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000171936 1001_ $$0P:(DE-HGF)0$$aShrestha, P.$$b0$$eCorresponding Author
000171936 245__ $$aA Scale-Consistent Terrestrial Systems Modeling Platform Based on COSMO, CLM, and ParFlow
000171936 260__ $$aWashington, DC [u.a.]$$bAMS87486$$c2014
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000171936 520__ $$aA highly modular and scale-consistent Terrestrial Systems Modeling Platform (TerrSysMP) is presented. The modeling platform consists of an atmospheric model (Consortium for Small-Scale Modeling; COSMO), a land surface model (the NCAR Community Land Model, version 3.5; CLM3.5), and a 3D variably saturated groundwater flow model (ParFlow). An external coupler (Ocean Atmosphere Sea Ice Soil, version 3.0; OASIS3) with multiple executable approaches is employed to couple the three independently developed component models, which intrinsically allows for a separation of temporal–spatial modeling scales and the coupling frequencies between the component models.Idealized TerrSysMP simulations are presented, which focus on the interaction of key hydrologic processes, like runoff production (excess rainfall and saturation) at different hydrological modeling scales and the drawdown of the water table through groundwater pumping, with processes in the atmospheric boundary layer. The results show a strong linkage between integrated surface–groundwater dynamics, biogeophysical processes, and boundary layer evolution. The use of the mosaic approach for the hydrological component model (to resolve subgrid-scale topography) impacts simulated runoff production, soil moisture redistribution, and boundary layer evolution, which demonstrates the importance of hydrological modeling scales and thus the advantages of the coupling approach used in this study.Real data simulations were carried out with TerrSysMP over the Rur catchment in Germany. The inclusion of the integrated surface–groundwater flow model results in systematic patterns in the root zone soil moisture, which influence exchange flux distributions and the ensuing atmospheric boundary layer development. In a first comparison to observations, the 3D model compared to the 1D model shows slightly improved predictions of surface fluxes and a strong sensitivity to the initial soil moisture content.
000171936 536__ $$0G:(DE-HGF)POF2-246$$a246 - Modelling and Monitoring Terrestrial Systems: Methods and Technologies (POF2-246)$$cPOF2-246$$fPOF II$$x0
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000171936 7001_ $$0P:(DE-HGF)0$$aSulis, M.$$b1
000171936 7001_ $$0P:(DE-HGF)0$$aMasbou, M.$$b2
000171936 7001_ $$0P:(DE-Juel1)151405$$aKollet, S.$$b3$$ufzj
000171936 7001_ $$0P:(DE-HGF)0$$aSimmer, C.$$b4
000171936 773__ $$0PERI:(DE-600)2033056-X$$a10.1175/MWR-D-14-00029.1$$gVol. 142, no. 9, p. 3466 - 3483$$n9$$p3466 - 3483$$tMonthly weather review$$v142$$x1520-0493$$y2014
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