SOIL-VEGETATION-ATMOSPHERE PROCESSES - SIMULATION AND FIELD MEASUREMENT FOR DEFORESTED SITES IN NORTHERN THAILAND

In recent efforts to predict the climatic impacts of tropical deforest ation an extreme scenario of impoverished grassland has been used to r epresent the future deforested landscape. Currently, deforested areas of the tropics are composed of a mosaic of crops, bare soil, grassland , and secondary vegetation of various ages. The dominant feature of de forested land is often secondary vegetation. Parameter values for impo rtant forest replacement land covers, including secondary vegetation, have been shown to differ from those of forest much less than that ass umed in general circulation model (GCM) deforestation experiments. For this study, the biosphere-atmosphere transfer scheme (BATS) is run in uncoupled mode using measured input data in place of GCM forcing and using the same parameter settings employed in recent deforestation exp eriments. Model output is compared with measurements taken over seven different deforested land surfaces in northern Thailand. Comparisons r eveal that the simulation of deforested land overestimates reflected s hortwave radiation, the diurnal range of surface temperature for secon dary vegetation, surface soil moisture loss during periods without rai n, and surface soil moisture increase at the start of a rainy period a nd underestimates net radiation, the diurnal range of surface temperat ure on recently used land surfaces, and root zone soil moisture increa se at the start of a rainy period at most sites. Most deforested land surfaces, especially intermediate and advanced secondary vegetation, a re more similar, in terms of land surface-atmosphere interaction, to t he model simulation of forest than of deforested land as depicted in G CM experiments. These comparisons suggest that modelers aspiring to ma ke realistic simulations of deforestation should adopt parameter setti ngs representative of the diverse range of forest replacement land cov ers, instead of again using the grassland scenario.