Estimating climatic implications of soy and pasture expansion in Mato Grosso
Julia
Pongratz, University of Maryland, julia.pongratz@gmx.de
Ruth
DeFries, University of Maryland, rdefries@geog.umd.edu
(Presenting)
Lahouari
Bounoua, NASA GSCF, bounoua@dounia.gsfc.nasa.gov
Douglas
Morton, University of Maryland, morton@geog.umd.edu
Liana
Anderson, INPE, liana@ltid.inpe.br
Yosio
Shimabukuro, INPE, yosio@ltid.inpe.br
Estimating the climatic implications of land cover change in the Brazilian Amazon has become a scientific priority, given the extensive transformation of areas of primary vegetation to pasture and agriculture. We simulate the sensitivity of climate parameters to these changes for a region in northern Mato Grosso using the Simple Biosphere Model SiB2 (GSFC/NASA). SiB2 simulates exchange of energy, moisture and momentum between the atmosphere and biosphere. An improved photosynthesis-conductance sub-model enables us to assess the differences in carbon assimilation and water vapor transfer between vegetation and the atmosphere. We address an important large-scale land cover transformation in the Brazilian Amazon by comparing transitions from C4 vegetation such as pasture to C3 soybean fields. To assess the impacts of recent changes in this region, we compare two parallel SiB2 model simulations for land cover classifications from 2000-2001 and 2002-2003. NDVI derived from MODIS data at 250 m resolution is used to calculate FPAR, LAI, and other biophysical parameters, and combined with soil and climate data as model inputs. The prognostic variables of SiB2 are canopy, soil surface, and deep soil temperatures as well as water storage from canopy interception and soil water balance at varying depths. These results provide the basis for our analysis of the impact of land cover change on local climate and hydrology for the two time periods.
Submetido por Douglas Morton em 17-MAR-2004
Tema Científico do LBA: LC (Mudanças dos Usos da Terra e da Vegetação)