Evidence that Global Temperature Trends Have Been Overstated
Dr. Pielke has a new paper, and asked if I’d help “get the word out” I’m happy to oblige – Anthony
Guest post by Dr. Roger Pielke Jr
The paper is important for two reasons. First, it provides confirmatory evidence that the globe has indeed been warming over the period of the satellite records. Indeed the argument that we make in the paper depends upon the presence of a warming trend, Second, it provides a parsimonious and logical explanation for a discrepancy observed in the temperature record that has been often highlighted but which to date been unsatisfactorily explained.
For several years my father has been talking about the possibility of a “warm bias” in the surface temperature record.
We begin our paper by noting a well-documented and puzzling discrepancy in global atmospheric temperature measurements:
Since 1979, when satellite observations of global atmospheric temperature became available, trends in thermometer-estimated surface warming have been larger than trends in the lower troposphere estimated from satellites and radiosondes as discussed in a recent Climate Change Science Program (CCSP) report [Karl et al., 2006]. Santer et al. [2005] presented three possible explanations for this divergence: i) an artifact resulting from the data quality of the surface, satellite and/or radiosonde observations; ii) a real difference due to natural internal variability and/or external forcings; or iii) a portion of the difference is due to the spatial coverage differences between the satellite and surface temperature data. Santer et al. [2005] focused on the second and third explanations, finding them insufficient to fully explain the divergence. They suggest in conclusion that, among other possible explanations, “A nonsignificant trend differential would also occur if the surface warming had been overestimated by 0.05°C per decade in the IPCC data.”
We call the discrepancy between trends observed at the surface and those in the lower troposphere a “divergence” meaning that they are behaving differently. In 2006 the Climate Change Science Program discussed this divergence and found the issue to be “still open.” Our paper conducts an investigation of the neglected first hypothesis proposed by Santer et al. (2005) as follows:
[W]e consider the possible existence of a warm bias in the surface temperature trend analyses using the following two hypotheses related to the divergence between the surface and lower tropospheric temperature records since 1979:
1. If there is no warm bias in the surface temperature trends, then there should not be an increasing divergence with time between the tropospheric and surface temperature anomalies [Karl et al., 2006]. The difference between lower troposphere and surface anomalies should not be greater over land areas.
2. If there is no warm bias in the surface temperature trends, then the divergence should not be larger for both maximum and minimum temperatures at high latitude land locations in the winter.
We conclude that the first explanation offered by Santer et al. [2005] provides the most parsimonious explanation for the divergence between surface and lower troposphere temperature trends, based on recent research suggestive of biases in the surface temperature record. Our findings suggest that the supposed reconciliation of differences between surface and satellite datasets [Karl et al., 2006] has not occurred.
What do we find?
First, we explain why it is that there is evidence of a “warm bias” in the global temperature record. It has to do with how surface temperatures used to calculate long-term trends are constructed – by averaging daily maximum and minimum temperatures combined with the effects of what are called “atmospheric boundary layer processes” on minimum temperatures. In the paper we provide a review of this well-understood area of meteorology. This discussion is somewhat complex and technical, but it is also well-supported and should be non-controversial.
We argue that:
Because the land surface temperature record does in fact combine temperature minimum and maximum temperature measurements, where there has been a reduction in nighttime cooling due to this disruption, the long-term temperature record will have a warm bias. The warm bias will represent an increase in measured temperature due to a local redistribution of heat, however it will not represent an increase in the accumulation of heat in the deep atmosphere. The reduction in nighttime cooling that leads to this bias may indeed be the result of human interference in the climate system (i.e., local effects of increasing greenhouse gases, surface conditions, aerosols or human effects on cloud cover), but through a causal mechanism distinct from the large-scale radiative effects of greenhouse gases.
It is important to underscore that our hypothesis depends upon (a) the presence of a real warming trend, and (b) (to some extent) an increase in greenhouse gases. So if you accept our arguments, then you necessarily are accepting the presence of a warming trend and corresponding increases in greenhouse gases. This too should be non-controversial, but I want to be clear to avoid any possible misinterpretations.
So then let’s look at the data. We use surface data from the Hadley Center in the UK and NOAA in the US, and for satellite data we use the UAH and the RSS datasets. We analyze the data over land and ocean. The figures below show the differences between the surface temperature records and the satellite records for the period 1979 to 2008. Also shown is the difference that would be expected based on the results of a number of climate model runs as presented by the CCSP (i.e., the values from the models are from the CCSP). Clearly there is a visual divergence represented as a increase in the differences over time as well as a visual difference between what has been observed and what the models suggest should be expected.
