Método de preenchimento de faltas de precipitação: o Nordeste e os índices oceânicos

Abstract

The Brazilian Northeast (NEB) is a region marked by great variability of rainfall both in time and space. Studies of variability are limited by the quantity of available data on rainfall. Most rainfall stations present time periods without observations or, in some cases, of data have to be eliminated because they are inconsistent. So, there is the need to essemble a rainfall database without missing data or gaps. This work has, as main goal, the development of a method for filling up gaps based on the calculation of the inverse transform of Haar wavelet analysis through the Multiresolution Analysis (AMR). For the study we selected data from 82 rainfall stations of the National Institute of Meteorology (INMET) and the National Water Agency (ANA) in the period 1975-2010. Analyzing the results of filling up series, it was observed that the method yielded results that preserve the statistical characteristics and intermittency of real rainfall fields, showing that the method is an efficient alternative to fill up the missing data. With the data filled, we evaluated the influence of sea surface temperature anomalies (SSTA) of the Pacific and Atlantic Oceans in the NEB rainfall totals. The cluster analysis applied to rainfall dataset identified three homogeneous groups within NEB territory, Northern, Eastern and Eastern. The results of the analysis of the standardized seasonal ASST series and rainfall for the Northern and Eastern of NEB showed a strong influence of El Niño-Southern Oscillation (ENSO), associated with cold and warm phases of the Pacific Decadal Oscillation (PDO), on rainfall totals. When ENSO and PDO are in phase - El Niño and PDO warm phase (ENWP) or La Niña and ODP cold phase (LNCP)- there is a greater likelihood that the impacts of extreme ENSO events are in opposite phases - El Niño and PDO cold phase (ENCP) or La Niña and ODP warm phase (LNMP)- the impacts of the ENSO episodes tend to be reduced, with less drier (wetter) conditions for ENCP (LNWP)