Schlosser We hypothesize that interactions between the land and atmosphere may be a considerable source of land surface memory, and that this memory poses an element of coupled land-atmosphere predictability in the climate system that can advance water-cycle prediction. However, accuracy of simulated land memory must be assessed, strength of land-atmosphere water recycling must be identified, and systematic errors in global prediction systems need to be corrected in order for climate models to faithfully harvest any degree of land-atmosphere predictability and advance global water-cycle prediction. An integrated and collaborative effort is proposed. Investigations into land surface memory include analysis of land-model simulations driven by observed meteorology (in conjunction with the Global Soil Wetness Project Phase 2) and available in situ observations to produce a global picture of soil moisture persistence; forward and backward water vapor trajectory analysis to quantify the extent of land-atmosphere water recycling across the globe; and contemporaneous and lagged correlations between the two analyses above to determine if indeed strong recycling is the cause of persistent soil moisture anomalies. Climate model sensitivity studies will verify the role of high-memory regions in the global water cycle suggested by the above analyses. Recent research indicates that removal of systematic errors in climate models improves their sensitivity to land surface anomalies, and improves predictive skill. We will also pursue development of an empirical correction of land and atmospheric errors in a global prediction system to improve the numerical simulation and seasonal-to-interannual prediction of the land-atmosphere branch of the global water cycle, with the ultimate aim of application of empirical correction to further improve climate prediction capability.
Adjustments to work plan: At the request of NSF, the original budget has been revised to reflect a 30% reduction. This had been achieved by roughly equal percentage cuts among the three collaborating institutions. Details of the changes that affect the original work plan are listed below. * The post-doc level of effort has been reduced to 6 months during year one, anticipating a later start date for the post-doc. * Levels of effort for the PIs have been reduced, meaning a slower rate of progress than originally proposed. * The work plan as been adjusted (below), shifting more work to later in the project and moving the final elements of the originally proposed work to a follow-on for which we will seek support from a future program solicitation. This shift will primarily delay the final synthesis between characterization of land memory and predictability, identification regions of strong land-atmosphere water recycling, and advancement of water-cycle prediction through these identifications of land memory and empirical correction of systematic errors in climate models. Characterizing Land Surface Memory to Advance Climate Prediction Dirmeyer & DelSole (COLA), Brubaker (UMCP), and Schlosser (UMBC/GEST).
