Rocket Scientist's Journal tag:www.rocketscientistsjournal.com,2008://1 2007-12-15T07:06:25Z Movable Type 3.31 SOLAR WIND tag:www.rocketscientistsjournal.com,2007://1.57 2007-07-06T13:42:20Z 2007-12-15T07:06:25Z SOLAR WIND HAS TWICE
THE GLOBAL WARMING EFFECT
OF EL NIÑO

THE CONSENSUS ON CLIMATE
MISTAKENLY ATTRIBUTES SOLAR WIND WARMING
TO MANMADE CARBON DIOXIDE

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SOLAR WIND, EL NIÑO/SOUTHERN OSCILLATION,
& GLOBAL TEMPERATURE:
EVENTS & CORRELATIONS

by Jeffrey A. Glassman, PhD

ABSTRACT

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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INTRODUCTION

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, ¶6.11.2.2, 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.

DATA SOURCES

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., ¶2.7.1.3, 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 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. The Third Assessment Report charts them in Figure 7.9 after subtracting the average for the first 100 years. [Rev. 7/10/07] 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.


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

Solar Wind Index (“aa”) data start January, 1868. ftp.ngdc.noaa.gov/STP/SOLAR_DATA/RELATED_INDICES/AA_INDEX/ [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, ¶6.11.2.2, 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.


SIGNAL ANALYSIS

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.
Landscheidt

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.

Köhnlein

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.

CONCLUSIONS

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, ¶6.11.2.2 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.

BIBLIOGRAPHY

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.

]]> CO2: "WHY ME?" tag:www.rocketscientistsjournal.com,2007://1.56 2007-06-11T19:43:55Z 2007-10-10T19:21:53Z ON WHY CO2 IS KNOWN NOT TO HAVE ACCUMULATED IN THE ATMOSPHERE & WHAT IS HAPPENING WITH CO2 IN THE MODERN ERA by Jeffrey A. Glassman, PhD Myles Goodman at Drexel posted the following question as a comment to...
ON WHY CO2 IS KNOWN
NOT TO HAVE ACCUMULATED IN THE ATMOSPHERE &
WHAT IS HAPPENING WITH CO2 IN THE MODERN ERA

by Jeffrey A. Glassman, PhD

Myles Goodman at Drexel posted the following question as a comment to the Acquittal of Carbon Dioxide:

You posit that CO2 does NOT accumulate in the atmosphere. How do you explain atmospheric concentrations of CO2 increasing over the last 100 years?

The Acquittal shows that carbon dioxide did not accumulate in the atmosphere during the paleo era of the Vostok ice cores. If it had, the fit of the complement of the solubility curve might have been improved by the addition of a constant. It was not. And because the CO2 presumably still follows the complement of the solubility curve, it should be increasing during the modern era of global warming in recovery from Earth's various ice epochs. These conclusions find support in a number of points in the IPCC reports.

So the answer to the post begins with supporting background on why CO2 is known not to accumulate in the atmosphere, and then goes on to other aspects of the model that global warming causes increases in CO2, which accounts for the last 100 years or so.

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1. Estimates vary, but climatologists in the Consensus say that the atmosphere contains 730 GTons (PgC) of carbon and the uptake to the oceans alone is at least 90 GTons/year. It's a ninth grade algebra problem to calculate how long it takes to empty a bucket with 730 units at the rate of 90 units per year. If you throw in uptake by photosynthesis at 120 GTons/year and perhaps leaf water at the IPCC figure of 270 GTons/year, thus including everything in the IPCC's Third Assessment Report, 480 GTons a year is pouring out of the bucket.

Now throw in approximately 100% replenishment, and you have an eleventh grade physics or chemistry problem where the level in the bucket is only slowly changed but the solution is quickly diluted.

Regardless of which way one poses the problem, the existing CO2 in the atmosphere has a mean residence time of 1.5 years using IPCC data, 3.2 years using University of Colorado data, or 4.9 years using Texas A&M data. The half lives are 0.65 years, 1.83 years, and 3.0 years, respectively. This is not “decades to centuries” as proclaimed by the Consensus. Climate Change 2001, Technical Summary of the Working Group I Report, p. 25.

See The Carbon Cycle: past and present, http://www.colorado.edu/GeolSci/courses/GEOL3520/Topic16/Topic16.html & Introduction to Biogeochemical Cycles Chapter 4, http://www.colorado.edu/GeolSci/courses/GEOL1070/chap04/chapter4.html, UColo Biogeochem cycles.pdf; The Carbon Cycle, the Ocean, and the Iron Hypothesis, http://oceanworld.tamu.edu/resources/oceanography-book/carboncycle.htm

2. In 1985, Keeling provided two estimates of the residence time (the reciprocal of his global air-sea transfer coefficient) and uptake of CO2 in the entire oceans, based on different methods from different locale. They were 7.9 years for 2 GTons/year and 5.2 years for 4.35 GTons/year. 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. No one today uses such small numbers for the uptake, so the residence time must be much less than Keeling suspected.

3. There are no separate, physical paths to pipe natural CO2 and anthropogenic CO2 in the atmosphere or to segregate them in any other reservoirs. There is a theory of plant isotopic preference, and a theory of isotopic bias comparing natural and manmade CO2, but the Consensus has not posited such an effect in the carbon cycle exchange between the atmosphere and the reservoirs. In fact, the Consensus accounts for the difference in the concentrations in carbon isotopes in the atmosphere and the ocean not by selective solubility but by selective photosynthesis in the ocean. Climate Change 2001, p. 207. Natural and anthropogenic are indiscriminately mixed in the atmosphere, and undergo similar if not identical residence times.

4. Sidebar: By losing its long residence time assumption, the Consensus finds its well-mixed conjecture invalidated. The admission in the TAR of CO2 gradients over the globe also contradicts its well-mixed claims. Independently, gradients must exist because of the highly concentrated outgassing of CO2 from equatorial waters, and the balancing concentrated polar uptake. Consequently, the concentration of CO2 depends on where it is measured. Keeling himself warned not to mix CO2 measurements without regard to sinks and sources. He used calibration techniques to mix records.

