Monthly Archives: December 2007

New Research Paper “Quantifying The Influence Of Anthropogenic Surface Processes And Inhomogeneities On Gridded Global Climate Data” By Ross McKitrick And Pat Michaels

There is an important new peer reviewed paper that further rasies questions on the robustness of using surface air temperature data to calculate the radiative imbalance of the cliimate system.

This peer reviewed paper is

McKitrick, R.R. and P.J. Michaels (2007), Quantifying the influence of anthropogenic surface processes and inhomogeneities on gridded global climate data, J. Geophys. Res., 112, D24S09, doi:10.1029/2007JD008465.

The abstract reads

“Local land surface modification and variations in data quality affect temperature trends in surface-measured data. Such effects are considered extraneous for the purpose of measuring climate change, and providers of climate data must develop adjustments to filter them out. If done correctly, temperature trends in climate data should be uncorrelated with socioeconomic variables that determine these extraneous factors. This hypothesis can be tested, which is the main aim of this paper. Using a new data base for all available land-based grid cells around the world we test the null hypothesis that the spatial pattern of temperature trends in a widely-used gridded climate data set is independent of socioeconomic determinants of surface processes and data inhomogeneities. The hypothesis is strongly rejected (P=7.1E-14), indicating that extraneous (nonclimatic) signals contaminate gridded climate data. The patterns of contamination are detectable in both rich and poor countries, and are relatively stronger in countries where real income is growing. We apply a battery of model specification tests to rule out spurious correlations and endogeneity bias. We conclude that the data contamination likely leads to an overstatement of actual trends over land. Using the regression model to filter the extraneous, nonclimatic effects reduces the estimated 1980-2002 global average temperature trend over land by about half.”

The conclusion includes the text

“These results are also consistent with previous findings showing that nonclimatic factors, such as those related to land use change and variations in data quality, likely add up to a net warming bias in climate data, suggesting an overstatement of the rate of global warming over land. They also provide support for attribution of some observed climate changes in recent decades to land surface modifications, rather than greenhouse gas emissions, a factor not typically evaluated in studies that attempt to attribute the causes of recent global warming.”

In a follow up, Ross McKitrick addressed the issue of spatial correlations, which could have reduced the significance of their results, in the article

Spatial Autocorrelation and Interactions between Surface Temperature Trends and
Socioeconomic Changes
. submitted to JGR.

The abstract of this contribution reads

“McKitrick and Michaels (2007) tested for independence between the spatial pattern of trends in surface climate data and the spatial pattern of socioeconomic indicators that serve as proxies for measurement inhomogeneities and anthropogenic surface processes. They found the relationship to be statistically significant, and in counterfactual simulation concluded that the extraneous signals explainabout half the post-1980 warming trend in surface data. This paper examines the robustness of these conclusions to treatment for possible spatial autocorrelation in the model residuals. Under a variety of weighting schemes, a robust LM test for no spatial autocorrelation is not rejected. Applying a correction for spatial autocorrelation anyway does not change the original conclusions.”

What is quite impressive of this study is that the data used is available for inspection (see).

This study provides further evidence on the use of inadequate data (in the multi-decadal trends of surface air temperature as reported in the 2007 CCSP Report – Temperature Trends in the Lower Atmosphere: Steps for Understanding and Reconciling Differences) to accurately quantify the magnitude of global warming (or cooling). Two of our new papers, that have just been published in the past week, which further document the failure in the CCSP assessment process, will be reported on this week by Climate Science. This CCSP report was used in the completion of the 2007 IPCC Report.

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UPDATE: Cause Versus Effect In Feedback Diagnosis by Roy W. Spencer 12/30/2007

On August 8, 2007, I posted here a guest blog entry on the possibility that our observational estimates of feedbacks might be biased in the positive direction. Danny Braswell and I built a simple time-dependent energy balance model to demonstrate the effect and its possible magnitude, and submitted a paper to the Journal of Climate for publication.

The two reviewers of the manuscript (rather uncharacteristically) signed their names to their reviews. To my surprise, both of them (Isaac Held and Piers Forster) agreed that we had raised a legitimate issue. While both reviewers suggested changes in the (conditionally accepted) manuscript, they even took the time to develop their own simple models to demonstrate the effect to themselves.

