Balanço de radiação através do satélite Landsat-8 na bacia do Rio Pajeú

O presente estudo tem como objetivo realizar a estimativa do saldo de radiação à superfície-Rn através do algoritmo SEBAL e imagens do satélite Landsat-8 para a Bacia do Rio Pajeú. Os dados de Rn estimados pelo SEBAL foram comparados com medições obtidas em duas estações automáticas localizadas nos municípios de Floresta e Serra Talhada. Foi utilizada uma imagem dos sensores OLI (Operational Land Image) e TIRS (Thermal Infrared Sensor) abordo do satélite Landsat-8, orbita 216 e ponto 66, para o dia 20 de novembro de 2016. A partir das imagens se obteve a radiância e reflectividade espectral, seguido do albedo de superfície, índices de vegetação, emissividade, temperatura superficial, radiação de onda curta incidente – Rs, radiação de onda longa incidente e emitida - Rol,atm e Rol,emi, respectivamente, e Rn. Nos resultados encontrados observa-se que os menores valores de albedo e temperatura foram observados em corpos d’água e vegetação, e maiores valores em áreas urbanas. Estas componentes estão ligadas diretamente com as componentes do saldo de radiação, onde se observou menores valores de Rol,atm e Rol,emi que estão diretamente ligadas a maior ou menor Rn. A validação dos dados do algoritmo SEBAL a partir das estações automáticas foi observado um erro relativo entre 9 e 11% para a imagem Landsat-8 para o dia 20/09/2016, verificando a acurácia das imagens para a estimativa do saldo de radiação à superfície – Rn, para a Bacia do Rio Pajeú.The present study aims to estimate the Balance of Radiation Surface-Rn through the SEBAL algorithm and images of the Landsat-8 satellite for the Pajeú River Basin. The Radiation Balance data, estimated by SEBAL, were compared with measurements obtained in two automatic stations, located in the municipalities of Floresta and Serra Talhada. An image of OLI (Operational Land Image) and TIRS (Thermal Infrared Sensor) sensors on Landsat-8 satellite, orbit 216 and point 66, was used for November 20, 2016. From the images obtained if the spectral radiance and reflectance, followed by surface albedo, vegetation index, emissivity, surface temperature, short-wave radiation incident - Rs, incidente and emitted long wave radiation - Role,atm and Rol,emi , Respectively, and Radiation Balance. The results showed that the lowest values of albedo and temperature were observed in bodies of water and vegetation, already the largest in urban areas. These items are linked directly to the components of the radiation balance, which observed lower values of incident and emitted long wave radiation that are directly linked to the higher or lower Radiation Balance. The validation of the SEBAL algorithm data from the automatic stations showed a relative error between 9% and 11% for the Landsat-8 image, thus verifying the accuracy of the images for the estimate of the surface radiation balance in the Pajeu River

Comportamento do dióxido de nitrogênio sobre a região nordeste do Brasil e sua relação com variáveis meteorológicas

