Watts Up With That?

NEW An update to this has been made here:

evidence of a lunisolar influence on decadal and bidecadal oscillations in globally averaged temperature trends

Part II

By Basil Copeland and Anthony Watts

In Part I, we presented evidence of a noticeable periodicity in globally averaged temperatures when filtered with Hodrick-Prescott smoothing. Using a default value of lambda of 100, we saw a bidecadal pattern in the rate of change in the smoothed temperature series that appears closely related to 22 year Hale solar cycles. There was also evidence of a longer climate cycle of ~66 years, or three Hale solar cycles, corresponding to slightly higher peaks of cycles 11 to 17 and 17 to 23 shown in Figure 4B. But how much of this is attributable to value of lambda (λ). Here is where lambda (λ) is used in the Hodrick-Prescott filter equation:

The first term of the equation is the sum of the squared deviations d_t = y_t − τ_t which penalizes the cyclical component. The second term is a multiple λ of the sum of the squares of the trend component’s second differences. This second term penalizes variations in the growth rate of the trend component. The larger the value of λ, the higher is the penalty.

For the layman reader, this equation is much like a tunable bandpass filter used in radio communications, where lambda (λ) is the tuning knob used to determine the what band of frequencies are passed and which are excluded. The low frequency component of the HadCRUT surface data (the multidecadal trend) looks almost like a DC signal with a complex AC wave superimposed on it. Tuning the waves with a period we wish to see is the basis for use of this filter in this excercise.

Given an appropriately chosen, positive value of λ, the low frequency trend component will minimize. This can be seen in Figure 2 presented in part I, where the value of lambda was set to 100.

Figure 2 – click for a larger image

A lower value of lambda would result in much less smoothing. To test the sensitivity of the findings reported in Part I, we refiltered with a lambda of 7. The results are shown in Figures 3 and 4.

Figure 3 – click for a larger image

As expected, the smoothed trend line, represented by the blue line in the upper panel of Figure 3, is no longer as smooth as the trend in the upper panel of Figure 1 from Part I. And when we look at the first differences of the less smoothed trend line, shown in Figure 4, they too are no longer as smooth as in Figure 2 from Part I. Nevertheless, in Figure 4, the correlation to the 22 year Hale cycle peaks is still there, and we can now see the 11 year Schwabe cycle as well.

Figure 4 – click for a larger image

The strong degree of correspondence between the solar cycle peaks and the peak rate of change in the smoothed temperature trend from HadCRUT surface temperature data is seen in Figure 5.

Figure 5 – click for a larger image

The pattern in Figure 4, while not as eye-catching, perhaps, as the pattern in Figure 2 is still quite revealing. There is a notable tendency for amplitude of the peak rate of change to alternate between even and odd numbered solar cycles, being higher with the odd numbered solar cycles, and lower in even numbered cycles. This is consistent with a known feature of the Hale cycle in which the 22 year cycle is composed of alternating 11 year phases, referred to as parallel and antiparallel phases, with transitions occurring near solar peaks.

Even cycles lead to an open heliosphere where GCR reaches the earth more easily. Mavromichalaki, et. al. (1997), and Orgutsov, et al. (2003) contend that during solar cycles with positive polarity, the GCR flux is doubled. This strongly implicates Galactic Cosmic Ray (GCR) flux in modulating global temperature trends. The lower peak amplitudes for even solar cycles and the higher peak amplitudes for odd solar cycles shown in Figure 4 appears to directly confirm the kind of influence on terrestrial climate postulated by Svensmark in Influence of Cosmic Rays on Earth’s Climate (1998)From the pattern indicated in Figure 4, the implication is that the “warming” of the late 20th century was not so much warming as it was less cooling than in each preceding solar cycle, perhaps relating to the rise in geomagnetic activity.

It is thus notable that at the end of the chart, the rate of change after the peak associated with solar cycle 23 is already in the negative range, and is below the troughs of the preceding two solar cycles. Again, it is purely speculative at this point, but the implication is that the underlying rate of change in globally averaged temperature trends is moderating, and that the core rate of change has turned negative.It is important to understand that the smoothed series, and the implied rates of change from the first differences, in figures 2 and 4, even if they could be projected, are not indications of what the global temperature trend will be.

