NEWS linkages: (pull, push, collaborate, external) Project Title: Integration of Energy and Water Cycle Research Products in a Global Land Surface Modeling and Assimilation System PI: Matt Rodell Science issue: A physically consistent and realistic representation of terrestrial hydrospheric processes is required in order to understand and predict variability in the global energy and water cycles. Approach: Integrate the best observation based hydrometeorological products as data for forcing, constraining, and evaluating sophisticated LSMs using advanced modeling and assimilation techniques. Satellite based data: GPCP & CMAP precip; AVHRR & MODIS veg and snow; AGRMET (GOES & DMSP) radiation Other data: CEOP; ECMWF & NOAA analyses; USDA soils Models: Land Information System (LIS) driving the Noah, CLM2, Mosaic, and VIC land surface models Study particulars: Global land 60S-90N, 0.25 and 1.0 degree resolutions; 1948-present, 3-hourly. Generically referred to as “GLDAS output”. Project status: Year 1 & 2 complete – Completed ten simulations with various configurations (model, resolution, forcing, data assimilation) and made several available through NASA/GSFC’s DISC website and the NEWS portal. Implemented improved MODIS snow cover assimilation algorithm. Implemented crop type database and irrigation algorithm in LIS/Noah. Published results of model sensitivity study using CEOP data. Compared evapotranspiration from various GLDAS simulations with other sources. Year 3 (now) – Writing manuscripts on new MODIS snow cover assimilation and irrigation algorithms. Installed and now running post-process source to sink runoff routing scheme. Year 4 & 5 – Install additional assimilation capabilities and incorporate any new datasets; test multivariate data assimilation. Develop global climatologies of terrestrial water and energy cycle states and fluxes, compare with those from other sources. NEWS linkages: (pull, push, collaborate, external) -Adler: Use TRMM based precip products in LIS and provide feedback. -Betts: GLDAS output provide a point of comparison or basis for various Betts-ian analyses. -Denning/Stockli: This is a new linkage; we hope to make use of developments by this group, including new dynamic vegetation algorithm. -Famiglietti: GLDAS output and GRACE data have been intercompared extensively, including many external studies. -Koster: Ongoing forecast initialization study. -Peters-Lidard: The LIS infrastructure is common to both projects, and developments by either group benefits both groups. -Reichle: Development and installation of state-of-the art data assimilation techniques in LIS. -Roads: The GLDAS archive has been a major data source for Roads’ water and energy budget studies. Others: Bosilovich, Sorooshian, Soden, Schlosser, Lin, Schubert Figure 1: A MODIS-based map of irrigation intensity was used to simulate irrigation of crops within LIS/Noah. The figure depicts differences (%) in evapotranspiration between irrigation and control runs during Aug-Sep 2003. The new results compared favorably with in situ data. C. Peters-Lidard, Updated: October 31, 2007