Of special note is the intellectual honesty shown by Piers Forster. Our paper directly challenges an assumption made by Forster in his 2005 J. Climate paper, which provided a nice theoretical treatment of feedback diagnosis from observational data. Forster admitted in his review that they had erred in this part of their analysis, and encouraged us to get the paper published so that others could be made aware of the issue, too.

And the fundamental issue can be demonstrated with this simple example: When we analyze interannual variations in, say, surface temperature and clouds, and we diagnose what we believe to be a positive feedback (say, low cloud coverage decreasing with increasing surface temperature), we are implicitly assuming that the surface temperature change caused the cloud change — and not the other way around.

This issue is critical because, to the extent that non-feedback sources of cloud variability cause surface temperature change, it will always look like a positive feedback using the conventional diagnostic approach. It is even possible to diagnose a positive feedback when, in fact, a negative feedback really exists.

I hope you can see from this that the separation of cause from effect in the climate system is absolutely critical. The widespread use of seasonally-averaged or yearly-averaged quantities for climate model validation is NOT sufficient to validate model feedbacks! This is because the time averaging actually destroys most, if not all, evidence (e.g. time lags) of what caused the observed relationship in the first place. Since both feedbacks and non-feedback forcings will typically be intermingled in real climate data, it is not a trivial effort to determine the relative sizes of each.

While we used the example of random daily low cloud variations over the ocean in our simple model (which were then combined with specified negative or positive cloud feedbacks), the same issue can be raised about any kind of feedback.

Notice that the potential positive bias in model feedbacks can, in some sense, be attributed to a lack of model “complexityâ€? compared to the real climate system. By “complexityâ€? here I mean cloud variability which is not simply the result of a cloud feedback on surface temperature. This lack of complexity in the model then requires the model to have positive feedback built into it (explicitly or implicitly) in order for the model to agree with what looks like positive feedback in the observations.

Also note that the non-feedback cloud variability can even be caused by…(gasp)…the cloud feedback itself!

Let’s say there is a weak negative cloud feedback in nature. But superimposed upon this feedback is noise. For instance, warm SST pulses cause corresponding increases in low cloud coverage, but superimposed upon those cloud pulses are random cloud noise. That cloud noise will then cause some amount of SST variability that then looks like positive cloud feedback, even though the real cloud feedback is negative.

I don’t think I can over-emphasize the potential importance of this issue. It has been largely ignored — although Bill Rossow has been preaching on this same issue for years, but phrasing it in terms of the potential nonlinearity of, and interactions between, feedbacks. Similarly, Stephen’s 2005 J. Climate review paper on cloud feedbacks spent quite a bit of time emphasizing the problems with conventional cloud feedback diagnosis.

I don’t have an answer to the question of how to separate out cause and effect quantitatively from observations. But I do know that any progress will depend on high time resolution data, rather than monthly, seasonal, or annual averaging. (For instance, our August 9, 2007 GRL paper on tropical intraseasonal cloud variability showed a very strong negative cloud “feedbackâ€? signal.)

Until that progress is made, I consider the existence of positive cloud feedback in nature to be more a matter of faith than of science.

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Third Follow Up To Climate Metric Reality Check #3 – Evidence For A Lack Of Water Vapor Feedback On The Regional Scale

There is a paper which adds to the discussion of long term tropospheric water vapor trends. It is

Shannon Brown, Shailen Desai, Stephen Keihm, Wenwen Lu and Christopher Ruf; 2007 Ocean water vapor and cloud burden trends derived from the Topex Microwave Radiomoeter.

The abstract reads

“An end-of-mission recalibration effort was recently completed for Topex Microwave Radiometer to generate climate data records of precipitable water vapor and cloud liquid water for 1992-2005. The TMR climate data is analysed for trends. The global trend in precipitable water vapor is found to be 0.9 + 0.06 mm/decade. Regional precipitable water vapor trends are found to be highly correlated with regional sea surface temperature trends. The cloud liquid water trends are observed to be generally negative outside the tropics and positive in the tropics.”

