Guest post by Girma Orssengo, B. Tech, MASc, PhD
The Intergovernmental Panel on Climate Change (IPCC) claims that human emission of CO2 causes catastrophic global warming. When such extraordinary claim is made, every one with background in science has to look at the data and verify whether the claim is justified or not. In this article, a mathematical model was developed that agrees with observed Global Mean Temperature Anomaly (GMTA), and its prediction shows global cooling by about 0.42 deg C until 2030. Also, comparison of observed increase in human emission of CO2 with increase in GMTA during the 20th century shows no relationship between the two. As a result, the claim by the IPCC of climate catastrophe is not supported by the data.
Fossil fuels allowed man to live his life as a proud human, but the IPCC asserts its use causes catastrophic global warming. Fortunately, the global warming claim by the IPCC that “For the next two decades, a warming of about 0.2°C per decade is projected for a range of SRES emission scenario” [1] is not supported by observations as shown in Figure 1, which shows a plateau for the global mean temperature trend for the last decade.
.”]
Figure 1 also shows that the observed temperatures are even less than the IPCC projections for emission held constant at the 2000 level.
As a result, the statement we often hear from authorities like UN Secretary-General Ban Ki-moon that “climate change is accelerating at a much faster pace than was previously thought by scientists” [3] is incorrect.
Thanks for the release of private emails of climate scientists, we can now learn from their own words whether global warming “is accelerating at a much faster pace” or not. In an email dated 3-Jan-2009, Mike MacCracken wrote to Phil Jones, Folland and Chris [4]:
I think we have been too readily explaining the slow changes over past decade as a result of variability–that explanation is wearing thin. I would just suggest, as a backup to your prediction, that you also do some checking on the sulfate issue, just so you might have a quantified explanation in case the prediction is wrong. Otherwise, the Skeptics will be all over us–the world is really cooling, the models are no good, etc. And all this just as the US is about ready to get serious on the issue.
…
We all, and you all in particular, need to be prepared.
Similarly, in an email dated 24-Oct-2008, Mick Kelly wrote to Phil Jones [5]:
Just updated my global temperature trend graphic for a public talk and noted that the level has really been quite stable since 2000 or so and 2008 doesn’t look too hot.
…
Be awkward if we went through a early 1940s type swing!
The above statements from the climategate emails conclusively prove that the widely used phrase by authorities in public that global warming “is accelerating at a much faster pace” is supported neither by climate scientists in private nor by the observed data.
Thanks also goes to the Climate Research Unit (CRU) of the Hadley Center for daring to publish global mean temperature data that is “quite stable since 2000”, which is contrary to IPCC projections of 0.2 deg C warming per decade. If the CRU had not done this, we would have been forced to swallow the extremely irrational concept that the gas CO2, a plant food, i.e. foundation of life, is a pollutant because it causes catastrophic global warming.
As IPCC’s “models are no good”, it is the objective of this article to develop a valid mathematical global mean temperature model based on observed temperature patterns.
Mathematical Model For The Global Mean Temperature Anomaly (GMTA) Based On Observed Temperature Patterns
The Global Mean Temperature Anomaly (GMTA) data from the Climate Research Unit (CRU) of the Hadley Center shown in Figure 2 will be used to develop the mathematical model. In this article, the observed GMTA data from the CRU are assumed to be valid.
Examination of Figure 2 shows that the globe is warming at a linear rate as shown by the least square trend central line given by the equation
Linear anomaly in deg C = 0.0059*(Year-1880) – 0.52 Equation 1
Figure 2 also shows that superimposed on this linear anomaly line there is an oscillating anomaly that gives the Global Mean Temperature Anomaly (GMTA) the characteristics summarized in Table 1.
Table 1. Characteristics of the observed Global Mean Temperature Anomaly (GMTA) shown in Figure 2.
|
From 1880s to 1910s |
End of warming, plateau at –0.2 deg C & then cooling trend |
|
From 1910s to 1940s |
End of cooling, plateau at –0.6 deg C & then warming trend |
|
From 1940s to 1970s |
End of warming, plateau at 0.1 deg C & then cooling trend |
|
From 1970s to 2000s |
End of cooling, plateau at –0.3 deg C & then warming trend |
|
From 2000s to 2030s |
End of warming, plateau at 0.5 deg C & then ? trend |
A mathematical model can be developed that satisfies the requirements listed in Table 1. If the model to be developed gives good approximation for the GMTA values at its turning points (plateaus) and the GMTA trends between its successive turning points as summarized in Table 1, the model may be used for prediction.
.”]
For the oscillating anomaly, the sinusoidal function cosine meets the requirements listed in Table 1. From Figure 2, the amplitude of the oscillating anomaly is given by the vertical distance in deg C from the central linear anomaly line to either the top or bottom parallel lines, and it is about 0.3 deg C. From Figure 2, the oscillating anomaly was at its maximum in the 1880s, 1940s, & 2000s; it was at its minimum in the 1910s and 1970s. The years between successive maxima or minima of the oscillating anomaly is the period of the cosine function, and it is about 1940–1880=1970–1910=60 years. For the cosine function, once its amplitude of 0.3 deg C and its period of 60 years are determined, the mathematical equation for the oscillating anomaly, for the years starting from 1880, can be written as
Oscillating anomaly in deg C = 0.3*Cos(((Year-1880)/60)*2*3.1416) Equation 2
In the above equation, the factor 2*3.1416 is used to convert the argument of the cosine function to radians, which is required for computation in Microsoft Excel. If the angle required is in degrees, replace 2*3.1416 with 360.
