Climate Science: Roger Pielke Sr. Research Group News

Originally posted on August 9, 2005.

A recent news article illustrates a popular understanding of carbon dioxide as a pollutant. Referring to carbon permit trading it reports:

“These brokers don’t trade stocks or bonds or gold or oil. What they trade is pollution. To be exact, they buy and sell the right to foul the air with carbon dioxide, a greenhouse gas that the U.S. National Academy of Sciences says causes global warming.”

The term “foul” has a number of definitions according to the Webster New World Dictionary, but the most appropriate in the context of the above quote is that it means:

“so offensive to the senses as to cause disgust; stinking; loathsome” and “extremely dirty or impure”; disgustingly filthy.”

A “pollutant” is defined as:

“a harmful chemical or waste material discharged into the water or atmosphere.”

To “pollute” is to:

“make unclean, impure, or corrupt; defile; contaminate; dirty.”

The American Meteorological Society’s Glossary lists the definition as:

air pollution - The presence of substances in the atmosphere, particularly those that do not occur naturally. These substances are generally contaminants that substantially alter or degrade the quality of the atmosphere. The term is often used to identify undesirable substances produced by human activity, that is, anthropogenic air pollution. Air pollution usually designates the collection of substances that adversely affects human health, animals, and plants; deteriorates structures; interferes with commerce; or interferes with the enjoyment of life. Compare airborne particulates, designated pollutant, particulates, criteria pollutants.

The question is: How does atmospheric carbon dioxide fit into this definition? Carbon dioxide does occur naturally, of course, and is essential to life on Earth, as it is an essential chemical component in the photosynthesis process of plants. This is in contrast with other trace gases in the lower atmosphere such carbon monoxide, ozone, and sulfur dioxide which are have direct health and environmental effects on humans and vegetation. Indeed, when combustion is optimized, less carbon monoxide and more carbon dioxide are produced. There are no positive effects that I am aware of at any level of these pollutants in the lower atmosphere.

Thus, it is more informative to define anthropogenic inputs of carbon dioxide as a climate forcing, as was done in the 2005 National Research Council Report. This provides the recognition that carbon dioxide does not have direct health effects as implied by the news article that carbon dioxide “fouls” the air, but it does significantly affect our climate. Of course, carbon monoxide, ozone, and sulfur dioxide are also climate forcings. When these other atmospheric constituents are referred to in news articles and elsewhere, we would benefit by a distinction between an “air pollutant” and a “climate forcing” depending on the context.

Originally posted on August 19, 2005.

A recent paper in Geophysical Research Letters by K. Zickfeld and colleagues (”Is the Indian summer monsoon stable against global change?” provides an example of investigating multiple climate forcings. According to their study, sulfur emissions and/or land-use changes as they affect planetary albedo, or natural variations in insolation and CO₂ concentrations, could trigger abrupt transitions between different monsoon regimes. While the paper uses a simple box model of the tropical atmosphere, it is a start at investigating a set of multiple climate forcings as causing rapid transitions of climate in India. Such rapid transitions are already part of the natural system; see Rial, J., R.A. Pielke Sr., M. Beniston, M. Claussen, J. Canadell, P. Cox, H. Held, N. de Noblet-Ducoudre, R. Prinn, J. Reynolds, and J.D. Salas, 2004: Nonlinearities, feedbacks and critical thresholds within the Earth’s climate system. Climatic Change, 65, 11-38.)

In contrast to the nearly linear, and monotonic predicted trends from the anthropogenic increases of CO2 such as reported by the IPCC, the occurrence of such sudden changes are more the norm and would have major societal impacts. Such nonlinear climate system responses, however, are likely to be impossible to skillfully predict. This provides further impetus to adopt the vulnerability perspective such as promoted by Jon Foley (subscription required) and here on this Weblog (see our July 19 and 26 and August 16 2005 postings).

The August 11 2005 paper published in Science Express Reports (Sherwood S., J. Lanzante ,and Cathryn Meyer: Radiosonde daytime biases and late-20th century warming; subscription required), for example, perpetuate the emphasis on large-scale linear trend analysis, in their study of tropospheric temperature trends. This is because the General Circulation Models focus on global- and zonally-averaged temperature trends, and linear trends from the observations are being compared with linear trends from the GCMs. As quoted by one of the authors (Sherwood) in a New York times interview (free subscription required).

