Qualidade das estimativas de precipitação do satélite TRMM no estado do Rio Grande do Sul

Abstract

Understanding the spatial and temporal rainfall occurrence, improves the water resources management, both in order to prevent losses related to the occurrence of floods and droughts events, as in relation to the supply of the various sectors. Thus, satellite rainfall estimates are an alternative to obtain representative data of large areas, since the gauge data from meteorological stations are scarce, frequently due the low density of stations per area. However, these satellite products contain uncertainties when compared to gauge data. In this way, this study aims to evaluate the representativeness of rainfall estimates derived from satellites in the Rio Grande do Sul state. To this, were used satellite TRMM (3B42 V7) products, which were compared with gauge data in the State provided by the Agência Nacional de Águas and by the Instituto Nacional de Meteorologia, considering the period from 1998 to 2013. This paper compared rainfall estimates and gauge data was accomplished through a set statistics like skill scores, such as event detection percentage (PC), hit rate (H), false alerts ratios (FAR and F), critical success index (CSI), the ratio of planned events and observed (B), and the indexes of Heidke (HSS) and Pierce (PSS). Some equations were applied too: correlation coefficient (r) mean absolute error (MPE), root mean square error (RMSE), the Nash-Sutcliffe efficiency coefficient (NS) and bias. The data were compared in daily and accumulated series of 15 and 30 days, through the following methods: Pixel to Point, Point to Point, Pixel to Pixel, from Sub-pixels and aggregate analysis. The 3B42 products were also evaluated for their skill to determine heavy rainfall, using as reference intensity-duration-frequency equations (IDF) derived from gauge data. The results obtained by the methods, except for the analysis of heavy rainfall, not differ much from each other. Spatial analysis showed the relationship of assessments estimates has to the density of stations and the regions of Rio Grande do Sul, while specific analyzes indicated the good performance of TRMM even in Pixel to Point comparison. The results improved in steps that the daily series were accumulated in 15 and 30 days. It was evident the decrease of the quality of the estimates in the eastern RS region, where the ocean effects generates overestimates.