Combining the linear anomaly given by Equation 1 and the oscillating anomaly given by Equation 2 gives the equation for the Global Mean Temperature Anomaly (GMTA) in deg C for the years since 1880 as
GMTA = 0.0059*(Year-1880) – 0.52 + 0.3*Cos(((Year-1880)/60)*2*3.1416) Equation 3
The validity of this model may be verified by comparing its estimate with observed values at the GMTA turning points as summarized in Table 2.
Table 2. Comparison of the model with observations for GMTA in deg C at its turning points.
|
Year |
Observed (Table 1) |
Model (Equation 3) |
|
Warming plateau for the 1880s |
-0.2 |
-0.22 |
|
Cooling plateau for the 1910s |
-0.6 |
-0.64 |
|
Warming plateau for the 1940s |
+0.1 |
+0.13 |
|
Cooling plateau for the 1970s |
-0.3 |
-0.29 |
|
Warming plateau for the 2000s |
+0.5 |
+0.48 |
Table 2 shows excellent agreement for the GMTA values between observation and mathematical model for all observed GMTA turning points.
A graph of the GMTA model given by Equation 3 is shown in Figure 3, which includes the observed GMTA and short-term IPCC projections for GMTA from 2000 to 2025. In addition to the verification shown in Table 2, Figure 3 shows good agreement for the GMTA trends throughout observed temperature records, so the model may be used for prediction. As a result, Figure 3 includes GMTA predictions until 2100, where the year and the corresponding GMTA values are given in parentheses for all the GMTA turning points.
As shown in Figure 3, a slight discrepancy exist between observed and model GMTA values at the end of the 1890s when the observed values were significantly warmer than the model pattern, and in the 1950s when the observed values were significantly colder than the model pattern.
From the model in Figure 3, during the observed temperature record, there were two global warming phases. The first was from 1910 to 1940 with a warming of 0.13+0.64=0.77 deg C in 30 years. The second was from 1970 to 2000 with a warming of 0.48+0.29=0.77 deg C in 30 years. Note that both warming phases have an identical increase in GMTA of 0.77 deg C in 30 years, which gives an average warming rate of (0.77/30)*10=0.26 deg C per decade.
From the model in Figure 3, during the observed temperature record, there were two global cooling phases. The first was from 1880 to 1910 with a cooling of 0.64-0.22=0.42 deg C in 30 years. The second was from 1940 to 1970 with a cooling of 0.13+0.29=0.42 deg C in 30 years. Note that both cooling phases have an identical decrease in GMTA of 0.42 deg C in 30 years, which gives an average cooling rate of (0.42/30)*10=0.14 deg C per decade.
The above results for the normal ranges of GMTA determined from the model can also be calculated using simple geometry in Figure 2. In this figure, almost all observed GMTA values are enveloped by the two parallel lines that are 0.6 deg C apart. Therefore, as a first approximation, the normal range of GMTA is 0.6 deg C. From Figure 2, the period for a global warming or cooling phase is about 30 years. Therefore, as a first approximation, the normal rate of global warming or cooling is (0.6/30)*10=0.2 deg C per decade.
The above approximation of 0.6 deg C for the normal range of GMTA should be refined by including the effect of the linear warming anomaly given by Equation 1 of 0.006 deg C per year, which is the slope of the two envelope parallel lines in Figure 2. As the oscillating anomaly changes by 0.6 deg C in 30 years between its turning points, the linear anomaly increases by 0.006*30=0.18 deg C. Due to this persistent warming, instead of the GMTA increasing or decreasing by the same 0.6 deg C, it increases by 0.6+0.18=0.78 deg C during its warming phase, and decreases by 0.6–0.18=0.42 deg C during its cooling phase. As a result, the refined normal ranges of GMTA are 0.77 deg C in 30 years during its warming phase, and 0.42 deg C in 30 years during its cooling phase. These results for the normal ranges of GMTA obtained using simple geometry in Figure 2 agree with those obtained from the model in Figure 3.
Correlation of Model and Observed Global Mean Temperature Anomaly (GMTA)
In Table 2, data points for only five years were used to verify the validity of Equation 3 to model the observed data. However, it is important to verify how well the observed GMTA is modeled for any year.
How well the observed data is modeled can be established from a scatter plot of the observed and model GMTA values as shown in Figure 4. For example, for year 1998, the observed GMTA was 0.53 deg C and the model GMTA is 0.47 deg C. In Figure 4, for year 1998, the pair (0.47,0.53) is plotted as a dot. In a similar manner, all the paired data for model and observed GMTA values for years from 1880 to 2009 are plotted as shown in Figure 4.
