Avaliação dos prognósticos de precipitação simulada pelo modelo BRAMS na Amazônia Ocidental na estação chuvosa Evaluation of prognostic of rainfall model BRAMS in Western Amazonia during the wet season

O objetivo deste estudo é avaliar o modelo de previsão numérica do tempo BRAMS (Brazilian Regional Atmospheric Modelling System), a partir da comparação entre os valores preditos e os observados (dados do NCEP/NOAA (National Centers of Environmental Predictions/ National Oceanic and Atmospheric Administration) e do satélite TRMM (Tropical Rainfall Measuring Mission)). O modelo foi assimilado com dados do modelo global do NCEP/NOAA e do CPTEC/INPE. Foram realizadas comparações entre os valores preditos e os observados através da raiz do erro quadrático médio (RMSE) e do erro médio (ME) para os prognósticos de precipitação para os horizontes de 24, 48, 72 e 96 horas, do período de novembro de 2008 a março de 2009. Os resultados mostraram que o modelo BRAMS teve uma performance melhor quando assimilado com dados do modelo global do NCEP/NOAA comparado com as saídas a partir das assimilações do modelo global do CPTEC/INPE.<br>The objective of this study is to evaluate the model of numerical forecast BRAMS (Brazilian Regional Atmospheric Modelling System) from the comparison between the forecast and observed rainfall (data of NCEP/NOAA (National Centers of Environmental Predictions/ National Oceanic and Atmospheric Administration) and of TRMM satellite (Tropical Rainfall Measuring Mission)). The model used the initial conditions of global model of NCEP/NOAA e do CPTEC/INPE. Comparisons between predicted values and observed through were the root medium square error (RMSE) and of medium error (ME) for the forecast of rainfall of 24, 48, 72 and 96 hours, of the period November of 2008 to March of 2009. The results showed that the BRAMS model had better performance when treated with global model data from NCEP / NOAA compared with the outputs from the assimilation of the global model of CPTEC / INPE

Understanding the sources of uncertainty to reduce the risks of undesirable outcomes in large-scale freshwater ecosystem restoration projects: an example from the Murray–Darling Basin, Australia

There are a growing number of large-scale freshwater ecological restoration projects worldwide. Assessments of the benefits and costs of restoration often exclude an analysis of uncertainty in the modelled outcomes. To address this shortcoming we explicitly model the uncertainties associated with measures of ecosystem health in the estuary of the Murray&ndash; Darling Basin, Australia and how those measures may change with the implementation of a Basin-wide Plan to recover water to improve ecosystem health. Specifically, we compare two metrics &ndash; one simple and one more complex &ndash; to manage end-of-system flow requirements for one ecosystem asset in the Basin, the internationally important Coorong saline wetlands. Our risk assessment confirms that the ecological conditions in the Coorong are likely to improve with implementation of the Basin Plan; however, there are risks of a Type III error (where the correct answer is found for the wrong question) associated with using the simple metric for adaptive management.&nbsp