Climatic variability of precipitation simulated by a regional dynamic model in tropical South America

Despite advances in dynamic weather and climate modelling, simulations still present systematic errors in several regions of the globe. One way to improve models is the regionalized analysis of long-term simulations. In this context, this study aimed to analyze the seasonal and interannual variability of simulated rainfall over two contrasting regions of Tropical South America. Unlike several previous studies, our analyses were focused on areas with different rainfall regimes within two major regions: the Amazon Basin (AMZ) and Northeast Brazil (NEB). For this purpose, we used the RegCM4.6 climate model and performed two continuous 30-year simulations (1981-2010) with a 50 km grid spacing. In the EXP_EM simulation we used the convection parameterization of Emanuel (1991) and in the EXP_GR experiment we used Grell’s parameterization (1993). Simulations were compared with gridded precipitation data originated from different official sources in Brazil. The average monthly precipitation and its interannual variability were analyzed. Differences between simulations and observations were assessed using the Student’s t-test, with a p-value>0.01. The mean bias and Willmott’s coefficient of agreement were calculated. Considering these metrics, the EXP_EM simulation presented an overall advantage over the EXP_GR simulation. The experiments were more accurate in reproducing seasonality and interannual variability in the NEB. However, the model failed to accurately reproduce rainfall in areas closer to the geographic equator in the NEB, which may be associated with the double Intertropical Convergence Zone systematically formed by the model. We conclude that the model presents a clear dry bias over the equatorial AMZ and NEB, although it seems to be suitable to simulate climate variability in most of the studied regions. This must be taken into consideration when using the RegCM model for long term analysis or applications in seasonal forecast over the AMZ and the NEB.