“Things being debated now are details about the models,” said Steven Sherwood, the lead author of the paper on the balloon data and an atmospheric physicist at Yale. “Nobody is debating any more that significant climate changes are coming.”

This statement is based on a linear analysis.

However, while their study of the accuracy of linear trends determined from radiosondes is scientifically interesting, if the Geophysical Research Letters study by Zickfeld et al. has merit, it is to show us that assessing large-scale linear trends is of little practical use in estimating our real threat from future climate change.

Originally posted on August 25, 2005.

Teleconnections are defined by the American Meteorological Society as:

“1. A linkage between weather changes occurring in widely separated regions of the globe. 2. A significant positive or negative correlation in the fluctuations of a field at widely separated points. Most commonly applied to variability on monthly and longer timescales, the name refers to the fact that such correlations suggest that information is propagating between the distant points through the atmosphere.”

This linkage can be accomplished by alterations of regional tropospheric temperatures which create changes in the large-scale pressure and wind fields, and/or by the advection of material from one region to another (such as from blowing dust or emissions of pollutants that are advected by the wind). The National Research Council report discusses teleconnections as related to radiative forcings.
Originally posted on August 25, 2005.

Two recent papers provide examples of the teleconnection associated with alterations in regional tropospheric temperatures (see Lu, Riyu, and Buwen Dong, 2005. Impact of Atlantic sea surface temperature anomalies on the summer climate in the western North Pacific during 1997-1998. J. Geophys. Res. - Atm., 110, D16102, doi:10.1029/2004JD005676, August 19, 2005, and Wang, D., C. Wang, X. Yang, and J. Lu, 2005. Winter Northern Hemisphere surface air temperature variability associated with the Arctic Oscillation and North Atlantic Oscillation. Geophys. Res. Lett., 32, L16706, doi:10.1029/2005GL022952, August 20, 2005). This work further illustrates the importance of climate patterns in one region affecting the climate elsewhere through alterations in the large-scale pressure field. Work that Chris Castro of our research group has completed has also illustrated how sea surface temperature anomalies in the Pacific Ocean affect the summer rainfall patterns in western North America by teleconnections.

The acceptance of sea surface anomaly patterns as a surface climate forcing that affects the weather at large distances, of course, is an accepted teleconnection effect. Indeed, this teleconnection effect is why there are major global climate anomalies when an El Niño occurs.

The influence of spatially heterogeneous climate forcing by land-use/land-cover change and by aerosol clouds as they produce teleconnections, however, is less accepted by the climate community despite the clear parallel between climate forcing from sea surface temperature anomalies and these forms of climate forcing. Each of these climate forcings is spatially coherent, persist for long time periods, and significantly affect the fluxes of heat, moisture, and momentum into and out of the atmosphere. We discussed the role of spatially focused climate forcings in our July 28th blog “What is the Importance to Climate of Heterogeneous Spatial Trends in Tropospheric Temperatures”? The two new papers by Lu and Dong, and by Wang and colleagues clearly show that it is the regional variations of the climate system that exerts a major influence on the weather we experience. The focus of the climate community on global-averaged and zonally-averaged surface and tropospheric temperature changes is a distraction from what the dominant spatial scales of climate forcing are, as exemplified by these two new papers.

Originally Posted on July 11, 2005.

The title of this weblog is “Climate Science,” so the first thing we need to do is define “climate.” For many, the term refers to long-term weather statistics. However, on this blog we are adopting the definition that is provided in the 2005 National Research Council (NRC) report where the climate is the system consisting of the atmosphere, hydrosphere, lithosphere, and biosphere. Physical, chemical, and biological processes are involved in interactions among the components of the climate system. Figure 1-1 and 1-2 in the report illustrate this definition of climate very clearly. In the NRC report, climate forcings were extended beyond the radiative forcing of carbon dioxide to include the biogeochemical influence of carbon dioxide, but also a variety of aerosol forcings (see Table 2-2 in the report), nitrogen deposition, and land-cover changes. Each of these forcings has been determined to influence long-term weather statisitics as well as other aspects of the climate.

