23
Radiation Balance at the Surface in the Brazilian Amazon Using MODIS/Terra Remote Sensing Data

- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner
Monday, 3 February 2014
Hall C3 (The Georgia World Congress Center )
Gabriel de Oliveira, INPE, São José dos Campos, SP, Brazil; and E. C. Moraes, Y. E. Shimabukuro, R. C. D. S. Alvalá, and T. V. D. Santos

The Amazon region has been focus of attention due to the effects that large-scale deforestation can cause on local, regional and global climate. Several field experiments have been conducted in this region to obtain information related to energy exchange between land surface and atmosphere. However, these experiments are concentrated in a few test sites due to the high cost involved to obtain the required information. The present study aimed to estimate the radiation balance components at the surface in the south-western part of the Brazilian Amazon using data acquired by Moderate Resolution Imaging Spectroradiometer (MODIS) sensor, onboard the Terra satellite, through the Surface Energy Balance Algorithms for Land (SEBAL) model. The validation of the results was done with information acquired by the micrometeorological towers of Large-Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) under the conditions of pasture (Fazenda Nossa Senhora Aparecida site) and primary tropical forest (Reserva Biológica do Jaru site). The SEBAL model was applied directly on the MODIS/Terra data including the computation of vegetation indices, albedo and atmospheric transmittance processing steps. Comparison between estimates obtained by the proposed method and the observations from the towers showed relative errors between 0.2 and 19.2% for the condition of pasture, and between 0.8 and 15.6% for the condition of primary tropical forest. The integration of data at different scales was a useful proposition for the estimation and spatialization of the radiation fluxes in the Amazon region, which may contribute to a better understanding of the interaction between Amazon rainforest and atmosphere, and generate input information needed to the surface models coupled to atmospheric general circulation models.