Figure 4 shows a strong linear relationship (correlation coefficient, r=0.88) between the model and observed GMTA. With high correlation coefficient of 0.88, Figure 4 shows the important result that the observed GMTA can be modeled by a combination of a linear and sinusoidal pattern given by Equation 3. The positive slope of the trend line indicates a positive relationship between model and observed GMTA. That is, global cooling from the model indicates observed global cooling, and global warming from the model indicates observed global warming.
Global Mean Temperature Prediction Calculations
The following patterns may be inferred from the graph of the Global Mean Temperature Anomaly (GMTA) model shown in Figure 3 for the data from the Climate Research Unit of the Hadley Center [2]:
-
Year 1880 was the start of a cooling phase and had a GMTA of –0.22 deg C.
-
During the global cooling phase, the GMTA decreases by 0.42 deg C in 30 years.
-
Global cooling and warming phases alternate with each other.
-
During the global warming phase, the GMTA increases by 0.77 deg C in 30 years.
The patterns in the list above are sufficient to estimate the GMTA values at all of its turning points since 1880.
For example, as year 1880 with GMTA of –0.22 deg C was the start of a cooling phase of 0.42 deg C in 30 years, the next GMTA turning point was near 1880+30=1910 with GMTA of –0.22–0.42=-0.64 deg C. This GMTA value for 1910 is shown as (1910,-0.64) in Figure 3.
As year 1910 with GMTA of –0.64 deg C was the end of a global cooling phase, it is also the start of a global warming phase of 0.77 deg C in 30 years. As a result, the next GMTA turning point was near 1910+30=1940 with GMTA of 0.77–0.64=0.13 deg C. This GMTA value for 1940 is shown as (1940,0.13) in Figure 3.
As year 1940 with GMTA of 0.13 deg C was the end of a global warming phase, it is also the start of a global cooling phase of 0.42 deg C in 30 years. As a result, the next GMTA turning point was near 1940+30=1970 with GMTA of 0.13–0.42=-0.29 deg C. This GMTA value for 1970 is shown as (1970,-0.29) in Figure 3.
As year 1970 with GMTA of -0.29 deg C was the end of a global cooling phase, it is also the start of a global warming phase of 0.77 deg C in 30 years. As a result, the next GMTA turning point was near 1970+30=2000 with GMTA of 0.77–0.29=0.48 deg C. This GMTA value for 2000 is shown as (2000,0.48) in Figure 3.
As the GMTA values calculated above using the global temperature patterns listed at the beginning of this section give good approximation of observed GMTA values at all GMTA turning points (1880, 1910, 1940, 1970 & 2000), it is reasonable to assume that the patterns may also be used for prediction.
As a result, as year 2000 with GMTA of 0.48 deg C was the end of a global warming phase, it is also the start of a global cooling phase of 0.42 deg C in 30 years. As a result, the next GMTA turning point will be near 2000+30=2030 with GMTA of 0.48–0.42=0.06 deg C. This GMTA value for 2030 is shown as (2030,0.06) in Figure 3.
In a similar manner, the GMTA values for the remaining GMTA turning points for this century can be calculated, and the results are shown in Figure 3.
Figure 3 shows a very interesting result that for the 20th century, the global warming from 1910 to 2000 was 0.48+0.64=1.12 deg C. In contrast, for the 21st century, the change in GMTA from 2000 to 2090 will be only 0.41–0.48=-0.07 deg C. This means that there will be little change in the GMTA for the 21st century! Why?
Why Does The Same Model Give A Global Warming Of About 1 deg C For The 20th Century But Nearly None For The 21st Century?
According to the data shown in Figure 3, it is true that the global warming of the 20th century was unprecedented. As a result, it is true that the corresponding sea level rise, melting of sea ice or the corresponding climate change in general were unprecedented. However, this was because the century started when the oscillating anomaly was at its minimum near 1910 with GMTA of –0.64 deg C and ended when it was at its maximum near 2000 with GMTA of 0.48 deg C, giving a large global warming of 0.48+0.64=1.12 deg C. This large warming was due to the rare events of two global warming phases of 0.77 deg C each but only one cooling phase of 0.44 deg C occurring in the 20th century, giving a global warming of 2*0.77-0.42=1.12 deg C.
In contrast to the 20th century, from Figure 3, there will be nearly no change in GMTA in the 21st century. This is because the century started when the oscillating anomaly was at its maximum near 2000 with GMTA of 0.48 deg C and will end when it is at its minimum near 2090 with GMTA of 0.41 deg C, giving a negligible change in GMTA of 0.41-0.48=-0.07 deg C. This negligible change in GMTA is due to the rare events of two global cooling phases of 0.42 deg C each but only one warming phase of 0.77 deg C occurring in the 21st century, giving the negligible change in GMTA of 0.77-2*0.42=-0.07 deg C. Note that this little change in GMTA for the 21st century is identical to that from 1880 to 1970, which makes the global warming from 1970 to 2000 by 0.77 deg C appear to be abnormally high.
If the period for a century had been 120 years, we wouldn’t have this conundrum of nearly 1 deg C warming in the 20th century but nearly none in the next!