However, this concept of climate and its alterations by humans, has been generally ignored. The NRC report listed above certainly appears to have been incompletely missed by policymakers. As an example, at the G-8 meeting, the term “climate change” is used interchangably with “global warming.” However, the human influence on climate is much more complex and multi-dimensional than captured by the term “global warming” (see, for example, http://www.climatesci.org/publications/pdf/R-260.pdf; http://www.nap.edu/books/0309095069/html/15.html and http://www.climatesci.org/pdf/R-225.pdf). The term “global warming” is generally used to refer to an increase in the globally-averaged surface temperature in response to the increase of well-mixed greenhouse gases, particularly CO₂.

If, however, we are interested in atmospheric and ocean circulation changes, which, afterall is what creates our weather, we need to focus on how humans are altering these circulations. Ocean heat content changes are the much more appropriate metric than a globally-averaged surface temperature when evaluating “global warming” in any case (http://www.climatesci.org.edu/publications/pdf/R-247.pdf).

Thus it matters how we define climate and climate forcing (http://www.nap.edu/books/0309095069/html/15.html). By ignoring a number of the other first-order climate forcings, we are not properly addressing the threat we face in the future, but instead relying on the overly simplistic view of focusing on reductions in carbon dioxide emissions as the way to reduce our “dangerous intervention” in the climate. With respect to the changes of circulations, and therefore, weather, we need to identify and quantify the role of spatially heterogeneous climate forcings such as from aerosols and land-cover change, in addition to the influence of well-mixed greenhouse gases. These heterogeneous climate forcings could represent a more significant threat to our future climate system than the risk of an increase in the atmospheric concentration of CO₂.

Hopefully, this blog will stimulate discussion, as well as illuminate reasons why this broader perspective on climate variability and change has been mostly ignored.

Originally posted on July 22, 2005.

In one of our July 11, 2005 posts, climate was defined so that climate forecasts are forecasts of the future state of the atmosphere, oceans, land, and continental glaciers, as defined using physical, chemical, and biological variables that we can measure. We can apply local, regional, or global averages over any time period we choose to characterize the future state of the climate. Weather forecasts are a subset of climate forecasts, in that we limit our forecasts to weather conditions, averaged over 12-hour periods, for example, out to a week or more, and generally assume a number of climate variables, such as vegetation and sea-surface temperatures, are invariant over this time period. It is important to note that the averaging time is not what distinguishes weather from climate (e.g., although called “seasonal climate predictions”, these forecasts are more accurately “seasonal-averaged weather predictions”).

As a necessary condition, climate forecasts must be able to skillfully reconstruct the observed temporal and spatial variability and change of local, regional, and global climate variables, when the forecast models are only given the external forcings (such as solar irradiance, volcanic eruptions, CO2 concentrations) as illustrated in Figure 1-2 in Radiative Forcing of Climate Change: Expanding the Concept and Addressing Uncertainties (2005). See also Tables 1 and 2 in Dynamical downscaling: Assessment of value retained and added using the Regional Atmospheric Modeling System (RAMS) where climate forecasts are called a Type 4 model simulation.

In 2000, we published a paper which demonstrated that the general circulation models were unable to skillfully reconstruct even the globally-averaged mid-tropospheric temperature trend during the 1979-2000 time periods. Thus, as of that date, the climate prediction models were shown to not be able to skillfully forecast the future climate even with respect to a single globally-averaged climate variable. (I am on a CCSP committee entitled “Temperature Trends in the Lower Atmosphere: Steps for Understanding and Reconciling Differences” and will update our assessment of the issue of climate prediction skill as soon as the report is public).

Mike MacCracken in his essay response to my Climatic Change essay seeks to distinguish a “prediction” from a “projection.” However, this only obscures the discussion, as GCM results are obviously packaged as forecasts in that specific time periods in the future are presented (see, as just one example, the 2070-2100 forecasts of the United Kingdom Hadley Centre). Even Mike recognizes there is no regional predictive skill in his paper entitled “Reliable regional climate model not yet on horizon.”

A conclusion of our evaluation is that papers which appear in the literature that present future values of a subset of (or all) climate variables are misrepresenting their results by implying that they are forecasts. They should be presented as sensitivity studies (as a process study; see my July 15, 2005 post on the types of model applications).