Figure 1. NCDC minus UAH lower troposphere (blue line) and NCDC minus RSS lower troposphere (green line) annual land temperature differences over the period from 1979-2008. The expected anomaly difference given the model amplification lapse rate factor of 1.2 is also provided. All differences are normalized so that the difference in 1979 is zero.
Figure 2. CRUTEM3v minus UAH lower troposphere (blue line) and CRUTEM3v minus RSS lower troposphere (green line) annual land temperature differences over the period from 1979-2008. The expected anomaly difference given the model amplification lapse rate factor of 1.2 is also provided. All differences are normalized so that the difference in 1979 is zero.
What is really interesting is that the divergence that we observe is statistically significant in 3 of 4 cases over land (that is, NCDC minus UAH, NCDC minus RSS, Hadley minus UAH) but not in any of the cases over the ocean, which is exactly what we’d expect in the presence of a warm bias in the land surface temperature measurements. We think as well that we can explain why there is not a statistically significant difference over land between Hadley and RSS, and this is discussed in the paper.
We then take the analysis a step further:
The warm bias in the temperature data would most likely be in evidence over land areas where larger vertical temperature stratification occurs near the ground along with a reduction of the atmospheric cooling rate. This effect will be largest in the higher latitudes, especially in minimum temperatures during the winter months, since any reduction in the cooling rate of the of the atmosphere will result in a particularly large temperature increase near the ground surface in this strongly stably stratified boundary layer.
So we look at the higher latitudes and find that:
… the northern polar areas have received considerably more warming in the boreal winter with regards to minimum temperatures than with regards to maximum temperatures. The reader should be careful in interpreting these results, however, since the 95% confidence intervals for maximum and minimum temperatures in the polar areas during the winter months is quite large. The trend in minimum temperatures in northern polar areas is statistically significantly greater than the trend in maximum temperature at the 95% level during the winter months. This is consistent with the findings reported in Pielke and Matsui [2005], Pielke et al. [2007] and Lin et al. [2007] of a warm bias in the global analysis of surface temperature trends. This is also consistent with the view that column climate sensitivity is dependent on the depth of the boundary layer [Esau, 2008]. At higher latitudes, boundary layer depths are in general lower and more stable and thus heat is distributed over a shallower layer making the proportional response greater. This leads to more warming at the surface than aloft and thus is not indicative of heat accumulation in the deep atmosphere.
So we believe that we have demonstrated compelling evidence for the presence of a warm bias in global temperature trends that may indeed be reflective of a human influence on the climate system, but is not due to the accumulation of heat in the system. The obvious conclusion from this result, should it be correct and hold up, is that the effects of carbon dioxide on global temperature trends may have been overstated in past assessments by some amount.
Again, this does not mean that increasing carbon dioxide is not a problem, nor does it mean that efforts to decarbonize the economy do not make sense. Our paper has not led me to alter the climate mitigation and adaptation policies that I advocate one bit. It does mean that there remains plenty of questions to ask and answers to find – some perhaps surprising – about the relationship of human activities and the global earth system.
Here is how we conclude our paper:
We find that there have, in general, been larger linear trends in surface temperature datasets such as the NCDC and HadCRUTv3 surface datasets when compared with the UAH and RSS lower tropospheric datasets, especially over land areas. This variation in trends is also confirmed by the larger temperature anomalies that have been reported for near surface air temperatures (e.g., Zorita et al., 2008; Chase et al., 2006; 2008, Connolley, 2008). The differences between surface and satellite datasets tend to be largest over land areas, indicating that there may still be some contamination due to various aspects of land surface change, atmospheric aerosols and the tendency of shallow boundary layers to warm at a greater rate [Lin et al., 2007; Esau, 2008; Christy et al., 2009]. Trends in minimum temperatures in northern polar areas are statistically significantly greater than the trends in maximum temperatures over northern polar areas during the boreal winter months.
We conclude that the fact that trends in thermometer-estimated surface warming over land areas have been larger than trends in the lower troposphere estimated from satellites and radiosondes is most parsimoniously explained by the first possible explanation offered by Santer et al. [2005]. Specifically, the characteristics of the divergence across the datasets are strongly suggestive that it is an artifact resulting from the data quality of the surface, satellite and/or radiosonde observations. These findings indicate that the reconciliation of differences between surface and satellite datasets [Karl et al., 2006] has not yet occurred, and we have offered a suggested reason for the continuing lack of reconciliation.


The highest recorded temps in my neck of the woods was 1933. Sticks out like a pre-AGW CO2 faster than previous thought sore thumb.