The emission of pollutants has become one of the subjects most debated in the last years, due to the increase of fixed emitting sources like industries and movable like the motor vehicles. In the Northeast of Brazil, the high concentrations of pollutants occur mainly in large urban centers, where one of these pollutants is emitted nitrogen dioxide, which is a highly polluting gas. Once observed high concentrations of this pollutant in the atmosphere can cause effects on human health and also influence the formation of acid rain. Thus the objective of this work was to investigate and quantify the total column of nitrogen dioxide gas over the northeastern region of Brazil based on data from the OMI sensor (Ozone Monitoring Instrument) between 2005 and 2015, through statistical techniques for analysis graphic and spatial. Significant variations of the pollutant were identified in the study area, highlighting Salvador, Teresina and Fortaleza, where they showed significant correlation results with meteorological variables. The results showed that Salvador had concentrations of up to 3.5 E+15 (1/m²) in the total NO2 column, while Teresina and Fortaleza had a maximum of 3.0 E+15 (1/m²) and 2,6 E+15 (1/m²), respectively. Therefore, the variations were different in the cities.A emissão de poluentes tem se tornado um dos assuntos mais debatidos nos últimos anos, devido ao aumento de fontes emissoras fixas como industrias e móveis como os veículos automóveis. No Nordeste Brasileiro as altas concentrações de poluentes se dão, principalmente, nos grandes centros urbanos, onde um destes poluentes emitido é o dióxido de nitrogênio. Uma vez observada altas concentrações desse poluente na atmosfera o mesmo podem causar efeitos na saúde humana e influencia ainda na formação de chuva ácida. Assim, o objetivo deste trabalho foi investigar e quantificar a coluna total do gás dióxido de nitrogênio sobre a região nordeste do Brasil baseado nos dados oriundos do sensor OMI (Ozone Monitoring Instrument) entre o período de 2005 a 2015, através de técnicas estatísticas voltadas a análise gráfica e espacial. Identificou-se variações consideráveis do poluente na área de estudo, destacando-se valores elevados em Salvador, Teresina e Fortaleza, onde as mesmas apresentaram ainda resultados significativos de correlação com variáveis meteorológicas. Os resultados apresentaram que Salvador teve concentrações de até 3,5 E+15(1/Cm²) na coluna total de NO2, enquanto Teresina e Fortaleza, tiveram máximo de 3,0 E+15 (1/Cm²) e 2,6 E+15 (1/Cm²), respectivamente. Portanto, as variações foram diferentes nas cidades

Avaliação das Parametrizações de Cúmulos do Modelo Climático Regional na Bacia do Rio São Francisco

Resumo O uso de modelos climáticos com ênfase na simulação de precipitação é estratégico para estudos climáticos e de recursos hídricos. O objetivo deste trabalho foi avaliar a precipitação simulada pelo modelo regional climático RegCM na bacia hidrográfica do Rio São Francisco, conforme a parametrização de cúmulos e o domínio. Nossa avaliação, com uso de diversos índices estatísticos e a combinação desses, mostram que o RegCM apresentou maior destreza em simular os padrões de precipitação quando neste foi prescrito (acionado) nele a parametrização de Emanuel ou de Tiedke. As outras parametrizações avaliadas, Kain-Fritsch e a de Grell, subestimaram consideravelmente a precipitação. Emanuel se destacou pela melhor representação da variabilidade temporal da precipitação, enquanto Tiedke apresentou maior correlação e menores erros médios. O baixo São Francisco foi a região em que o RegCM apresentou a menor destreza em simular a precipitação durante maio a julho (período chuvoso), indicando a dificuldade do modelo em representar o transporte de umidade do oceano para o continente e a ocorrência dos distúrbios ondulatórios de leste. Por fim, o modelo prescrito com um domínio maior simulou melhor os padrões de precipitação provavelmente por contemplar a região de atuação dos sistemas meteorológicos de escalas maiores atuantes na bacia

Evaluation of Wind and Wave Estimates from CMEMS Reanalysis for Brazil’s Offshore Energy Resource Assessment

This study aims to evaluate wind speed and significant wave height data from the Copernicus Marine Environment Monitoring Service (CMEMS) reanalysis using buoy measurements for offshore energy application off the east coast of Brazil. Such analysis has become important, since reanalysis datasets can be fundamental tools in identifying regions with wind energy potential that are suitable for the installation of offshore farms. Two sets of reanalysis were used: wind speed (with spatial resolution of 0.25° and temporal resolution of 6 h) and significant wave height (with spatial resolution of 0.2° and temporal resolution of 3 h). For validation, seven MetOcean buoys were selected. In the statistical validation, Pearson’s correlation, coefficient of determination (R2), slope of the straight line, root mean square error (RMSE), mean square error (MSE), probability density function (PDF), mean and standard deviation were calculated. In the evaluation of offshore wind energy resources, the calculation of energy density was performed. The results showed correlations above 0.70 for wind speed and above 0.91 for significant wave height, and additionally, the RMSE values showed maximums of 2.31 m/s for wind speed and 0.28 cm for significant wave height. In the PDF comparison of buoy data and reanalysis, similarities were observed, mainly in the PDF parameters. The energy density presented values consistent with other studies (352–461 W/m²). The results show that the reanalysis data can be applicable in studies focusing on offshore wind potential

