A multi-criteria evaluation of land-surface models and application to semi-arid regions

Abstract

Soil-Vegetation-Atmosphere-Transfer Schemes (SVATS) are used in global climate studies to simulate and help understand the complex interactions between the climate and the biosphere. There currently exists a multitude of SVATS of varying complexity differing in terms of the modeled physics and the manner and sophistication with which the processes are represented. This analysis uses systems-based multi-criteria techniques to investigate the performance and sensitivity of various SVATS and their parameters. Results indicate that, once complexity reaches a certain level, incorporating more physics does not necessarily result in improved simulations or reduced errors and that several parameters in the models are insensitive regardless of the input data (i.e., vegetation type). To better understand SVATS performance in semi-arid regions, and to evaluate the various impacts of data on the parameter estimation problem, an intensive calibration and validation study is undertaken. Findings show that calibrated parameters result in improved performance over default, proxy site parameters result in similar performance for many time periods, and there is a need to include wet periods with elevated latent heat to capture the variability of climatic conditions such as the monsoon and El Nino winters. Last, a preliminarily investigation of the performance of the BATS2 model is undertaken to evaluate the capabilities to simulate carbon (along with energy and water) fluxes in semi-arid regions. Results show poor performance for carbon flux simulations and that improvements are needed to better represent C4 vegetation for semi-acid regions. Future research will be directed toward integrated modeling (carbon, energy, and water) in semi-arid regions.