Avaliação da chuva prevista em curto prazo por radar meteorológico

This article presents the first evaluation of the method used by the Brazilian Centre for Monitoring and Early Warning of Natural Disasters for the short term forecast (nowcasting) of precipitation by weather radar. In this evaluation, four cases of intense rainfall in the radius of Pico do Couto radar were studied, giving the flood risk alerts sent for the municipality of Nova Friburgo, in the state of Rio de Janeiro. In relation to rain gauge data, a median under rate of 43% for the radar precipitation was observed when using the SRI (Surface Rainfall Intensity) method. After the rainfall correction, the cross-correlation extrapolation method was evaluated for the 30, 60, 90 and 120 minute forecast horizons, with accumulated precipitation every 30 minutes. The probabilities of detection (POD) obtained higher values for lower rainfall thresholds (at least 1 or 5 mm of accumulated rainfall) when compared to larger amount accumulated (20 and 30 mm). The spatial and temporal series of rainfall presented higher errors (MAE and RMSE) for 90 and 120 minutes of forecast. For all the events, an overestimate (PBIAS positive) of the predictions was observed in relation to the observed radar rain field itself.Este artigo traz a primeira avaliação do método utilizado pelo Centro Nacional de Monitoramento e Alerta de Desastres Naturaispara os prognósticos em curto prazo da precipitação por radares meteorológicos. Nesta avaliação foram estudados quatro casosde chuva intensa no raio de cobertura do radar Pico do Couto, que originaram alertas de risco para o município de nova Friburgo,no estado do Rio de Janeiro. Em relação aos dados pluviométricos in situ, foi observada uma subestimativa mediana de 43% daprecipitação pelo radar ao utilizar o método SRI (Surface Rainfall Intensity). Após a correção dos campos de chuva, a metodologiapara extrapolação por cross-correlation (correlação cruzada) foi avaliada para os horizontes de previsão de 30, 60, 90 e 120minutos, com a precipitação acumulada a cada 30 minutos. As probabilidades de detecção (POD) obtiveram maiores valores paralimiares de chuva mais baixos (pelo menos 1 ou 5 mm de chuva acumulada) ao comparado com acumulados de chuva maiores(20 e 30 mm), como observado em estudos anteriores. Da mesma forma, as séries espaciais e temporais de chuva apresentarammaiores erros (MAE e RMSE) para os prognósticos de 90 e 120 minutos de previsão. Em todos os eventos foi observada umasuperestimativa (PBIAS positivo) média das previsões em relação ao próprio campo observado de chuva do radar

SIMULAÇÃO DE CAMPOS PROBABILÍSTICOS DE PRECIPITAÇÃO A PARTIR DE UM MÉTODO GEOESTATÍSTICO

Inúmeras regiões no mundo já foram atingidas, pelo menos uma vez, por eventos extremos de inundação os quais causaram grandes perdas socioeconômicas, ambientais entre outros. Os dados de estimação de precipitação são essenciais para realizar a previsão destes eventos e gerar alertas que possam minimizar os danos que podem ser causados. Uma das características principais destes eventos é a elevada variabilidade espacial e temporal. Devido a sua complexidade, a previsão dos mesmos possui diversas fontes de incertezas, como as incertezas provenientes dos campos de chuva observados. Estes dados, por sua vez, possuem papel importante no desempenho dos sistemas de previsão. Este estudo tem como objetivo principal desenvolver uma metodologia, baseada em um método geoestatístico, capaz de gerar cenários possíveis de chuva a partir de dados de radar meteorológico e de pluviômetros. A área de estudos localiza-se na região de Campinas, estado de São Paulo, na qual inúmeros eventos extremos já foram detectados. Os resultados obtidos apresentam que o método desenvolvido neste estudo pode ser uma solução para quantificar as incertezas que podem ser encontradas nos dados de precipitação observada

Impact of soil moisture over Palmer Drought Severity Index and its future projections in Brazil Avaliação da umidade do solo e do Índice de Severidade de Seca de Palmer no Brasil e suas projeções futuras

Soil moisture is a main factor for the study of drought impacts on vegetation. Drought is a regional phenomenon and affects the food security more than any other natural disaster. Currently, the monitoring of different types of drought is based on indexes that standardize in temporal and regional level allowing, thus, comparison of water conditions in different areas. Therefore, in order to assess the impact of soil moisture during periods of drought, drought Palmer Severity Index was estimated for the entire region of the territory. For this were used meteorological data (rainfall and evapotranspiration) and soil (field capacity, permanent wilting point and water storage in the soil). The data field capacity and wilting point were obtained from the physical properties of soil; while the water storage in soil was calculated considering the water balance model. The results of the PSDI were evaluated during the years 2000 to 2015, which correspond to periods with and without occurrence of drought. In order to assess the future drought projections, considering the set of the Coupled Model Intercomparison rainfall data Project Phase 5 (CMIP5). Climate projections precipitation in CMIP5 for the period 2071-2100 was extracted generating entitled forcing scenarios Representative Concentration Pathways - RCPs, and referred to as RCOP 8.5, corresponding to an approximate radiative forcing the end the twenty-first century of 8.5 Wm-2. The results showed that the PDSI is directly associated with climatological patterns of precipitation and soil moisture in any spatial and temporal scale (including future projections). Therefore, it is concluded that the PDSI is an important index to assess soil moisture different water conditions, as well as the association with economic and social information to create risk maps for subsidies to decision makers.Peer ReviewedPostprint (published version

