Analyse comparative des données pluviométriques in-situ vs les produits satellitaires TRMM3B42 pendant la saison des pluies au Mato Grosso.

International audienceThe validation of the algorithm TRMM3B42 is made from a hundred stations operated by the ANA across Mato Grosso for January of 2005 to 2008. Each precipitate volume in a grid cell satellite (0,25 ° * 0, 25 °) is compared statistically with the values of specific ground data. There is an average correlation R of 0.67 over the period studied. Bias and RMSD means are respectively 0.24 mm and 18.11 mm. The SKILL are fairly low, others techniques for validation of rainfall algorithms are then considered. The temporal analysis of statistical criteria shows that there is noticeable variation of quantitative estimates of rainfall by satellite as a function of time intervals.La validation de l'algorithme TRMM3B42 est réalisée à partir d'une centaine de stations gérées par l'ANA à l'échelle du Mato Grosso pour les mois de janvier de 2005 à 2008. Chaque volume précipité d'une cellule de la grille satellitaire (0,25°*0 ,25°) est comparé statistiquement aux valeurs ponctuelles des données au sol. On relève une corrélation moyenne R de 0,67 sur la période étudiée. Les biais et les RMSD moyens sont respectivement de 0,24 mm et de 18,11 mm. Les SKILL sont cependant faibles; d'autres techniques de validation d'algorithmes de précipitations sont alors envisagées. A partir de l'analyse temporelle des critères statistiques, on note des variations quantitatives des estimations des précipitations par satellite en fonction des intervalles de temps considérés

Analyse comparative des données pluviométriques in-situ vs les produits satellitaires TRMM3B42 pendant la saison des pluies au Mato Grosso.

International audienceThe validation of the algorithm TRMM3B42 is made from a hundred stations operated by the ANA across Mato Grosso for January of 2005 to 2008. Each precipitate volume in a grid cell satellite (0,25 ° * 0, 25 °) is compared statistically with the values of specific ground data. There is an average correlation R of 0.67 over the period studied. Bias and RMSD means are respectively 0.24 mm and 18.11 mm. The SKILL are fairly low, others techniques for validation of rainfall algorithms are then considered. The temporal analysis of statistical criteria shows that there is noticeable variation of quantitative estimates of rainfall by satellite as a function of time intervals.La validation de l'algorithme TRMM3B42 est réalisée à partir d'une centaine de stations gérées par l'ANA à l'échelle du Mato Grosso pour les mois de janvier de 2005 à 2008. Chaque volume précipité d'une cellule de la grille satellitaire (0,25°*0 ,25°) est comparé statistiquement aux valeurs ponctuelles des données au sol. On relève une corrélation moyenne R de 0,67 sur la période étudiée. Les biais et les RMSD moyens sont respectivement de 0,24 mm et de 18,11 mm. Les SKILL sont cependant faibles; d'autres techniques de validation d'algorithmes de précipitations sont alors envisagées. A partir de l'analyse temporelle des critères statistiques, on note des variations quantitatives des estimations des précipitations par satellite en fonction des intervalles de temps considérés

Controle de qualidade dos dados diários de chuva na Amazônia Legal brasileira (1998-2009)

http://sic2011.com/sic/arq/68145907326576814590732.pdfInternational audienceThe reports of rainfall data can be altered for technical or human reasons. This study presents an approach to detect erroneous raingauges data in Legal Brazilian Amazon over the period (1998-2009). We examine the precipitation data from a target station with those of nearby stations belonging to a buffer. This buffer of 260 km is determined from the decorrelation of rainfall data versus the distance between the raingauges. Differences normalized of nine statistical criteria of a given station with the average of these criteria of nearby raingauges are calculated to build a risk index. This risk index shows a gloal quality of rainfall data used.Os relatórios dos dados de precipitação podem ser alterados por razões técnicas ou humanas. Esse estudo apresenta uma metodologia para detectar dados errôneos nos medidores na Amazônia Legal brasileira ao longo do período (1998-2009). Examinamos os dados de precipitação de uma estação com os de estações vizinhas pertencentes a um buffer. Esse buffer de 260 km é determinado a partir da decorrelação dos dados de precipitação com base na distância entre os pluviômetros. As diferenças normalizadas entre nove critérios estatísticos de uma estação e a média desses critérios das estações próximas são calculadas para construir um índice de risco. Esse índice de risco representa a qualidade global dos dados pluviométricos utilizados

ANÁLISE GEOSTÁSTICA DAS PRECIPITAÇÕES MENSAIS NA AMAZÔNIA BRASILEIRA.

