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.
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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
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See: Don Easterbrook’s AGU paper on potential global cooling for a similar temperature projection based on the PDO cycle. In 2001, Easterbrook predicted temperature would be declining until 2040, then increasing till 2060 and then declining till 2090. See papers at Easterbrook’s home page.
Is this just throwing the IPCC models under a bus to keep the Warmist theory alive?
John Cooke (13:13:35) :
“As such, any predictions made with it are purely based on the (relatively recent) past observational history. It makes no attempt to understand the underlying physics.
This lack of a proper understanding of the physics involved (including a lot of stuff that apparently is not included in climate models at present, such as solar activity effects) means that predictions made with it are not particularly helpful. If the parameters change, such as (for example) a change in solar activity that does not fit the pattern of recent years, then the ‘model’ has no way to take account of this.”
Totally. My findings on solar variation did enable forecasts for the recent N.H cold winters and wet summers (and the El Nino), and can easily hincast the coldest winters of the last 2 thousand years that we have records for, and follow most monthly anomalies on 351yrs of CET. I would still largely stick to this forecast;
http://landscheidt.auditblogs.com/2008/06/03/the-sunspot-cycle-and-c24/
although my outlook for 2025 to 2038 is of a very warm period. Harris Mann also have this period marked as hot and dry. If it is to be dry, then there would have to be an absence of significant temperature drops during summer months, such as we have had in the last few summers, and no serious temperature rises in winter months.
Some time ago I read a post contending that complex systems, like weather, are more accurately predicted by mathematical equations than by systems analysis. I guess this is an attempt to prove that. Even if this particular effort has some flaws, I’m interested in seeing the concept tested.
Alexander (12:36:19) :
Excellent research and superb exposition. My only worry is as follows:
if the Cru data base is biased upward due to the increasing UHI effect not being corrected for, this research suggests that instead of 30-yr warming then cooling cycles, we are actually heading toward 30-yr cooling then 30-yr increased cooling periods.
No one is suggesting that all the warming since the 1970s is due to the UHI effect.
The exact match between the two warm periods is only statistically fortuitous. Values of equivalent magnitude are enough in a projection to validate the study provided the difference is not statistically significant.
We have no idea what effect UHI has on the CRU data but values of say .01 or .03 over a thirty year period would not alter the broader scope of the study.
lol. this is great. go girma. however, you should change the model so 2003 – 2100 is just a mirror image of 1880 -2002. you need to make the linear trend a low frequency triangle wave oscillation.
I look forward to the update.
I don’t understand the criticisms of this analysis. Yes itz a mathematical model that does nothing to explain the physics but it has tremendous value. It clearly shows that there is a 60 year climate cycle superimposed on a gradually rising trend that for the time being I will assume is part of a larger cycle or cycles too long in time span to be visible in this short a data set. The point is that NEITHER correlate to CO2 theory. So the question becomes, what the heck DO they correlate to and what are the physcis of THOSE processes?
BTW my 1974 Encylopaedia Britannica (which is an excellent source of climate information uncontaminated by ridiculous politics) talks about the data in terms of 60 to 75 year cycles. Too bad we didn’t spend the last 40 years figuring out what their driving factors were instead of trying to tax them. Instead we “forgot” that this is not new, and have to rediscover it again. Like the earth was flat, then the Greeks said no itz round, and then it was flat again for a few hundred years and now itz round again.
Henry Galt (12:29:59) : You asked, “Does anyone have any current address for the Central England Temperature (CET) series please?”
Daily CET temps from 1772 are available through the KNMI Climate Explorer and they look current:
http://climexp.knmi.nl/getindices.cgi?UKMOData/daily_cet+Central_England_Temperature+t+someone@somewhere+366
And the monthly CET data from 1659 is also available there:
http://climexp.knmi.nl/getindices.cgi?UKMOData/cet+Central_England_Temperature+t+someone@somewhere
The model is similar to Syun-Ichi Akasofu’s projection (see: http://www.appinsys.com/GlobalWarming/GW_TemperatureProjections.htm)
While strictly mathematical models that do not contain representations of the underlying causative factors have limited value, Hansen and IPCC models that misunderstand the causative factors are no better. Their models basically come down to GHG as the only significant forcing (see: http://www.appinsys.com/GlobalWarming/HansenModel.htm)
The mathematical models that simply reproduce the 60-year cycle with an upwards trend don’t include the underlying longer-term cycle since we don’t have observations from a sufficiently long time frame to know what the cycle length may be. (Or even what causes these cycles.)