Ocean Current Cycles
One of the most important variables that affect global mean surface temperature is ocean current cycles. The rising of cold water from the bottom of the sea to its surface results in colder global mean surface temperature; weakening of this movement results in warmer global mean surface temperature. Various ocean cycles have been identified. The most relevant to global mean temperature turning points is the 20 to 30 years long ocean cycle called Pacific Decadal Oscillation (PDO) [6]:
Several independent studies find evidence for just two full PDO cycles in the past century: “cool” PDO regimes prevailed from 1890-1924 and again from 1947-1976, while “warm” PDO regimes dominated from 1925-1946 and from 1977 through (at least) the mid-1990’s (Mantua et al. 1997, Minobe 1997).
These cool and warm PDO regimes correlate well with the cooling and warming phases of GMTA shown in Figure 3.
The model in Figure 3 predicts global cooling until 2030. This result is also supported by shifts in PDO that occurred at the end of the last century, which is expected to result in global cooling until about 2030 [7].
Effect Of CO2 Emission On Global Mean Temperature
Examination of Figure 3 shows that the Global Mean Temperature Anomaly (GMTA) for 1940 of 0.13 deg C is greater than that for 1880 of –0.22 deg C. Also, the GMTA for 2000 of 0.48 deg C is greater than that for 1940 of 0.13 deg C. This means that the GMTA value, when the oscillating anomaly is at its maximum, increases in every new cycle. Is this global warming caused by human emission of CO2?
The data required to establish the effect of CO2 emission on global mean temperature already exist. The global mean temperature data are available from the Climate Research Unit of the Hadley Centre shown in Figure 3, and the CO2 emission data are available from the Carbon Dioxide Information Analysis Centre [8]. For the period from 1880 to 1940, the average emission of CO2 was about 0.8 G-ton, and the increase in the GMTA was 0.13+0.22=0.35 deg C. For the period from 1940 to 2000, the average emission of CO2 was about 4 G-ton, but the increase in GMTA was the same 0.48-0.13=0.35 deg C. This means that an increase in CO2 emission by 4/0.8=5-fold has no effect in the increase in the GMTA. This conclusively proves that the effect of 20th century human emission of CO2 on global mean temperature is nil.
Note that the increase in GMTA of 0.35 deg C from 1880 to 1940 (or from 1940 to 2000) in a 60 year period has a warming rate of 0.35/60=0.0058 deg per year, which is the slope of the linear anomaly given by Equation 1. As a result, the linear anomaly is not affected by CO2 emission. Obviously, as the oscillating anomaly is cyclic, it is not related to the 5-fold increase in human emission of CO2.
Figure 4, with high correlation coefficient of 0.88, shows the important result that the observed GMTA can be modeled by a combination of a linear and sinusoidal pattern given by Equation 3. This single GMTA pattern that was valid in the period from 1880 to 1940 was also valid in the period from 1940 to 2000 after about 5-fold increase in human emission of CO2. As a result, the effect of human emission of CO2 on GMTA is nil.
Further evidence for the non-existent relationship between CO2 and GMTA is IPCC’s projection of a global warming of 0.2 deg C per decade, while the observed GMTA trend was “quite stable since 2000” [5]. The evidence will be “unequivocal” if global cooling by about 0.42 deg C starts soon and continues until about 2030, as shown by the model in Figure 3. The IPCC projection for the GMTA for 2020 is 0.8 deg C, while the prediction from the model for this value is 0.2 deg C, a large discrepancy of 0.6 deg C. If this global cooling is confirmed, it will then be time to bury the theory that CO2, a plant food, causes catastrophic global warming. Fortunately, we don’t have to wait too long for the burial. Less than ten years. It will be cheering news!
IPCC Projections
According to the IPCC [1], “For the next two decades, a warming of about 0.2°C per decade is projected for a range of SRES emission scenario.”
IPCC explains this projection as shown in Figure 5 where GMTA trend lines were drawn for four periods from 2005 to 1856, 1906, 1956 & 1981. These trend lines give increasing warming rate from a low value of 0.045 deg C per decade for the RED trend line for the first period from 1856 to 2005, to a greater value of 0.074 deg C per decade for the PURPLE trend line for the second period from 1906 to 2005, to a still greater value of 0.128 deg C per decade for the ORANGE trend line for the third period from 1956 to 2005, and to a maximum value of 0.177 deg C per decade for the YELLOW trend line for the fourth period from 1981 to 2005. IPCC then concludes, “Note that for shorter recent periods, the slope is greater, indicating accelerated warming” [9].
If this IPCC interpretation is correct, catastrophic global warming is imminent, and it is justified for the world to be griped by fear of global warming. However, is IPCC’s “accelerated warming” conclusion shown in Figure 5 correct?
What the GMTA pattern in Figure 3 shows is that it has cooling and warming phases. As a result, in Figure 5, comparing the warming rate of one period that has only one warming phase with another period that has a combination of warming and cooling phases will obviously show the maximum warming rate for the first period. This is comparing apples to oranges.
Comparing apples to apples is to compare two periods that have the same number of cooling and/or warming phases.
.”]
One example of comparing apples to apples is to compare one period that has one warming phase with another that also has one warming phase. From Figure 3, two 30-year periods that have only one warming phase are the periods from 1910 to 1940 and from 1970 to 2000. For the period from 1910 to 1940, the increase in GMTA was 0.13+0.64=0.77 deg C, giving a warming rate of (0.77/30)*10=0.26 deg C per decade. Similarly, for the period from 1970 to 2000, the increase in GMTA was 0.48+0.29=0.77 deg C, giving an identical warming rate of 0.26 deg C per decade. Therefore, there is no “accelerated warming” in the period from 1970 to 2000 compared to the period from 1910 to 1940.
