The gridded database provided by National Aeronautics and Space Administration/Prediction of World Wide Energy Resources (NASA/POWER) presents a global coverage of complete weather data at horizontal resolution of 1° latitude–longitude, becoming a potential source for agrometeorological studies. Once Brazil is a country with continental dimensions and the major sugarcane world producer, and its density of ground weather stations suitable for an efficient agricultural planning is sparse, the objectives of this study were to test how robust is the NASA/POWER database through its comparison with the Brazilian ground weather stations network records (INMET) and to quantify the impacts on potential (Yp) and attainable (Yatt) sugarcane yield simulations when setting NASA/POWER as source of input weather data. The comparisons for weather data records and sugarcane yield simulations were carried out from 1997 to 2016. Statistical indices presented a satisfactory performance for average air temperature (R2 = 0.73; d = 0.91), minimum air temperature (R2 = 0.72; d = 0.91), maximum air temperature (R2 = 0.57; d = 0.84), solar radiation (SR) (R2 = 0.71; d = 0.92), sunshine hours (R2 = 0.68; d = 0.90) and reference evapotranspiration, when calculated through Priestley–Taylor (ETo‐PT) method (R2 = 0.76; d = 0.93). When the weather variables were aggregated and compared with a 10‐day time scale, a strong improvement of statistical indices was obtained. Yp presented root mean square error (RMSE) smaller than 10 t ha−1 while relative mean error (RME) ranged between ±10% for majority of grid cells, with exception for southern Brazil due to low and frost temperatures that satellite cannot capture accurately. Even NASA/POWER offering a relatively coarse grid size database and perhaps some regional data fitting would give better results at higher latitudes and elevation. The results found in this study proved that NASA/POWER products could be used as a source of climatic data for agricultural activities with a reasonable confidence for regional and national spatial scales.

The present study analyzes the impacts of global warming of 1.5ºC, 2ºC, and 4ºC above pre-industrial levels in the Brazilian territory. Climate change projected among the different global warming levels has been analyzed for rainfall, temperature and extreme climate indices. The projections are derived from the global climate model HadGEM3-A, from the High-End cLimate Impacts and eXtremes (HELIX) international project, from the United Kingdom, forced by sea surface temperature and sea ice concentration of a subset of six CMIP5 (Coupled Model Intercomparison Project phase 5) global climate models and considering the RCP 8.5 (Representative Concentration Pathways) emissions scenario throughout the 21st century. Projections indicate robust differences in regional climate characteristics. These differences include changes: in the minimum and maximum air temperature close to the surface to all the country’s regions, in extremes of heat, particularly in northern Brazil, in the occurrence of heavy rainfall (Southern and Southeastern regions), and in the probability of droughts and rain deficits in some regions (Northern and Northeastern Brazil).

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The intraseasonal variability over South America is investigated using a multivariate index based on maximum covariance analysis (MCA). This technique identifies the correlation patterns of two different data sets. The Climate Prediction Center (CPC) grid precipitation over South America and the tropical means (15°N–15°S) of outgoing long wave radiation (OLR) and zonal wind component at 850 and 200 hPa (National Oceanic and Atmospheric Administration (NOAA) and National Centers for Environmental Prediction (NCEP)/National Center for Atmospheric Research (NCAR) reanalysis, respectively) are used in the study. The MCA was applied to these data sets and a Multivariate Intraseasonal Rainfall Index for South America for South America (MIRI.SA) was constructed based on the phase and amplitude vectorial projections of the first two modes. Composites of selected cases when the amplitude was above a threshold are discussed for different phases of the Madden–Julian Oscillation (MJO). Phases (8+1) and (4+5) present strong convection anomalies over the maritime continent and South America, but with opposite signs. These patterns represent the dominant mode of precipitation over South America. Phases (2+3) and (6+7) are transient and related to the secondary mode of precipitation over South America. A space‐phase diagram calculated using the MIRI.SA index at different lags represents the positive precipitation locations over both South America and the Equatorial Pacific. The construction of this diagram in near real time could be used for monitoring precipitation extremes over different areas of South America.