We can illustrate their misuse as forecasts by an analog. If we could run a numerical weather prediction model to provide a forecast of rainfall for tomorrow and publish a paper on it today, would this be considered sound science justifying a paper? Of course not. First we would want to wait to see if the forecast was skillful. This is possible with weather forecasts for tomorrow, but we cannot yet verify a climate forecast model’s skill, for decadal-averaged weather conditions decades into the future.

The climate modeling community runs ensembles of multi-decadal predictions (with different initial conditions, different models) and they average their results over decadal time periods, which they claim distinguishes their simulations from the numerical weather prediction community’s application. Of course the numerical weather prediction community also runs ensembles of simulations. The fundamental difference is that the weather community can validate their model results thousands of times. There is no such ability with multi-decadal climate prediction models.

Our conclusions are the following:

1. Peer-reviewed papers, and national and international assessments, which present model results for decades into the future, or provide impact studies in response to these model simulations, should never be interpreted as skillful forecasts (or skillful projections). They should be interpreted as process (sensitivity) studies, even though the authors use definitive words (such as this “will” occur) and display model output with specific time periods in the future.
2. The US National Assessment, which provided model simulations on regional scales for the coming decades, is inaccurately portrayed when their results are given to stakeholders with the interpretation that their results bracket what is expected in the future. This is misleading when transmitted to policymakers, as process studies are inappropriately interpreted to be forecasts.
3. Climate forecasts (projections) decades into the future have not demonstrated skill in forecasting local, regional, and global climate variables. They have shown that human climate forcing has the capacity to alter the climate system, but we should not present these model simulations as forecasts. To present them as forecasts is misleading to policymakers and others who use this information.

Originally posted on July 15, 2005.

Climate models are comprised of fundamental concepts and parameterizations of physical, biological, and chemical components of the climate system, expressed as mathematical formulations, and then averaged over grid volumes. These formulations are then converted to a programming language so that they can be solved on a computer and integrated forward in discrete time steps over the chosen model domain. A global climate model needs to include component models to represent the oceans, atmosphere, land, and continental ice and the interfacial fluxes between each other. Weather models are clearly a subset of a climate model (a discussion of mesoscale weather models is given in Pielke, R.A., Sr., 2002: Mesoscale meteorological modeling. 2nd Edition, Academic Press, San Diego, CA, 676 pp), where the basic framework of all scales of weather models is presented). On the global scale, it is very important to distinguish global atmospheric-ocean circulation models (AOGCMs) from global climate models. Global climate models need to include all important components of the climate system as discussed in a 2005 National Research Council report, while AOGCMs up the present have not.

There are three types of applications of these models: for process studies, for diagnosis, and for forecasting.

Process studies: The application of climate models to improve our understanding of how the system works is a valuable application of these tools. In an essay, I used the term sensitivity study to characterize a process study. In a sensitivity study, a subset of the forcings and/or feedback of the climate system may be perturbed to examine its response. The model of the climate system might be incomplete and not include each of the important feedbacks and forcings.

Diagnosis: The application of climate models, in which observed data is assimilated into the model, to produce an observational analysis that is consistent with our best understanding of the climate system as represented by the manner in which the fundamental concepts and parameterizations are represented. Although not yet applied to climate models, this procedure is used for weather reanalyses (see the NCEP/NCAR 40-Year Reanalysis Project).

Forecasting: The application of climate models to predict the future state of the climate system. Forecasts can be made from a single realization, or from an ensemble of forecasts which are produced by slightly perturbing the initial conditions and/or other aspects of the model. Mike MacCracken, in his very informative response to my Climatic Change essay seeks to differentiate between a prediction and a projection.

With these definitions, the question is where does the IPCC and US National Assessment Models fit? Since the General Circulation Models do not contain all of the important climate forcings and feedbacks (as given in the aforementioned 2005 NRC report) the models results must not be interpreted as forecasts. Since they have been applied to project the decadal-averaged weather conditions in the next 50-100 years and more, they cannot be considered as diagnostic models since we do not yet have the observed data to insert into the models. The term projection needs to be reserved for forecasts, as recommended in Figure 6 in R-225.

Therefore, the IPCC and US National Assessments appropriately should be communicated as process studies in the context that they are sensitivity studies. It is a very convoluted argument to state that a projection is not a prediction. The specification to periods of time in the future (e.g., 2050-2059) and the communication in this format is very misleading to the users of this information. This is a very important distinction which has been missed by impact scientists who study climate impacts using the output from these models and by policymakers.