5. The TAR says,

CO2 naturally cycles rapidly among the atmosphere, oceans and land. However, the removal of the CO2 perturbation added by human activities from the atmosphere takes far longer. This is because of processes that limit the rate at which ocean and terrestrial carbon stocks can increase. Anthropogenic CO2 is taken up by the ocean because of its high solubility (caused by the nature of carbonate chemistry), but the rate of uptake is limited by the finite speed of vertical mixing. Climate Change 2001, Technical Summary of the Working Group I Report, p. 51.

The first sentence is semantic gamesmanship to imply that CO2 cycles rapidly only if the CO2 is natural. That conjecture is made specific in the next sentence. The rest is fraught with error.

The physics of gas solubility in water is well-established, and should not be changed to suit the AGW conjecture. Solubility depends on the partial pressure difference of the gas and water temperature. It is not known to depend on ionic concentrations in the liquid (including the pH (see Climate Change 2001, p. 185)), nor on carbonate or any other chemistry. By the minimizing isotopic fractionation in ocean exchanges, above, the Consensus dismisses the possibility of any solubility preference between anthropogenic and natural CO2 based on the distribution of carbon isotopes.

Nor does solubility favor natural CO2 over anthropogenic CO2 based on the rate of vertical mixing. It is the same for both. There is no centrifuge effect to segregate heavy CO2 from light CO2.

One would expect no chemical reaction between ions in the ocean and molecular CO2 in the atmosphere. Solubility should be a purely physical process bringing CO2 into solution where it can dissociate first and then participate in the chemical reactions.

6. The IPCC provides the following data in Climate Change 2001:

Parameter Value  Page
Fossil fuel CO2 uptake to emissions ratio [u/e]    50%  187
Ocean CO2 uptake, PGC/yr    90  188
Land CO2 uptake, PGC/yr    120  188
Calculated total uptake, nominal    210        
Fossil fuel emissions, 1980-1989, PGC/yr    5.4  185
Fossil Fuel emissions, 1990-1999, PGC/yr    6.3  185
Calculated Fossil Fuel emissions, average    5.8      
Ratio CO2 total increase to Fossil Fuel emissions, 50%/yr    2.9  187
Total ACO2 = Fossil Fuel emissions/(3/4)     7.8  185
El Niño reduced emissions, min, PGC/yr    0.2  185
El Niño reduced emissions, max, PGC/yr    1  185
Estimated El Niño incidence    50%      
Calculated El Niño reduced emissions, weighted average, PGC/yr    .3        
Net gain in CO2, PgC/yr    3.3  185

Note: 1 Petagram (Pg) = 1 Gigaton (GTon)

So the natural

u/e = 210/207.8 = 101.06%,

a net uptake of CO2 from the atmosphere. Adding ACO2 emissions and crediting the El Niño reduction in natural emissions,

u/e = 211.9/215.2 = 98.41%,

is a net addition (denominator - numerator) of 3.3 PgC/yr.

Next the IPCC segregates anthropogenic parts in both the numerator and denominator

u/e = (2.9 + 209.2)/(5.8 + 209.4)

but converts it into

2.9/5.8 + 209.2/209.4 =

50% explicit fossil fuel CO2 emission reduction +

99.80% implicit natural CO2 emission reduction.

Only in IPCC algebra does

(a+b)/(c+d) = a/c + b/d.

This is the result of assigning net transactions, whether fluxes or radiative forcings, to individual components in the transaction without physical justification. Consensus physics here is no better than its algebra. Because measured increases in CO2 concentration appear to be correlated with reasonable estimates for the growth of anthropogenic emissions, the Consensus assumes it has established a cause and effect relationship. Assuming correlation implies cause and effect is the same error the Consensus made in assuming that the increase in CO2 caused the increase in temperature in the Vostok ice core reductions.

Until the Consensus can show that the solubility of CO2 in water depends on the carbon isotope or some other as yet unknown property differing between natural and manmade CO2, the IPCC data support the conclusion that all CO2 is reduced by the same number, approaching 98.41% per year.

7. The Consensus says,

Although there is sufficient uptake capacity in the ocean to incorporate 70 to 80% of foreseeable anthropogenic CO2 emissions to the atmosphere, this process takes centuries due to the rate of ocean mixing. As a result, even several centuries after emissions occurred, about a quarter of the increase in concentration caused by these emissions is still present in the atmosphere. To maintain constant CO2 concentration beyond 2300 requires emissions to drop to match the rate of carbon sinks at that time. Climate Change 2001, Technical Summary of the Working Group I Report, p. 75.

This argument, at the crux of the Anthropogenic Global Warming alarm, is contradicted by the Consensus' own data. Considering the uptake to the ocean alone, which is at least 90 GTons/year, the Mean Residence Time of the 730 GTons of atmospheric CO2 is 8.1 years, and the half life is 5.3 years. The CO2 concentration is down to one quarter in twice the half-life, or 10.6 years, more than an order of magnitude less than several centuries.

Thus the Consensus bases its key argument on its fallacious 50% calculation, which it then applies to its scenarios of accelerating anthropogenic CO2. That calculation nakedly assumes different residence times for anthropogenic and natural CO2. Instead of centuries, the Mean Residence Time of both kinds of CO2 is 8.1 years, based on elementary mathematics applied to the Consensus' own data on the oceanic uptake alone. Relative to the Consensus model, CO2 does not accumulate in atmosphere.

8. The Consensus says in the same section of the TAR,

Before the Industrial Era, circa 1750, atmospheric carbon dioxide (CO2) concentration was 280 ±10 ppm for several thousand years. It has risen continuously since then, reaching 367 ppm in 1999.

The present atmospheric CO2 concentration has not been exceeded during the past 420,000 years, and likely not during the past 20 million years. Climate Change 2001, p. 185.

The 420,000 year figure was the greatest age of the Vostok CO2 data, which achieved peaks of about 300 ppm. See IPCC Figure 3.2(d) on page 201. A rough straight line fit to the Mauna Loa data (Figure 3.2(a), page 201) shows the measurements have exceeded 300 ppm for roughly 50 years.

Check the Vostok data. ftp://ftp.ncdc.noaa.gov/pub/data/paleo/icecore/antarctica/vostok/deutnat.txt. The CO2 samples number 283, covering 414,085 years. The average spacing is 1463 years. The chances of sampling an epoch like the present 50 year record, if it existed, is about 50/1463 or 3.4%.

