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Bio
Clemens Simmer is an expert in coupled modelling of the regional Earth system, model evaluation, data assimilation, satellite and ground-based remote sensing, and regional climate analysis. He chairs of the transregional collaborative research center TR32 (www.tr32.de) on “Patterns in soil-vegetation-atmosphere systems” which developed and maintains TerrSysMP, the distributed research unit FOR2131 (www.for2131.de) on “Data Assimilation for Improved Characterization of Fluxes across Compartmental Interfaces”, which applies TerrSysMP for data assimilation in fully coupled terrestrial systems (both funded by the German national science foundation, DFG), and the distributed research unit S4 on landsurface heterogeneity (www.hdcp2.eu/index.php?id=3722) funded by the German federal ministry of education and research (BMBF) within its research program “Clouds and Precipitation in de Climate System” HD(CP)2. He is member of the of the Center for High-Performance Computing of Terrestrial Systems HPSC TerrSys (www.hpsc-terrsys.de), which helps geoscientists of the Geoverbund ABC/J (alliance of the geosciences within the universities RWTH Aachen, Bonn and Cologne and the Forschungszentrum Jülich) to efficiently use the JSC supercomputers for geoscientific modelling. In the field of ground-based remote sensing, he concentrates on microwave-based active and passive methods with a current focus on precipitation and cloud processes in cooperation with the Jülich Observatory for Cloud Cartography - Core Facility (JOYCE-CF). His efforts in regional climate analysis concentrated in the past on the evaluationof extremes and trends from German and European precipitation observation stations and moved recently to dynamic downscaling of global climate runs.
Research Interests
Papers共 458 篇Author StatisticsCo-AuthorSimilar Experts
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ATMOSPHERIC CHEMISTRY AND PHYSICSno. 22 (2023): 14219-14237
Cold Regions Science and Technology (2023): 103674-103674
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. (2023): 4039-4049
QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETYno. 742 (2022): 141-158
semanticscholar(2022)
Journal of Remote Sensing (2022): 1-19
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