Bottom line is that these figmented dangers contrived to save the Planet have as their end result to rip out all development in the Free World and hand it over to those who operate with no restrictions.
i.e. – instead of having a good portion of industry operate in a far cleaner fashion, those that operate cleaner will either relocate or close thier doors, leading to a return to environmental disasters of massive dumping and truly noxious emissions.
Wasn’t the toxic waste dump of the Eastern Bloc scene enough of a prelude of what this will look like?
Dr. Pielke says that there is a warm bias when comparing surface land temperatures to surface sea temperatures. He further says that this bias should be greatest at higher latitudes. To the 2nd point, he considers the discrepancy over the north polar region.
1. UHI effects specifically are not being considered in this study (which could be a weakness of the study), because there are no significant UHIs in the arctic.
2. The north polar ice cap rests atop the Arctic Ocean, so it is questionable whether this area should be considered “land.” Warm sea currents could affect surface temperatures greatly.
While the study is interesting, I doubt it proves Dr. Pielke’s point. I’d like to see the analysis expanded to actually include high latitude LAND areas, some of which might display UHI effects.
I don’t really follow the logic here:
* I have yet to see any actual observed evidence that increasing carbon dioxide is a problem.
* The economy will decarbonize itself when something better and more economical comes along.
* Adaptation makes the most sense as the climate always changes and always will change.
As to the “minimax” dayly temperature records, such data gives the correct average daily temperature (at that place) in the case of a sinusoidal diurnal temperature cycle (24 hrs). I believe it also is the correct average if the diurnal temperature cycle is any time symmetric waveform. (some of you younger math majors can check my Fourier assumptions).
And a minimax record, does give the minimum two samples per cycle for a sinusoidal cyclic variation to satisfy the Nyquist sampling criterion.
But I don’t believe anyone thinks that the diurnal temperature cycle is time symmetric. The daily heating and cooling is a non linear function, and it isn’t time symmetric.
So that means that the actual daily cyclic temperature contains at least a second harmonic component, or a 12 hour period signal component. So a minimax two reading daily regimen, violates the Nyquist Criterion already by a factor of two, and doesn’t even allow for higher frequency variations for example due to vartiable cloud coverage.
With a sampling rate violation by a factor of two the aliassed noise is folded back all the way to zero frequency. OOoops ! The daily average is now corrupted with aliassing noise (irretrievably).
Now OMS insisted that climatologists know all about Nyquist, and sampled data theory; they evidently don’t know that they are supposed to pay attention to such details in planning their experimental regimens.
So garbage in garbage out. GISStemp is simply a record of the results of an AlGorythm that Hansen performs on some random set of numbers fed to him from some ersatz temperature measurement sites. Other than that, it has no physical meaning; and it certainly cannot be taken as a proxy for the mean global temperature or even the anomaly for the planet earth; it doesn’t even give correct average values for any single day.
Oh; and if you thought the temporal aliassing problem is bad; wait till you look into the aliassing problem for the spatial variable; we should pray for a violation by only a factor of two, instead of the orders of magnitude we now have.
They once actually had 12 whole temperature recoding stations for the Arctic (nth of +60 deg).
Then there’s that little matter about the energy flows in and out of the earth not being linearly related to the local temperature; so what good is a temperature average; even if you could extract one.
The apparent small discrepancy in trends over the last three decades may have a somewhat different source than the large UHI discrepancy evident over much longer time spans between urban and non-urban surface records. But both appear to be the product of a human effect not on widespread climate but on station data.
Since the collapse of the Soviet Union and the capitalistic boom in China in the 90’s, a large segment of the Eurasian land mass where automobiles were not the common commodity they became earlier in the 20th century in the developed world was quite suddenly inundated with them. It is precisely in that part of the world that the most abrupt and greatest increases in annual average temperatures have been recorded. Unlike the USA, station records there come almost entirely from cities and large towns, where heat pollution from exhaust systems and radiators is considerable. And the temperature effect of such pollution is always greater in colder climtes. Cities and towns being islands of capitalism, this might be termed the CHI effect.
Not only is Dr Pielke a very astute scientist who knows his onions, he’s also rather cute. Can I say that? :0)
A very interesting paper.
Since land area is only ~30% of the total, the net global average “artifact” in the surface station data will not be so big as shown in the graphs; looks like it should be in the range of +0.15C for the GISS data over the entire period, and maybe +0.04 in the Hadley data, for net artifacts of +0.05 and +0.013per decade.