That translates into a 3.4% confidence level for the statement that the present CO2 trend was unprecedented in the last 420 Kyears. That confidence level does not begin to rise to an acceptable standard for a scientific conclusion.

This unprecedented claim is a mantra of the Consensus. It made a normal scatter plot of the Vostok data, but then seduced itself by connecting the dots!

9. The Vostok record (Figure 3.2(d)) shows five peaks in 420,000 years. What are the chance that the peaks shown are below the true maximum given that the average sample interval is a millennium and a half? A. The chances are about 96.6%. Thus the confidence is greater than 95% that any measured maximum is more than 50 years from the peak CO2.

10. So the question about the CO2 record for the last century asks for an explanation of an implicit exaggeration of an exaggeration. The measured record is actually only 50 years old, and it may show a high rate of CO2 growth. The elements of a model to fit the record should accommodate all the following.

11. The CO2 growth rate at Mauna Loa is unprecedented because no comparable measurements exist.

12. The CO2 level at Mauna Loa is substantially higher than the calculations from Vostok ice cores. Because Mauna Loa sits in the plume of the massive CO2 outgassing from the Eastern Equatorial Pacific, and because Vostok sits inside one of the great polar CO2 sinks, Mauna Loa should be higher than Vostok records for the same average, global CO2 concentration. How much higher is for further study by climatologists. The origin of the CO2 at Mauna Loa is dominated by Eastern Equatorial Pacific outgassing.

13. As shown in the Acquittal of Carbon Dioxide, the CO2 concentration lags global warming and is shaped like the complement of the solubility curve. The current epoch of global warming is just one more such epoch shown several times in the Vostok data, and the increase in CO2 concentration is similar to the paleo record, within the resolution of that record.

The Consensus had no explanation for the increase in CO2 it alleged caused the historical ice epoch recoveries. Once the Consensus accepts those new results from the Acquittal of Carbon Dioxide, it will have an explanation for the CO2 but no satisfactory explanation for the global warming at any time.

14. Also, small changes in ocean or atmospheric currents could have an additional profound effect on the CO2 measured at Mauna Loa. The center of the CO2 plume may now be moving toward Hawaii, causing an increase in CO2 concentration there. This could also account for the seasonal effects evident in the Keeling curve.

15. The CO2 rich atmosphere rises near the equator and splits into north and south plumes. As it rises in each hemisphere, it enters a Hadley Cell, carrying it first poleward, and then down into and to feed the westerly trade winds. The trade winds carry the CO2-rich atmosphere across Hawaii. However, the trade winds are also seasonal, varying cyclically in direction and magnitude. The seasonal fluctuations Keeling attributed to the biosphere growing seasons might be better correlated with the trade wind vector at Hawaii.

16. Anthropogenic CO2 may be an additional component of the 3.3 PgC/yr seen at Mauna Loa. It is at most 7.8 parts in 90, or less than 9%. The 3.3 PgC/yr is not unabsorbed ACO2.

To the extent that the record at Mauna Loa is influenced by the venting of CO2 from the Thermohaline Circulation, the changes in plume intensity may be due to events a millennium old.

18. The Consensus assumes anthropogenic changes act in a state of climate equilibrium. It assumes that both the CO2 and the global temperature are in equilibrium but for man. Instead, climate change forecasts must operate in the state of Earth's on-going, triple recovery from the last ice age, the last glacial epoch, and the Little Ice Age, whatever the causes might be. Any valid forecast must first account for that natural warming.

Kyoto-like arrangements can have no measurable effects on the rise in CO2. To stop the rise in CO2, man must stop global warming.

The Consensus weaves a tangled web.

]]> Gavin Schmidt on the Acquittal of CO2 tag:www.rocketscientistsjournal.com,2006://1.55 2006-11-09T21:56:28Z 2007-10-10T21:56:17Z GAVIN SCHMIDT'S RESPONSE TO THE ACQUITTAL OF CO2SHOULD SOUND THE DEATH KNELL FOR AGW by Jeffrey A. Glassman, PhD Gavin A. Schmidt is a well-placed leader of the Anthropogenic Global Warming movement. He is a climate modeler at NASA....
GAVIN SCHMIDT'S RESPONSE TO THE ACQUITTAL OF CO2
SHOULD SOUND THE DEATH KNELL FOR AGW

by Jeffrey A. Glassman, PhD

Gavin A. Schmidt is a well-placed leader of the Anthropogenic Global Warming movement. He is a climate modeler at NASA. While London trained as a mathematician, he was an NOAA Postdoctoral Fellow in “Climate and Global Change Research”. He is an editor for the Journal of Climate. He is the principal of an authoritative blog called RealClimate.org.

As he has admitted and has been shown to be true, he usually doesn't respond to outside criticism. E.g., re newspapers see http://www.realclimate.org/index.php/archives/2004/12/. However, he deigned to answer the Acquittal of Carbon Dioxide. See the discussion of the Acquittal at website for CrossFit, Comment #48, 10/31/06, www.crossfit.com. This is what he has to say:

“[Response: That's pretty confused. He neither understands the physics of CO2, nor the implications of the Vostok record, nor the concept of positive feedback. We've discussed each of these issues before, and I would refer you there. - gavin]

“Dec 2004. What does the lag of CO2 behind temperature in ice cores tell us about global warming? http://www.realclimate.org/index.php/archives/2004/12/how-do-we-know-that-recent-cosub2sub-increases-are-due-to-human-activities-updated/

“22 Dec 2004. How do we know that recent CO2 increases are due to human activities? http://www.realclimate.org/index.php/archives/2004/12/co2-in-ice-cores/

“5 Jul 2006. Runaway tipping points of no return. http://www.realclimate.org/index.php/archives/2006/07/runaway-tipping-points-of-no-return/Gavin Schmidt on Physics”

RSJ dissects Dr. Schmidt's reply categorically.

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GAVIN SCHMIDT ON PHYSICS

Schmidt's opening, “[Response: That's pretty confused. He neither understands the physics of CO2, … “, doesn't tell the reader what physics is relevant, what misunderstanding Schmidt might have perceived, or who or what is confused.

