by Judith Curry
My paper “Climate Science and the Uncertainty Monster” is in press at the Bulletin of the American Meteorological Society.
Climate Science and the Uncertainty Monster
Judith A. Curry and Peter J. Webster
Abstract. How to understand and reason about uncertainty in climate science is a topic that is receiving increasing attention in both the scientific and philosophical literature. This paper provides a perspective on exploring ways to understand, assess and reason about uncertainty in climate science, including application to the Intergovernmental Panel on Climate Change (IPCC) assessment reports. Uncertainty associated with climate science and the science-policy interface presents unique challenges owing to complexity of the climate system itself, the potential for adverse socioeconomic impacts of climate change, and politicization of proposed policies to reduce societal vulnerability to climate change. The challenges to handling uncertainty at the science-policy interface are framed using the ‘monster’ metaphor, whereby attempts to tame the monster are described. An uncertainty lexicon is provided that describes the natures and levels of uncertainty and ways of representing and reasoning about uncertainty. Uncertainty of climate models is interpreted in the context of model inadequacy, uncertainty in model parameter values, and initial condition uncertainty. We examine the challenges of building confidence in climate models and in particular, the issue of confidence in simulations of the 21st century climate. The treatment of uncertainty in the IPCC assessment reports is examined, including the IPCC 4th Assessment Report conclusion regarding the attribution of climate change in the latter half of the 20th century. Ideas for monster taming strategies are discussed for institutions, individual scientists, and communities.
The paper is online [here].
For those of you who have followed my previous uncertainty threads, there isn’t any new material here, but the significance is in its publication in a refereed journal so that it will reach the audience that we hope will be most influenced by this.
This paper is pretty much guaranteed to generate controversy. We anticipated this at the time this was submitted, and requested that the editors NOT select any reviewers participating as lead authors in the AR4 or AR5. Apparently our request was honored, and we received two very useful and constructive reviews on the paper.
Not suprisingly, a Comment on the paper has already been submitted, focused on Section 4 of the paper regarding attribution. I’m providing the text of the reply to the Comment that we have submitted, preserving the anonymity of Comment.
Reply to XXX’s Comment on “Climate Science and the Uncertainty Monster”
Judith A. Curry and P.J. Webster
We would like to thank the authors of the Comment for their interest in our paper. The authors are correct that since the Third Assessment Report, the IPCC has placed a high priority on communicating uncertainty, and perhaps their methods have been effective in communicating with the public. However, communicating uncertainty is a very different endeavor from actually characterizing and understanding uncertainty, an effort in which we feel the IPCC falls short, especially from the perspective of scientists outside the IPCC process (climate scientists as well as scientists from other technical fields).
Curry and Webster (2011) raise the issue of how the IPCC has actually undertaken to investigate and judge uncertainty. XXX’s comments focus on section 4 Uncertainty in attribution of climate change of our paper (Curry and Webster, 2011), which addresses the IPCC AR4 conclusion regarding attribution:
“Most of the observed increase in global average temperatures since the mid-20th century is very likely due to the observed increase in anthropogenic greenhouse gas concentrations.”
The text in the IPCC AR4 (chapter 9) referenced by XXX describes general issues and methodology for investigating uncertainty on the topic of attribution, including listing uncertainty locations. In preparing our original manuscript, we read these passages and the cited references numerous times. Listing a large number of uncertainty locations, and then coming up with a “very likely” likelihood statement using expert judgment in the context of a consensus building approach, is at the heart of our concern regarding the IPCC’s treatment of uncertainty.
XXX’s statement “The remaining uncertainty in our estimates of internal climate variability is discussed as one of the reasons the overall assessment has larger uncertainty than individual studies.” Translating this uncertainty in internal climate variability (among the many other sources of uncertainty) into a “very likely” likelihood assessment is exactly what was not transparent in their assessment.
We most definitely “do not appreciate the level of rigour with which physically plausible non-greenhouse gas explanations of the recent climate change are explored.” Specifically with regards to solar forcing, a rigorous uncertainty assessment would have included a systematic exploration of individual model sensitivity to different solar forcing datasets and the associated range of uncertainty. Further, some account for known unknowns associated with indirect solar effects should be included in any assessment of confidence or likelihood. Chapter 2 in the AR4 WG1 report characterizes the uncertainty associated with aerosol direct forcing as medium to low, and the uncertainty associated with the aerosol indirect effect on cloud albedo is characterized as low. This characterization of aerosol forcing does not even include most of the known aerosol indirect forcing mechanisms, which adds even greater uncertainty to the aerosol forcing. With regards to aerosol forcing, a rigorous uncertainty assessment would have included sensitivity simulations of individual models to a range of aerosol forcing (which is associated with low to medium confidence levels) and some account for the absence of known mechanisms of aerosol indirect forcing.