The artifact in the ground station data nicely explains why the GISS trend continues to show a slight warming trend since 2000, while ocean heat accumulation does not. If you take 0.05C away from the GISS trend over the past decade, then it becomes clearly negative from 2000 through 2008, consistent with the Argo measurements of slightly falling total ocean heat content from 2003 to 2008. Too bad the paper does not seem to note this.
Very telling is the large discrepancy between the actual difference between ground and satellite trends and the expected difference due to the “amplification lapse rate factor of 1.2” used in climate models. This amplification factor says there should be a gradually increasing difference between the surface temperature increase and the tropospheric temperature increase, but this difference should be in the OPPOSITE direction… the ground stations should be consistently cooler than the tropospheric measurements. This puts the discrepancy between model projections of temperature in the troposphere and satellite measurements of the troposphere in the range 0.2C to 0.3C over 30 years, a pretty big number.
Difficult to see how this can be ignored by the “climate modeling community”, since it appears to directly refute one of the foundations for the extreme climate sensitivity projected by the models (that is, amplification of radiative forcing due to increases in water vapor in the troposphere). If this amplification is not real, as Richard Lindzen has been saying for a long time, then all the GCM’s would have to sharply lower their assumed sensitivity to radiative forcing as well as their projections of warming.
Most likely response: a weak paper from Gavin and a bunch of other very well known authors which attempts to assign extreme uncertainty levels to both the ground and (especially) the satellite data…. thus providing fig leaves for the climate models, and an excuse for not changing the assumed water vapor feed back in the models. Unfortunately, we’ve seen this type of paper from Gavin et al too many times already.
Obviously, or maybe not, the corrupted temperature stations around the world shed at least significant doubt to the land mearsurements value. It seems that if just the CRN1 and CRN2 stations were used, there would still be about 150 stations available to reconstruct land temperatures. That result could be compared to the satellite data sets and to the published temperature trends. My guess would be less difference between the CRN1/2 analysis and the UAH and RSS datasets. The only real problem then would be having to admit that UHI is significant and is biasing the temperature record. Nah, it’ll never happen.
Now, you developing countries, you stop polluting right this instant. Or we’ll blow what’s left of both kneecaps off of our economies, and then whom will you sell your products to?
Keep in mind that UAH and RSS data do not account for anything north of 82.5 N. So the comment about the polar ice cap is irrelavent. What is relavent is the drastic reduction of rural surface stations in Canada and Siberian during the 1990’s leaving “urban” stations. The “urban” are more prone to siting issues/movements that affect the temperature record, especially in the minimum temperature reading.
The Urban Heat Island can account for some of this discrepancy. The latest estimates show the UHI is 0.1C per decade.
We have = 3 * 0.1C * % stations impacted by UHI = max 0.15C
That still leaves a lot of difference to explain.
[The scientists in charge of the other two surface temperature series are Phil Jones and Thomas Karl. Both of whom strongly believe that temperatures should be increasing at 0.2C per decade rather than the lower numbers which are occurring.
They were both wrong about the Urban Heat Island to start with (so it is possible that the adjustments they have applied to the raw data (to get closer to 0.2C per decade)) are also in error.]
1990 Urban Heat Island assessment by Jones and Karl.
http://www.informath.org/apprise/a5620/b90.pdf
2008 Urban Heat Island assessment by Jones.
http://www.agu.org/pubs/crossref/2008/2008JD009916.shtml
Roger Sr. also has some comments:
http://climatesci.org/2009/08/13/new-paper-documents-a-warm-bias-in-the-calculation-of-a-multi-decadal-global-average-surface-temperature-trend-klotzbach-et-al-2009/
This is relevant:
http://ocean.dmi.dk/arctic/meant80n.uk.php
It’s quite rural up there, above 80N.
For anyone living anywhere near the Arctic Circle this winter, it’s going to get strongly relevant.
33 days and counting.
40+ days until equinox.
Need I remind anyone what happened last fall as soon as the Arctic Sun fell below the horizon?
So now we know why Siberia is always toasty warm.
His dancing around the “need to decarbonize” and the double negative about CO2 just goes to show how politically careful one has to be in his position.
Lucy Skywalker (08:35:27) :
Daly died suddenly and unexpectedly. His familly maintain the site in his honour, AFAIK.
