gases), which is very unusual for the Quaternary (about the last two million years). The concentration of CO2 is now known accurately for the past 650,000 years from Antarctic ice cores. During this time, CO2 concentration varied between a low of 180 ppm during cold glacial times and a high of 300 ppm during warm interglacials. Over the past century, it rapidly increased well out of this range, and is now 379 ppm (see Chapter 2). For comparison, the approximately 80-ppm rise in CO2 concentration at the end of the past ice ages generally took over 5,000 years. Higher values than at present have only occurred many millions of years ago (see FAQ 6.1).

Temperature is a more difficult variable to reconstruct than CO2 (a globally well-mixed gas), as it does not have the same value all over the globe, so that a single record (e.g., an ice core) is only of limited value. Local temperature fluctuations, even those over just a few decades, can be several degrees Celsius, which is larger than the global warming signal of the past century of about 0.7°C. AR4, FAQ 6,2, p. 465.

[CO2 is not globally well-mixed as IPCC's own reports admit, and C. D. Keeling himself warned against intermixing CO2 data from sinks and sources, e.g., from within a polar sink and the MLO record, situated as it is in the plume of a massive CO2 source. Regardless, the Carbon Dioxide Information Analysis Center, U.S. Department of Energy, provides information and data on the Vostok ice core historical record at


[and on the EPICA Dome C ice core historical record at


[Both state from the same sources that

[there is a linear relationship between the average annual surface temperature and the snow deuterium content. The slope of this δD/surface temperature relationship was found by Jouzel et al. (1993, 1996) and Petit et al. (1999) to be 9 ‰ per °C.

[However, neither data set contains a linear relationship between temperature and δD, and the best fit lines to the relationship is about half the quoted 9 ‰ per °C. A PowerPoint presentation by Eric Wolff of EPICA reports on studies of the relationship by various investigators who bring in additional parameters of dust, oxygen isotopic ratios, carbon isotopic ratio, ice volume, insolation, and other palaeocean proxies. However analysts might have made the temperature reductions, the data were not the result of a linear transformation between the deuterium ratio and temperature as the Trends articles strongly imply, and as Gore's chart suggest was done by his small group of isolated scientists.

[IPCC had ample justification for not converting the deuterium record into a temperature record. Of course, IPCC had an ulterior motive because the temperature reduction from the Vostok ice core data had the most embarrassing effect of showing that temperature led CO2, not the other way around as its model required. Undaunted, IPCC declared that CO2 amplified the temperature rise from natural causes. It provided no support for this claim whatsoever, not even an analogy to another branch of physics to demonstrate the mathematics of such an amplification.

[Whoever prepared the transcript of "Truth" had the good sense to replace Gore's doctored chart with a simpler and valid chart containing three unaltered traces from IPCC's Figure 6.3. However, that replacement left transcript Gore saying "Here is what the temperature has been on our earth" with no temperature record on the screen.

[Gore says in "Truth",

[But the scientists that specialize in global warming have computer models that long ago predicted this range of temperature increase.

[At this point, Gore is referring to the Hockey Stick graph. His version of the Hockey Stick is the left hand side of his chart 00_20_53. In the transcript, someone replaced his version with a faithful reproduction of IPCC's version from the Third Assessment Report, Figure 2.20, p. 134. This is another error shared by IPCC and Gore, since the Hockey Stick reduction was discredited and discarded by IPCC. It is an error tangential to counting the errors in Gore's presentation on ice core data. The point here is that "Truth" provides no sources for its data except for this thin admission that it relied on climatologists and their computer models. In presenting the ice core record, Gore altered data to create a temperature record where none existed, where the matter is unsettled, and where IPCC refused to accept the proxy derivation of temperature from the deuterium ratio.

[Gore could have used the Vostok record which goes back 420,000 years and contains a temperature reduction. That should have been dramatic enough for his audience. IPCC has relied on this record (TAR, Figure 2.22, p. 137), and did not repudiate it in the Fourth Assessment Report even though it was invalidating of its anthropogenic global warming model. At least this way he'd have had a valid temperature record to illustrate his documentary instead of the invalid Hockey Stick and his concocted record.

[Gore's Second Mistake: Gore repeats that the CO2 has never exceeded 300 parts per million in 650,000 years. The interval between ice core samples is about 1,300 years, based on the 420,000 year data set. The present record exceeding 300 ppm has existed for just 50 years. Such an event could be hidden between samples in any of the records, and with 96% probability (1–50/1300) of not being detected. If the firn takes a century to close so that each sample represents a 100 year average, then ignoring that the level would be lower, the odds of detection double from around 4% to over 7%. In other words, the accuracy in saying that 300 ppm has never occurred is not the usual statistical threshold of a 80% to 95% confidence level, but around 4% to 7%, far worse than a guess. What Gore has done is equivalent to cutting a deck of cards for a red ace, and when another card turns up, to proclaim that the deck has no red aces. IPCC makes the same mistake.