There is a cyclical component to the change in global temperature that will impose itself over the underlying trend. The cyclical component is probably dominated by terrestrial dynamics, while the smoothed series seems to be evidence of a solar connection. So it is possible for the underlying trend to be declining, or even negative, while actual global temperature increases because of positive cyclical factors. But by design, there is no trend in the cyclical component, so that over time, if the trends indicated in Figures 2 and 4 hold, global warming will moderate, and we may be entering a phase of global cooling.

Some are probably wondering which view of the historical correspondence between globally averaged temperatures and solar cycles is the “correct” one: Figure 2 or 4?

Such a question misconstrues the role of lambda in filtering the data. Here lambda is somewhat like the magnification factor “X” in a telescope or microscope. A low lambda (less smoothing) allows us to “focus in” on the data, and see something we might miss with a high lambda (more smoothing). A high lambda, precisely because it filters out more, is like a macroscopic view which by filtering out lower level patterns in the data, reveals larger, longer lived processes more clearly. Both approaches yield valuable insights. In Figure 2, we don’t see the influence of the Schwabe cycle, just the Hale cycle. In Figure 4, were it not for what we see in Figure 2, we’d probably miss some similarities between solar cycles 15, 16, and 17 and solar cycles 21, 22, and 23.In either case, we are seeing strong evidence of a solar imprint in the globally averaged temperature trend, when filtered to remove short term periodicities, and then differenced to reveal secular trends in the rate of change in the underlying long term tend in globally averaged temperatures.

At one level we see clear evidence of bidecadal oscillations associated with the Hale cycle, and which appear to corroborate the role of GCR’s in modulating terrestrial climate. At the other, in figure 4B, we see a longer periodicity on the order of 60 to 70 years, correspondingly closely to three bidecadal oscillations. If this longer pattern holds, we have just come out of the peak of the longer cycle, and can expect globally average temperature trends to moderate, and increased likelihood of a cooling phase similar that experienced during the mid 20th century.

In Lockwood and Fröhlich 2007 they state: “Our results show that the observed rapid rise in global mean temperatures seen after 1985 cannot be ascribed to solar variability, whichever of the mechanisms is invoked and no matter how much the solar variation is amplified.” . Yet, as Figure 5 demonstrates, there is a strong correlation between the solar cycle peaks and the peak rate of change in the smoothed surface temperature trend.

The periodicity revealed in the data, along with the strong correlation of solar cycles to HadCRUT surface data, suggests that the rapid increase in globally averaged temperatures in the second half of 20th century was not unusual, but part of a ~66 year climate cycle that has a long history of influencing terrestrial climate. While the longer cycle itself may be strongly influenced by long term oceanic oscillations, it is ultimately related to bidecadal oscillations that have an origin in impact of solar activity on terrestrial climate.

We are continuing to look at different methods of demonstrating a correlation. Please watch for future posts on the subject.

NEW An update to this has been made here:

evidence of a lunisolar influence on decadal and bidecadal oscillations in globally averaged temperature trends

References:

Demetrescu, C., and V. Dobrica (2008), Signature of Hale and Gleissberg solar cycles in the geomagnetic activity, Journal of Geophysical Research, 113, A02103, doi:10.1029/2007JA012570.

Hadley Climate Research Unit Temperature (HadCRUT) monthly averaged global temperature data set (description of columns here)

J. Javaraiah, Indian Institute of Astrophysics, 22 Year Periodicity in the Solar Differential Rotation, Journal of Astrophysics and Astronomy. (2000) 21, 167-170

Katsakina, et al., On periodicities in long term climatic variations near 68° N, 30° E, Advances in Geoscience, August 7, 2007

Kim, Hyeongwoo, Auburn University, “Hodrick-Prescott Filter” March 12, 2004

M. Lockwood and C. Fröhlich, Recent oppositely directed trends in solar climate forcings and the global mean surface air temperature, Proceedings of the Royal Society of Astronomy doi:10.1098/rspa.2007.1880; 2007, 10th July

Mavromichalaki, et. al. 1997 Simulated effects at neutron monitor energies: evidence for a 22-year cosmic-ray variation, Astronomy and Astrophysics. 330, 764-772 (1998)

Svensmark, Henrik, Danish Metorological Institute, Influence of Cosmic Rays on Earth’s Climate, Physical Review Letters 15th Oct. 98

Wikipedia, Hodrick-Prescott Filter January 20, 2008

NEW An update to this has been made here:

evidence of a lunisolar influence on decadal and bidecadal oscillations in globally averaged temperature trends

NOTE: This essay represents a collaboration over a period of a week via email between myself and Basil Copeland. Basil did the statistical heavy lifting and the majority of writing, while I provided suggestions, reviews, some ideas, editing, and of course this forum. Basil deserves all our thanks for his labor. This is part one of a two part series.  -Anthony

It is very unlikely that the 20th-century warming can be explained by natural causes. The late 20th century has been unusually warm.