Nogw (09:31:07) :
We unbelievers suspect that those satellites were already “adjusted” to begin with…so
As Ian Plimer says in his book, the highest recorded temperatures in the 20th century were not in 1998 El Nino, but in 1932
Check this out then weep at the response.
http://www.guardian.co.uk/environment/georgemonbiot/2009/aug/05/climate-change-scepticism
http://www.guardian.co.uk/environment/georgemonbiot/2009/aug/12/climate-change-climate-change-scepticism
A couple of days ago I plotted 4 of the AMSu data series.
http://img512.imageshack.us/img512/6769/amsua19982009.jpg
The slope gets progressively less as height increases
Near surface slope is slightly positive but less than 3300ft
Bill Illis
Your talk of UHI reminded me of some graphs I produced a while ago to look at this very effect, when I factored in 0.1c UHI effect per decade on two long temperature data sets
The first graph is of CET (in red) to 1660-unadjusted for uhi- to which have over laid in green the Zurich figures (unadjusted for uhi) to 1864. The amount of mirroring is remarkable through the decades until the rapid growth of Zurich since the war.
Consequently I factored in .1c uhi per decade from the 1960’s into the second graph below. This has dramatically reduced the observed warming and puts it closer again to the CET figures- which aren’t perfect but don’t suffer quite as much from UHI
http://cadenzapress.co.uk/download/combined_mencken.xls
http://cadenzapress.co.uk/download/zurich_mencken_modified.xls
As regards UHI, a new study illustrates that our personal observations that it is often much hotter in urban than rural areas -particularly at night- appears more correct than the previous scientific studies that minimised the apparent observed UHI effect.
The amount of adjustment to take into account this UHI factor ihas been limited and the apparent impact on temperatures will consequently be larger than had previously been factored in if this new study is accepted.
http://www.timesonline.co.uk/tol/news/environment/article6256520.ece
Tonyb
from the document p7
The rate of heat loss to space is dependent on several factors, including cloudiness and the local atmospheric concentrations of carbon dioxide and of water vapor (e.g., Pielke, 2002). Under cloudy conditions, cooling is much less. An atmosphere with higher concentrations of the greenhouse gases, CO2 and H2O, also reduces the cooling at night.
Consequently if, for instance, there is a long-term positive trend in greenhouse gas concentrations or cloudiness over the observing site, it may introduce an upward bias in the observational record of minimum temperatures that necessarily will result in an upward bias in the long-term surface temperature record.
Local CO2 raises temperature!!
bill (12:59:24) :
Yeah, I read shocker question # 13:
“Reconcile your calculations with at least five atmospheric CO2 proxies.”
So, which is the cart and which is the horse?
The calculations must agree with the proxies is the way I read that.
What are those golden proxies? One has to hope they aren’t the ‘faster than we expected” model output.
There’s 2 things rising at this point:
1.) GCM output and
2.) hold the phone rejection of “faster than we anticipated” lottery tickets
Thursday, August 13, 2009, and that’s the way it is.
Great work indicating global warming has been overstated by about 0.15ºC over the past three decades, indicating bias over the past 150 years is somewhat higher than 0.15ºC.
Back in March I estimated that the APPARENT global warming of about 0.8ºC over the past 150 years has been overstated by about 30% due to Data Bias (mainly encroachment of land-based sensors by civilization), which would be between 0.2ºC to 0.3ºC. That means the ACTUAL warming over 150 years is about 0.5ºC to 0.6ºC.
In that and subsequent postings, I separated the 0.8ºC APPARENT warming into four major components: 30% Data Bias, 40% Natural Cycles, 20% Ocean Carbon (net outgassing of carbon gasses due to the actual warming) and only about 10% to Human Carbon (net excess carbon gasses in atmosphere due to human activities burning previously sequestered coal, oil and natural gas), see Data Bias, Natural Cycles, and Ocean Carbon. (My posting on Human Carbon will appear soon.)
INGSOC (09:49:32) :
“So if you accept our arguments, then you necessarily are accepting the presence of a warming trend and corresponding increases in greenhouse gases.”
My more hysterical friends become apoplectic when I make statements like this! They seem to think that I am agreeing with them. Sigh…
Heh, I missed that in my haste. Good catch.
bill (13:24:15) :
from the document p7
if, for instance, there is a long-term positive trend in greenhouse gas concentrations or cloudiness over the observing site, it may introduce an upward bias in the observational record
Local CO2 raises temperature!!
Or more accurately
Local co2 or cloudiness may raise temperature.
Does this have some bearing?
http://chiefio.wordpress.com/2009/08/10/well-theres-your-global-warming-problem/
Tony R (09:06:07) :
That’s a question I’ve been wondering about for years.
A question to those who study this more, how is the dissipation and transportation of heat from UHI’s to the rest of the atmosphere controlled and ruled out for the GCM’s? I constantly see UHI expressed in Temperature, which seems wrong to me since the real issue is heat, and how it gets transported through the climate system.