Originally posted on July 11, 2005.

The globally-averaged surface temperature trend has been highlighted as an icon of climate change. For example, a meeting was held In Exeter, United Kingdom from Feb 1-3, 2005 entitled “Avoiding Dangerous Climate Change.” The focus on a globally-averaged temperature trend was clear in the emphasis at the meeting. The Hadley Centre brochure relevant to this meeting stated “Once a tolerable (i.e., non-dangerous) change has been determined - say in terms of a global temperature rise - we then have to calculate what this corresponds to in terms of tolerable greenhouse concentrations in the atmosphere.” The message is that a clear global surface temperature threshold exists over which there are dangerous effects on the climate system.

This perspective however, avoids discussing the real issue associated with long-term variability and changes in climate.

First, in the context of atmospheric circulation changes (which is, after all what produces our weather), it is the regional tropospheric temperature and humidity trends that are important, not a global average surface temperature A change in the globally-averaged surface, or even globally-averaged tropospheric, temperature are important primarily in the context of how this results in circulation changes. The globally-averaged surface temperature is a very poor metric to use to assess these circulation changes. The 2005 NRC report recognized this limitation in using globally-averaged surface temperatures. Secondly, with respect to even “global warming” the ocean heat content changes, rather than the surface temperature anomaly provides a more robust metric (see R-247).

With respect to the surface temperature itself, there are several issues with respect to the spatial representativeness of the trends that have been incompletely (or not at all) investigated. These are:

1. Poor microclimate exposure:

This is a land issue. The use of photographs to exclude questionable stations is obvious (and we are quite puzzled why anyone would not make this a high priority). The effect of poor exposure (which results in different site exposure depending on the wind direction) and changes in the site conditions over time have not been quantified. Our qualitative assessment based on the photographs that we have seen is that this it is likely to insert a warm bias for most sites. [Note added Nov 11 2008 see the outstanding summary of observation sites in Watts Up With That]

2. Moist enthalpy:

This is both a land and an ocean issue. The use of the terms “warming” and “cooling” are being incompletely used when there is significant water vapor in the surface air (tropics and mid-latitude warm seasons, in particular). This will produce a warm bias when the air actually became drier over time, and a cool bias when the air becomes more humid over time. This effect has not been quantified with respect to how it influences regional and global surface temperature trends. It has been shown to be significant for individual sites.

3. Vertical lapse rate issues (paper in preparation [noted added Nov 11 2008 : see the two papers which have appeared -  see and see)]:

The influence of different lapse rates, heights of observations and surface roughness have not been quantified. For example, windy and light wind nights should not have the same trends at most levels in the surface layer, even if the surface-layer averaged temperature trend was the same.

4. Uncertainty in homogeneity adjustments:

Time of observation, instrument changes, and urban effects have been recognized as important adjustments (see R-234) that are required to revise temperature trend information in order to produce improved temporal and spatial homogeneity. However, these adjustments do not report in the final homogenized temperature anomalies, the statistical uncertainty that is associated with each step in the homogenization process.

Thus even if the globally-averaged surface temperature was a particularly appropriate metric to assess climate change, there are issues on the robustness of this data set which have been overlooked. Our recommendation, however, is to deemphasize the globally-averaged surface temperature as a climate change metric and assess instead circulation changes as defined by tropospheric temperature and water vapor (and for the ocean, temperature and salinity) variability and trends.

Originally posted on July 28, 2005.

The 2005 National Research Council report concluded that:

“regional variations in radiative forcing may have important regional and global climate implications that are not resolved by the concept of global mean radiative forcing.”

And furthermore:

“Regional diabatic heating can cause atmospheric teleconnections that influence regional climate thousands of kilometers away from the point of forcing.”

This regional diabatic heating produces temperature increases or decreases in the layer-averaged regional troposphere. This necessarily alters the regional pressure fields and thus the wind pattern. This pressure and wind pattern then affects the pressure and wind patterns at large distances from the region of the forcing which we refer to as teleconnections.

