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Evaluation of South American LDAS atmospheric forcing datasets for use in regional land surface modeling over the LBA region

Luis G G de Goncalves, NASA/ESSIC-UMD, gustavo@hsb.gsfc.nasa.gov (Presenting)
W. James Shuttleworth, University of Arizona, shuttle@hwr.arizona.edu
Rafael Rosolem, University of Arizona, rafael@hwr.arizona.edu
David Toll, NASA, David.L.Toll@nasa.gov
Dirceu Herdies, CPTEC/INPE, dirceu@cptec.inpe.br
Ian Baker, Colorado State, baker@atmos.colostate.edu

Significant advances have been made in the past few years by the LBA project on towards understanding how the water, energy and carbon cycles function in the Amazon. However, most of these studies have been limited to results from point measurements from strategically located sites in the tropical forest and other LBA-related areas. As the LBA project progresses into its synthesis phase, there is increased interest in using the acquired knowledge to better understand how Amazonia works as a regional entity. The South American Land Data Assimilation System (SALDAS) initiative, which involves NASA/GSFC, CPTEC/INPE and University of Arizona, provides the capability to integrate results within the robust land surface modeling and data assimilation infrastructure that has already been developed at NASA/GSFC and used for regional studies over the LBA region. This study investigates the feasibility of using the SALDAS atmospheric forcing datasets (a 5 years combination of CPTEC reanalysis and surface observations) for land surface modeling over the Amazonia by comparing thse forcing data with seven LBA flux towers observations. The discussion of the results focuses on whether the ranges shown in the evaluation (e.g. standard deviation, bias) are within acceptable ranges for land surface modeling over the region. The results of applying this forcing datasets to force the Noah and SiB3 land surface models over the LBA region are also discussed, with emphasis on the integrated water, energy and carbon budgets.

Science Theme:  HY (Hydrometeorology)

Session:  1C: Regional Hydrometeorology

Presentation Type:  Oral (view presentation (8330 KB))

Abstract ID: 77

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