Intensive rainfall is an important meteorological variable that is of technical interest in hydraulic projects. This study therefore generated Intensity-Duration-Frequency equations (IDF) for 14 weather stations in Mato Grosso State, based on pluviograph analysis. Annual maximum rainfall data regarding 10-to-1440-minute long rainfall events were collected from digitized daily pluviographs. Data adherence to the generalized extreme value distribution (GEV) was checked through the Kolmogorov-Smirnov test at a 20% significance level. Next, the maximum probable rainfall for return periods such as 2, 5, 10, 20, 30, 50 and 100 years was calculated and the IDF equations were adjusted. The performance of the IDF equations was evaluated based on mean absolute error (MAE), root mean square error (RMSE), bias, Willmott's concordance index and Nash-Sutcliffe efficiency index (ENS). Adjusting the IDF equations was only possible for rainfall durations ranging from 10 to 360 min at each station due to the low frequency of longer rainfalls. High variation was present in parameters of the IDF equation and in maximum rainfall intensity between stations. The satisfactory performance of the models, as attested to by statistical indices, allows using IDF equations adjusted for rainfall durations from 10 to 360 min, and return periods from 2 to 100 years, in the regions of the Mato Grosso weather stations.

Objetivou-se avaliar o crescimento inicial de Handroanthus serratifolius (Vahl) S. O. Grose. e Handroanthus ochraceus (Vahl) S.O. Grose. sob telas de sombreamento pretas e coloridas. O trabalho foi desenvolvido no Departamento de Produção Vegetal da UFMT – SINOP, com mudas produzidas seminalmente e transplantadas para vasos com 8 litros de capacidade contendo substrato comercial e fertilizante. O delineamento experimental empregado foi o inteiramente casualizado em esquema fatorial 9 x 2 (coberturas x espécies) com 16 repetições sendo os tratamentos empregados: Pleno sol, telas pretas com 35, 50, 65 e 80%; telas coloridas vermelha, azul e verde 50%; e tela aluminet prata com 50% de retenção da radiação global. As análises dos parâmetros altura, diâmetro do coleto, número de folhas e índice spad foram realizadas a cada 20 dias.

Our understanding of spatiotemporal variability in reference evapotranspiration (ETo) and its long-term trends is of paramount importance for water cycle studies, modeling, and water resource management, especially in the context of climate change. Therefore, the primary aim of this study is to critically evaluate the performance of various CMIP5 global climate models in simulating the Penman–Monteith reference evapotranspiration and its associated climate variables (maximum and minimum air temperature, incident solar radiation, relative humidity, and wind speed). This evaluation is based on data from nine climate models and 33 automatic meteorological stations (AWSs) in the state of Mato Grosso, spanning the period 2007–2020, within the areas of the biomes Amazon and Cerrado and around the Pantanal biome. The statistical metrics used for evaluation include bias, root mean square error, and Pearson and Spearman correlation coefficients. The projections of the most accurate model were then used to analyze the spatial and temporal changes and trends in ETo under the Representative Concentration Pathways (RCPs) of 2.6, 4.5, and 8.5 scenarios from 2007 to 2100. The HadGEM2-ES model projections indicate static averages similar to current conditions until the end of the century in the RCP 2.6 scenario. However, in the RCP 4.5 and 8.5 scenarios, there is a continuous increase in ETo, with the most significant increase occurring during the dry period (May to September). The areas of the Amazon biome in the north of Mato Grosso exhibit the largest increases in ETo when comparing the observed (2007–2020) and projected (2020–2100) averages. The trend analysis reveals significant changes in ETo and its variables across the state of Mato Grosso in the RCP 4.5 and 8.5 scenarios. In the RCP 2.6 scenario, significant trends in ETo are observed only in the northern Amazon areas. Despite not being observed in all AWSs, the trend analysis of the observed data demonstrates more intense changes in ETo and the existence of the evapotranspiration paradox, with an increase in the Cerrado areas and reductions in the Pantanal and southern Amazon areas.

This paper aimed to introduce the GapMET software, developed by the authors, and evaluate the accuracy of its six methods for gap-filling the main meteorological variables monitored by weather station in the state of Mato Grosso, Brazil, using reference time series from neighbour weather station and/or remote sensing products. The methods were tested on seven different databases, with 25 to 80% artificial gaps, and their accuracy was given by the number of gaps left unfilled, the bias, the RMSE, and Pearson’s correlation. The GapMET software showed good results in filling meteorological gaps regardless of the method applied. Methods that use only one neighbour weather station as a reference series showed better results because, in the state, the minimum distance for a weather station to have at least three neighbours as reference was 350 km, reducing the climatic similarity between them and consequently the accuracy when more than one reference series were needed. The use of satellite reference series reduced the probability of unfilled gaps; however, it showed higher bias and RMSE and lower correlations.

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.

The understanding of spatiotemporal variations in reference evapotranspiration (ETo) and its long-term trends is of paramount importance for water cycle studies, modeling, and water resource management, especially in the context of climate change. Therefore, the primary aim of this study is to critically evaluate the performance of various CMIP5 global climate models in simulating the Penman-Monteith reference evapotranspiration and its associated climate variables (maximum and minimum air temperature, incident solar radiation, relative humidity, and wind speed). This evaluation is based on data from nine climate models and 33 automatic meteorological stations (EMA) in the state of Mato Grosso, spanning the period 2007-2020. The statistical metrics used for evaluation include Bias, root mean square error, and Pearson and Spearman correlation coefficients. The projections of the most accurate model were then used to analyze the spatial and temporal changes and trends in ETo under the RCP 2.6, 4.5, and RCP 8.5 scenarios from 2007 to 2100. The HadGEM2-ES model projections indicate static averages similar to current conditions until the end of the century in the RCP 2.6 scenario. However, in the RCP 4.5 and 8.5 scenarios, there is a continuous increase in ETo, with the most significant increase occurring during the dry period (May to September). The areas of the Amazon biome in the north of Mato Grosso exhibit the largest increases in ETo when comparing the observed (2007-2020) and projected (2020-2100) averages. The trend analysis reveals significant changes in ETo and its variables across the state of Mato Grosso in the RCP 4.5 and 8.5 scenarios. In the RCP 2.6 scenario, significant trends in ETo are observed only in the northern Amazon areas. Despite not being observed in all AWSs, the trend analysis of the observed data demonstrates more intense changes in ETo and the existence of the evapotranspiration paradox with an increase in the Cerrado areas and reductions in the Pantanal and southern Amazon areas.