So begins the IPCC AR4 WG1 response to Frequently Asked Question 9.2 (Can the Warming of the 20th Century be Explained by Natural Variability?).  Chapter 3 of the WG1 report begins:

Global mean surface temperatures have risen by 0.74°C ± 0.18°C when estimated by a linear trend over the last 100 years (1906-2005). The rate of warming over the last 50 years is almost double that over the last 100 years (0.13°C ± 0.03°C vs. 0.07°C ± 0.02°C per decade).

Was the warming of the late 20th century really that unusual?  In recent posts Anthony has noted the substantial anecdotal evidence for a period of unusual warming in the earlier half of the 20th century.  The representation by the IPCC of global trends over the past 100 years seems almost designed to hide the fact that during the early decades of the 20th century, well before the recent acceleration in anthropogenic CO2 emissions beginning in the middle of the 20th century, global temperature increased at rates comparable to the rate of increase at the end of the 20th century.

I recently began looking at the longer term globally averaged temperature series to see what they show with respect to how late 20th century warming compared to warming earlier in the 20th century.  In what follows, I’m presenting just part of the current research I’m currently undertaking.  At times, I may overlook details or a context, or skip some things, for the sake of brevity.  For example, I’m looking at two long-term series of globally averaged annual temperature trends, HadCRUTv3 and GHCN-ERSSTv2.  Most of what I present here will be based on HadCRUTv3, though the principal findings will hold true for GHCN-ERSSTv2.

I began by smoothing the data with a Hodrick-Prescott (HP) filter with lambda=100.  (More on the value of lambda later.) The results are presented in Figure 1.

Figure 1 – click for a larger image

The figure shows the actual data time series, a cyclical pattern in the data that is removed by the HP filter, and a smoothed long term low frequency trend that results from filtering out the short term higher frequency cyclical component. Hodrick-Prescott is designed to distinguish short term cyclical activity from longer term processes.

For those with an electrical engineering background, you could think of it much like a bandpass filter which also has uses in meteorology:

Outside of electronics and signal processing, one example of the use of band-pass filters is in the atmospheric sciences. It is common to band-pass filter recent meteorological data with a period range of, for example, 3 to 10 days, so that only cyclones remain as fluctuations in the data fields.

(Note: For those that wish to try out the HP filter, a freeware Excel plugin exists for it which you can download here)

When applied to globally averaged temperature, it works to extract the longer term trend from variations in temperature that are of short term duration.  It is somewhat like a filter that filters out “noise,” but in this case the short term cyclical variations in the data are not noise, but are themselves oscillations of a shorter term that may have a basis in physical processes.

For example, in Figure 1, in the cyclical component shown at the bottom of the figure, we can clearly see evidence of the 1998 Super El Niño.  While not the current focus, I believe that analysis of the cyclical component may show significant correlations with known shorter term oscillations in globally averaged temperature, and that this may be a fruitful area for further research on the usefulness of Hodrick-Prescott filtering for the study of global or regional variations in temperature.

My original interest was in comparing rates of change between the smoothed series during the 1920’s and 1930’s with the rates of change during the 1980’s and 1990’s.  Without getting into details (ask questions in comments if you have them), using HadCRUTv3 the rate of change during the early part of the 20th century was almost identical to the rate of change at the end of the century. Could there be some sense in which the warming at the end of the 20th century was a repeat of the pattern seen in the earlier part of the century?  Since the rate of increase in greenhouse gas emissions was much lower in the earlier part of the century, what could possibly explain why temperatures increased for so long during that period at a rate comparable to that experienced during the recent warming?

As I examined the data in more detail, I was surprised by what I found.  When working with a smoothed but non-linear “trend” like that shown in Figure 1, we compute the first differences of the series to calculate the average rate of change over any given period of time.  A priori, there was no reason to anticipate a particular pattern in time (or “secular pattern”) to the differenced series.  But I found one, and it was immediately obvious that I was looking at a secular pattern that had peaks closely matching the 22 year Hale solar cycle.  The resulting pattern in the first differences is presented in Figure 2, with annotations showing how the peaks in the pattern correspond to peaks in the 22 year Hale cycle.

