The proposed research is based on the hypothesis that the predictability of persistent large-scale drought is due the competition among three processes:
(i) The nature of local coupled atmosphere-land feedbacks (i.e., strength, growth rate, saturation)
(ii) The predictability limiting affects of atmospheric noise or stochastic forcing
(iii) The remote forcing from low frequency global SST variability (e.g., AMO, PDO, NPO…).
We propose to test this hypothesis through a series of modeling experiments that isolate the relative importance of coupled atmosphere-land feedbacks vs. atmospheric stochastic forcing vs. remote SST forcing. These experiments include using the novel interactive ensemble coupling strategy (Kirtman and Shukla 2002) previously used to isolate coupled ocean-atmosphere feedbacks vs. atmospheric stochastic forcing, extended to the problem of atmosphere-land interactions. Part of our modeling strategy builds on the success of the US Clivar drought WG (http://www.usclivar.org/Organization/drought-wg.html) and the international Global Land-Atmosphere Coupling Experiment (GLACE) by explicitly leveraging their experimental protocol. We have chosen to focus on the question of North American drought because of its societal importance to US interests; however, the approach is equally applicable to terrestrial hydro-climate predictability on multiple space and time scales throughout the globe.