A second example of comparing apples to apples is to compare one period that has one cooling and warming phases with another that also has one cooling and warming phases. From Figure 3, two 60-year periods that have only one cooling and warming phases are the periods from 1880 to 1940 and from 1940 to 2000. For the period from 1880 to 1940, the increase in GMTA was 0.13+0.22=0.35 deg C, giving a warming rate of (0.35/60)*10=0.06 deg C per decade. Similarly, for the period from 1940 to 2000, the increase in GMTA was 0.48-0.13=0.35 deg C, giving an identical warming rate of 0.06 deg C per decade. Therefore, there is no “accelerated warming” in the period from 1940 to 2000 compared to the period from 1880 to 1940.
From the above analysis, IPCC’s conclusion of “accelerated warming” is incorrect, and its graph shown in Figure 5 is an incorrect interpretation of the data.
Based on observed GMTA pattern shown in Figure 3, a global warming phase lasts for 30 years, and it is followed by global cooling. As a result, the recent global warming phase that started in the 1970s ended in the 2000s as shown by the current GMTA plateau, and global cooling should follow. Therefore, IPCC’s projection for global warming of 0.2 deg C per decade for the next two decades is incorrect. Also, divergence between IPCC projections and observed values for the GMTA has started to be “discernible” since 2005 as shown in Figure 3.
According to the Occam’s Razor principle, given a choice between two explanations, choose the simplest one that requires the fewest assumptions. Instead of applying the Occam’s Razor principle by assuming the cause of GMTA turning points to be natural, the IPCC assumed the cause to be man-made [9]:
From about 1940 to 1970 the increasing industrialisation following World War II increased pollution in the Northern Hemisphere, contributing to cooling, and increases in carbon dioxide and other greenhouse gases dominate the observed warming after the mid-1970s.
Like in the 1880s & 1910s, what if the causes of the GMTA turning points in the 1940s and 1970s were also natural?
Figure 4, with high correlation coefficient of 0.88, shows the important result that the observed GMTA can be modeled by a combination of a linear and sinusoidal pattern given by Equation 3. This single GMTA pattern that was valid in the period from 1880 to 1940 was also valid in the period from 1940 to 2000 after about 5-fold increase in human emission of CO2. As a result, the effect of human emission of CO2 on GMTA is nil. Also, IPCC’s conclusion of “accelerated warming” shown in Figure 5 is incorrect.
What is the cause of the GMTA turning point from warming to plateau in the 2000s? Here is the suggestion by Mike MacCracken [4]:
I think we have been too readily explaining the slow changes over past decade as a result of variability–that explanation is wearing thin. I would just suggest, as a backup to your prediction, that you also do some checking on the sulfate issue, just so you might have a quantified explanation in case the prediction is wrong.
According to the IPCC and the above suggestion, the 1940 GMTA turning point from global warming to cooling was caused by sulfates, the 1970 GMTA turning point from cooling to warming was caused by carbon dioxide, and the 2000 GMTA turning point from warming to plateau was caused by sulfates. It is interesting to note that sulfate and carbon dioxide gave the globe a 30-year alternate cooling and warming phases from 1940 to 2000. This is just absurd.
Instead of saying, “Be awkward if we went through a early 1940s type swing!” in private, but global warming “is accelerating at a much faster pace” in public, please release the world from the fear of climate catastrophe from use of fossil fuels, as this catastrophe is not supported by your own data. It is extremely callous not to do so.
Is the theory that “human emission of CO2 causes catastrophic global warming” one of the greatest blunders or something worse of “science”? We will find the unambiguous answer within the next ten years. Hope they don’t succeed in calling the plant food a pollutant and tax us before then.
==========================================
This document is also available as a PDF file, link below:
For any criticism, please leave a comment below, or contact me at orssengo@lycos.com
Girma J Orssengo
Bachelor of Technology in Mechanical Engineering, University of Calicut, Calicut, India
Master of Applied Science, University of British Columbia, Vancouver, Canada
Doctor of Philosophy, University of New South Wales, Sydney, Australia
===========================================
REFERENCES
[1] IPCC Fourth Assessment Report: Climate Change 2007
“a warming of about 0.2°C per decade is projected”
http://www.ipcc.ch/publications_and_data/ar4/wg1/en/spmsspm-projections-of.html
[2] Observed Global Mean Surface Temperatures from the Climate Research Unit of the Hadley Center.
