This is one of 16 Rapid Response (RAPID) projects funded as the result of a Dear Colleague Letter (NSF 11-006) encouraging diagnostic analyses of climate model simulations prepared for the Intergovernmental Panel on Climate Change Fifth Assessment Report (IPCC AR5). Research conducted in these projects is expected to lead to more detailed model intercomparisons, better understanding of robust model behaviors, and better understanding and quantification of uncertainty in future climate simulations.

This project considers the extent to which model simulations prepared for AR5 are capable of reproducing the low-frequency hydroclimate variability found in the instrumented and paleo-proxy records. The earlier generation of models used in the IPCC Fourth Assessment Report (AR4) was found to be deficient in capturing low-frequency hydroclimate variability, and this deficiency could mean that future projections from the models underestimate the risk of prolonged drought in regions including the US southwest. Research conducted here seeks to determine if the current generation of models produces more realistic low-frequency hydroclimate variance. In addition, methods are developed to rescale drought projections from the models to produce observationally corrected estimates of future drought risk.

The broader impact of the project lies in its support of the IPCC AR5, which is intended to provide information on climate change and its consequences to decision makers worldwide. Hydroclimate variability and change are of great societal interest given their large impacts on people, agriculture, and ecosystems. This is particularly true in southwestern North America, a focus region for the research.

Project Report

How well do climate models simulate persistent drought? Droughts lasting a decade or more are a well-known feature of past climate in many parts of the world. This project builds on a body of work that has suggested persistent droughts (lasting 1 or more decades) occur naturally in many regions, whereas older versions of climate models tend to produce shorter droughts almost exclusively. Our analysis looks at the latest generation of climate models (collectively termed the CMIP-5 models) and compares the long-term variability with the short-term. We have found that the long-term variations are generally too weak in the models, relative to short-term variations. This is a consequence of different problems in different regions. In some regions, long-term variance is lacking, whereas in others, the short-term variance is simply too strong and washes out the longer-term variability. Our results suggest climate models will probably underestimate the risk of future prolonged drought, because they have insufficient long-term intrinsic variability. While we await model improvements, we have begun to develop ways to compensate for this shortcoming. By using instrumental and paleoclimate data to estimate the degree of long-term variability, we can add this as "statistical noise" to a model projection of rainfall and then examine the consequences for drought duration. We have limited our results to specific regions with the best observational data. In the southwestern US, for example, the data support the occurrence of substantial long-term variations in drought. State-of-the-art climate model projections suggest the region’s risk of a decade-scale megadrought in the coming century is less than 50%; our analysis (using a statistical noise model that mimics the data) suggests that the risk is at least 80%, and may be higher than 90% in certain areas. The likelihood of longer-lived events (>35 years) is between 20% and 50%, and the risk of an unprecedented 50-year megadrought is non-negligible under the most severe warming scenario (5-10%). Such a multidecadal megadrought – worse than almost anything seen during the last 2000 years – would pose unprecedented challenges to water resources in this rapidly growing region. Our analysis is probably a best-case scenario, because we only looked at rainfall changes. Warmer temperatures will almost certainly make droughts worse (stronger and longer). This grant supported the career development of a recent PhD graduate and assisted in the training of current graduate students in the diagnosis and analysis of climate model output.

Agency
National Science Foundation (NSF)
Institute
Division of Atmospheric and Geospace Sciences (AGS)
Type
Standard Grant (Standard)
Application #
1127331
Program Officer
Eric T. DeWeaver
Project Start
Project End
Budget Start
2011-05-01
Budget End
2013-04-30
Support Year
Fiscal Year
2011
Total Cost
$29,999
Indirect Cost
Name
University of Arizona
Department
Type
DUNS #
City
Tucson
State
AZ
Country
United States
Zip Code
85721