Lightning and precipitation produced by severe weather systems over Belém, Brazil

Eventos de raios nuvem-solo registrados pela rede de detecção do SIPAM, integrada por 12 sensores VAISALA LPATS IV, distribuídos no leste da Amazônia, foram analisados durante 4 tempestades com ocorrência de precipitação intensa em Belém-PA-Brasil, em 2006-2007. Esses casos selecionados, correspondem a eventos de chuva com mais de 25 mm/hora ou 40 mm/ 2 horas, de precipitação registrada por um pluviômetro instalado em 1º 47' 53" and 48º 30' 16" O. Com centro nessa localização, um círculos de 30, 10 e 5 km de raio foram traçados através de um sistema de informação geográfica e os dados de eventos de raios nessas áreas foram separados para analise. Durante essas tempestades, os eventos de raios ocorreram de maneira quase aleatória, sobre a área maior que já havia sido previamente coberta por sistemas convectivos de mesoescala, em todos os casos. Esse trabalho também mostrou a grande influencia dos sistemas de larga escala nas condições de tempo que levaram às tempestades severas estudadas. Adicionalmente, foi observado que, quando existe interação entre sistemas de larga e meso escalas, tanto a precipitação como o numero de relâmpagos aumentaram significativamente e a atividade elétrica nos círculos maiores pode anteceder a chuva no ponto central.

Weather forecasting for Eastern Amazon with OLAM model

O modelo OLAM tem como característica a vantagem de representar simultaneamente os fenômenos meteorológicos de escala global e regional através de um esquema de refinamento de grades. Durante o projeto REMAM, o modelo foi aplicado para alguns estudos de caso com objetivo de avaliar o desempenho do modelo na previsão numérica de tempo para a região leste da Amazônia. Estudos de caso foram feitos para os doze meses do ano de 2009. Os resultados do modelo para estes casos foram comparados com dados observados na região de estudo. A análise dos dados de precipitação mostrou que o modelo consegue representar a distribuição média da precipitação acumulada e os aspectos da sazonalidade da ocorrência dos eventos, mas não consegue prever individualmente a acumulação de precipitação local. No entanto, avaliação individual de alguns casos mostrou que o modelo OLAM conseguiu representar dinamicamente e prever, com alguns dias de antecedência, o desenvolvimento de fenômenos meteorológicos costeiros como as linhas de instabilidade, que são um dos mais importantes sistemas precipitantes da Amazônia.

Extended ionospheric amplitude scintillation model for GPS receivers

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Tropical Healthcare Epidemiology: Weather Determinants of the Etiology of Bloodstream Infections in a Brazilian Hospital

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Weather variables, water balance, growth, and agro industrial yield of sugarcane

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Monitoramento das irregularidades ionosféricas e cintilação dos sinais GNSS: em tempo real e pós-processado

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Weather Derivatives as a Potential Risk Management Tool for Irrigators

Irrigators in the Republican Basin and in parts of the North Platte Basin must learn to incorporate multiple year drought risk into their management plans, as they adapt to the limitations imposed by five-year pumping allocations. A major concern involves the implications of being water-short during the later years of the allocation period, because of an accumulative rainfall shortage or drought. Currently, producers can either ignore the risk of substantially lower incomes if their allocation is exhausted too soon, or reduce the risk by using less water early in the allocation period. The latter approach, however, may substantially reduce the present value of total net income over the five-year period. Alternatively, in the future it may be possible to use weather derivatives to manage income risk.

Polarimetric X-band weather radar measurements in the tropics: radome and rain attenuation correction

A polarimetric X-band radar has been deployed during one month (April 2011) for a field campaign in Fortaleza, Brazil, together with three additional laser disdrometers. The disdrometers are capable of measuring the raindrop size distributions (DSDs), hence making it possible to forward-model theoretical polarimetric X-band radar observables at the point where the instruments are located. This setup allows to thoroughly test the accuracy of the X-band radar measurements as well as the algorithms that are used to correct the radar data for radome and rain attenuation. For the campaign in Fortaleza it was found that radome attenuation dominantly affects the measurements. With an algorithm that is based on the self-consistency of the polarimetric observables, the radome induced reflectivity offset was estimated. Offset corrected measurements were then further corrected for rain attenuation with two different schemes. The performance of the post-processing steps was analyzed by comparing the data with disdrometer-inferred polarimetric variables that were measured at a distance of 20 km from the radar. Radome attenuation reached values up to 14 dB which was found to be consistent with an empirical radome attenuation vs. rain intensity relation that was previously developed for the same radar type. In contrast to previous work, our results suggest that radome attenuation should be estimated individually for every view direction of the radar in order to obtain homogenous reflectivity fields.

Assimilation of Meteosat Second Generation (MSG) satellite data in a regional numerical weather prediction model using a one-dimensional variational approach

The quality of temperature and humidity retrievals from the infrared SEVIRI sensors on the geostationary Meteosat Second Generation (MSG) satellites is assessed by means of a one dimensional variational algorithm. The study is performed with the aim of improving the spatial and temporal resolution of available observations to feed analysis systems designed for high resolution regional scale numerical weather prediction (NWP) models. The non-hydrostatic forecast model COSMO (COnsortium for Small scale MOdelling) in the ARPA-SIM operational configuration is used to provide background fields. Only clear sky observations over sea are processed. An optimised 1D–VAR set-up comprising of the two water vapour and the three window channels is selected. It maximises the reduction of errors in the model backgrounds while ensuring ease of operational implementation through accurate bias correction procedures and correct radiative transfer simulations. The 1D–VAR retrieval quality is firstly quantified in relative terms employing statistics to estimate the reduction in the background model errors. Additionally the absolute retrieval accuracy is assessed comparing the analysis with independent radiosonde and satellite observations. The inclusion of satellite data brings a substantial reduction in the warm and dry biases present in the forecast model. Moreover it is shown that the retrieval profiles generated by the 1D–VAR are well correlated with the radiosonde measurements. Subsequently the 1D–VAR technique is applied to two three–dimensional case–studies: a false alarm case–study occurred in Friuli–Venezia–Giulia on the 8th of July 2004 and a heavy precipitation case occurred in Emilia–Romagna region between 9th and 12th of April 2005. The impact of satellite data for these two events is evaluated in terms of increments in the integrated water vapour and saturation water vapour over the column, in the 2 meters temperature and specific humidity and in the surface temperature. To improve the 1D–VAR technique a method to calculate flow–dependent model error covariance matrices is also assessed. The approach employs members from an ensemble forecast system generated by perturbing physical parameterisation schemes inside the model. The improved set–up applied to the case of 8th of July 2004 shows a substantial neutral impact.