[3] Climate Change Science Compendium 2009
“is accelerating at a much faster pace”
http://www.unep.org/pdf/ccScienceCompendium2009/cc_ScienceCompendium2009_full_en.pdf
[4] Climategate Email from Mike MacCracken to Phil Jones, Folland and Chris
“that explanation is wearing thin”
http://www.eastangliaemails.com/emails.php?eid=947&filename=1231166089.txt
[5] Climategate Email from Mick Kelly to Phil Jones
“Be awkward if we went through a early 1940s type swing!”
http://www.eastangliaemails.com/emails.php?eid=927&filename=1225026120.txt
[6] The Pacific Decadal Oscillation (PDO)
http://jisao.washington.edu/pdo/
[7] Pacific Ocean Showing Signs of Major Shifts in the Climate
http://www.nytimes.com/library/national/science/012000sci-environ-climate.html
[8] Carbon Dioxide Information Analysis Center
Global CO2 Emissions from Fossil-Fuel Burning, Cement Manufacture, and Gas Flaring
http://cdiac.ornl.gov/ftp/ndp030/global.1751_2006.ems
[9] Climate Change 2007: Working Group I: The Physical Science Basis
How are Temperatures on Earth Changing?
http://www.ipcc.ch/publications_and_data/ar4/wg1/en/faq-3-1.html
Discover more from Watts Up With That?
Subscribe to get the latest posts sent to your email.
How does the CO2 trend – assuming the AGW advocates’ claim of “constant CO2 (until evil mankind began raising it artificially) in the mid 50’s, then a rapid increase thereafter) fit the 30 year cyclical temperature trend?
Nothing but the PDO + AMO changes, or solar influence fit those up and down cycles….
A “least squares best fit” is merely ….. a straight line. It is nothing but a “naive guess” – as complained about by a equally critical observer earlier.
Steven mosher (09:53:39) :
Exactly! The interesting thing to me is that the observed T/CO2 relationship shows little evidence of positive feedback, which is the cornerstone of Hansen’s belief system.
Without feedback, the temperature stays within 2C (the oft stated “safe temperature”) and thus the whole CAGW religion has no support from observation.
And with these sorts of discussions, we take the high road on the scientific side.
Mike Jonas (16:46:12)
Date Flux SSN
2010 02 08 94 71
source: http://www.swpc.noaa.gov/ftpdir/latest/DSD.txt
Mike Jonas (16:46:12)
That is the report number you are looking at, not the sunspot number!!
or are you reading 1049? that was a region.
http://www.swpc.noaa.gov/ftpdir/forecasts/SRS/0218SRS.txt
The SESC sunspot number definately was SSN 71 on the 8th Feb.
I can`t find my way around the swpc files but you can see it also on the spaceweather archive: http://www.spaceweather.com/archive.php?view=1&day=09&month=02&year=2010 down the left hand column.
Dr. Roy Spencer will be interviewed tonight (Mon.) on Coast-to-Coast from 10pm to 2am Pacific time.
Ulric Lyons : “The SESC sunspot number definately was SSN 71 on the 8th Feb.”
You are quite right. My apologies. The site from which I source SSN, USAF/NOAA daily Sunspot Summary:
http://www.swpc.noaa.gov/ftpmenu/forecasts/SRS.html
unfortunately only gives the last 75 days, and 8 Feb has just dropped off the list. I do have the data archived, and for 9 Feb (it evidently differs from your source by a day) it was indeed 71:
1045 N23W17 256 0420 Fkc 20 35 Beta-Gamma-Delta
1046 N24E52 186 0030 Bxo 10 04 Beta
1047 S15E70 169 0010 Axx 02 02 Alpha
(10+35 + 10+04 + 10+02 = 71)
I have now checked everything again and found where I had treated multiple groups incorrectly for some past dates. Corrected graph posted here:
http://members.westnet.com.au/jonas1/SunspotGraph.JPG
By my calculations, the average SSNs for Jan-Mar 2010 were 21.5, 30.8, 24.2, but the NASA monthly SSN data at http://solarscience.msfc.nasa.gov/greenwch/spot_num.txt appears to me to show them as 13.1, 18.6, 15.4.
There is a comment on their website at
http://solarscience.msfc.nasa.gov/greenwch.shtml
“Note that the data in the raw data files (gyyyy.txt) are uncorrected for the change in data source in 1977. The derived data [..] now ALL include the correction factor of 1.4x after 1976/12/31.”
which shows how the data needs handling with care but doesn’t explain the discrepancy.
Except that temps and SST’s correlate better than any of it. Add oceanic/atmospheric oscillations and ya got a winner! I believe it will eventually be possible to predict when a cold spell is overdue, much like earthquakes are predicted today. We don’t know what day, but we do know that one is coming.
What we must not forget is that we need an answer.
1. IPCC claims a warming of 0.2 deg C per decade and acclerated warming [Figure 5]
2. Not us, but themselves in private say “slow changes over past decade” [REF 4] and “the level has really been quite stable since 2000 or so and 2008 doesn’t look too hot” [REF 5] (so in private they don’t agree with point 1)
3. The question each of us has to answer is that in the next 10 to 20 years, will the globe have further warming or cooling.
I bet anyone, based on my article, as the GMTA pattern was valid for 129 years, we will have global cooling in the next 10 to 20 years.
Cheering News:
The Australian Government shelfed its Emission Trading Scheme (tax on air).
That is a big win.
The plant food is not a pollutant, yet!
Very good article, being a “scientist” myself but in a realm far away from climatology or metorology I was able to follow the general theme and found it quite “rational”. I think that is going to be the problem with this presentation, it is to simple and logical for any politician etc. to consider plausible.