Relevant physics. According to the Intergovernmental Panel on Climate Change (IPCC), jointly established by the World Meteorological Organization (WMO) and the United Nations Environment Programme (UNEP) in 1988, the physics of CO2 includes an annual gross exchange of about 90 PgC (90 Gigatons of carbon) per year, that determines the fate of CO2 in the atmosphere, it must be calculated in a numerical model, and it depends on the solubility of CO2 in water, and in particular, on the solubility pump.

The Acquittal of Carbon Dioxide extensively addresses the solubility of CO2 in water. So what Gavin cannot reveal as my misunderstanding of CO2 physics must be an error of commission, not omission.

What does Gavin say about solubility and CO2 on his website, www.realclimate.org? First, Google says: Your search - “solubility pump” site:realclimate.org - did not match any documents. So apparently he completely neglects the CO2 physics of the solubility pump!

If you Google for solubility and “carbon dioxide” at realclimate.org, you'll find the following six unique citations.

(1) Schmidt, 16 May 2006, Current volcanic activity and climate?

“There is an obvious spike in the rate of CO2 increase at that time -- in the other direction!

“I've been all over the CO2 record from Mauna Loa, and I can tell you that just after the Mt. Pinatubo explosion, the growth rate of atmospheric CO2 decreased. From about 1977 to 1990, atmospheric CO2 was increasing at about 1.5 ppmv/yr, but from 1991-1992 the rate dropped to about 0.9 ppmv/yr. It rebounded quickly, and by 1994 was above 1.5 ppmv/yr.

“Gavin? Could the Mt. Pinatubo explosion have caused a decrease in atmospheric CO2 increase rate? Or is the dip due to some other cause?

“[Response: A small dip is completely understandable in terms of the carbon cycle response to the cooling. It could be a solubility effect (cooler oceans take up more CO2), but it's more likely a biosphere effect - reduced soil respiration maybe. I'd have to look up the relevant literature to be more precise... - gavin].” Comment #6. www.realclimate.org/index.php/archives/ 2006/05/current-volcanic-activity-and-climate/. www.realclimate.org/index.php/archives/ 2006/05/positive-feedbacks-from-the-carbon-cycle/

Gavin admits his confusion. Could solubility be playing a role, he asks!

(2) Archer of RealClimate.org, 27 May 2006, Positive feedbacks from the carbon cycle.

“The oceans are presently taking up about 2 Gton C per year, a significant dent in our emissions of 7 Gton C per year. This could slow in the future, as overturning becomes inhibited by stratification, as the buffer loses its capacity due to acidification. Eventually, the fluxes could reverse as with a decrease in CO2 solubility due to ocean warming.” www.realclimate.org/index.php/archives/ 2006/05/positive-feedbacks-from-the-carbon-cycle/

Here the author admits only to the possibility that CO2 solubility could play a role. However, another aspect of this citation is far more important. Climatologists calculate that annually the oceans dissolve between 92 and 107 Gigatons of carbon, and emit variously between 90 and 103 Gigatons back into the atmosphere, accuracy unknown. (Google for 90 PgC/yr for an idea of the extent of this calculation.) The anthropogenic crowd presume that the 90 GT figure is natural equilibrium and that the excess uptake of 2 GT is associated with anthropogenic CO2. Of course, this is nonsense. The 2 GT figure is merely the difference between two large, uncertain estimates. The sources for both the 90 GT and 92 GT figures and the 103 GT and 107 GT remain a mystery, concealing the method of computation, its probable accuracy, and the dependence on conditions and assumptions, especially but not exclusively global temperature (climate).

These observations point to one of several persistent scientific flaws in the AGW conjecture. In this case, the GCMs do not work in the most significant figures, but they claim validity in the region of the middle most significant figures. Now restricting the domain of a scientific model is a routine practice, and is quite acceptable. If the climatologists wish to restrict the domain of their GCMs to the present post glacial period, or even to the time since the Little Ice Age, they should so state this restriction. If they do so, however, they are bound to express their models against a doubly warming background: the post glacial period of about 60 to 80 thousand years, or to the post LIA period of a hundred and fifty years or so.

Instead, the climatologists glue the dubious CO2 measurements of the last fifty years onto the record of several centuries or the record of several hundred millennia, thus to proclaim an unprecedented level of CO2 due to man. They fail to account for the differences in measurement methods and the problems that implies with regard to calibration. They fail to account for the global temperature and the effects that has on the CO2 concentration. They fail to account for the difference in sampling intervals. They ignore that some technicians making the modern measurements reported that they waited until the wind was from the sea because that lead to higher CO2 levels. [Gray, Vincent R. “Atmospheric Carbon Dioxide”, letter 3/1/99, Re: paper on pre-industrial carbon dioxide. http://www.john-daly.com/bull120.htm.] They ignore the hint in that admission that maybe the CO2 was fresh outgassing and not manmade at all.

(3) Schmidt, 8 Mar 2006, Art and climate, no response to Comment # 17:

“Similarly is there a graph somewhere giving the solubility of CO2 versus temperature in sea water?” www.realclimate.org/index.php/ archives/2006/03/art-and-climate/

Gavin never answered. The graph is in the Acquittal of Carbon Dioxide.

(4) Schmidt, 5 Dec 2005, Debate over the Early Anthropogenic Hypothesis, by response to Comment #36.

“It seems that increases in ocean temperature and CO2 outgassing go hand in hand. [Citations]

“'The total amount of carbon in the ocean is about 50 times greater than the amount in the atmosphere, and is exchanged with the atmosphere on a time-scale of several hundred years. Dissolution in the oceans provides a large sink for anthropogenic CO2, due in part to its high solubility, but above all because of its dissociation into ions and interactions with sea water constituents'

“'CO2 solubility is temperature dependent, hence air-sea heat transfer contributes to seasonal and regional patterns of air-sea CO2 transfer (Watson et al., 1995). Net cooling of surface waters tends to drive CO2 uptake; net warming drives outgassing.'” www.realclimate.org/index.php/archives/ 2005/12/early-anthropocene-hyppothesis/

Gavin never took the hint. The evidence of the CO2 solubility affecting the CO2 concentration in the atmosphere is in the Vostok data, reported and measured in the Acquittal of Carbon Dioxide.