Besides the obvious correspondence in the peaks of the first differences in the smoothed series to peaks of the 22 year Hale solar cycle, there is a kind of “sinus rhythm” in the pattern that appears to correspond, roughly, to three Hale cycles, or 66 years.  Beginning in 1876/1870, the rate of change begins a long decline from a peak of about +0.011 (since these are annual rates of change, a decadal equivalent would be 10 times this, or +0.11C/decade) into negative territory where it bottoms out about -0.013, before reversing and climbing back to the next peak in 1896/1893.  A similar sinusoidal pattern, descending down into negative annual rates of change before climbing back to the next peak, is evident from 1896/1893 to 1914/1917.  Then the pattern breaks, and in the third Hale cycle of the triplet, the trough between the 1914/1917 peak and the 1936/1937 peak is very shallow, with annual rates of change never falling below +0.012, let alone into the negative territory seen after the previous two peaks.  This same basic pattern is repeated for the next three cycles: two sinusoidal cycles that descend into negative territory, followed by a third cycle with a shallow trough and rates of change that never descend below +0.012.  The shallow troughs of the cycles from 1914/1917 to 1936/1937, and 1979/1979 to 1997/2000, correspond to the rapid warming of the 1920’s and 1930’s, and then again to the rapid warming of the 1980’s and 1990’s.

While not as well known as the 22 year Hale cycle, or the 11 year Schwabe cycle, there is support in the climate science literature for something on the order of a 66 year climate cycle.  Schlesinger and Ramankutty (1994) found evidence of a 65-70 year climate cycle in a number of temperature records, which they attributed to a 50-88 year cycle in the NAO.  Interestingly, they sought to infer from this that these oscillations were obscuring the effect of AGW.  But that probably misconstrues the significance of the mid 20th century cooling phase.  In any case, the evidence for a climate cycle on the order of 65-70 years extends well into the past.  Kerr (2000) links the AMO to paleoclimate proxies indicating a periodicity on the order of 70 years.  What I think they may be missing is that this longer term cycle shows evidence of being modulated by bidecadal rhythms.  When the AMO is filtered using HP filtering, it shows major peaks in 1926 and 1997, a period of 71 years.  But there are smaller peaks at 1951 and 1979, indicating that shorter periods of 25, 28, and 18 years, or roughly bidecadal oscillations.  There is a growing body of literature pointing to bidecadal periodicity in climate records that point to a solar origin.  See, for instance, Rasporov, et al, (2004).  A 65-70 year climate cycle may simply be a terrestrial driven harmonic of bidecadal rhythms that are solar in origin.

In terms of the underlying rates of change, the warming of the late 20th century appears to be no more “unusual” than the warming during the 1920’s and 1930’s.  Both appear to have their origin in a solar cycle phenomenon in which the sinusoidal pattern in the underlying smoothed trend is modulated so that annual rates of change remain strongly positive for the duration of the third cycle, with the source of this third cycle modulation perhaps related to long term trends in oceanic oscillations.  It is purely speculative, of course, but if this 66 year pattern (3 Hale cycles) repeats itself, we should see a long descent into negative territory where the underlying smoothed trend has a negative rate of change, i.e. a period of cooling like that experienced in the late 1800’s and then again midway through the 20th century.

Figure 2 – click for a larger image

Figure 2 uses a default value of lambda (the parameter that determines how much smoothing results from Hodrick-Prescott filtering) that is 100 times the square of the data frequency, which for annual data would be 100.  This is conventional, and is consistent with the lambda used for quarterly data in the seminal research on this technique by Hodrick and Prescott.  I’m aware, though, of arguments for using a much lower lambda, which would result in much less smoothing.

In Part 2, we will look at the effect of filtering with a lower value of lambda.  The results are interesting, and surprising.

Part 2 is now online here

NEW An update to this has been made here:

evidence of a lunisolar influence on decadal and bidecadal oscillations in globally averaged temperature trends

My good friend Jim Goodridge, former state climatologist for California, came to visit yesterday to offer some help on my upcoming trip, as well as to talk shop a bit about the state of affairs on climate change.

He had previously authored a paper that I had hoped to present on his behalf at ICCC, but unfortunately it got excluded from the schedule by an omission. Yesterday he decided to rework that paper to bring out it’s strongest point.