My analogy is this: we have been measuring temperatures for two days (each day is the 60-year cycle). Today was warmer than yesterday (because it is spring). We haven’t been measuring long enough to know how long until summer (or what the length of the “annual” cycle is).
This type of analysis which is based on past history is only valid for a short time in the future. Maybe 30 years at most. As a result few AGW followers will take this seriously.
It’s like looking at the stock market history for any short period of time. Quite often you can predict the future but eventually something not incorporated in the model comes into play and everything changes.
roger (13:08:57) : Regarding your reply to Henry Galt, “they are indeed unobtainable,” scroll up a comment or two to my reply to Henry. The data is available through KNMI.
astonerii (13:28:08) : You wrote, “1934 was warmer than 1998…”
Are you discuss U.S. temperatures or Global temperatures? If global, are you discussing land or sea surface tempertures?
The model predicts a steadily increasing temperature. However, that is NOT true. There is a roughly 178-year cycle superimposed on top of a larger 356-year cycle for temperature based upon the solar cycles. (Some even suppose a ~1424-year cycle, but temperature records before the 1600s are virtually nonexistent). These cycles both contribute to a slow warming for roughly 80-90% of the time, followed by a steep drop (4-9X the rate of the rise) during the other 10-20% of the time. Currently both cycles are near the top. Numerous predictions of the solar cycle agree that a solar minimum of strength between the Dalton and Maunder is coming starting in Cycle 24 (now), strengthening in Cycle 25. Livingston and Penn provide a mechanism for the original Maunder Minimum, and also an extrapolation that produces the same characteristics within 10-15 years. Should a 1,424-year cycle exist, it is also due to go down fast during the same time. Oh, and don’t even get me started about the Milankovitch cycles.
Thank you Dr Orssengo. It will take a bit more time to review the references, but this is a thorough and concise presentation that adheres to fact rather than fiction. Devilishly delightful that you thought to credit HADCRU for the data! Truly a refreshing read!
Here’s to many more such truths, made so clear and plain. It’s Occam approved!
Cheers!
MUST READ: The Greenhouse Effect: Origins, Falsification, & Replacement by Timothy Casey B.Sc. (Hons.)
Sunday, April 25th 2010, 4:58 PM EDT
Co2sceptic (Site Admin)
This is a MAJOR paper that Hans Schreuder informed Alan Siddons about today
A few choice plums:
#Everyone knows what the greenhouse effect is. Well … do they? Ask someone to explain how the greenhouse effect works. There is an extremely high probability that they have no idea.
#Beware of wheels within energy diagrams as these usually constitute the energy creation mechanism of perpetual motion machines. One such gem of clarity, used uncited by Plimer (2009, p. 370), was offered by Kiehl and Trenberth…
#The mechanism by which the addition of carbon dioxide warms the atmosphere has no empirical basis. Therefore the assertion that global warming is anthropogenic, may well be philosophical and perhaps political, but it is most certainly not scientific.
#Increasing visible radiation, even by quite a large amount, results in no measurable rise in temperature because no appreciable amount of visible radiation is converted into infrared when absorbed and re-emitted – contrary to Arrhenius’ hypothesis.
#Tyndall’s confusion of absorption and opacity is a major error that was propagated into Arrhenius’ Greenhouse hypothesis, and constitutes a fact not accounted for in Arrhenius’ calculation of “Climate Sensitivity” to carbon dioxide.
#Although the greenhouse effect died with the Wood experiment, the diverse multitude of radiation “budgets” shows that the greenhouse effect is far from buried. This is a classic case of shifting the goalposts, because the greenhouse effect is not a scientific hypothesis that can be buried when it dies from experimental causes; it is a political symbol that cannot be allowed a proper burial, and so remains forever on display at the funeral parlor; an eternal viewing just like Lenin’s.
By the way, he’s an Aussie.
Alan S
Download the PDF here: http://climaterealists.com/attachments/ftp/The Greenhouse Effect Origins Falsification Replacement by Timothy Casey3.pdf
Another study that blows-up the IPCC models, whats not to like.
It’s not making predictions.
Seems like it validates climate variability.
Al Gore et al., are running out of time, we are now on the downslope of the temperature curve.
