1. 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 The new results compared favorably with in situ data.
C. Peters-Lidard, Updated: October 31, 2007