Consistency in Global Climate Change Model Predictions of Regional Precipitation Trends

Abstract

Abstract Projections of human-induced climate change impacts arising from the emission of atmospheric chemical constituents such as carbon dioxide typically utilize multiple integrations (or ensembles) of numerous numerical climate change models to arrive at multimodel ensembles from which mean and median values and probabilities can be inferred about the response of various components of the observed climate system. Some responses are considered reliable in as much as the simulated responses show consistency within ensembles and across models. Other responses—particularly at regional levels and for certain parameters such as precipitation—show little intermodel consistency even in the sign of the projected climate changes. The authors’ results show that in these regions the consistency in the sign of projected precipitation variations is greater for intramodel runs (e.g., runs from the same model) than intermodel runs (e.g., runs from different models), indicating that knowledge of the internal “dynamics” of the climate system can provide additional skill in making projections of climate change. Given the consistency provided by the governing dynamics of the model, the authors test whether persistence from an individual model trajectory serves as a good predictor for its own behavior by the end of the twenty-first century. Results indicate that, in certain regions where intermodel consistency is low, the short-term trends of individual model trajectories do provide additional skill in making projections of long-term climate change. The climate forcing for which this forecast skill becomes relatively large (e.g., correct in 75% of the individual model runs) is equivalent to the anthropogenic climate forcing imposed over the past century, suggesting that observed changes in precipitation in these regions can provide guidance about the direction of future precipitation changes over the course of the next century.