The ~60 year cycle has been found in temperature proxies extending back 1000-1500 years:
http://hockeyschtick.blogspot.com/2010/01/fourier-analysis-of-climate.html
Numerology.
You fit the “model” to the data and the model “fits” the data. The problem is the model has no physical meaning. Fitting a straight line to a cloud of points is not the same thing as finding the trend. that is merely finding a line that minimizes the error. estimating a trend is more complicated than that, see the thread on Barts blog where VS explains.
The other problem is your out of sample performance: If your model is a “physical” model rather than a merely a ‘curve fit’ then we can use it to hindcast.
a simple test: hind cast the GATA for 1850: hadcru3 has that, decidely warmer than your model hindcasts. Or hindcast back to the MWP. bad idea there. or build your “model” with just part of the data ( from 1850 to 1950)
see how you do on 1950-2010. or build it from 1940 to 2000 and then see how well it works for 2000-2010 and from 1850-1940
My sense is that you are long way worse than the typical GCM. That’s not an endorsement of GCMs, but they have more skill than your “model.”
http://climateaudit.org/2008/05/09/giss-model-e-data/
25 April: Daily Mail: The ash cloud that never was: How volcanic plume over UK was only a twentieth of safe-flying limit and blunders led to ban
By David Rose, Matt Sandy and Simon Mcgee
The Mail on Sunday can today reveal the full extent of the shambles behind the great airspace shutdown that cost the airlines £1.3 billion and left 150,000 Britons stranded – all for a supposed volcanic ash cloud that for most of the five-day flights ban was so thin it was invisible.
As the satellite images of the so-called ‘aerosol index’ published for the first time, right, demonstrate, the sky above Britain was totally clear of ash from Iceland’s Eyjafjallajoekull volcano…
Attempts to measure the ash’s density were hampered because the main aircraft used by the Meteorological Office for this purpose had been grounded as it was due to be repainted.
Computers at the Met Office, which earlier forecast a ‘barbecue summer’ last year and a mild winter for this year, produced a stream of maps predicting the ash would cover a vast area, eventually stretching from Russia to Newfoundland. But across almost all of it, there was virtually no ash at all, and none visible to satellites….
As the Met Office is responsible for forecasting ash for Europe, air traffic controllers across the continent soon followed the UK lead, closing down aviation…
Unfortunately, the Met Office’s main research plane, a BAE 146 jet, had been stripped of its gear ahead of a paint job, so could not fly until last Tuesday – the last day of the ban..
http://www.dailymail.co.uk/news/article-1268615/The-ash-cloud-How-volcanic-plume-UK-twentieth-safe-flying-limit-blunders-led-lock-down.html
A wonderful article which brings it all together.
However, asking them to release the world from worrying about global warming is to ignore the fact that this is a global political scam with the goal to alter the world’s power structure, make governments in control of all energy and, thus, every aspect of our lives and finances, and form a one world government (the UN has high aspirations).
They have no intention of informing the public that there is no problem. They are the problem and only we can educate the public by spreading the real science of our climate as widely and loudly as possible.
This is a propaganda campaign to confuse the public enough to allow the passage of falsely based legislation to further their agenda.
Why do you think there has been a move to make conspiracy theory and theorists illegal? The global warming/climate change scam is one huge conspiracy!
our daily dose of alarmism, already being covered by ABC australia:
25 April: Nature: Richard A. Love: An oceanic ‘fast-lane’ for climate change
But estimates of its speed, taken as “snapshots” by instruments deployed from research vessels, had been “all over the place”, says Steve Rintoul, a physical oceanographer at the Antarctic Climate and Ecosystem Cooperative Research Centre in Hobart, Australia, and a co-author of the new study1.
Yasushi Fukamachi, an ocean scientist at Hokkaido University in Sapporo, Japan, led a team effort to determine the exact nature of the current…
This is significant because it represents a “fast lane” by which climatic and environmental changes affecting the Southern Ocean can propagate northward, says Alejandro Orsi, a physical oceanographer at Texas A & M University in College Station, who was not involved in the study..
Understanding such currents could help scientists to predict how the world will react to increasing levels of carbon dioxide, says Richard Alley, a geoscientist at Pennsylvania State University in University Park..
