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Cited by 270

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A catchment‐based approach to modeling land surface processes in a general circulation model: 2. Parameter estimation and model demonstration

Open access
Ducharne, Agnès, Koster, Randal D., Suarez, Max J., Stieglitz, Marc, Kumar, Praveen·2000·Journal of Geophysical Research: Atmospheres

Abstract

The viability of a new catchment‐based land surface model (LSM) developed for use with general circulation models is demonstrated. First, simple empirical functions, tractable enough for operational use in the LSM, are established that faithfully capture the control of topography on the subgrid variability of soil moisture and the surface water budget, as predicted by theory. Next, the full LSM is evaluated off‐line. Using forcing and validation data sets developed for the Project for Intercomparison of Land‐Surface Parameterization Schemes Phase 2c, the minimally calibrated model is shown to reproduce observed evaporation and runoff fluxes successfully in the Red‐Arkansas River Basin. A complementary idealized study that employs the range of topographic variability seen over North America demonstrates that the simulated surface water budget does vary strongly with topography, which can, by itself, induce variations in annual runoff as high as 20%.

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Crossref · 10.1029/2000jd900328

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Metadata

Authors
Ducharne, A., Koster, R. D., Suarez, M. J., Stieglitz, M., & Kumar, P.
Venue
Journal of Geophysical Research: Atmospheres
Published
2000-10
Volume
105
Issue
D20
Pages
24823-24838
ISSN
0148-0227 (ISSN-L)
OpenAlex
W2165632940
Cited by
270
References
1
FWCI
23.34
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: A catchment‐based approach to modeling land surface processes in a general circulation model: 2. Parameter estimation and model demonstration. https://app.cochat.ai/papers/10.1029/2000jd900328
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Ducharne, A., Koster, R. D., Suarez, M. J., Stieglitz, M., & Kumar, P. (2000). A catchment‐based approach to modeling land surface processes in a general circulation model: 2. Parameter estimation and model demonstration. Journal of Geophysical Research: Atmospheres. https://doi.org/10.1029/2000jd900328

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.