ALBERT

Description: The USCLIVAR working group on drought recently initiated a series of global climate model simulations forced with idealized SST anomaly patterns, designed to address a number of uncertainties regarding the impact of SST forcing and the role of land-atmosphere feedbacks on regional drought. Specific questions that the runs are designed to address include, What are the mechanisms that maintain drought across the seasonal cycle and from one year to the next? What is the role of the leading patterns of SST variability, and what are the physical mechanisms linking the remote SST forcing to regional drought, including the role of land-atmosphere coupling? The runs were carried out with five different atmospheric general circulation models (AGCMs), and one coupled atmosphere-ocean model in which the model was continuously nudged to the imposed SST forcing. This talk provides an overview of the experiments and some initial results focusing on the responses to the leading patterns of annual mean SST variability consisting of a Pacific El Nino/Southern Oscillation (ENSO)-like pattern, a pattern that resembles the Atlantic Multi-decadal Oscillation (AMO), and a global trend pattern. One of the key findings is that all the AGCMs produce broadly similar (though different in detail) precipitation responses to the Pacific forcing pattern, with a cold Pacific leading to reduced precipitation and a warm Pacific leading to enhanced precipitation over most of the United States. While the response to the Atlantic pattern is less robust, there is general agreement among the models that the largest precipitation response over the U.S. tends to occur when the two oceans have anomalies of opposite sign. That is, a cold Pacific and warm Atlantic tend to produce the largest precipitation reductions, whereas a warm Pacific and cold Atlantic tend to produce the greatest precipitation enhancements. Further analysis of the response over the U.S. to the Pacific forcing highlights a number of noteworthy and to some extent unexpected results. These include a seasonal dependence of the precipitation response that is characterized by signal-to-noise ratios that peak in spring, and surface temperature signal-to-noise ratios that are both lower and show less agreement among the models than those found for the precipitation response. Another interesting result concerns what appears to be a substantially different character in the surface temperature response over the U.S. to the Pacific forcing by the only model examined here that was developed for use in numerical weather prediction. The response to the positive SST trend forcing pattern is an overall surface warming over the world's land areas with substantial regional variations that are in part reproduced in runs forced with a globally uniform SST trend forcing. The precipitation response to the trend forcing is weak in all the models. It is hoped that these early results will serve to stimulate further analysis of these simulations, as well as suggest new research on the physical mechanisms contributing to hydroclimatic variability and change throughout the world.