But the currents could change. “We’re not saying this could happen instantaneously, like the movie The Day After Tomorrow,” Fukamachi says, “but understanding this kind of current is very important to understanding global climate.”…
http://www.nature.com/news/2010/100425/full/news.2010.201.html?s=news_rss
Since you asked for criticism…
This is silly. No one consciously stands at the gas pump thinking: “Gee, I’m so proud at how far civilization has come thanks to these fossil fuels that I’m pumping into the gas tank of my modern internal combustion engine.” More likely, they’re thinking: “Hmmm, I wonder if those doughnuts on sale at the Quicky Mart are still fresh?”. As such, I would suggest the following minor revisions to your sentence (in italics):
Aside from that, the only other criticism I have about your essay is that it reads more like a compendium of user comments stitched together from the pages of WUWT rather than anything resembling a scientific critique or rebuttal to CAGW. For example, you cannot simply cite an arbitrary comment from the Climategate emails and make the claim that it conclusively proves or refutes anything about the “science” of global warming. Other people smarter than you have already tried that and have been rebuffed based on legitimate arguments involving context and certain other technicalities related to the casual and private nature of the discussions. In other words, It’s not that simple.
Nice try though.
An interesting post. Within its limitations, it shows that the IPCC alarmograph is deceptive.
David L. Hagen (15:25:54) :
See: Don Easterbrook’s AGU paper on potential global cooling for a similar temperature projection based on the PDO cycle. In 2001, Easterbrook predicted temperature would be declining until 2040, then increasing till 2060 and then declining till 2090. See papers at Easterbrook’s home page.
Perhaps it would be useful to validate Easterbrook’s projections now that the first decade is complete (Easterbrook predicted cooling from 2000).
Politely, as a long time propoenent of cyclical behavior in climate outcomes, I must midly disagree with a few points and assumptions made by the authors, and very strongly disagree with a few of the criticisms.
1. The short 30 year cycle is bounding (enclosing) almost all of the 30 year cyclical data points. The 30 year mathematical curve should instead have a smaller coefficient such that it predicts the average trend of the year-to-year curve, rather than be higher than max points, and lower than the min points. The equation period appears correct though, and explains much of the current propaganda (“This decade is the hottest ever” etc…) about the climate.
2. The linear term should be replaced with a 800 year periodic cycle rising from the depths of the 1600’s Little Ice Age, peaking at the 1150’s Medieval Warming Period, dropping again in the Dark Ages, peaking again earlier at the Roman Warm Period. This change will NOT change the ternd in the next 60 years, but will show that the next 200 years will begin a “significant” long-term decline.
3. Plotting the 60 cycle on top of the longer 800 cycle will allow the rpevious descrepancies in the past 1200 years of data to be resolved: A temperature proxy at ANY given year that “now” appears “off” significantly from other studies thanuse a date only 30 to 40 years different will, after getting plotted on a cyclical trend line, either fall into place, or allow a correction to the short range cycle.
Perhaps 62 or 66 or 72 years will prove more correct. Perhaps (more likely even!) is that the short term cycle is not “prefectly periodic” but reflects a dynamic whose PERIOD itself changes slowly over time.
4A. Several readers have condemned this paper “because it does not have a theory of “why” their is a period, but instead merely claims that there IS a short-term (and – as suggested above) a long-term period of climate temperatures.
Fine. So be it. (For now.) When continental drift was proposed as a theory, there was NO theory (or even a practical mechanism) to explain”WHY” the continents moved, but the theory began with the simple and elegant observation that “They DID move (in the past).” Later, as earthquake patterns became more clear, and undersea vents and ridges were discovered – though at the time of the theory, there was NO WAY to ancipate either line of reseach, no way to predict satellite radars, undersea mounts, etc!)
When the Periodic Table was laid out, there was no theory abut WHY the elements exhibited their patterns, but merely that EACH element FOLLOWED a specific repeating pattern, and that PATTERN was enough to predict the behaivor of future (entirely unknown) elements.
Copernicous, Brache and others could use simple circles for orbits, and such orbits were “good enough” to serve as a new models of the solar system – though the “theory of gravity” was NOT available to explain “why” a planet could orbit a distant object. Refinements are needed – just as eliptical orbits proved more accurate than Grecian-old plots.
Be humble – Recognize that the Greeks were more accurate in predicting motion than the “perfect circles” that attempted to replace them. It took many years for the more elegant, more accurate elliptical paths to come forth.
But even a “simple mathematical model” IS sufficient to show that a complex CO2-based fabrication of radiation feedbacks and artificial feedbacks is “false.”