Climate change is a phenomenon directly attributed to human activity due to greenhouse gas emissions and changes in land use and land cover. In this way, climate change has and will have direct and indirect impacts on the components of the climate systems, including the hydrological cycle, through an increase in the frequency and intensity of extreme events, such as heavy rains or droughts, which impact natural systems, groups, and human systems, as well as on economic activity, such as the energy, agricultural and water sectors that are directly dependent on the variables of the hydrological cycle. The southeast region of Brazil (São Paulo, Minas Gerais, Rio de Janeiro, and Espírito Santo) produces 60\% of the national wealth and much of the country's electricity, in addition to housing 80 million people. Extreme weather events have hit this region in recent decades, causing an increasing number of natural disasters. Good examples are the 2014/15 water crisis and the occurrence of heavy rains, particularly in the summers. Given the importance of this theme, the present study aims to analyze the spatial and temporal variability of precipitation over southeast Brazil through the Generalized Extreme Values (GEV) distribution. To this end, seasonal variability and changes in the patterns of precipitation extremes in the period 1981-2020 were analyzed, based on data obtained from the CPC (Climate Predict Center). This research revealed that the frequency and intensity of extreme rainfall events have been changing, notably decreasing during winter.

Espaciais (INPE) monitora fluxos da Radiação Ultravioleta (R-UV), em solo, desde 1990, através de uma rede de espectrofotômetros Brewer no Brasil, Bolívia, Chile e Antártida. O espectrofotômetro é reconhecido pela Organização Mundial de Meteorologia (OMM) e pelo programa "Global Atmosphere Watch" (GAW) como padrão para medições de ozônio e R-UV. O objetivo deste trabalho é descrever e avaliar o funcionamento do instrumento no processo de coleta da R-UV, ao mesmo tempo em que apresenta metodologia desenvolvida para validação de dados referentes ao período de 1997 a 2012 nas cidades de La Paz, Bolívia e Natal, Brasil. Avaliou-se o funcionamento da parte óptica com destaque nas Lâmpadas Padrão (SL) dos espectrofotômetros. Observaram-se desgastes naturais no funcionamento dos instrumentos. Utilizou-se o modelo matemático de transferência radiativa TUV "Tropospherical Ultraviolet Visible Model" para simular uma base de dados do índice de radiação ultravioleta (IUV). Por meio de análise de regressão linear entre as duas bases, realizou-se o ajuste da série temporal do Brewer (variável preditora) por meio da série temporal do TUV (variável resposta). Este review apresenta algoritmo para validação dos registros e um roteiro para a pré-análise dos dados coletados. Palavras-chave: Radiação Ultravioleta, Espectrofotômetro Brewer, Tropospherical Ultraviolet Visible Model.

Resumo A Leishmaniose Visceral (LV) representa um grave problema de saúde pública, considerada pela Organização Mundial de Saúde (OMS, 2016) como uma das doenças tropicais negligenciadas pelo poder público. A LV tem como fatores de exposição a sua expansão geográfica, as condições sociodemográficas da população e as condições climáticas. Diante desse cenário, o objetivo deste estudo é identificar possíveis fatores climáticos e sociodemográficos que influenciam na transmissão da LV no Nordeste brasileiro (NEB). Os dados climáticos foram coletados a partir de informações disponibilizadas pelo Climate Prediction Center / National Oceanic and Atmospheric Administration (CPC/NOAA), de janeiro de 2001 a dezembro de 2015. As informações sociodemográficas foram obtidas dos censos 2000 e 2010, enquanto as estimativas populacionais foram disponibilizadas pelo Instituto Brasileiro de Geografia e Estatística (IBGE). As notificações dos casos registrados de LV foram disponibilizadas pelo Departamento de Informática do SUS (DATASUS).