One of the best and simplest ways of seeing the solar connection is to look at accumulated departure. Here is Jim’s essay on the subject:

Solar – Global Warming Connection
Jim Goodridge
State Climatologist (Retired)
jdgoodridge – (at) – sbcglobal dot net
March 22, 2008

Solar irradiance has been monitored from satellites for three sunspot cycles. The sunspot numbers and solar irradiance were shown to be highly correlated. Since sunspot numbers have been increasing since 1935 the irradiance must also be increasing.

The sun was once considered to be constant in its output, hence the term “Solar Constant”. Recent observations suggest that the sun is a variable star. Observations of solar irradiance have been made with great precision from orbiting satellites since about 1978. These observations are from Wikipeda: http://en.wikipedia.org/wiki/Solar_variation

They clearly indicate that the solar irradiance varies with the historic sunspot numbers:

Click for a larger graph

Click for a larger graph:

Using this relationship, 307 years of solar irradiance is easily inferred.

Sunspot numbers since 1700 were plotted as accumulated departure from average in order to compare them with weather variables. The sunspot number index indicates a declining trend for the 1700 to 1935 period and an increase from 1935 to 2008. The eleven-year cycle is clearly visible.

An increase in sunspot activity, and by inference, irradiance since 1935 is plainly indicated.

Moderators note: And I want to also call attention to these graphs, which shows the change in solar irradiance since 1611 and Geomagnetic activity over the last 150 years:

Clearly, solar geomagnetic activity has been on the rise. There will be more interesting posts on sunpots coming in the next week or two, stay tuned -Anthony

Two days ago I highlighted a news story from the Washington Post Arctic Ocean Getting Warm; Seals Vanish and Icebergs Melt dated from November 2nd 1922. That brought a flood of interest and some other interesting finds along with it as other readers contributed what they found on the story.

One of the most interesting finds was a study published in the Monthly Weather Review in September 1933 Titled:  IS OUR CLIMATE CHANGING? A STUDY OF LONG-TIME TEMPERATURE TRENDS.

The first page of the original article is below:

Click this link for the full PDF of the article.

What is most interesting about this article is that it stems from a  realization that the regular weather patterns they used to know were now acting differently. For example this form the article:

And when you look at some of the city temperature graphs presented in the article, such as the one below, the parallels between them and some graphs presented in the present day are striking:

There is even the familiar argument and rebuttal about the Urban Heat Island effect:

In the concluding remarks, the is the recognition of climate change to a warmer regime:

All of these confirm the general statement that we are in the midst of a period of abnormal warmth, which has come on more less gradually for many years.

Of course we all know what happened next, 1934 became the hottest year on record, the dust bowl and great depression occurred, followed by World War II. The climate changes again, a return to a colder phase lasting all the way until about 1978 when the “new ice age” was being discussed. Then the great PDO shift occurred and warming has been the norm since then. Read the rest of this entry »

As I mentioned a few days ago, there was a panel that NASA convened to look at solar cycle 23/24 predictions.

From this story on space.com where they talk about the opposing views solar scientists have for cycle 24 they offer some opinions. NOAA Space Environment Center scientist Douglas Biesecker, who chaired the panel, said in a statement:

 […] despite the panel’s division on the Sun cycle’s intensity, all members have a high confidence that the season will begin in March 2008

Well, obviously March 2008 isn’t happening:

Current sun: blank

So now there’s a new set of numerical predictive numbers issued by NASA solar physicist David Hathaway. You can see the March 2008 updated prediction page here:

http://solarscience.msfc.nasa.gov/predict.shtml

There is a lot of discussion there on how the numbers are derived, but plainly absent from the discussion is the real meat of the issue. The goalposts for the start of Cycle 24 have now been moved to May 2008. In addition to the discussion of the “hows” on that page, he also produced a set of numerical data for the prediction curves which you can see here: http://solarscience.msfc.nasa.gov/images/ssn_predict.txt

I’ve plotted the data for you below.

Click for a larger image

Notice how cycle 23 gets longer and longer, with a sharp upturn for cycle 24 starting in late 2008 and early 2009. Hathaway still believes cycle 24 will be slightly more in amplitude than cycle 23, while others think it will be lower.