Actually, climatologists' calculations indicate a little more than one eighth of the CO2 in the atmosphere is exchanged annually. The record indicates that CO2 stream has a transport lag of about one millennium, but the exchange is perpetual.

(5) RealClimate.org, 7 Jun 2005. How much of the recent CO2 increase is due to human activities?

“Why are the ocean and land taking up carbon, when we know that warming of the oceans reduces the solubility of CO2 and warming of the land accelerates bacterial degradation of the soils? The answer is that warming is not the only process that influences the oceans and land biosphere. The dominant process in the oceans is the response to increasing atmospheric CO2 itself. If the oceans had not warmed, they might have taken up even more carbon, although we cannot say for sure because warming may have other impacts, for example on marine biota. On land, bacterial degradation of the soils may have increased in response to warming, but for the moment this effect is smaller than the land response to other processes (for example fertilization by CO2 and nitrogen, changes in precipitation, etc).” www.realclimate.org/index.php?p=160

This is all qualitative, with no references to computations. It is dismissive of the effect on solubility of warming, which is, after all, the principal independent variable of the solubility curve (solubility as a function of temperature, with a parameter of partial pressure.)

Once the climatologists re-integrate ocean models with their Global Circulation Models, they are likely to discover that the uptake of CO2 is relatively constant (at least until the entire sea surface freezes), and is limited by exposure time, partial pressure, wind velocities, and area. However, the outgassing is likely to be the more important parameter with respect to CO2 concentrations. At the same time, the greenhouse effect will be minor, mostly dependent on water vapor, and relatively constant.

(6) Schmidt, 21 Jan 2006. Calculating the greenhouse effect, no response to Comment #24 by Dave Nicosia (NOAA):

“Also, in the ice core data, CO2 appears to passively follow the inferred temperature trends through the millennia suggesting its concentration follows the glacial to interglacial periods and the increased solubility of the oceans at lower temperatures.” www.realclimate.org/index.php/archives/ 2006/01/calculating-the-greenhouse-effect/

Gavin did not answer. As the Acquittal of Carbon Dioxide shows, Dave Nicosia was insightful.

GAVIN SCHMIDT ON THE IMPLICATIONS OF VOSTOK

Schmidt says of the Acquittal of Carbon Dioxide, “nor [does the author understand] the implications of the Vostok record … .”

The Acquittal says that the shape of the Vostok relationship between CO2 concentration and the temperature traces is fully represented by the solubility of CO2 in water, with no constant offset (no “forcing” component), and is confirmed by the CO2 lag, which the article quantifies, and which is consistent with the transport lag caused by the oceanic thermohaline circulation. Has anything written by or for Schmidt contradicted these new findings in the Acquittal?

In support of his accusations, Schmidt refers us to three papers he authored, all on his website. None of these citations says that the Vostok record demonstrates the essential fact that atmospheric CO2 and any temperature are correlated!

Schmidt's first citation is “What does the lag of CO2 behind temperature in ice cores tell us about global warming?”, 12/3/04, http://www.realclimate.org/index.php/archives/2004/12/how-do-we-know-that-recent-cosub2sub-increases-are-due-to-human-activities-updated/. With regard to the Vostok record, this paper says only what is NOT significant. That insignificant fact, Schmidt asserts, is the lag of the CO2 concentration trace behind temperature trace. If that fact were insignificant, it would weaken the discoveries in the Acquittal, depriving its thesis of the lag that tends to confirm the model of the ocean controlling the atmospheric CO2 content.

In reality, the lag is an inconvenient fact to AGW. Enthusiasts must discredit this lag because their AGW conjecture rests on manmade CO2 causing global warming. That causal conjecture is severely damaged by the reversed timing: temperature changes precede CO2 concentration changes!

The AGW advocates postulate a rehabilitating theory: CO2 amplifies global warming. But this residual amplification conjecture is equally bizarre. This model states that the amplified warming somehow releases more CO2, and hence the amplification is a positive feedback.

First, to the extent that this amplification could be so, the instability should soon cause the CO2 record to lead temperature. It never has. Schmidt has no data to confirm his amplification suggestion. Also see Schmidt's reliance on feedback, below.

Schmidt's second citation, How do we know that recent CO2 increases are due to human activities? http://www.realclimate.org/index.php/archives/2004/12/co2-in-ice-cores/, 12/22/04, includes only the following with respect to Vostok:

“In addition to the data from tree rings, there are also of measurements of the 13C/12C ratio in the CO2 trapped in ice cores. The tree ring and ice core data both show that the total change in the 13C/12C ratio of the atmosphere since 1850 is about 0.15%. This sounds very small but is actually very large relative to natural variability. The results show that the full glacial-to-interglacial change in 13C/12C of the atmosphere -- which took many thousand years -- was about 0.03%, or about 5 times less than that observed in the last 150 years.”

plus

“CO2 levels are currently higher than for any time when we have direct measurements (directly, from 1950; before that, from air trapped in ice cores), which amounts to the last 780,000 years (see, e.g., a picture here for the last 400 kyr). Various considerations suggest that in the far past CO2 levels were considerably higher. From memory, the last time CO2 levels exceeded present was about 40 million years ago/” Response to Comment #4.

This modern increase in CO2 is often found supported by a graph showing the Vostok CO2 concentration in time, with rapidly rising modern data linked added to the end of the Vostok record. Nowhere do the climatologists justify the method linking data taken by different methods, in different locations, and with grossly different granularity.

Data show that carbon dioxide levels are rising, they are now 30% higher than at any time during at least the past 650,000 years, and likely even the past several million years. 31 Mar 2006, Bush on “The Fundamental Debate”, by the group, www.realclimate.org/index.php/archives/2006/03/bush-on-the-debate/

The Unprecedented Assumption

The absence of evidence is not evidence of the absence, even when abundant samples have proved negative. A tenet of the AGW conjecture is that the present levels of CO2 are unprecedented, going back four million years. The Vostok data goes back 420,000 to 780,00 years, but the sample interval is one to two millennia. The current surge in CO2 is known by a different method, and is only 150 years long, a seventh of a millennium. If there had been just one similar epoch to the present during the period covered by Vostok, the odds are strong that it would not have been detected.

