The analysis of gross primary production (GPP) is crucial to better understand CO₂ exchanges between terrestrial ecosystems and the atmosphere, while the quantification of water-use efficiency (WUE) allows for the estimation of the compensation between carbon gained and water lost by the ecosystem. Understanding these dynamics is essential to better comprehend the responses of environments to ongoing climatic changes. The objective of the present study was to analyze, through AMERIFLUX and LBA network measurements, the variability of GPP and WUE in four distinct tropical biomes in Brazil: Pantanal, Amazonia, Caatinga and Cerrado (savanna). Furthermore, data measured by eddy covariance systems were used to assess remotely sensed GPP products (MOD17). We found a distinct seasonality of meteorological variables and energy fluxes with different latent heat controls regarding available energy in each site. Remotely sensed GPP was satisfactorily related with observed data, despite weak correlations in interannual estimates and consistent overestimations and underestimations during certain months. WUE was strongly dependent on water availability, with values of 0.95 gC kg⁻¹ H₂O (5.79 gC kg⁻¹ H₂O) in the wetter (drier) sites. These values reveal new thresholds that had not been previously reported in the literature. Our findings have crucial implications for ecosystem management and the design of climate policies regarding the conservation of tropical biomes, since WUE is expected to change in the ongoing climate change scenario that indicates an increase in frequency and severity of dry periods.

This study analyzed the performance of the Brunt (1932), Swinbank, (1963), Idso and Jackson (1969), Brutsaert (1975), Idso (1981), and Bignami et al. (1995) methods to estimate atmospheric emissivity under grass-dominated savannas (known as campo sujo Cerrado), in the region of Baixada Cuiabana. The estimates were compared with data obtained by energy balance equation in two seasons, dry season (May to August), and wet season (September to December) of 2009. The Swinbank and Idso and Jackson methods, that consider only air temperature, show better performances for the wet season. However, methods that consider water vapor pressure and air temperature (Brunt, Brutsaert, Bignami and Idso) show good performances for the dry season. The Idso and Brutsaert methods show the highest index of agreement and are recommended to estimate atmospheric emissivity for the region.

This paper aimed to evaluet the changes in the biophysical parameters and trends of the annual extremes of air temperature in Sinop, Mato Grosso, Brazil, using data from automatic meteorological stations (EMA) installed in the rural and urban areas of the municipality. The estimates of changes in soil use, surface albedo, radiation balance (Rn) and sensible heat (H) and latent heat (LE) were obtained by images from the Landsat 8 and Landsat 5 satellites in August of the years of 2007, 2011 and 2017. With the Rclimdex software, the trends of six extreme indices of the maximum, minimum and mean values of the annual maximum and minimum temperatures were calculated with least squares calibration and statistical significance considering the Fisher test with significance level equal to α: 0.05. It was observed changes in soil use and biophysical parameters like albedo increase and reduction of Rn in the rural area, while in the urban station (UFMT Sinop) occurred inversion of the ration of LE and H. The extreme indexes indicated a tendency of increase in the extreme temperatures in the urban area, being significant the changes in the indices TNx, DTR, Tn90p and Tx90p. In the last decade, with the expansion of the municipality of Sinop-MT, there have been changes in trends of temperature extremes indices, which are attributed to changes in soil use and biophysical parameters.

A radiação de onda longa atmosférica (ROL) é a variável chave para o cálculo do balanço de radiação da superfície terrestre, sendo a componente mais difícil de ser medida. Neste estudo, foi avaliado o desempenho de seis modelos que estimam ROL em dias de céu claro, parcialmente nublado e nublado, para dados obtidos na região do Cerrado Campo Sujo, na Baixada Cuiabana, em dois períodos distintos: seco (maio a agosto) e úmido (setembro a dezembro) de 2009. Dois modelos levam em consideração apenas a temperatura do ar em suas estimativas, Swinbank (1963) e de Idso et al. (1969), e os modelos de Brunt (1932), Brutsaert (1975), Idso (1981) e Bignami (1995) levam em consideração a temperatura do ar e a pressão de vapor d’água. Os seis modelos foram avaliados estatisticamente pelo coeficiente de determinação (R2) da regressão robusta e o p-valor (M-Estimador) do teste de viés dado pela regressão. Os modelos de Swinbank (1963) e de Idso et al. (1969) foram os que melhores estimaram ROL e o modelo de Idso (1981) o pior modelo estimador para o local de estudo. Sendo as equações que levam em consideração apenas a temperatura do ar em suas estimativas obtiveram melhor desempenho do que as que utilizam apenas a temperatura do ar e a pressão de vapor d’água para os dois períodos estudados, visto os valores de R2 obtidos através da regressão robusta.