I’m no solar physicist, but based on what I’ve seen, I’m betting the goalposts will be moved again in May, pointing to a start in August or September 2008. This would be more in line with the latest numbers predicted by the Space Environment Center (SEC):

We’ll see what happens. I’m still very much concerned about the apparent step change in 2005 to a lower plateau of the Geomagnetic Average Planetary (Ap) index. Which is something that does not appear in the previous cycle:

click for a larger image

What is most interesting about the Geomagnetic Average Planetary Index graph above is what happened around October 2005. Notice the sharp drop in the magnetic index and the continuance at low levels, almost as if something “switched off”.

UPDATE - Joe D’Aleo of ICECAP writes in with this:

This site http://users.telenet.be/j.janssens/SC24.html catalogs the many forecasts of the next cycle with links where available. The majority of these forecasts (23 of the 33) forecast a quieter cycle 24 than 23.

The Clilverd forecast http://users.telenet.be/j.janssens/SC24Clilverd.pdf  is the lowest (peak SSN 42).

Dikpati http://www.ucar.edu/news/releases/2004/sunspot.shtml  the highest (peak SSN 169). Hathaway of NASA was second highest (peak SSN 160) though he projected that cycle 25 could be quietest in centuries due to dramatic slowing of the conveyor belt of hot plasma http://science.nasa.gov/headlines/y2006/10may_longrange.htm

If we go to May or later before the solar min is reached, cycle 23 will be the longest cycle since the late 1800s.

Over on Climate Audit, Steve McIntyre has been making a series of posts that have been putting the final nails in the coffin for Michael Mann’s MBH98 paper. This paper was responsible for the famous hockey stick graph which is based on tree ring data from Bristlecone Pine trees. Mann’s work implies them to be excellent proxy indicators of temperature, and due to their age, a profound record of temperature. Problem is,  it looks like most of the results is Mann’s paper have been thoroughly discredited by the work of McKittrick and McIntyre in 2005, plus McIntyre’s more recent work.

At 4600-4800 years old for some of the oldest trees, Bristlecone Pines (BCP) certainly have seen most if not more than all of human recorded history, so it seems logical to look to them for answers about our temperature history.

One of the graphs Steve McIntyre recently produced was this one:

About this graph he notes:

Here’s the MBH98 PC1 (bristlecones) again marking 1934. Given that bristlecone ring width are allegedly responding positively to temperature, it is notable that the notoriously hot 1934 is a down spike.

Since 1934 is generally accepted now to be the hottest year on record in 20th century it is indeed curious that 1934 in Mann’s data shows up as a down spike.

But seeing what happened with 1934, one has to wonder what do these trees really record in their tree ring growths? Is it temperature as Mann speculates? Or is it any number of other things related to plant growth in various combinations? Read the rest of this entry »

To Tell The Truth: Will the Real Global Average Temperature Trend Please Rise?

Part III

A guest post by Basil Copeland

Again, I want to thank Anthony for the kind invitation to guest blog these musings about what is going on with global average temperature metrics.  It has been a most interesting, and personally rewarding, experience.  My original aim was quite modest, but I fear that the passion that many feel for this issue prevented them from seeing that.  So in this final part to this series, I want to try to make my aim more clear, and to show how a lively exchange of ideas can lead to new insights.

The IPCC has made the earth’s global average temperature trend a central focus in the debate over anthropogenic global warming.  In the AR4 report of Working Group 1, they state:

The range (due to different data sets) of global surface warming since 1979 is 0.16°C to       0.18°C per decade compared to 0.12°C to 0.19°C per decade for MSU estimates of        tropospheric temperatures.  (Chapter 3, Page 237)

Similar, if not the same, estimates are reported in Table 3.3, Page 61, of the Synthesis and Assessment Product 1.1 of the U.S. Climate Change Science Program (accessible here: http://www.climatescience.gov/Library/sap/sap1-1/finalreport/sap1-1-final-all.pdf ).  Presumably, these estimates provide some kind of basis for the IPCC SRES scenarios that assume 0.2C per decade warming over the next two decades. 

Figure 1

From what I can tell in reading the representations of the sources for these estimates, they are based on a straight-line linear regression that includes corrections for serial correlation.  In other words, regressions that look something like what are shown in Figure 1.  The trend at the top is from Appendix A, Page 130, Figure 1, of the U.S. Climate Change Science Program report just cited.  The second is taken from the RSS website (http://www.remss.com/data/msu/graphics/plots/sc_Rss_compare_TS_channel_tlt.png  accessed on March 15, 2008).  Both show a warming trend of 0.17C/decade since 1979.