The association of sea surface temperature (SST) trend with tropospheric water vapor is concluded, as summarized in Figures 6 and 7, but, unfortunately, the explained variance is only 21% for all SST trends and 13% for SSTs greater than 15 C. Nonetheless, there is a physical reason that larger amounts of tropospheric water vapor should be expected (due to great evaporation from the warmer ocean surface).

There is a more substantive issue, however, with the trend values that they present. While the authors focus on the linear trends from 1992 to 2005 which they plot in each of the panels in Figure 2, the trends since about 2002 have been flat, or in the case of the 0-60N values, have even been negative!

This lack of continued moistening of the troposphere since about 2002 is consistent with the conclusions of Climate Science that

1. The 60S-60N SSTs have cooled since 2002 (see)

2. The water vapor content over land has not been increasing (see).

3. The added information that results when we examine shorter time periods (particularly the most recent years) should be encouraged for all papers that examine trends and variability in time of climate metrics, including tropospheric water vapor content.

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Follow Up #1 To “Reality Check #4 Most Societal and Environmental Effects Are Influenced By Regional, Not Global Average, Climate Variability and Change

This follow up to the Climate Science weblog of December 24th entitled

“Reality Check #4 Most Societal and Environmental Effects Are Influenced By Regional, Not Global Average, Climate Variability and Change”

is to emphasize the significance of that weblog.

Using the climate metric of a large scale average (for 37 N to 37 S),

Matsui, T., and R.A. Pielke Sr., 2006:Measurement-based estimation of the spatial gradient of aerosol radiative forcing. Geophys. Res. Letts., 33, L11813, doi:10.1029/2006GL025974,

found that the radiative forcing of the human contribution of well-mixed greenhouse gas and of aerosols were of the same order of magnitude (although of opposite sign). This is what is also concluded in the 2007 IPCC Report for the global average, as given in Figure SPM.2 in the Statement for Policymakers.

However, when evaluating the spatial gradient of these human radiative forcings, the radiative effect of the aerosol forcing is 60 times larger!

Since it is the spatial gradient of diabatic that forces atmospheric circulation patterns, the regional climate forcing metric is a much more valid climate metric to assess most climate impacts due to human activities than is a global, or other very large scale, average.

Land use/land cover change also has such large radiative effects as it is a spatially heterogeneous climate forcing; e.g. see

Pielke Sr., R.A., G. Marland, R.A. Betts, T.N. Chase, J.L. Eastman, J.O. Niles, D. Niyogi, and S. Running, 2002: The influence of land-use change and landscape dynamics on the climate system- relevance to climate change policy beyond the radiative effect of greenhouse gases. Phil. Trans. A. Special Theme Issue, 360, 1705-1719.

Since the other effects of aerosols are not considered (e.g. their effect on precipitation; e.g. see

Rosenfeld Daniel Atmosphere: Aerosols, Clouds, and Climate, Perspectives. Science 2 June 2006:Vol. 312. no. 5778, pp. 1323 – 1324 DOI: 10.1126/science.1128972,

the aerosol climate effect is even larger than its radiative effect alone.

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Reality Check #4 Most Societal and Environmental Effects Are Influenced By Regional, Not Global Average, Climate Variability and Change

Climate Science has emphasized that it is regional climate variability and change, both from human and natural effects, that matter the most to society and the environment, rather than global average metrics such as a global average radiative forcing as diagnosed by near surface air temperatures. Important exceptions to this conclusion due occur (such as sea level rise and the increase in atmospheric concentration of well-mixed greenhouse gases), but almost all other climate metrics, such as hurricanes, winter storms, droughts, floods, etc are regional in scale.

Climate Science has written on this subject; e.g. see

What is the Importance to Climate of Heterogeneous Spatial Trends in Tropospheric Temperatures?

The Failure of the 2007 IPCC WG1 Report To Perfom A Spatial Analyses of Human Climate Forcings And Their Influence on Atmospheric and Ocean Circulations

Documentation Of IPCC WG1 Bias by Roger A. Pielke Sr. and Dallas Staley – Part II

Request To Scientists Recommended By Gavin Schmidt To Assess The Relative Role of Human Climate Forcings In Altering Weather and Other Aspects of Climate

As reported before on Climate Science (e.g. see), there are publications on the role of aerosols and well-mixed greenhouse gases as climate forcings, which provide evidence that the more heterogeneous forcing of aerosols have a much greater effect on atmospheric circulations than does the more spatially homogeneous climate forcing of the well mixed greenhouse gases.