Our overall concerns about the IPCC AR4 attribution statement and uncertainty analysis are best illustrated in the context of the recent publication by Gent et al. (2011), showing simulations of the 20th century climate of the NCAR Community Climate System Model Version 4. Figure 1 [the link downloads the file] compares the results of the CCSM3 (used in the AR4) with the CCSM4 simulations (for the AR5). In spite of using a better model and better forcing data for the CCSM4 simulations, the CCSM4 simulations show that after 1970, the simulated surface temperature increases faster than the data, so that by 2005 the model anomaly is 0.4oC larger than the observed anomaly. By contrast, the CCSM3 simulations show very good agreement with the surface temperature data. The critical difference is that the CCSM4 model was tuned for the pre-industrial period and used accepted best estimates of the forcing data, whereas the CCSM3 model was tuned to the 20th century observations and each modeling group was permitted to select their preferred forcing data sets. The contrast between the CCSM3 and CCSM4 simulations illustrate the bootstrapped plausibility of climate model simulations that influenced the AR4 attribution assessment.
The heart of our argument is that the broader scientific and other technical communities (beyond the field of climate science) have higher expectations for understanding and characterizing uncertainty than has been portrayed thus far by the IPCC. We hope that the forthcoming IPCC AR5 will improve its exploration and characterization of uncertainty, with the actual communication of uncertainty to policy makers following from a detailed and transparent assessment of the uncertainties written for a technical audience.
While looking at the other early online papers, I spotted this one:
A weather and climate enterprise strategy for generating and communicating forecast uncertainty information
Paul A. Hirschberg, Elliot Abrams, Andrea Bleistein, William Bua, Luca Delle Monache, Thomas W. Dulong, John E. Gaynor, Bob Glahn, Thomas M. Hamill, James A. Hansen, Douglas C. Hilderbrand, Ross N. Hoffman, Betty Hearn Morrow, Brenda Philips, John Sokich, and Neil Stuart
Abstract. The American Meteorological Society (AMS) Weather and Climate Enterprise Strategic Implementation Plan for Generating and Communicating Forecast Uncertainty (Plan) is summarized. The Plan (available on the AMS Web site at http://bit.ly/gbkcc1) is based on, and intended to provide a foundation for implementing, recent recommendations regarding forecast uncertainty by the National Research Council (NRC), AMS, and World Meteorological Organization. It defines a vision, strategic goals, roles and responsibilities, and an implementation roadmap to guide the weather and climate enterprise (Enterprise) toward routinely providing the nation with comprehensive, skillful, reliable, and useful information about the uncertainty of weather, water, and climate (hydrometeorological) forecasts. Examples are provided describing how hydrometeorological forecast uncertainty information can improve decisions and outcomes in various socioeconomic areas. The implementation roadmap defines objectives and tasks that the four sectors comprising the Enterprise (i.e., government, industry, academia, and nongovernmental organizations) should work on in partnership to meet four key, interrelated strategic goals: (1) Understand social and physical science aspects of forecast uncertainty; (2) Communicate forecast uncertainty information effectively and collaborate with users to assist them in their decision-making; (3) Generate forecast uncertainty data, products, services, and information; and (4) Enable research, development, and operations with necessary information technology and other infrastructure. The Plan endorses the NRC recommendation that the National Oceanic and Atmospheric Administration and in particular, the National Weather Service, should take the lead in motivating and organizing Enterprise resources and expertise in order to reach the Plan’s vision and goals, and shift the nation successfully to a greater understanding and use of forecast uncertainty in decision making.
Link to online paper [here].
JC comments. The reaction to the uncertainty monster paper promises to be interesting. The community on the weather side of the house (reflected by the Hirschberg et al. paper) seems to understand the issues. Such efforts should help tame the weather and seasonal climate uncertainty monster. As for the uncertainty monster surrounding the climate change issue, I can only hope this paper and the forthcoming issue in Climatic Change on framing and communicating uncertainty for the IPCC will help, and pave the way for the IPCC to do a better job of characterizing and assessing uncertainty.