Givanildo de Gois

Spatial Interpolation of Annual Rainfall in the State Mato Grosso Do Sul (Brazil) Using Different Transitive Theoretical Mathematical Models

Based on the interpolation method ordinary kriging, it was compared the spherical, exponential, Gaussian and circular models that best fits in the spatial distribution of mean annual precipitation for the state of Mato Grosso do Sul (MS). The rainfall data from 32 sites were obtained from the database of the National Water Agency - ANA, in the period 1954-2013. The variographic parameters evaluated were nugget effect, level and reach. From these, were calculated the Index of Spatial Dependence. The criteria used to choose the best transitive theoretical mathematical model were the root of the root mean square error (RMSE), Pearson‟s correlation coefficient (d), mean absolute error (EMA) and mean error percentage (EMP), index of agreement (d) and coefficient of determination (R²). The transitive theoretical mathematical models circular, spherical and Gaussian and can be used with satisfactory performance for data interpolation of annual rainfall in State of Mato Grosso do Sul.

Avaliação das Estimativas de Precipitação do Produto 3B43-TRMM do Estado do Amazonas / Assessment of Rainfall Estimates from the TRMM-3B43 Product in the State of Amazonas

The aim of this study was to evaluate the rainfall data via satellites in Amazonas state, Brazil. To this end, the estimates from the TRMM-3B43 product (2004-2008) were compared with data from seven Conventional Weather Stations (CWS). The comparison was based on the following statistical parameters: Average Error (AE), Root Mean Square Error (RMSE), linear correlation coefficient (r), and Wilmott’s index of agreement (d). The TRMM-3B43 estimates were similar to the surface data and represent well the seasonal variability of rainfall. The data showed high linear correlation (r = 0.83), high index of agreement (d = 0.85), and satisfactory RMSE (66.6 mm/month). Therefore, rainfall estimates from the TRMM-3B43 product can be used as an alternative source of quality data.

Cenários Climáticos da Radiação Solar Global Baseados no Modelo Regional HadRM3 para o Estado do Acre / Climate Scenarios of Global Solar Radiation Based on the HadRM3 Regional Climate Model for the State of Acre, Brazil

ABSTRACT Two future climate scenarios have been proposed for the the Western Amazon region - state of Acre, Brazil - using the HadRM3 regional climate model for global solar radiation (Rg). The two climate scenarios, A2 (pessimistic) and B2 (optimistic), are based on findings of the IPCC (Intergovernmental Panel on Climate Change) report. Two distinct seasons were defined for both climate scenarios (dry and rainy): the dry season (from April to September) and the rainy season (from October to March). We chose the time period between 1961 and 1990 as baseline and carried out future simulation from 2070 to 2100 for the A2 and B2 settings. The grid point conversion of the HadRM3 model was based on the Ordinary Kriging method. The smallest values of Rg are found for the western part of Acre state during the dry season in both scenarios. Intermediate values of Rg are observed for the north to south direction, followed by the highest values of Rg for the east side of the state, with significant increase of Rg during the rainy season between 2080 and 2090 for both settings adopted in this study. Based on

Incoming Longwave Radiation Evaluation for the Legal Amazon Using HadRM3 and Geostatistic Theoretical Models

Incoming longwave radiation was estimated using air temperature data from the output of the regional HadRM3 model in the Intergovernmental Panel on Climate Change’s (IPCC) A2 scenario for projections up to 2070, 2080 and 2090 and using Swinbank’s equation. Spatial distribution was done by Ordinary Kriging through three theoretical mathematical models for the IPCC A2 scenario for the whole Legal Amazon. It was found that the highest averages and outliers occurred in 2090 compared to other years evaluated. The average incoming longwave radiation for 2070, 2080 and 2090 was 394.8, 403.9 and 413.0 Wm-2year-1, respectively. The coefficients of variation (CV) were higher for 2080 (2.6%) and 2090 (2.8%), similar to the results found by standard deviation. 2070 obtained CV (2.2%) for estimated values of incoming longwave radiation with greater accuracy. Again, 2070 was the only year that could be interpolated because the average degree of spatial dependence found for all models was 12.23%. Lastly, 2080 could only be interpolated using the Gaussian model in the Legal Amazon.

Probable monthly rainfall associated with distinct biomes of Mato Grosso do Sul state

The aim of this study was to determine the probable monthly rainfall for the state of Mato Grosso do Sul, considering the level of 75% probability, and study the spatial distribution associated with its different biomes. The rainfall data of 32 stations (sites) in the state of Mato Grosso do Sul were collected in the period 1954-2013. In each of the 384 series, the average monthly rainfall was calculated, for at least 30 years of observation. The Kolmogorov-Smirnov adhesion test was applied to the rainfall time series to check the fit of the data to a normal distribution. The likely fallout was estimated at 75% probability, using the normal probability distribution and, subsequently, it was adopted the method of Ordinary Kriging interpolation mathematics to spatial data. Based on the likely monthly precipitation estimated, the State of Mato Grosso do Sul possess three distinct periods, with the precipitation associated with different biomes: the rainy season (between the months November to March, where increased precipitation occurred in the Savanna biome), dry season (between the months from June to August, when the highest rainfall occurred in the Atlantic Forest) and transition period (April and May and September and October).

SO DO SENSOR TM NA ESTIMATIVA DA TEMPERATURA DA SUPERFÍCIE E MUDANÇA NO USO DO SOLO EM VIÇOSA, MG, BRASIL

O objetivo deste trabalho foi avaliar a dinâmica nouso e cobertura da terra em area de abrangencia de Vicosa, Minas Gerais. Para tanto, utilizou-se o algoritmo SEBAL (Surface Energy Balance Algorithm for Land) e o metodo de classificacao nao supervisionada por meio do algoritmo ISODATA. Foi utilizada uma serie historicade temperatura do ar (oC), da Estacao Meteorologica Convencional (EMC) do Instituto Nacional de Meteorologia (INMET) e imagens do sensor TM Landsat 5 do Instituto Nacional de Pesquisas Espaciais (INPE), noperiodo que compreendeu 16 anos (1994-2010). Os resultados mostraram que nos anosde 1999, 2000, 2003, 2006, 2009 e 2010 mais de 20 mil hectares foram antropizadas, porem, a partir de 1999 inicia-se um acentuado crescimento das areas classificadas como mata. Os valores demonstraram avanco das areas antropizadas (58,92% em 1994 para 71,90% em 2010) e uma reducao das areas de pastagens (27,04% em 1994 para 5,90% em 2010). A temperatura da superficie estimada pelo algoritmo SEBAL para os anos de 1994 e 2010, apresentaram valores maximos de 38oC em areas antropizadas e valores minimos de 18oC em areas de vegetacao. Com base no calculo do vies medio (VM), o presente estudo mostrou que os dados estimados da temperatura da superficie apresentaram boa correlacao de 0,67 com os dados do INMET, ja que as temperaturas foram subestimadas e superestimadas com valores minimos e maximos de -3,83oC e 2,65oC em 1994 e 2003. Os resultados obtidos, ainda que em carater preliminar, indicam a eficiencia do Sensoriamento Remoto (SR) por meio da analise das bandas refletivas e termal do satelite Landsat 5 como ferramenta de analise na identificacao da dinâmica do uso do solo, mostrando-se eficaz quanto a espacializacao dessas anomalias no espaco e no tempo.