Climate Prediction Advocacy By Shukla Et Al 2010 “Toward a New Generation Of World Climate Research And Computing Facilities”

There is a recent article in the Bulletin of the American Meteorological Society that advocates for major funding for climate prediction by well respected climate scientists. The article is

J. Shukla, T. N. Palmer, R. Hagedorn, B. Hoskins, J. Kinter, J. Marotzke, M. Miller, J. Slingo, 2010: Toward a New Generation of World Climate Research and Computing Facilities. Bull. Amer. Met. Soc. pages 1407–1412.

The abstract reads

“To accelerate progress in understanding and predicting regional climate change, national climate research facilities must be enhanced and dedicated.”

Excerpts from the text read

“Weather and climate are undisputedly major factors for the well-being and development of society, impacting all scales from individual lives to global economies (Sachs 2008). Societies have flourished by adapting to and taking advantage of current climate conditions. However, this relationship between climate and society is fragile and volatile: during the past 25 years, weather-related disasters have caused more than 600,000 fatalities and $1.3 trillion (U.S. dollars) of economic losses. This paper is part of an ensemble of papers proposing an international multidisciplinary prediction initiative (Shapiro et. al. 2010).

Considering the increasing frequency of extreme weather and climate events (Alley et al. 2007) together with our enhanced vulnerability (WMO 2006) to weather and climate hazards caused by rapid economic and population growth, mortality and economic losses will continue to rise. As the Stern report has emphasized (Stern 2007), climate change is a trillion dollar problem: inaction will be many times costlier than cutting greenhouse gas emissions, which itself could cost the world economy as much as 1% of its gross domestic product (GDP).

Since current climate systems models are not able to provide predictions with adequate accuracy and detail, climate prediction needs to be revolutionized to be able to fulfill society’s expectations……We recommend the creation of a small number (at least three) of highly connected multinational facilities with computer capability for each facility of at least 20 petaflops in the near term, 200 petaflops within five years, and 1 exaflop by the end of the next decade.

The last paragraph of the article succinctly presents the perspective and advocacy of the authors where they conclude

“Soon the societal demand for policy-relevant climate predictions will be so great that the most advanced technology and the best available talent must be brought to bear to address this great challenge. The time to begin that process is now!”

There are major issues with their proposal, however.

First, they are combining the risks from climate that have always occurred (which are real and serious) from possible deviations from possible changes climate conditions in the future which fall outside of what has occurred in the historical or recent paleo-historical record. There are, however, NO examples of skillful regional forecasts decadal  forecasts even using hindcasts for the past 100 years.   There  is no way to even validate their forecasts decades from now, so how would their predictions be evaluated?

Also, despite their claim of an

“….increasing frequency of extreme weather and climate events”

the evidence of a climate change component of such an increase is disputed.

Second, there is an assumption in the article that policymakers are awaiting these forecasts in order to make more informed decisions.  Apparently, the authors have not read my son’s books The Honest Broker or  The Climate Fix.  The linear model of transfering science knowledge to policymakers is not an accurate description of how the real world works.

My recommendation is to invert the scientific investigation by bringing the stakeholders into the assessment process. I overviewed this perspective in my post

A Way Forward In Climate Science Based On A Bottom-Up Resourse-Based Perspective

where I wrote

“There are 5 broad areas that we can use to define the need for vulnerability assessments : water, food, energy, [human] health and ecosystem function. Each area has societally critical resources. The vulnerability concept requires the determination of the major threats to these resources from climate, but also from other social and environmental issues. After these threats are identified for each resource, then the relative risk from natural- and human-caused climate change (estimated from the GCM projections, but also the historical, paleo-record and worst case sequences of events) can be compared with other risks in order to adopt the optimal mitigation/adaptation strategy.”


The questions [to be asked to the stakeholders]……. are listed below.

 1. Why is this resource important?  How is it used? To what stakeholders is it valuable?
2. What are the key environmental and social variables that influence this resource?
3.  What is the sensitivity of this resource to changes in each of these key variables? (this includes, but is not limited to, the sensitivity of the resource to climate variations and change on short (e.g. days); medium (e.g. seasons) and long (e.g. multi-decadal) time scales.
4. What changes (thresholds) in these key variables would have to occur to result in a negative (or positive) response to this resource?
5. What are the best estimates of the probabilities for these changes to occur? What tools are available to quantify the effect of these changes. Can these estimates be skillfully predicted?
6. What actions (adaptation/mitigation) can be undertaken in order to minimize or eliminate the negative consequences of these changes (or to optimize a positive response)?

7. What  are specific recommendations  for policymakers and other stakeholders?

The Shukla et al paper perpetuates the top-down global model driven perspective to provide regional and local information to the resource communities. I propose the inversion of the process which is bottom-up, resource based.  Three-way interactions between the science community, stakeholders and policymakers provides a more robust way forward to reduce the risk to climate (regardless of the extent that human’s are altering the climate system) as well  from the risk due to other environmental and societal threats.

The expenditure of large funds for a small set of computer centers devoted to multi-decadal climate predictions therefore, in my view, is a very poor use of tax money.

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