An investigation of the sensitivity of a land surface model to climate change using a reduced form model |
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Authors: | A. H. Lynch S. McIlwaine J. Beringer G. B. Bonan |
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Affiliation: | (1) PAOS/CIRES, CB 216, University of Colorado, Boulder, CO 80309-0216, USA E-mail: manda@cires.colorado.edu, US;(2) Institute of Arctic Biology, University of Alaska Fairbanks, Alaska, AK 99775, USA, US;(3) National Center for Atmospheric Research, PO Box 3000, Boulder, CO 80307, USA, US |
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Abstract: | In an illustration of a model evaluation methodology, a multivariate reduced form model is developed to evaluate the sensitivity of a land surface model to changes in atmospheric forcing. The reduced form model is constructed in terms of a set of ten integrative response metrics, including the timing of spring snow melt, sensible and latent heat fluxes in summer, and soil temperature. The responses are evaluated as a function of a selected set of six atmospheric forcing perturbations which are varied simultaneously, and hence each may be thought of as a six-dimensional response surface. The sensitivities of the land surface model are interdependent and in some cases illustrate a physically plausible feedback process. The important predictors of land surface response in a changing climate are the atmospheric temperature and downwelling longwave radiation. Scenarios characterized by warming and drying produce a large relative response compared to warm, moist scenarios. The insensitivity of the model to increases in precipitation and atmospheric humidity is expected to change in applications to coupled models, since these parameters are also strongly implicated, through the representation of clouds, in the simulation of both longwave and shortwave radiation. Received: 27 March 2000 / Accepted: 11 September 2000 |
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