National audienceThe validation of TRMM-3B43 algorithm is performed using ground data available from January 2000 to December 2008 in the Brasilian Amazon. The statistical results of the validation allow to consider spatio-temporal variations of precipitation in Mato Grosso. Bias and error ratios means, independent of rainfall intensities, correctly detect seasonal patterns and alternating rainy seasons and dry seasons. Furthermore, the spatial statistics of these criteria highlights the climatic gradients for these periods. This study should be completed by an inter-comparison of global and regional precipitation satellite products in the Brazilian Amazonia.A validação do algoritmo TRMM-3B43 é realizada utilizando dados de campo disponíveis a partir de janeiro 2000 a dezembro de 2008 na Amazônia brasileira. Os resultados estatísticos da validação permitem fazer analises espaço-temporais das precipitaçãoes em Mato Grosso. Os razoes dos viés médios e os razoes dos erros médios, independentes da intensidade da precipitação, detectam corretamente os padrões sazonais e a mudança das estações chuvosas e secas. Além disso, a estatística espacial desses critérios, destaca os gradientes climáticos para esses dois períodos. Este estudo deve ser complementado por uma intercomparação de métodos de estimativa de precipitação global e regional em toda a Amazônia brasileira

Analyse géostatistique des précipitations mensuelles en Amazonie brésilienne.

International audienceThe validation of TRMM-3B43 algorithm was performed using ground data available from January 2000 to January 2008 in the Brasilian Amazon. The statistical results of the validation allowed to consider spatiotemporal variations of precipitation in Mato Grosso. Bias and error ratios means, independent of rainfall intensities, correctly detected seasonal patterns and alternating rainy and dry seasons. Furthermore, the spatial statistics of these criteria highlighted the climatic gradients for the dry season months characterized by low rainfall. It is expected to complete the investigation using inter-comparison of global and regional precipitation satellite products in the Brazilian Amazonia.La validation de l'algorithme TRMM-3B43 est réalisée à l'aide de données au sol disponibles de janvier 2000 à janvier 2008 en Amazonie brésilienne. Les résultats statistiques corrects de la validation permettent d'envisager l'étude spatio-temporelle des précipitations au Mato Grosso. Les biais et les ratios d'erreurs moyens, indépendants des intensités des précipitations, détectent correctement les régimes saisonniers et l'alternance des saisons des pluies et des saisons sèches. De plus, la spatialisation de ces critères statistiques met en évidence les gradients climatiques pour les mois de la saison sèche à faible pluviométrie. Cette étude doit être complétée par une inter comparaison de méthodes d'estimation des précipitations régionales et globales à l'échelle de l'Amazonie Brésilienne

Influence des surfaces terrestres sur l'erreur d'estimation des précipitations quotidiennes par satellite en Amazonie brésilienne

International audienceQuantitative precipitation estimates by remote sensing are performed on two areas with different physical properties: a forest area and deforested area in the Brazilian Amazonia. Rainfall ground data are used as a reference for validation of the merged satellite product CMORPH and the microwave product MWCOMB. The statistical results show larger errors for both satellite products over forest area. On this land surface, precipitation estimates by microwave are relatively inaccurate.L'estimation quantitative des précipitations par satellite est réalisée sur deux zones aux propriétés physiques différentes : une zone forestière et une zone déforestée en Amazonie Brésilienne. Les données pluviométriques au sol servent de référence aux validations du produit satellitaire multi-sources CMORPH et du produit micro-ondes MWCOMB. Les résultats statistiques montrent des erreurs plus importantes pour les deux produits satellitaires sur la zone forestière. Sur cette surface terrestre, les estimations des précipitations par micro-ondes sont relativement erronées

Rainfall Sensitivity Analyses for the HSB Sounder: An Amazon Case Study

This work examines the sensitivity of the different channels of the HSB (Humidity Sensor for Brazil), on board the AQUA satellite, for the purpose of retrieving surface rainfall over land. The analysis is carried out in two steps: (a) a theoretical study performed using two radiative transfer models, RTTOV and the so‐called Eddington method; and (b) the determination of the correlation between coincident measurements of HSB brightness temperatures and radar rainfall estimates during the DRY‐TO‐WET/AMC/LBA field campaign held in the Amazon region during September and October 2002. Theoretical results indicate the sensitivity of the HSB to water vapour content and cloud liquid water in the precipitation estimation. Theoretical and experimental analyses show that the channels 150 and 183±7 GHz are more adapted to estimate precipitation than the 183±1 and 183±3 GHz channels. The simulation analyses clearly show a hierarchy in physical effects that determine the brightness temperature of these channels. The rain and ice scattering dominate over the absorption of liquid water, and the liquid water absorption effect dominates over the absorption of water vapour. The results show that the 150 and 183±7 channels are more sensitive to the variation of liquid water and ice than the 183±1 and 183±3 channels. For the precipitation estimation using these channels, it was found that it is best adapted to the low precipitation rate situations, since the brightness temperature is rapidly saturated in the presence of high intense precipitation. A case study to estimate precipitation using the radar data has shown that it is possible to adjust a curve that relates the precipitation rate to the brightness temperature of the 150 GHz channel with a good level of accuracy for low precipitation rates