Leaf area index (LAI) is a key driver of forest productivity and evapotranspiration; however, it is a difficult and labor-intensive variable to measure, making its measurement impractical for large-scale and long-term studies of tropical forest structure and function. In contrast, satellite estimates of LAI have shown promise for large-scale and long-term studies, but their performance has been equivocal and the biases are not well known. We measured total, overstory, and understory LAI of an Amazon-savanna transitional forest (ASTF) over 3 years and a seasonal flooded forest (SFF) during 4 years using a light extinction method and two remote sensing methods (LAI MODIS product and the Landsat-METRIC method), with the objectives of (1) evaluating the performance of the remote sensing methods, and (2) understanding how total, overstory and understory LAI interact with micrometeorological variables. Total, overstory and understory LAI differed between both sites, with ASTF having higher LAI values than SFF, but neither site exhibited year-to-year variation in LAI despite large differences in meteorological variables. LAI values at the two sites have different patterns of correlation with micrometeorological variables. ASTF exhibited smaller seasonal variations in LAI than SFF. In contrast, SFF exhibited small changes in total LAI; however, dry season declines in overstory LAI were counteracted by understory increases in LAI. MODIS LAI correlated weakly to total LAI for SFF but not for ASTF, while METRIC LAI had no correlation to total LAI. However, MODIS LAI correlated strongly with overstory LAI for both sites, but had no correlation with understory LAI. Furthermore, LAI estimates based on canopy light extinction were correlated positively with seasonal variations in rainfall and soil water content and negatively with vapor pressure deficit and solar radiation; however, in some cases satellite-derived estimates of LAI exhibited no correlation with climate variables (METRIC LAI or MODIS LAI for ASTF). These data indicate that the satellite-derived estimates of LAI are insensitive to the understory variations in LAI that occur in many seasonal tropical forests and the micrometeorological variables that control seasonal variations in leaf phenology. While more ground-based measurements are needed to adequately quantify the performance of these satellite-based LAI products, our data indicate that their output must be interpreted with caution in seasonal tropical forests.

The direct estimation of the soil heat flux (G) by remote sensing data is not possible. For this, several models have been proposed empirically from the relation of G measures and biophysical parameters of various types of coverage or not vegetated in different places on earth. Thus, the objective of this study was to evaluate the relation between G/Rn ratio and biophysical variables obtained by satellite sensors and evaluate the parameterization of different models to estimate G spatially in three sites with different soil cover types. The net radiation (Rn) and G were measured directly in two pastures at Miranda Farm and Experimental Farm and and Monodominant Forest of Cambará. Rn, G, and G/Rn ratio and MODIS products, such as albedo (α), surface temperature (LST), vegetation index (NDVI) and leaf area index (LAI) varied seasonally at all sites and inter-sites. The sites were different from each other by presenting different relation between measures of Rn, G and G/Rn ratio and biophysical parameters. Among the original models, the model proposed by Bastiaanssen (1995) showed the best performance with r = 0.76, d = 0.95, MAE = 5.70 W m -2 and RMSE = 33.68 W m -2 . As the reparameterized models, correlation coefficients had no significant change, but the coefficient Willmott (d) increased and the MAE and RMSE had a small decrease. Keywords: Mato Grosso, pasture, monodominant forest, orbital sensors. RESUMO: PARAMETRIZAÇÃO DE MODELOS PARA ESTIMAR O FLUXO DE CALOR NO SOLO EM TRÊS REGIÕES DO PANTANAL DO MATO GROSSO USANDO SENSORIAMENTO REMOTOA estimativa do fluxo de calor no solo (G) diretamente por dados de sensores remotos não é possível. Para isso, diversos modelos foram proposto relacionando empiricamente medidas de G e parâmetros biofísicos de diversos tipos de cobertura vegetada, ou não, em diferentes locais do planeta. Sendo assim, o objetivo deste trabalho foi avaliar a relação entre G/Rn e variáveis biofísicas obtidas por sensores orbitais e avaliar a parametrização de diferentes modelos de estimativa de G espacialmente em três sítios experimentais com distintos tipos coberturas do solo. O saldo de radiação (Rn) e G foram medidos diretamente em duas áreas de pastagens na Fazenda Miranda e na Fazenda Experimental e em uma Floresta Monodominante de Cambará. Rn, G, razão G/Rn e os produtos MODIS, tais como albedo (α), temperatura da superfície (LST), índice de vegetação da diferença normalizada (NDVI) e índice de área foliar (LAI) variaram sazonalmente em todos os sítios experimentais e entre os sítios experimentais. Os sítios experimentais mostraram-se diferentes entre si por apresentar distintas relações entre as medidas de Rn, G e a razão G/Rn e os