The AGW advocates suffer from the same problem as creationists. Transition species are missing from the paleontology record, but fossilization is an infrequent event, much longer than the periods of speciation. The chances of discovering a brief epoch in gas concentration, like the chances for discovering transition species, is quite small. Neither proof of God's hand nor of man's lies in such sparse data.

The 12/22/04 paper also says,

“If we see CO2 increasing in the atmosphere, and humans emitting enough CO2 to account for that rise, then you have to go through some odd contortions to avoid a connection. You would have to postulate a suddenly increased natural sink (to remove the human CO2) and then a suddenly increased natural source (to increase the atmospheric CO2)”. Response to Comment #6.

To the contrary, to make the connection is to rely on correlation instead of a cause and effect model. This false reliance has blinded the AGW advocates to the on-going physics. Suddenly developed sinks and sources are not needed at all. The cold ocean is a sink to all atmospheric CO2, manmade, accidental, or ocean emitted. The cold sink is limited not by capacity, but by exposure, pressure, and winds. But for the ocean outgassing, the cold waters would scrub the atmosphere of all CO2 in less than a decade by the climatologists own uncertain carbon and flux estimates. The natural source is dominantly the oceans. CO2 concentration has increased because the oceans are warming, and have been since the Little Ice Age and since the last glacial period.

The Residence Time Assumption

Another AGW tenet is that the buildup of CO2 in the Mauna Loa Record is an accumulation of CO2 throughout the brunt of the industrial era. To make that accumulation viable, AGW advocates claim the duration of CO2 in the atmosphere is a century or more.

To the extent that the mean residence time of CO2 is less than a century, the build up must be from other sources. Others have claimed the residence time is the order of five years or less, and that appears to be supported by their calculations of the total concentration of CO2 in the atmosphere and the flux into the biosphere and especially the ocean. With such short CO2 persistence, the AGW conjecture needs shoring up with a new rationale for the 150 year growth in CO2.

The Keeling Curve Assumptions

The unprecedented rise in CO2, correlated to an extent with the calculated production of anthropogenic CO2, was discovered and analyzed by Charles David Keeling of the Scripps Institution of Oceanography, UCSD, from measurements made at the Mauna Loa observatory in Hawaii. The data comprise a seasonal oscillation on top of a steadily rising and even accelerating, non-seasonal base. Keeling warned that the data were a reliable indicator in a localized space, the middle, troposphere layers in the region. Keeling, C.D. & T. P. Whorf, Atmospheric carbon dioxide record from Mauna Loa, 1958-2004. www.cmdl.noaa.gov/ccgg/trends/. Reportedly he also said that his data reflected natural events, including perhaps an unprecedented process. Keeling, C.D. & T. P. Whorf, Atmospheric carbon dioxide record from Mauna Loa, 1958-2004. www.cmdl.noaa.gov/ccgg/trends/. He came to conclude that the seasonal portion was natural, and due to seasonal changes in the biosphere. See Kaufmann, Robert K. SEASONAL CHANGES IN ATMOSPHERIC CARBON DIOXIDE: LONGER GROWINGS SEASONS VERSUS GREENER SUMMERS, Boston University, Center for Energy & Environmental Studies. www.bu.edu/cees/people/faculty/kaufmann/documents/carbon_dioxide.pdf. However, he concluded that the non-seasonal part was anthropogenic. See Scripps CO2 Program, Charles David Keeling Biography. http://scrippsco2.ucsd.edu/program_history/charles_david_keeling_biography.html.

Later A.C. Manning in association with Keeling's son, Ralph, also a PhD oceanographer at Scripps, concluded that variations in north-south transport were likely a particularly important cause of the short-term variability of atmospheric CO2 at Mauna Loa. Manning, A.C. & R. F. Keeling, Scripps Institution of Oceanography, UCSD, Correlations in Short-Term Variations in Atmospheric Oxygen and Carbon Dioxide at Mauna Loa Observatory. www.cmdl.noaa.gov/publications/annrpt22/MANNING.pdf . These results raise the question whether the seasonal variations may be due simply to the variations in prevailing or trade winds at Mauna Loa. Did Charles Keeling consider wind as the cause, and subsequently rule it out?

Likewise, what evidence did Charles Keeling have for his conclusion that the rapid, non-seasonal increase observed at Mauna Loa was manmade?

The possibility that weather causes the seasonal fluctuations at Mauna Loa suggests that the non-seasonal part might be related to climate, too. Perhaps Mauna Loa is down-current and downwind from undersea volcanic activity. Or, perhaps Mauna Loa is located in the seasonally shifting stream of ordinary CO2 outgassing from the oceans.

Regardless, implicit in the climatologists use of the data are the unlikely assumptions that the MLO atmosphere is already well-mixed and globally representative. These were not Charles Keeling's original findings.

Schmidt's third and last citation, Runaway tipping points of no return, http://www.realclimate.org/index.php/archives/2006/07/runaway-tipping-points-of-no-return/, 7/5/06, helps little in gathering Schmidt's take on the relevance of the Vostok data. Just as the first paper established that the CO2 lag in the Vostok record is not helpful, the third paper says the CO2 concentration record is not helpful in understanding the present record! Here in a response to Comment #4, Gavin says

“So if CO2 levels are so much higher now (26% higher than any point since 420K years before the industrial era), why aren't temperatures lining up?

“[Response: The orbital configuration was different, with warmer [Northern Hemisphere] summers than today (or even the early Holocene). That seasonal change may have been crucial for the ice sheets. See the recent Overpeck et al and Otto-Bleisner et al papers in Science for what climate differences one would expect. With respect to today's CO2, that is not being changed by anything like the same mechanism, and so simply correlations with past data are not going to help. -gavin]” Bold added.

So Gavin urges the mechanisms affecting CO2 concentrations in the Vostok record are nothing like the mechanisms today. Therefore, he says, one should not attempt to correlate the two records. To the contrary, that is exactly what climatologists do when they tack the Mauna Loa measurements onto the Vostok record, or when they make proclamations about the unprecedented CO2 levels in the post-industrialization period. Gavin seems to recognize a difference in geophysical processes, but not in the measurement methods. The first is a conjecture. The second is a certainty.