[Gore's Third Mistake: Gore claims the ice core temperature and CO2 records are linked. This is Mr. Justice Burton's error 4, who only decided that the claimed coincidence was not established by the graph. The coincidence does exist, though not in the way Gore imagined, but that requires analysis with Vostok, 420,000 year data set and not the EPICA Dome C, 650,000 year set. See The Acquittal of CO2.

[Next Gore says that the present CO2 level is off the chart, implying that warming is going off the chart, too. But if he had used the valid chart, he would have seen four preceding warm states for the climate that run about 1ºC to 3ºC above the present. So notwithstanding any record CO2 levels, Earth has yet to match the four warmest periods in the last half million years. We have 1ºC to 3ºC to go from natural causes. And, from the way things look for the last decade plus, we're not on track to match the natural record.

[Gore's Fourth Mistake: Gore implies that more CO2 causes more warming. In fact, the warming precedes the CO2 in the only ice core record he could have used legitimately. The real conclusion is that more warming causes more CO2, and this is supported by Henry's Law of solubility, which IPCC never mentions and fails to use. Any CO2 that man emits accumulates a little everywhere, and can only cause warming in the atmosphere, but that warming is far too small to be measured.

[Gore's Fifth Mistake: Gore's concocted graph runs the ice core CO2 measurements right into the modern measurements taken principally at Mauna Loa. The MLO measurements are the most extensive, and IPCC adjusts measurements from other stations so they all agree with MLO. Hooking the two records together causes an almost instantaneous rise from around 280 ppm to about 315 ppm at the start of MLO record, rising to 370 ppm by 2000, and then to about 500 ppm in another 50 years. What Gore's small group of scientists should have done is adjust the two records for their location. The ice core data are collected inside the South Pole CO2 sink, and should be well below the global average. The MLO date are collected in the plume of CO2 outgassing from the Eastern Equatorial Pacific, and should be well above the global average. The two records should not connect.

[Gore's Sixth Mistake: Gore says of the CO2 increase, "If we allow this to happen, it is deeply unethical." He, like IPCC before him, implies that the high CO2 at MLO is manmade, when it is not. The ocean outgasses 15 times as much CO2 as man emits, and the amount it outgasses depends on the sea surface temperature at the time, increasing when the temperature is rising. And we know from the record that the temperature rises naturally, and brings the CO2 along with it.

[IPCC claims that half of manmade CO2 persists in the atmosphere, while at the same time it says every year the ocean absorbs all the natural CO2 emitted. Manmade CO2 is slightly lighter weight, but far from enough to make a measurable difference in its rate of absorption in water. Man is adding CO2 to the atmosphere and to the ocean, but the CO2 in the atmosphere has been 20 times as great in the past with no known harmful or warming effects. See TAR, Figure 3.2(f), p. 201, where four estimates of atmospheric CO2 have run as high as about 6,000 ppm, and the modern level is nearly a historic low. The claim that the observed increase in CO2 is manmade violates an established law of physics: Henry's Law of solubility.

[Gore's Seventh Mistake: Gore says that CO2 traps heat inside. For this he may be excused, but not his technical sources and advisors. Even though he studied under Revelle, he probably never took first year thermodynamics. It teaches the how and the why of heat being the flow of energy from a warm body to a cooler one. It can never be trapped.

[IPCC made more mistakes based on the Vostok record, but Gore didn't repeat them all. For example, IPCC initializes its models to be in equilibrium in year 1750. The ice core records show that CO2 and temperature were both increasing at initialization. That increase was natural, and per force became falsely attributed to man in IPCC's model.

[None of Gore's errors is unique to him, but by not crediting his sources, and instead boasting of his credentials from studying under Revelle to his public responsibilities on "science round tables and the like", and writing "a book about it", he has earned the full rack of albatrosses.

[The problem here is that faux science needs to be debunked with real science, and for that, plenty of ammunition remained untouched in Gore's film. Contrary to its title, "Not Evil, Just Wrong" emphasizes the evil over the wrong. It's counter offensive is little more than whining, and being a weak defense it tends to validate the initial fraud. A proper debunking should not rely on ad hominem attacks for tangential past errors, i.e., the DDT mass homicide. Nor should an answer try to thwart misguided wishes to rescue the planet with sob stories about the few millions who will be displaced in order to protect hundreds of millions allegedly threatened. The displaced certainly can be relocated and retrained to save humanity from the deluge. The federal government can do anything – prospectively. There will be no deluge, either.

[Global warming may happen, but it will be neither manmade nor anything soon. An ice age is quite probable, too, and indeed may be the next climate extreme in a few score millennia. Possible, too, is a collision with a meteor, and almost certainly and most imminent of all, a super eruption of Yellowstone. Man can do nothing to prevent any of these, but could far better spend his technology toward a plan for survival rather than futilely crippling the economy that produces the technology.]

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This page contains a single entry from the blog posted on July 6, 2007 6:42 AM.

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