Impact of field-calibrated vegetation parameters on GCM climate simulations

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Abstract

This paper describes a study in which, for the first time, advanced systems-engineering parameter-estimation techniques were applied to data from several field studies to estimate the preferred set of parameters for some of the most common biomes represented in an advanced Soil-Vegetation-Atmosphere Transfer (SVAT) scheme (BATS2, a recent version of the Biosphere-Atmosphere Transfer Scheme); the effect on modelled climate was also investigated. Observational data from field sites in Brazil, Canada, Arizona and Kansas/Oklahoma in the USA, and the Netherlands were chosen as representative of tropical rain forest, coniferous forest, semi-arid vegetation, agricultural crops, and grassland biomes, respectively. Together, these five biomes make up 50% of the land area represented in BATS2. Multi-criteria calibration algorithms do not produce a unique set of model parameters and, when different combinations of the available objective functions at each site are considered, the number of solutions increases substantially. The need for a single parameter-set for each site (biome) is an important practical issue that was necessarily addressed in this study. A procedure was defined in which optimized parameter-sets were successively discarded by successively applying a cut-off threshold to single observable objective functions following a preference hierarchy. In this study, only the vegetation-related parameters are calibrated for each of the five biomes and implemented into BATS2; however, in a separate experiment, the effect of including soil parameters in the optimization was investigated. When the calibrated parameters are adopted and used in BATS2, there are significant changes between the climates calculated in an eight-year run with Version 3 of the Community Climate Model and in an equivalent eight-year run in which the original default parameters were used. The overall conclusion of this exploratory study is that advanced parameter-estimation techniques and appropriate field data can be used successfully to improve representation of surface exchanges and the modelled climate given by a GCM, by defining appropriate values for vegetation-related parameters in an advanced SVAT scheme.

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