The regional diabatic forcing can be caused by land-use/land-cover change (e.g. , Chase et al. 2000a) or by aerosol emissions. Even natural surface variations such as in ocean color produce such teleconnections in a general circulation model (see Atmospheric response to solar radiation absorbed by phytoplankton Shell et al. 2003)

There is debate, however, regarding whether the magnitude of the regional diabatic forcing is large enough to result in long distance teleconnections. However, observed multi-decadal trends in tropospheric-averaged temperatures are large enough to result in large-scale circulation trends (see, for example, A Comparison of Regional Trends in 1979-1997 Depth-Averaged Tropospheric Temperatures for the magnitude of the 1979-1997 regional trends). Thus land-use/land-cover changes and aerosol clouds that produce regional tropospheric temperature anomolies of a similar magnitude (or larger magnitude) would be expected to have significant teleconnection effects.

If this is true, than regional diabatic heating due to human activities represents a major, but under-recognized climate forcing, on long-term global weather patterns. Indeed, this heterogenous climate forcing may be more important on the weather that we experience than changes in weather patterns associated with the more homogeneous spatial radiative forcing of the well-mixed greenhouse gases (see the NASA press release, which is based on the multi-authored paper 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).

For the next several weeks Climate Science is reposting a number of weblogs that are worth repeating. We have quite a few more readers now than we did when my weblog started. The first reposting appears below.

Originally posted on July 29, 2005.

The different definitions of climate, have done much to confuse policymakers in the discussion of climate science.

The American Meteorological Society (AMS) definition of “climate change” is

“(Also called climatic change.) Any systematic change in the long-term statistics of climate elements (such as temperature, pressure, or winds) sustained over several decades or longer. Climate change may be due to natural external forcings, such as changes in solar emission or slow changes in the earth’s orbital elements; natural internal processes of the climate system; or anthropogenic forcing.”

The AMS defines anthropogenic forcing as

“Human-induced or resulting from human activities; often used to refer to environmental changes, global or local in scale.

The AMS defines the climate system as the

“system, consisting of the atmosphere, hydrosphere, lithosphere, and biosphere, determining the earth’s climate as the result of mutual interactions and responses to external influences (forcing). Physical, chemical, and biological processes are involved in the interactions among the components of the climate system.”

Here we have an inconsistency with the definition even by a very distinguished professional society! Climate, as defined by the AMS, is focused on the atmosphere, while the climate system consists of the atmosphere, hydrosphere, lithosphere, and biosphere. No wonder policymakers misapply this terminology.

As one example of the misuse by policymakers, the Royal Society released the following statement by Lord May:

“The science points to the need for a Herculean effort to make massive cuts in the amount of greenhouse gases that we pump into the atmosphere. So, while this encouraging new deal may play a role in this, it will only be part, and not all, of the solution.”

“But we have serious concerns that the apparent lack of targets in this deal means that there is no sense of what it is ultimately trying to achieve or the urgency of taking action to combat climate change. And the developed countries involved with this agreement must not be tempted to use it as an excuse to avoid tackling their own emissions.”

“All eyes should be on the United Nations Framework Convention on Climate Change in Montreal at the end of November [2005]. Top of the agenda at this meeting should be the initiation of a study into what concentration of greenhouse gases in the atmosphere we can allow without suffering the most catastrophic effects of climate change. This would allow us to plan cuts in worldwide emissions accordingly and provide direction to such efforts to tackle what is the biggest environmental threat we face today.”

Here the conclusion is made that to “combat climate change” we must initiate “a study into what concentration of greenhouse gases in the atmosphere we can allow without suffering the most catastrophic effectsof climate change.”

Ignored in this statement is the role of the other anthropogenic climate forcings that we identified in the National Research Council report.

Lord May, President of the Royal Society, has clearly overlooked a very critical definition of what really constitutes the climate system and what the anthropogenic forcings and feedbacks are that influence climate. He is, unfortunately, cherrypicking climate science.

My weblog of October 28 stirred up quite some dust here in Holland. The Director-in-chief of KNMI was upset enough to send me an e-mail (the first ever!) explaining the official position of his institute. He wrote that KNMI supports the choice of 130 cm of sea-level rise as a worst-case estimate  based on the worst-case scenario of IPCC. I responded by writing that I felt it was his duty to declare in public that Professors Kabat and Vellinga had made  statements that go far beyond this extreme scenario, and were badly damaging legitimate concerns about climate change that way. He did not respond to that. I also sent him a draft of this second weblog, giving him the chance to respond or to prepare a weblog himself. He didn’t react to that either.