GAVIN SCHMIDT ON POSITIVE FEEDBACK

“[N]or [does the author understand] the concept of positive feedback”,

urges Gavin. For this position, Schmidt refers readers to his 7/5/06 tome, “Runaway tipping points of no return“. http://www.realclimate.org/index.php/archives/2006/07/runaway-tipping-points-of-no-return/. Here he says,

“The idea is that in many non-linear systems (of which the climate is certainly one), a small push away from one state only has small effects at first but at some 'tipping point' the system can flip and go rapidly into another state. This is fundamentally tied to the existence of positive feedbacks … . However, [tipping point] is currently being used interchangeably a number of potentially confusing ways and so I thought I'd try and make it a little clearer.”

This introductory paragraph suggests the romantic, grammar school notion of the “Delicate Blue Planet”. This model has been so successful that it has distorted the thinking of climatologists, environmentalists, and chaos theorists. It holds that natural objects and systems are found in a delicate balance, and that the most minimal disturbance by man could upset that balance, and so produce a catastrophe. These delicate systems and objects are always invisible, of course. But if the model were to extend to the observable, nature would contain cones standing on their tips, and rounded boulders perched on slopes.

Climatologists need to rid themselves of this Delicate Blue Planet misapprehension. They need to abandon their pursuit, however attractive, of knife edges over catastrophes. They should reconfigure their models to account for stable states, past and present, of all the parameters in their domain. These include not just global climate, but gas mixtures, the water cycle, the carbon cycle, and the ozone layer. They should be modeling these phenomena in their natural, closed-loop states to discover the controlling parameters and their dynamic ranges.

Where does the ozone come from? What controls its concentration? What controls the thickness of the ozone layer, and why is it as thick as it is?

Next under the heading “Positive feedback”, Gavin begins,

“A positive feedback occurs when a change in one component of the climate occurs, leading to other changes that eventually 'feeds back' on the original change to amplify it.”

Leaving room for some climate jargon, this is almost a valid and workable definition. But it omits, among other things, the necessary control system context, and the concepts of gain, ordinary feedback, open loop and closed loop. Regardless, Gavin next attempts to explain what he thinks positive feedback means:

“A simple example leads to a geometric series for instance; i.e. if an initial change to a parameter is D, and the feedback results in an additional rD then the final change will be the sum of D+rD+r2D...etc.”

This explanation and Schmidt's understanding of positive feedback, or even feedback, are fatally flawed.

First, Schmidt's equation expresses a change in the parameter value, not the value of the amplified, closed loop output in his definition, or anything related to it. By reference to “in an additional rD”, and by the plus signs in the series, Gavin reveals that he is thinking of the change as an additive amount. By his definition, the feedback is to cause an amplification of the original parameter. Amplification is multiplicative, not additive. If the original parameter value was P, after positive feedback the value would be rP, with r greater than one, or it might be written as (1+g)P, where g is now the feedback gain, and is greater than zero for positive feedback. Schmidt's algebraic example does not represent his verbal definition.

Second, Schmidt's change formulation converges to a constant, D/(1-r), for |r| less than 1. This he urges is to demonstrate a positive feedback which does not run away, or in scientific terms, diverge. In fact, what he has demonstrated is a kind of feedback which converges to zero as the number of iterations increases. What he calls feedback is only a transient, and its steady state value is neither positive nor negative, but is arbitrarily close to zero. This example briefly resembles a positive feedback, but in the long run Schmidt's example has no feedback at all.

In its Glossary, RealClimate.org provides the following definition dated 28 Nov 2004:

“Forcings in the climate sense are external boundary conditions or inputs to a climate model. Obviously changes to the sun's radiation are external, and so that is always a forcing. The same is true for changes to the Earth's orbit (“Milankovitch cycles”). Things get a little more ambiguous as you get closer to the surface. In models that do not contain a carbon cycle (and that is most of them), the level of CO2 is set externally, and so that can be considered a forcing too. However, in models that contain a carbon cycle, changes in CO2 concentrations will occur as a function of the climate itself and in changes in emissions from industrial activity. In that case, CO2 levels will be a feedback, and not a forcing. Almost all of the elements that make up the atmosphere can be considered feedbacks on some timescale, and so defining the forcing is really a function of what feedbacks you allow in the model and for what purpose you are using it. A good discussion of recent forcings can be found in Hansen et al (2002) and in Schmidt et al (2004).” http://www.realclimate.org/index.php/archives/2004/11/forcings/

From this, a feedback is any model parameter which is not a forcing, that is, which is not a boundary condition. This is not the definition of feedback in control system theory, and it makes the concept of positive feedback at least awkward to define.

Schmidt uses other definitions anyway. In a posting on 4/6/05, “Water vapour: feedback or forcing?”, Schmidt wrote,

“While water vapour is indeed the most important greenhouse gas, the issue that makes it a feedback (rather than a forcing) is the relatively short residence time for water in the atmosphere (around 10 days).”

Now either a positive feedback is not a subset of feedback, or Schmidt's tutorial definition of positive feedback omitted the criterion of atmospheric residence time. According to RealClimate's Glossary,

“Water vapour act as a powerful greenhouse gas absorbing long-wave radiation. If the atmospheric water vapour concentration increases as a result of a global warming, then it is expected that it will enhance the greenhouse effect further. It is well known that the rate of evaporation is affected by the temperature and that higher temperatures increase the (saturated) vapour pressure (the Clausius-Clapeyron equation). This process is known as the water vapour feedback.” http://www.realclimate.org/index.php/archives/2004/11/water-vapour-feedback/.

So warming increases water vapor, which causes warming. Consequently, water vapor amplifies global temperatures. This fits Schmidt's definition of a positive feedback without reliance on Schmidt's essential criterion of residence time. Schmidt contributes to the confusion he set out to settle.

And why is water vapor a feedback and CO2 not? Because, goes the AGW scenario, the persistence of CO2 in the atmosphere is greater than 100 years. “What If … the 'Hockey Stick' Were Wrong?”, http://www.realclimate.org/index.php?p=114, Gavin's response to Comment #20. The IPCC puts the residence time of CO2 at “5 to 200 yr” with the note, “No single lifetime can be defined for CO2 because of the different rates of uptake by different removal processes.” IPCC, Climate Change 2001, ¶C.1, p. 38.