OT: I consider myself a skeptical skeptic when it comes to AGW, truth is I don’t know what to believe. I am certain that the debate is not over, and I am not convinced that CO2 (my science is Biochemistry) is in fact a factor in GW at all, certainly not enough to take on heroic efforts and costs associated with eliminating it. I am supportive of alternative energy etc and welcome the time when those are widely availble and affordable for everyone. What concerns me is the AGW supporters constant claims that NOT ONE CLIMATOLOGIST (Is that even a university degree?) stands on the side of the “deniers”……Is this true, or is it that in order to be titled “Climatologist” you have to believe in AGW?
stevengoddard (14:47:21)
Not true. CO2 statistically does no better as an explanatory variable than a straight line since 1880. And it does no better than the US Postal Rates since 1880. The 120-year correlation of temperature with the cost of mailing a letter is just as good as the 120-year correlation of temperature with CO2.
You repeatedly claim that this correlation means something, but it doesn’t mean any more than the 120-year correlation of temperature with the distance to Alpha Centauri.
Absolutely not, that’s why there is huge debate about size of the “climate sensitivity”. The fact that CO2 is a greenhouse gas is well defined by physics. The effect of CO2 on temperature is what all the debate is about, and it is neither well defined nor well understood …
This “it’s just simple physics” argument is nonsense. See my post on “The Unbearable Complexity of Climate” if you don’t understand why that is so.
In addition, if the “CO2 drives temperature” theory were true, you’d expect the logarithm of CO2 to correlate better with temperature than does the raw CO2 level. But this is not the case. Over the 120-year period, the correlation of the two are within 0.01 of each other. Perhaps you can explain that, as it directly contradicts your theory.
You’ll be glad to know, however, that the best correlation in the bunch is the 120-year correlation between CO2 and US Postal Rates …
John A. (23:30:34) wrote: “I think the temptation to think that “the future is a continuation of the present trends” is at the root of the global warming scare and pretty much every apocalyptic movement there has ever been.”
John, you are bang on target.
The brainless extrapolation of a trend without seeking to identify the processes behind it is to be avoided like the plague. Before Kepler and Newton, one might reasonably extrapolate the Earth’s orbit over a cherrypicked timescale (say, a week) and claim that we were headed for Alpha Centauri. Without the underlying physics, it’s just numerology.
This gentleman claims, having identified a 129-year trend, that it’s reasonable to suppose it will continue another 20. Sorry, this is not science; it’s no better than IPCC numerology.
stevengoddard (09:31:38) :
You came up with the same numbers I did. At 550 PPM, the temperature increase is 1.5C above the present.
If we use the figures we’re using now:-
1959/1-2009/11 = 621 months.
CO2 1958/3 = 316ppm, 2009/11 = 386ppm. So 386 – 316=70ppm.
70ppm / 621 months = 0.11272142ppm per month.
Now if we assume CO2 constant growth @ur momisugly 0.11272142ppm per month
and we calculate from 2009/11 at the present 386ppm and we get.
550 – 386 = 164
164 / 0.11272142 = 1455 months or 211.25 years to reach 550ppm.
Checking the 1.5c figure (not that I don’t trust you) and using my figure of 0.00928571C per 1 ppm CO2 I have.
1.5 / 0.00928571 = 161.53853609ppm
So my temp rise per 1ppm Co2 is a little higher than yours.
1.5 / 0.00914671 = 163.99339216ppm
The difference of 0.000139C per 1 ppm is not statisticly significant so our findings are robust.
We can say by the year 2221 it’s gonna be 1.5C warmer.
I’ll alert the media.
It is my personal opinion that correlation is a poor choice of indicator to form the basis for a scientific theory because this is, at best, only circumstantial evidence. I also agree that our general climate dynamics may be so complex that no elegant solution or theory will ever be possible.
My suggestion would be to find the simplest possible environments, such as a cloudless tropical desert, or cloudless arctic night and calculate the expected greenhouse effects for these conditions and compare the predictions with results observed over the years.
I do remember the purple three cent Jefferson stamps and the 19-cent hamburgers.
Reply: I remember 10 cent hamburgers and 10 cent cokes and I’m only 52. Upon doing research either it was a special, or I have a false memory. ~ ctm
Willis Eschenbach (00:45:33) :
dT/dt and dCO2/dt are not constants (linear slope) as you keep insisting.
https://spreadsheets.google.com/oimg?key=0AnKz9p_7fMvBdE9rZ3lzMHRRaGxUb3JHRXZfU0daeWc&oid=2&v=1272367154522
The rate of increase of CO2 has increased sharply since the 1950s, just as the rate of increase in my age has increased sharply since the 1950s. Furthermore, the relationships you chose (like population growth) are directly tied to the amount of CO2 in the atmosphere. If there are more people, there are more cars. They are not the independent relationships you claim them to be.