Are these “good” estimates of the historical trend since 1979?  Forgive me, but I refuse to accept them as authoritative ex cathedra, nor will any true scientist expect me to.  Bear in mind, I’m taking the data for what it’s worth, and am overlooking any questions about the reliability of the surface record, such as what Anthony is looking into (or Steve Mcintyre at www.climateaudit.org), or the kind of urbanization and land use effects reported by Ross McKitrick and Patrick Michaels. My concern is solely with the technical procedures used to estimate the “trends” that are commonly cited for evidence of global warming.  Bottom line?  There are problems with the way those trends are computed that overestimate the degree of global warming since 1979 by 16.3% to 41.3% (based on results presented below).

In Part II I attempted a demonstration of this using what might be considered to be rather a rather blunt or brute force approach — a test of whether there was a significant “structural break” (the way we describe it in my field of study) after 2001, along with whether or not linear trends are distorted by the effect of the 1998 El Nino.  Nothing in the comments that followed the posting of Part II fundamentally undermined the validity of my conclusions.  The chief concerns seemed to be that my decision to test for a structural break (or “change point”) at the end of 2001 was arbitrary (it wasn’t), or whether one could say anything meaningful about a cyclical system like climate from linear trend lines.  Well, with respect to the latter, that horse is out of the barn, and we’re being told — by supposed authorities — that there has been X degrees of global warming per decade since 1979 on the basis of linear trend lines.  If they can use linear regression to claim that global warming is proceeding apace, well please excuse me for doing the same in questioning them.

Still, the comments were provocative, and encouraged me to dig further into my toolbox of econometric techniques to see if I might be able to come up with something that would alleviate some of the concerns commenters had about what I did.  So it occurred to me that I might treat the weather like a “business cycle” and model it with Hodrick-Prescott smoothing.  (If you want an explanation of what that is, look here: http://en.wikipedia.org/wiki/Hodrick-Prescott_filter ).  The results are presented, for the four global average temperature metrics we are using, in Figures 2 through 5.

Figure2 – click for a larger image

Figure3 – click for a larger image

Figure4 – click for a larger image

Figure5 – click for a larger image

Those who think we should let the data tell us where the “change points” are should find this approach more appealing, as well as those who believe we should be modeling the data with non-linear techniques.  But in the end, the point is the same: the “real trend” over the 29 years we are looking at is substantially less than we get using straight-line regression.  With the exception of GISS, Hodrick-Prescott smoothing results in even lower estimates of the degree of global warming over the past 29 years.  As shown in the following Table 1, compared to the two methods I’ve employed, the straight line regression method relied upon by IPCC and the U.S. Climate Change Science Program overstates global warming since 1979 by anywhere from 16.3% (using GISS) to 41.3% (HadCRUT). 

No one should be offended by what I’ve done, or what I’m saying.  True science is always open to the possibility of refutation.  Given the policy implications that hang on conclusions about the degree of global warming that has occurred in recent decades, we should take a closer look at what the supposed authorities are telling us, and see if there are not perhaps some significant short-comings in the way they have calculated the degree of global warming in recent decades.

This is a quick post since I’m caught up in a lot of work this weekend. Moderation will be slow so don’t be worried if your posts don’t show for several hours.

Last month I wrote:

———————
From this story on space.com where they talk about the opposing views solar scientists have for cycle 24 they offer some opinions. NOAA Space Environment Center scientist Douglas Biesecker, who chaired the panel, said in a statement:

 […] despite the panel’s division on the Sun cycle’s intensity, all members have a high confidence that the season will begin in March 2008.

———————-

We are halfway through March, and the sun has been very quiet, Ap magnetic index remains low, sunspots are zilch, all we have is a bit of solar wind from the occasional coronal hole.

The forecast from SWPC is flatness for the 10.7cm band:

This is the one that worries me though, as I’ve pointed out before, we have that step function (or discontinuity) in 2005 (see red arrows) which gives the impression that something just “switched off” in the solar magnetic dynamo:

Additionally, the sunspot forecast from SWPC calls for sunspot numbers to be very low for the remainder of 2008, which seems to put a kibosh on the consensus formed by NASA’s convened solar scientist panel which made that prediction of “…the season will begin in March 2008” uttered by panel chair Biesecker quoted above.

We live in interesting times.