Comparative Skill of Numerical Weather Forecasts in Eastern Amazonia

Abstract

<p class="MsoNormal"> <span lang="EN-US">The present study evaluates the performance of three numerical weather forecasting models: Global Forecast System (GFS), Brazilian Regional Atmospheric Modelling System (BRAMS) and ETA Regional Model (ETA), by means of the Mean Error (<i>ME</i>) and the Root Mean Square Error (<i>RMSE</i>), during the most rainy four months period (January to April 2012) on Eastern Amazonia. The models displayed errors of superestimation and underestimation with respect to the observed precipitation, mainly over center-north of Pará and all of Amapá, where the precipitation is higher. Among the analyzed models, GFS shows the best performance, except during January and March, when the model to underesti</span><span lang="EN-US">mated precipitation, possibly due to the anomalously high values recorded.</span><span lang="EN-US"><?xml:namespace prefix = o /><o:p></o:p></span> </p

Dynamical Donwscaling for Railroad Areas in Eastern Amazon and Southeastern Brazil: Current Climate and Near-Future Projections

“…These results are consistent with observational analysis that used stations and satellite data [3] [7] [8] [17]. Although models have presented generalized underestimation, the REGCM4 regional simulations for the current climate rainfall patterns showed improvements on spatial representation and intensity of the rainfall in comparison with the MPI global model results.…”

Analyses of Shallow Convection over the Amazon Coastal Region Using Satellite Images, Data Observations and Modeling

“…For decades, relating the local nature of convection and its interaction with the atmosphere on a large scale has been one of the main challenges of the assessment of tropical meteorology of the Amazon region (Adams et al, 2009). Although the centers of Brazilian meteorology show generally good accuracy in predicting the weather through the use of Atmospheric General Circulation Models (AGCMs) or Regional Forecast Models (see Chou and Nobre (2015) and also Nobre et al (2013) for the complete evaluation of these models) they still experience some difficulty in prediction in the Amazon, considered a peculiar region, with complex interactions and various convective regimes where those models do not have an accurate parameterization to represent the atmospheric mechanisms that cause precipitation over that region (Moraes et al, 2013;Bechtold et al, 2004). Convection parameterization relates unresolved convective properties and its associated transport to the resolved large scale.…”