Improving the parameterization of land-surface interactions in GCMs using field data

Abstract

General Circulation Models are important tools in the study of the earth's climate system. The terrestrial surface forms the lower boundary to such models over continents and a well-defined lower boundary is crucial for reliable climate simulations because the Earth interacts with the atmosphere via this boundary. The primary motivation for this research is to improve the parameterization of these interactions in General Circulation Models using field data and calibration techniques. For this purpose, a recent version of Biosphere-Atmosphere Transfer Scheme was selected, studied, and then calibrated for five different vegetation types using multi-criteria calibration techniques. The associated parameter sets were then tested in a ten-year climate integration with Version 3 of the Community Climate Model. The present study explored the methodology needed to use the growing number of relevant field data sets effectively and efficiently better to parameterize the land surface in a GCM. It showed that such field data can, indeed, be used in this way, not only to improve simulations but also to understand models' capabilities and deficiencies. Calibrating the land surface parameterization significantly improved simulations relative to the original default parameterization but several physically based land surface models studied, once calibrated, were found to give equally good simulations of the land surface processes. The primary results are that it is possible to obtain a single preferred parameter sets for different vegetation types using multi-criteria calibration, and that using calibrated parameter sets in climate models can improve the representation of surface exchanges and the modeled climate given by a GCM.