Rainfall in Brazilian Northeast via in situ data and CHELSA product: mapping, trends, and socio-environmental implications.

Rainfall is a climatic variable that dictates the daily rhythm of urban areas in Northeastern Brazil (NEB) and, therefore, understanding its dynamics is fundamental. The objectives of the study were (i) to validate the CHELSA product with data in situ, (ii) assess the spatial-temporality of the rains, and (iii) assess the trends and socio-environmental implications in the Metropolitan Region of Maceió (MRM). The monthly rainfall data observed between 1960 and 2016 were flawed and were filled with the imputation of data. These series were subjected to descriptive and exploratory statistics, statistical indicators, and the Mann-Kendall (MK) and Pettitt tests. CHELSA product was validated for MRM, and all stations obtained satisfactory determination coefficients (R2) and Pearson correlation (r). The standard error of the estimate (SEE), root mean square error (RMSE), and mean absolute error (MAE) were satisfactory. The highest annual rainfall accumulated occurred near the Mundaú and Manguaba lagoons. The Pettitt test identified that abrupt changes occur in El Niño and La Niña years (strong and weak). The monthly rain boxplots showed high variability in the rainy season (April-July). Outliers have been associated with extreme rainfall at MRM. The drought period was 5 months in all MRM seasons, except in Satuba and Pilar. The Mann-Kendall test and the Sen method showed a tendency for a significant increase in rainfall in Satuba and not significant in the Pilar, while in the others, there was a tendency for a decrease in rainfall. The MRM rainfall depends on physiographic factors, multiscale meteorological systems, and the coastal environment. These results will assist in planning conservationist practices, especially in areas of socio-environmental vulnerability.

Temporal record and spatial distribution of fire foci in State of Minas Gerais, Brazil.

The objectives of this study are: (i) to evaluate the space-temporal variability of fire foci by environmental satellites, CHIRPS and remote sensing products based on applied statistics, and (ii) to identify the relational pattern between the distribution of fire foci and the environmental, meteorological, and socioeconomic variables in the mesoregions of Minas Gerais (MG) - Brazil. This study used a time series of fire foci from 1998 to 2015 via BDQueimadas. The temporal record of fire foci was evaluated by Mann-Kendall (MK), Pettitt (P), Shapiro-Wilk (SW), and Bartlett (B) tests. The spatial distribution by burned area (MCD64A1-MODIS) and the Kernel density - (radius 20 km) were estimated. The environmental variables analyzed were: rainfall (mm) and maximum temperature (°C), besides proxies to vegetation canopy: NDVI, SAVI, and EVI. PCA was applied to explain the interaction between fire foci and demographic, environmental, and geographical variables for MG. The MK test indicated a significant increasing trend in fire foci in MG. The SW and B tests were significant for non-normality and homogeneity of data. The P test pointed to abrupt changes in the 2001 and 2002 cycles (El Niño and La Niña moderated), which contributes to the annual increase and in winter and spring, which is identified by the Kernel density maps. Burned areas highlighted the northern and northwestern regions of MG, Triângulo Mineiro, Jequitinhonha, and South/Southwest MG, in the 3rd quarter (increased 17%) and the 4th quarter (increased 88%). The PCA resulted in three PCs that explained 71.49% of the total variation. The SAVI was the variable that stood out, with 11.12% of the total variation, followed by Belo Horizonte, the most representative in MG. We emphasize that the applied conceptual theoretical model defined here can act in the environmental management of fire risk. However, public policies should follow the technical-scientific guidelines in the mitigation of the resulting socioeconomic - environmental damages.