Evaluation of Wind and Wave Estimates from CMEMS Reanalysis for Brazil’s Offshore Energy Resource Assessment

This study aims to evaluate wind speed and significant wave height data from the Copernicus Marine Environment Monitoring Service (CMEMS) reanalysis using buoy measurements for offshore energy application off the east coast of Brazil. Such analysis has become important, since reanalysis datasets can be fundamental tools in identifying regions with wind energy potential that are suitable for the installation of offshore farms. Two sets of reanalysis were used: wind speed (with spatial resolution of 0.25° and temporal resolution of 6 h) and significant wave height (with spatial resolution of 0.2° and temporal resolution of 3 h). For validation, seven MetOcean buoys were selected. In the statistical validation, Pearson’s correlation, coefficient of determination (R2), slope of the straight line, root mean square error (RMSE), mean square error (MSE), probability density function (PDF), mean and standard deviation were calculated. In the evaluation of offshore wind energy resources, the calculation of energy density was performed. The results showed correlations above 0.70 for wind speed and above 0.91 for significant wave height, and additionally, the RMSE values showed maximums of 2.31 m/s for wind speed and 0.28 cm for significant wave height. In the PDF comparison of buoy data and reanalysis, similarities were observed, mainly in the PDF parameters. The energy density presented values consistent with other studies (352–461 W/m²). The results show that the reanalysis data can be applicable in studies focusing on offshore wind potential

Performance Assessment of Different Precipitation Databases (Gridded Analyses and Reanalyses) for the New Brazilian Agricultural Frontier: SEALBA

Since the early 2000s, Brazil has been one of the world’s leading grain producers, with agribusiness accounting for around 28% of the Brazilian GDP in 2021. Substantial investments in research, coupled with the expansion of arable areas, owed to the advent of new agriculture frontiers, led the country to become the world’s greatest producer of soybean. One of the newest agricultural frontiers to be emerging in Brazil is the one known as SEALBA, an acronym that refers to the three Brazilian states whose areas it is comprised of—Sergipe, Alagoas, and Bahia—all located in the Northeast region of the country. It is an extensive area with a favorable climate for the production of grains, including soybeans, with a rainy season that takes place in autumn/winter, unlike the Brazilian regions that are currently the main producers of these kinds of crops, in which the rainfall regime has the wet period concentrated in spring/summer. Considering that precipitation is the main determinant climatic factor for crops, the scarcity of weather stations in the SEALBA region poses an obstacle to an accurate evaluation of the actual feasibility of the region to a given crop. Therefore, the aim of this work was to carry out an assessment of the performance of four different precipitation databases of alternative sources to observations: two from gridded analyses, MERGE and CHIRPS, and the other two from ECMWF reanalyses, ERA5, and ERA5Land, and by comparing them to observational records from stations along the region. The analysis was based on a comparison with data from seven weather stations located in SEALBA, in the period 2001–2020, through three dexterity indices: the mean absolute error (MAE), the root mean squared errors (RMSE), and the coefficient of Pearson’s correlation (r), showing that the gridded analyzes performed better than the reanalyses, with MERGE showing the highest correlations and the lowest errors (global average r between stations of 0.96, followed by CHIRPS with 0.85, ERA5Land with 0.83, and ERA5 with 0.70; average MAE 14.3 mm, followed by CHIRPS with 21.3 mm, ERA5Land with 42.1 mm and ERA5 with 50.1 mm; average RMSE between stations of 24.6 mm, followed by CHIRPS with 50.8 mm, ERA5Land with 62.3 mm and ERA5 with 71.4 mm). Since all databases provide up-to-date data, our findings indicate that, for any research that needs a complete daily precipitation dataset for the SEALBA region, preference should be given to use the data in the following order of priority: MERGE, CHIRPS, ERA5Land, and ERA5