Resumo A substituição de florestas naturais para o cultivo de monoculturas pode provocar alterações no clima local e regional devido às mudanças nas trocas líquidas de radiação

ABSTRACT. Cuiabá is located on the border of the Pantanal and Cerrado, in Mato Grosso State, which is recognized as one of the biggest agricultural producers of Brazil. The use of natural resources in a sustainable manner requires knowledge of the regional meteorological variables. Thus, the objective of this study was to RESUMO. Cuiabá está localizado na fronteira do Pantanal com o Cerrado, no Mato Grosso, queé reconhecido como um dos maiores produtores agrícolas do Brasil.A utilização dos recursos naturais de forma sustentável requer o conhecimento das variáveis meteorológicas em escala regional. Assim, o objetivo deste estudo foi caracterizar o padrão sazonal e interanual das variáveis meteorológicas em Cuiabá. Os dados meteorológicos de 1961 a 2011 foram fornecidos pelo Instituto Nacional de Meteorologia (INMET). Os resultados mostraram variações interanuais e sazonais de precipitação, radiação solar, temperatura e umidade relativa do ar e velocidade e direção do vento, estabelecendo duas principais estações distintas (chuvosa e seca). Em média, 89% da precipitação ocorreu na estação chuvosa. Os valores médios anuais de radiação diária global, temperatura do ar média, mínima e máxima e umidade relativa do ar foram 15,6 MJ m -2 y -1 , 27,9 • C, 23,0 • C, 30,0 • C e 71,6%, respectivamente. A temperatura máxima e a velocidade do vento não tiveram padrão sazonal. A velocidade média do vento diminuiu na direção NW e aumentou na direção S.Palavras-chave: variáveis meteorológicas, climatologia, ENOS.

Rainfall is the key element in regional water balance, and have direct influence over economic activity. In this study, we evaluate the estimates of precipitation by TRMM satellite (Tropical Rainfall Measuring Mission) on the Midwest region of Brazil. The rainfall measured by TRMM satellite was compared with rainfall series obtained by the Office of Instituto de Controle de Espaço Aéreo (ICEA) of Comando da Força Aérea. The TRMM satellite overestimated annual rainfall between 0.6 and 37.4%, with greater overestimation in the dry season. However, the rainfall estimate by TRMM satellite had a high correlation (0.88) with the rainfall series and had high Willmott coefficient. The Northern of Brazilian Midwest had the highest annual accumulated rainfall and the Southwest and Northeast of Midwest had the lowest annual accumulated rainfall. There was a inverse seasonal pattern of accumulated rainfall, with higher values in the Northern of Midwest during the rainy season in the Southwest and Northeast during the dry season.

The gross primary production (GPP) of ecosystems is an important variable in the study of global climate change. Generally, the GPP has been estimated by micrometeorological techniques. However, these techniques have a high cost of implantation and maintenance, making the use of orbital sensor data an option to be evaluated. Thus, the objective of this study was to evaluate the potential of the MODIS (Moderate Resolution Imaging Spectroradiometer) MOD17A2 product and the vegetation photosynthesis model (VPM) to predict the GPP of the Amazon-Cerrado transitional forest. The GPP predicted by MOD17A2 (GPP MODIS) and VPM (GPP VPM) were validated with the GPP estimated by eddy covariance (GPP EC). The GPP MODIS, GPP VPM and GPP EC have similar seasonality, with higher values in the wet season and lower in the dry season. However, the VPM performed was better than the MOD17A2 to estimate the GPP, due to use local climatic data for predict the light use efficiency, while the MOD17A2 use a global circulation model and the lookup table of each vegetation type to estimate the light use efficiency.

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