What is a constant is the ratio of dT/dCO2.
https://docs.google.com/Doc?docid=0AXKz9p_7fMvBZGR3ODJ3d3NfNjE2Yzdxc2MzZ20&hl=en
We expect from physics that temperature will increase with CO2. I don’t think you will find a serious atmospheric physicist (including Spencer or Lindzen) who believes otherwise. Spencer and Schmidt have both stated that they expect to see a doubling of CO2 produce a 1.2 degree increase in temperature, similar to what observations and Stefan-Boltzman predict.
https://docs.google.com/Doc?docid=0AXKz9p_7fMvBZGR3ODJ3d3NfNjE2Yzdxc2MzZ20&hl=en
MartinGAtkins (03:16:31) :
You provided a constant of 0.00928571 C / PPM
(550-390) * 0.00928571 = 1.49
Your formula predicts a further increase in temperature of ~1.5C going from 390 PPM to 550 PPM, just as my plot and physics does.
https://docs.google.com/Doc?docid=0AXKz9p_7fMvBZGR3ODJ3d3NfNjE2Yzdxc2MzZ20&hl=en
Meant to say :
“Spencer and Schmidt have both stated that they expect to see a (non-feedback) doubling of CO2 produce a 1.2 degree increase in temperature”
Girma (21:59:12) :
The low end IPCC estimates predict a warming of 2C from “pre-industrial levels” which is much less than a “0.2C/increase per decade.”
The problem with the IPCC report is that it predicts a “most likely” 3C, and high end 6C – which both appear to be too high.
stevengoddard (07:00:14) :
Chris Wright (03:24:11) :
“There are no tricks in the plots. They are straight up Temperature vs. CO2 and show good correlation. The fact that you don’t like the results doesn’t invalidate them.”
The first argument against these graphs is that you could demonstrate equally good correlation with lots of random factors, but Willis got in there first. Bearing in mind that global temperatures have been increasing since the end of the LIA, it’s hardly surprising that the temperature shows an upwards trend, just as CO2 does.
My original point was that there is no filtering, so the points tend to fill a wide band that looks linear. Of course, the standard plots of temperature against time show that for much of the time temperatures are going down while CO2 goes up.
Some time ago I reproduced those graphs, but also added some filtering as follows:
1. No filtering:
http://www.kline.demon.co.uk/AANoFiltering.jpg
It looks similar to the plots you showed. Blue line is CO2, red is temperature against time (I think it was CRUTEMP, I did the plots a long time ago).
2. One year rolling average
http://www.kline.demon.co.uk/AAOneYearFilter.jpg
With filtering it now looks very similar to CRUTEMP (of course, the horizontal scales are different, the upper one is plotter against CO2, not time). That’s what you would expect, as the CO2 graph is, very approximately, a straight line.
When you remove the noise caused by short-term variation, what seemed to be vaguely a straight line is now obviously not. The lack of warming over nearly the last decade shows a distinct lack of correlation. The Climategate emails show a prominent team member agonising over the lack of warming. Doesn’t sound like high correlation to me.
The reason why I don’t like those plots is that no filtering was used. Filtering is a standard procedure in climate science because it reduces the noise and makes trends easier to see. With this kind of plot the noise makes it look like a straight line, which is clearly misleading.
So, an obvious question: why was no filtering used? I think I know what the answer to that is, but what do you think?
Chris
Dr Orssengo – a careful, thoughtful and well presented analysis from a new perspective – thank you sir.
Its best quality is the very good fit with reality for recent decades and its greatest value is the projection for the next five to 10 years.
We are at or near a ‘tipping point’ in public opinion on climate change in the US and getting close in the UK and other countries. High quality input like yours will influence many thousands of thinking people everywhere and hasten the mass shift away from the AGW mania that has gripped the world for over 20 years.
I don’t think we will have to wait 10 years to see the benefit of your work – another couple of winters like the last one in Europe and the USA and we will see a seriously large majority of people who no longer believe in AGW or greenhouse gasses. Soon the sheer weight of public opinion will put Messrs Gore, Pachauri, et al, firmly on the back foot. Next the important work of demolishing the whole Carbon edifice – low Carbon energy, Carbon footprints, the Carbon Trust, Cap and Trade, Carbon offsets, Carbon emission permits, etc., etc., can get going. The proponents are well entrenched and well funded (with our tax Dollars) so it will be an epic struggle – but thanks to people like you, Anthony and the great army of like minds, this is now, at last, a winnable fight.
Thank you again.
d marloil
Chris Wright (05:01:04) :
Try scaling your CO2 plot by 0.5 along the Y-axis and see what happens.
https://spreadsheets.google.com/oimg?key=0AnKz9p_7fMvBdE9rZ3lzMHRRaGxUb3JHRXZfU0daeWc&oid=2&v=1272370776872
You are plotting the same data as me, and there is no reason to expect different results.
Chris Wright (05:01:04) :
Interesting to hear people here complaining about plots of raw data.
I keep wishing that NCDC, USHCN and GISS would make plots of raw data readily available.
stevengoddard (05:38:25) :
“I keep wishing that NCDC, USHCN and GISS would make plots of raw data readily available.”
When GISS posts what they say is “raw data,” why does it change from one month to another? click
Smokey (05:51:40) :
Looks to me like you have mixed raw data with homogeneity adjusted data in your blink graphs. The current Decatur raw plot looks just like your 2006 raw plot
http://data.giss.nasa.gov/cgi-bin/gistemp/gistemp_station.py?id=425745600020&data_set=0&num_neighbors=1