In the meantime, my mailbox was inundated. One Dutch climate scientist, who wishes to remain anonymous because of possible loss of job security, sent me the letter reproduced  below. I need not comment on the Climate of Fear apparently prevailing in the Dutch climate research community.

My respondent wrote: “I recently learned that there has been some debate about the contribution of KNMI, the Royal Netherlands Meteorological Institute, to the report by the Delta Commission. In this report, the Commission gives an estimate for the sea-level rise in the Netherlands in a “worst-case” scenario. Following the presentation of the report, two members of the Commission, Pavel Kabat and Pier Vellinga, stated that the sea level rise in this scenario - 130 cm rise in 2100 - is actually not a worst-case scenario, but a very likely one. This is a bit awkward, as you would think that everyone contributing to the report has agreed that this is actually a plausible-yet-very-unlikely scenario, and that by definition it cannot get worse than the worst possible case.”
 
“In a magazine interview, Pavel Kabat said: “I think we can easily reach or exceed 130 cm. We have given a cautious estimate of ice-cap meltdown. A new British study presents even higher figures.”  In an official lecture at Wageningen University, Pier Vellinga said: “It is very likely that we have to act within thirty years or less if we wish to prevent the Earth from warming up six to ten degrees in the next two centuries and the sea level from rising six meters or more.”
 
“Clearly, Kabat and Vellinga claim that the danger far exceeds the conclusions in the report to which they themselves have contributed. Normally you would expect that this would provoke an angry response from the other contributors. However, the Dutch climate research community has remained conspicuously silent. I would be willing to respect KNMI’s choice to remain silent, but only if everyone involved agrees that 130 cm is indeed an upper limit, based on a culmination of unfavorable scenarios. On its website, KNMI states that the policy with regard to coastal defense for the coming period continues to be based on the KNMI-2006 scenarios. KNMI  agrees on 130 cm as a plausible upper limit, but will adjust that number in the light of new observational evidence.”
 
“But how on earth are you going to validate the estimate of an upper limit? I would love to have explained in detail how we are going to establish, based on observations, whether or not the 130 cm is plausible. What methods, which observations, which time frames are required? By definition, validating something that is only a possibility is not possible beforehand. Since it is only a possibility it might not even occur.” 

“To complicate matters further, recent scientific publications show that we are not even capable of determining sea level rise during the last 5 years (2003-2007), while this is a period with by far the best available observations (Willis, JGR-oceans, 2008; Wunsch, J. Climate, 2008). Estimates range from zero rise to  3 mm/year; it is suggested in the literature that 3 mm might be an overestimation. These findings were recently  presented at a KNMI seminar. Yet no mention of these new findings anywhere.”
 
“KNMI could adopt another attitude. Take the KNMI or IPCC scenarios as starting point, and make very clear that these are the most likely results. Then take the scenario from the Delta-report - the background report indicates that even for the worst-case scenario the possibility exists of zero sea level rise despite the 6 degrees warming if all conditions are favorable - and draw the conclusion that it is simply not possible to derive anything meaningful from the worst-case scenario. It would have been possible that the worst-case scenario would have narrowed down uncertainties, but alas, that is not the case. This fact - the large uncertainty margin - could just as well be used to develop policy, a policy that can be adapted according to the progress of our knowledge and understanding. There are various possibilities for such a policy and there are plenty of scientists and researchers who promote developing these ideas.”

“I feel I have an obligation to warn society about people like Vellinga. I consider him dangerous because of his alarmism, his unfounded speculations about climate change, and his  misrepresentation of the findings in the Delta-report. Also, it would be good for the reputation of KNMI if it would adopt a more critical attitude. If KNMI does not accept and promote the idea that in the end it is all about truth, finding the truth, being objective and letting scientists be scientists, discussing and disagreeing with one another, then KNMI cannot be considered an independent scientific institute anymore. Independence and authenticity, that is what separates scientists from politicians or the common people.” 
 
That was my respondent’s reaction to the official position of KNMI. Like him, I am reluctantly willing to go along with 130 cm as an upper limit obtained by an accumulation of extreme assumptions, but only if no statements beyond that extremely unlikely scenario are tolerated. KNMI is in danger of losing its reputation as an authoritative scientific institution. As a retired KNMI research chief, I feel both ashamed and dismayed.