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Using MODIS Data to Characterize Climate Model Land Surface Processes and the Impacts of Land Use/Cover Change on Surface Hydrological Processes
Project Start Date
01/01/2004
Project End Date
01/01/2007
Project Call Name
Regional_Initiative_Name
Region
Solicitation

Team Members:

Person Name Person role on project Affiliation
Robert Dickinson Principal Investigator Georgia Institute of Technology, Atlanta, United States
Abstract
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MODIS in principle, is producing all the pieces needed by climate models to generate their albedo and emissivityfrom the same radiation, but some of the pieces may be inconsistent (differences in algorithms). Climate models wish to return the same radiation using these pieces, but their radiation formulation is inconsistent with that used by any of the MODIS algorithms.Climate models: two-stream radiation schemeAccurate for horizontally homogeneous canopies but large errors for semiarid and snow-covered vegetated surfaces.climate model view of vegetationwhat it looks like for semi-arid system. An optimal connection between models and observations: reformulating climate model processes so that they are consistent with MODIS observations. Establishing a new radiation model in such way that it is able to reproduce the observed spectralalbedos. Most directly related to MODIS observed reflectances most directly related to other model parameters key constraint on energy balance. Rapid urbanization in China -a good case study to quantify the urbanization effect on climate. KalnayandCai(2003) estimated the impact of urbanization and other land use changes on climate by comparing trends in observed and reanalysis surface temperatures –the latter is insensitive to changes in land surface. We adopted the same method but paid more attention to its problems and deficiencies: using an improved new reanalysis dataset (Kanamitsuet al., 2001) and focusing only on southeast Chinawinter to ensure the best quality in both observational and reanalysis data.

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