Statistical identification of global hot spots in soil moisture feedbacks among IPCC AR4 models

Soil moisture feedbacks can regulate climate change and offer the potential for seasonal climate predictability, yet their strengths and regional importance are poorly understood. A statistical analysis of soil moisture feedbacks on boreal and austral summer precipitation is performed using output from 19 climate models in the Intergovernmental Panel on Climate Change's Fourth Assessment Report. The methodology, using lagged covariance ratios, was previously applied to study ocean-atmosphere and vegetation-atmosphere interactions. Reflecting ensemble-based findings from the Global Land-Atmosphere Coupling Experiment (GLACE) for boreal summer, positive soil moisture feedback hot spots are identified over central United States, North Africa, India, northern Brazil, and western Eurasia. Hot spots for austral summer include the Amazon, Congo, Australia, Indonesia, Mexico, and southwest United States. This statistical approach focuses on appropriate spatial and temporal scales of interaction, quantifies local feedbacks with significance testing, and expedites a reliable model intercomparison of feedbacks, without producing additional dynamical experiments.