ESTUDO DAS TENDÊNCIAS DO TOTAL DE PRECIPITAÇÃO E DO NÚMERO DE DIAS PARA EVENTOS EXTREMOS NO LITORAL NORTE, SP

Eventos extremos de chuvas podem tornar-se mais frequentes, aumentando a possibilidade de desastres naturais, tais como grandes inundações e deslizamento de solos. O interesse da sociedade ocorre devido às possíveis perdas materiais e humanas. Assim, as tendências anual e sazonal do número de dias chuvosos e total de precipitação foram estudadas para vários limiares de taxas diárias de precipitação extrema no Litoral Norte de São Paulo. De acordo com o número de dias de chuva, observou-se que houve um aumento de eventos com taxas maiores ou iguais a 50 mm/dia. Para as taxas maiores que 25,4 mm/dia, houve um provável aumento significativo de ambas as tendências para Maresias/SS, Caraguatatuba e Picinguaba/U para o ano, verão e primavera. De acordo com o número de dias chuvosos, observou-se que houve um aumento provável da tendência em Caraguatatuba para taxas maiores ou iguais a 50 mm/dia no ano e outono. Picinguaba/U apresentou provável aumento significante das tendências no inverno e ano. No verão, não houve nenhum caso de tendência significante para 25,4 mm/dia; aumentou significantemente provável em Picinguaba/U e Caraguatatuba para total de precipitação para 50 mm/dia e para ambas as variáveis em Mato Dentro/U, Caraguatatuba e São Francisco/SS para 75 mm/di

Rainfall characteristics over tropical and subtropical South America

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Avaliação da umidade do solo em áreas densamente vegetadas sobre o Brasil, utilizando observações do sensor MIRAS/SMOS

In order to assess the pattern of soil moisture in densely vegetated areas, obtained from the new version of the algorithm LPRM calibrated for Brazil (LPRM_BR), we used data of brightness temperature sensor MIRAS aboard the SMOS satellite during the period 04-09 March to different regions. These locations were selected according to availability of soil moisture data measured "in situ". Thus, observational data of volumetric water content in the soil (at 10 cm) were collected from automatic meteorological stations of CPTEC/INPE distributed in different regions with dense vegetation. To calculate the degree of association between satellite and observed data, we used statistical tools such as correlation (R) and BIAS. The results of both R and BIAS were satisfactory in various locations. The correlation coefficients were relatively high for regions with dense vegetation, such as Esec Maraca (RR), Parna Jaú (AC), Tailândia (PA) e Votuporanga (AM), whose coefficients were 0.84, 0.99 and 1, respectively. Therefore, we conclude that the LPRM_BR infer accurate values of soil moisture to areas with dense vegetation, using the MIRAS sensor L band. So, products derived from the LPRM_BR can be used for different purposes such as: monitoring of soil moisture in extreme rain events contributing to issuing warnings of landslides; support in planning for planting and / or irrigation for certain crops; data assimilation in models of numerical weather prediction, which may contribute to the improvement of weather forecasting. However, research with more detailed data from SMOS become necessary to better evaluate the performance of LPRM_BR.Pages: 9248-925

Ground-Based Microwave Radiometer Calibration: an Overview

<div><p>ABSTRACT This paper intends to briefly present some basic concepts on the microwave radiometry and radiometer calibration research in remote sensing applications and demonstrate results and analysis of the cryogenic calibration of a microwave ground-based radiometer currently deployed in scientific campaigns in Brazil. The equipment described in this text operates at 22 - 30 GHz and at 51 - 59 GHz frequency ranges and uses as the calibration standard a target cooled by liquid nitrogen. Since an accurate calibration (with observation errors below 0.5 K) is important to provide confidence in the retrieval of vertical temperature and humidity profiles, this work aims also to comment on some effects of the errors in calibration procedure on the atmospheric parameters of interest.</p></div

Diurnal cycle of rainfall over tropical South America using 3-yr TRMM-PR data

Three years of Tropical Rainfall Measuring Mission Precipitation Radar (TRMM-PR) data, acquired during the period 01/01/1998 31/12/2000 over the tropical South America, were analysed in order to evaluate and model the diurnal cycle of rainfall near the surface. Amplitude and phase of the first harmonic revealed five main centres of high rainfall and the timing of maximum precipitation occurrence. The phase map showed the preferred path of rainfall and suggested that precipitation tends to propagate in bands which originate in the east and west extrems of the Amazon region. The easterly rain bands occur in the same area where squall lines were previously detected and mapped by others. Because there is little reference to the westerly bands in scientific literature, the results presented in this assignment are considered new findings. Those bands originate along the eastern slopes of the Andes Cordillera during the first hours of the day and propagate Northwest-Southeast oriented towards the Central Amazon for up to 18 hours. The results should be considered preliminary rather than definitive due to the low TRMM-PR sampling rate. More studies using ground radar or a longer TRMM-PR time series must be carried out in order to confirm the existence of the westerly propagating systems and shed more light on the results presented by this work