Space-temporal evaluation of changes in temperature and soil use and cover in the metropolitan region of baixada santista / Avaliação espaço-temporal das mudanças do uso e cobertura do solo e temperatura na região metropolitana da baixa da santista

The Metropolitan Region of Baixada Santista (MRBS) harbors one of the main port areas of Brazil: the Port of Santos. Due to the accelerated urban development in this region, the monitoring of biophysical parameters is fundamental. Therefore, this paper aims to i) estimate the soil surface temperature (Ts) and identify the Urban Heat Islands (UHI) formation; and ii) compare the Ts and the normalized difference vegetation index (NDVI) for MRBS from 1986 to 2016 using Landsat 5 and 8 images. Remote sensing tools are essential to meet the objectives of this work for providing both the spatial and temporal evaluation of a region. The spatial analysis was based on the NDVI to evaluate the vegetation density and size from five previously established classes (i.e., water bodies, urban grid, exposed soil and road corridors, shrub, and dense vegetation). The NDVI mapping showed a significant reduction in the cover area referred to the dense vegetation class (91.7%), while the urban grid category increased by 29.4%, resulting from the urban expansion and green cover reduction over the region during this period. Surface temperature thematic maps showed high-temperature values related to increased urbanization and decreased rainfall. Moreover, an 8°C rise in surface temperature over the last 30 years was registered due to the regional development, which has replaced natural soils by anthropic materials and reduced dense vegetation. This phenomenon has resulted in the formation and intensification of UHI, especially after the 2000s.

A Região Metropolitana da Baixada Santista (RMBS) abriga uma das principais zonas portuárias do Brasil, o Porto de Santos. Devido ao grau de urbanização dessa região, o monitoramento dos parâmetros biofísicos torna-se fundamental. Desta forma, este estudo tem como objetivo i) estimar a Temperatura de superfície terrestre (Ts) da RMBS, seguido da identificação da formação de ICU e ii) relacionar a Ts e o NDVI da RMBS no período de 1986 a 2016, a partir das imagens do Landsat 5 e 8. A análise espacial foi baseada no Normalized Difference Vegetation Index (NDVI), no sentido de verificar as condições da densidade e porte da vegetação a partir de cinco classes previamente estabelecidas (Corpo d'água, Malha urbana, Solo exposto e corredores viários, Substrato Arbustivo e Vegetação densa). Os mapas de NDVI indicam uma redução significativa na área de cobertura correspondente à classe vegetação densa, com o valor de cobertura de 91,7%. Por outro lado, a classe Malha urbana apresentou um aumento de 29,4%, resultantes da expansão urbana e da redução da cobertura verde na RMBS ao longo do período. Os mapas temáticos de Tsmostraram altos valores de temperatura, relacionados ao aumento da malha urbana e redução da precipitação. Além disso, houve um aumento de 8ºC na Ts nos últimos 30 anos, causados pelo avanço do desenvolvimento regional, associados à substituição do solo natural por materiais antrópicos e à redução da vegetação densa. Esses fatores resultaram no surgimento de ICU e sua intensificação a partir dos anos 2000.

Influence of meteorological variables on dengue incidence in the municipality of Arapiraca, Alagoas, Brazil

Abstract INTRODUCTION: Meteorological influences along with the lack of basic sanitation has contributed to disease outbreaks, resulting in large socio-economic losses, especially in terms of dengue. This study aimed to evaluate the meteorological influences on the monthly incidence of dengue in Arapiraca-AL, Brazil during 2008-2015. METHODS: We used generalized linear models constructed via logistic regression to assess the association between the monthly incidence of dengue (MID) of and 8 meteorological variables [rainfall (R), air temperature (AT), dew point temperature (DPT), relative humidity (RH), pressure surface, wind speed (WS), wind direction (WD), and gust], based on data obtained from DATASUS and meteorological station databases, respectively. The dengue-1 model included R, AT, DPT, and RH and the dengue-2 model included AT, DPT, RH, WS, and WD. A MID >100 (classified as moderate incidence) indicated an abnormal month. RESULTS: Based on the dengue-1 model, variables with the highest odds ratio included R-lag1, DPT-lag1, and AT-lag1 with a 10.1, 18.3, and 26.7 times greater probability of a moderate MID, respectively. Based on the dengue-2 model, variables with the highest odds ratio were AT-lag1 and RH-lag0 indicating an 8.9 and 18.1 times greater probability of a moderate MID, respectively. CONCLUSIONS: AT, DPT, R, RH and WS influenced the occurrence of a moderate MID.