One of our papers on this subject is

Matsui, T., and R.A. Pielke Sr., 2006: Measurement-based estimation of the spatial gradient of aerosol radiative forcing. Geophys. Res. Letts., 33, L11813, doi:10.1029/2006GL025974,

where we write in the abstract

“This paper diagnoses the spatial mean and the spatial gradient of the aerosol radiative forcing in comparison with those of well-mixed green-house gases (GHG). Unlike GHG, aerosols have much greater spatial heterogeneity in their radiative forcing. The heterogeneous diabatic heating can modulate the gradient in horizontal pressure field and atmospheric circulations, thus altering the regional climate. For this, we diagnose the Normalized Gradient of Radiative Forcing (NGoRF), as a fraction of the present global heterogeneous insolation attributed to human activity. Although the GHG has a larger forcing (+1.7 W per meter squared) as measured than those of aerosol direct (-1.59 per meter squared) and possible indirect effect (-1.38 per meter squared) in terms of a spatially averaged top-of-atmosphere value, the aerosol direct and indirect effects have far greater NGoRF values (~0.18) than that of GHG (~0.003).”

Land use and land cover change, of course, are also vary spatially heterogeneous climate forcings, as documented, for example, in the paper

Feddema et al. 2005: The importance of land-cover change in simulating future climates., 310, 1674-1678.

with the abstract

“Adding the effects of changes in land cover to the A2 and B1 transient climate simulations described in the Special Report on Emissions Scenarios (SRES) by the Intergovernmental Panel on Climate Change leads to significantly different regional climates in 2100 as compared with climates resulting from atmospheric SRES forcings alone. Agricultural expansion in the A2 scenario results in significant additional warming over the Amazon and cooling of the upper air column and nearby oceans. These and other influences on the Hadley and monsoon circulations affect extratropical climates. Agricultural expansion in the mid-latitudes produces cooling and decreases in the mean daily temperature range over many areas. The A2 scenario results in more significant change, often of opposite sign, than does the B1 scenario.”

Thus such peer reviewed papers necessitate the following conclusions:

Future IPCC assessments that do not adequately investigate in depth the role of all regional climate forcings will, as a result, produce an incomplete report of the role of humans in the climate system and, thus, an incorrect communication of information to policymakers. This is the case with the 2007 IPCC Report

As a result of the neglect by the IPCC of a quantitative assessment of the relative role of all human and natural climate forcings as they alter regional climate patterns, attempts to significantly influence regional and local-scale climate based on controlling CO2 emissions alone as policy for this purpose will necessarily fail.

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Comment By Andrew C. Revkin On The Weblog Comments On The Weblog Entitled “Climate Consensus ‘Busted’?? And The Climate Science Reply

Andy Revkin was gracious to provide a comment in response to the Climate Science weblog of this morning titled “Comments On The Weblog By Andrew C. Revkin Entitled “Climate Consensus ‘Busted’?â€?

Andy Revkin’s comment is

I’m on tough deadlines today (on whale hunts by Japan) but would
still like to fit in a brief comment, although I see you have
comments OFF on that post.

One main comment:

I’m mystified about your assertion that I’ve concluded and conveyed
that the “science is settled” on human-induced climate change. I’ve
written (and blogged) repeatedly that the one undisputed aspect of
greenhouse theory is that more greenhouse gases will warm the world
(and a warmer planet will have less ice and higher seas, as climate
history shows clearly). Michael Crichton and Richard Lindzen and (I
believe you?) don’t dispute that.

Every other aspect of this phenomenon, particularly those most
important to people, remains laden with varying degrees of
uncertainty (pace and extent of rise in temperatures and seas, impact
on cyclones, etc). Maybe you’ve missed my extensive coverage of that
reality, and my critiques of those overplaying either the calamity
side or the hoax side? Much of it is here: www.nytimes.com/revkin and
here: www.nytimes.com/energychallenge.

The rest (questions about what is, and is not, science) must wait for
another day (realistically probably another year, 2008).

Best wishes. I hope, in fairness, you’ll post the comment above promptly.

Andy R.