Gat et al in “Environmental Isotopes in the Hydrological Cycle, Principles and Applications”, Volume II: Atmospheric Water, Chapter 1, The Atmosphere, p. 1, place the residence time of CO2 at 4 years. See http://www.iaea.org/programmes/ripc/ih/volumes/volume2.htm . Would a four year persistence for CO2 qualify it as a feedback? Gavin's analysis doesn't answer that question. Regardless, as the Acquittal of Carbon Dioxide teaches, CO2 must not be treated as a forcing so that the GCM can reproduce a CO2 output consistent with the Vostok record.

Schmidt's tutorial concludes where he has the title, “points of no return”. Now he waxes literary, as if some being, human or spiritual, were in control and desirous of some outcome. He anthropomorphizes his science.

Will the earth return to a glacial state? Most assuredly. Will it recover with similar flora and fauna and climate as the present. That's not so certain.

At this point in his paper, Schmidt abruptly applies his errant tutorial to model based AGW via hypothesized ACO2 accumulation in the atmosphere. This is under the heading “10 years?”, a reference to his opening citation of Jim Hansen's doomsday prediction. If this part is to have any validity, it must overcome the fallacy of the manmade CO2 increases in his citations.

Schmidt's switch from his tutorial is itself a tipping point -- a linguistic or literary tipping point.

Nowhere does Schmidt suggest that the models on which he relies to frighten the public might have been validated. He relies instead on an incompetent tutorial to support the AGW conjecture.

The Acquittal of Carbon Dioxide survives Gavin Schmidt's opening salvo. The burden remains on the GCM operators advocates to revise their models. They need to abandon CO2 as a forcing, and instead make the atmospheric CO2 concentration respond to global temperature as dictated by the solubility of CO2 in water. This should be a fatal blow to anthropogenic global warming.

A Meta View

Transcending physics, scientific standards, understandable by a literate layman, must be satisfied. The AGW supporters are not meeting them. They need to divulge the domain in which their models meet all available data. They need to use their models to make significant and novel predictions which can be subject to experiment. (This is a modern reformulation of the Popper falsification criterion.) They need to discard their reliance on consensus, ad hominem attacks, and beliefs, and instead rely solely on the technical fidelity of their models to the climate record. Until their models are validated, they should disavow any public policy consequences of their work. Any of their work destined for public consumption must rely on nothing of significance that is available only for a fee.

On a higher technical plane are additional, widely understandable standards to be met. Information sources should be readily discoverable for all parameter values and models. All data values, raw or reduced, must be discoverable, or accompanied by a statement of the method, the accuracy, or better, an error analysis.

Global Climate on the Margin

In the final analysis of the AGW conjecture, proponents model their chosen phenomena on the margins and without justification. They admit the overwhelming greenhouse gas is water vapor, probably 30 to 50 times more important than CO2. They admit the CO2 attributed to man is minuscule, about 6 to 7 PgC/yr (calculated) into an atmospheric reservoir variously estimated between 720 and 760 PgC. That's around 1% of 2.5%, or 0.025% of GHG.

They estimate the uptake of CO2 by the ocean from 92 to 107 PgC/yr, an error of about ±7 PgC/yr, approximately equal to the anthropogenic total. They estimate the outgassing of CO2 from 90 to 103 PgC/yr, an error of roughly another ±7 PgC/yr. Without putting too fine a point on the method, and in consideration of the range of values by other, undiscovered authorities and the sources and methods employed by any of them, the net difference between uptake and outgassing estimates is about 3PgC/yr, ±14 PgC/yr. Nonetheless, the climatologist use a figure of 2 PgC/yr as their estimate of the oceanic uptake of the manmade CO2 of 7 PgC/yr. Regardless, they then proclaim that CO2 persists in the atmosphere of 50 to 500 years.

Water vapor is not only dominant among the greenhouse gases, it, like CO2, increases with increasing temperatures. Increase in water vapor should bring increases in cloud cover, decreasing solar radiation, and shutting down the warming effect.

CONCLUSION

Categorically, each of Gavin Schmidt's criticisms of the Acquittal of Carbon Dioxide missed its mark.

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]]> CO2 ACQUITTAL tag:www.rocketscientistsjournal.com,2006://1.54 2006-10-24T13:06:19Z 2008-06-29T20:08:43Z Rocket Scientist&#8217s Journal … UNDER CONSTRUCTION … THE ACQUITTAL OF CARBON DIOXIDE by Jeffrey A. Glassman, PhD ABSTRACT Carbon dioxide in the atmosphere is the product of oceanic respiration due to the well&#8209;known but under&#8209;appreciated solubility pump. Carbon dioxide...


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Rocket Scientist’s Journal

… UNDER CONSTRUCTION …

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THE ACQUITTAL OF CARBON DIOXIDE

by Jeffrey A. Glassman, PhD

ABSTRACT

Carbon dioxide in the atmosphere is the product of oceanic respiration due to the well‑known but under‑appreciated solubility pump. Carbon dioxide rises out of warm ocean waters where it is added to the atmosphere. There it is mixed with residual and accidental CO2, and circulated, to be absorbed into the sink of the cold ocean waters. Next the thermohaline circulation carries the CO2‑rich sea water deep into the ocean. A millennium later it appears at the surface in warm waters, saturated by lower pressure and higher temperature, to be exhausted back into the atmosphere.

Throughout the past 420 millennia, comprising four interglacial periods, the Vostok record of atmospheric carbon dioxide concentration is imprinted with, and fully characterized by, the physics of the solubility of CO2 in water, along with the lag in the deep ocean circulation. Notwithstanding that carbon dioxide is a greenhouse gas, atmospheric carbon dioxide has neither caused nor amplified global temperature increases. Increased carbon dioxide has been an effect of global warming, not a cause. Technically, carbon dioxide is a lagging proxy for ocean temperatures. When global temperature, and along with it, ocean temperature rises, the physics of solubility causes atmospheric CO2 to increase. If increases in carbon dioxide, or any other greenhouse gas, could have in turn raised global temperatures, the positive feedback would have been catastrophic. While the conditions for such a catastrophe were present