My Reply is

“Hi Andy

I will post your comment now. You are always welcome to comment (just
e-mail me).

On your reply, I would like to follow up with you in more detail on the
issue of climate change as there are quite a few issues that conflict with
the IPCC view (and your views as I have read them). If I have
misinterpreted them, I will certainly highlight on my weblog.

However, as I read your reply below, you are convinced that the climate
will continue to warm from the greenhouse gases. Yet the lack of warming
in recent years by several measures (upper ocean heat content, lower
tropospheric temperatures), and the at best muted positive feedback from
the water vapor feedback, indicates that we know quite a bit less on
global warming than you indicate.

I agree the warming could resume (due to the diversity of positive
climate forcings of which CO2 is up to 30% in a global average) but the
lack of recent agreement between the models and the observations raises
questions on whether negative feedbacks and negative climate forcings
could actually result in cooling, at least for a period of time. After
all the IPCC SPM admits that they left off climate forcings with a low
level of scientific understanding.

With respect to added CO2, I am becoming convinced that its effect
(threat?) is more from alterations in ocean and land biogeochemistry.
rather than its radiative heating. I am also convinced (and have published
on this as well) that the more heterogenous climate forcings (due to
aerosols and land use/land cover) have a much greater impact on climate
through alterations in atmospheric and ocean circulations than do the
well-mixed greenhouse gases.

I look forward to discussing this with you further.

Best wishes on your whale hunting article. On that issue, I am certain we
are in complete agreement!

All of the best to you for the Holidays!

Roger

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Second Follow Up To Climate Metric Reality Check #3 – Evidence For A Lack Of Water Vapor Feedback On The Regional Scale

As a second follow up on the Climate Science weblog on water vapor feedback (see and see) Ross McKitrick alerted Climate Science to an important claim by two world class scientists in 2000 from the paper

Issac M. Held and Brian J. Soden, 2000: Water vapor feedback and global warming. Annu. Rev. Energy. Environ. 2000.25:441-475.

On page 471 they wrote,

“Given the acceleration of the trends predicted by many models, we believe that an additional 10 years may be adequate, and 20 years will very likely be sufficient, for the combined satellite and radiosonde network to convincingly confirm or refute the predictions of increasing vapor in the free troposphere and its effects on global warming.”

Their abstract is an effective summary of the issue and reads

“Water vapor is the dominant greenhouse gas, the most important gaseous
source of infrared opacity in the atmosphere. As the concentrations of other greenhouse
gases, particularly carbon dioxide, increase because of human activity, it is centrally
important to predict howthewater vapor distribution will be affected. To the extent that
water vapor concentrations increase in a warmer world, the climatic effects of the other
greenhouse gases will be amplified. Models of the Earth’s climate indicate that this
is an important positive feedback that increases the sensitivity of surface temperatures
to carbon dioxide by nearly a factor of two when considered in isolation from other
feedbacks, and possibly by as much as a factor of three or more when interactions with
other feedbacks are considered. Critics of this consensus have attempted to provide
reasons why modeling results are overestimating the strength of this feedback.
Our uncertainty concerning climate sensitivity is disturbing. The range most often
quoted for the equilibrium global mean surface temperature response to a doubling
of CO2 concentrations in the atmosphere is 1.5C to 4.5C. If the Earth lies near
the upper bound of this sensitivity range, climate changes in the twenty-first century
will be profound. The range in sensitivity is primarily due to differing assumptions
about how the Earth’s cloud distribution is maintained; all the models on which these
estimates are based possess strong water vapor feedback. If this feedback is, in fact,
substantially weaker than predicted in current models, sensitivities in the upper half of
this range would be much less likely, a conclusion that would clearly have important
policy implications. In this review, we describe the background behind the prevailing
view on water vapor feedback and some of the arguments raised by its critics, and
attempt to explain why these arguments have not modified the consensus within the
climate research community.”

So far, however, the evidence of an increase in water vapor in the atmosphere is weak, as discussed on Climate Science. If this becomes a robust finding, then, as Issac Held and Brian Soden state

“If this feedback is, in fact, substantially weaker than predicted in current models, sensitivities in the upper half of this range would be much less likely, a conclusion that would clearly have important policy implications”.

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