ABSTRACT
We studied rainfall characteristics of Brazil for the period 1979–2011. This is an update for an earlier study with data from 1958 to 1978. We compared the three consecutive wet and dry ...months in the two data sets. In the northern most part rainy season earlier was in April to July and now it is occurring later. In a large part of the south central region the rainy season in austral summer and dry season in austral winter did not change. However, to the east of this region rainy season in the latter data occurs earlier. Calculation of linear tendencies showed, that over the northern Amazon region there is a significant increase of rainfall. This agreed with previous results. Over this region dry season is becoming drier and wet season wetter. In the west of Northeast Brazil (NEB) there is an increase of rainfall. In southeast Brazil there is a region of highly significant decrease of rainfall in both wet and dry seasons. This is confirmed in our analysis on river discharges in Sao Paulo and Minas Gerais states. The negative tendencies in rainfall have great impact on the hydroelectric generation not only in this region but also at the national level because the hydroelectric dams furnish energy on a national level. The increase in rainfall in Northern Amazon is probably associated with Atlantic warming that resulted in higher moisture transport from east. The decrease of rainfall in southeast Brazil seems to be associated with the plummet of rain producing systems from south due to increase of mean sea level pressure in the south.
In an attempt to validate the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) over Brazil, TRMM PR estimates are compared with rain gauge station data from Agência Nacional de ...Energia Elétrica (ANEEL). The analysis is conducted on a seasonal basis and considers five geographic regions with different precipitation regimes. The results showed that TRMM PR seasonal rainfall is well correlated with ANEEL rainfall (correlation coefficients are significant at the 99% confidence level) over most of Brazil. The random and systematic errors of TRMM PR are sensitive to seasonal and regional differences. During December to February and March to May, TRMM PR rainfall is reliable over Brazil. In June to August (September to November) TRMM PR estimates are only reliable in the Amazonian and southern (Amazonian and southeastern) regions. In the other regions the relative RMS errors are larger than 50%, indicating that the random errors are high.
Large precipitation deficits observed during the 2001 austral summer over the southeast region of Brazil contributed to the worsening of the energy crisis that was occurring in the country, with ...unprecedented social and economic consequences. Reliable information on the beginning of the rainy season was essential for the Brazilian government to manage the energy crisis. The purpose of this study is to determine the rainy season in this region and to point out the risk of using outgoing longwave radiation (OLR) data to estimate the beginning of it. The results show that when OLR data are used the beginning and the end dates of the rainy season are wrongly anticipated and delayed, respectively. The present study aims to provide useful information for the management of the impact of adverse climate conditions such as the one in 2001 by basing the analysis on rainfall data instead of on OLR.
A comparison between TRMM PR rainfall estimates and rain gauge data from ANEEL and combined gauge/satellite data from GPCP over South America (SA) is made. In general, the annual and seasonal ...regional characteristics of rainfall over SA are qualitatively well reproduced by TRMM PR and GPCP. It is found that over most of SA GPCP exceeds TRMM PR rainfall. The largest positive differences between GPCP and TRMM PR data occur in the north SA, northwestern and central Amazonia. However, there are regions where GPCP rainfall is lower than TRMM PR, particularly in the Pacific coastal regions and in southern Brazil. We suggest that the cause for the positive differences GPCP minus TRMM PR rainfall are related to the fact that satellite observations based on infrared radiation and outgoing longwave radiance sensors overestimate convective rainfall in GPCP and the cause for the negative differences are due to the random errors in TRMM PR. Rainfall differences in the latter phases of the 1997/98 El Niño and 1998/99 La Niña are analyzed. The results showed that the rainfall anomalies are generally higher in GPCP than in TRMM PR, however, as in the mean annual case, there are regions where the rainfall in GPCP is lower than in TRMM PR. The higher positive (negative) differences between the rainfall anomalies in GPCP and TRMM PR, which occur in the central Amazonia (southern Brazil), are reduced (increased) in the El Niño event. This is due to the fact that during the El Niño episode the rainfall decreases in the central Amazonia and increases in the southern Brazil. Consequently, the overestimation of the convective rainfall by GPCP is reduced and the overestimation of the rainfall by TRMM PR is increased in these two regions, respectively.
The relationships of strong winds and heavy rainfall in Sao Paulo State, Brazil, was investigated. Wind data from Project Elektro/Climatico collected by thirteen Platforms of Data Collection were ...used. The results showed that in the west sector the occurrence of strong winds was higher in the center and south areas and decreased northwards. In the central sector the occurrence of strong wind episodes was higher southwards while in the litoral it was lower due to probably the lack of wind data collected during the austral summer. In Teodoro Sampaio, Andradina, Santa Rita d'Oeste, Votuporanga (west), Rio Claro, Tatui (central) and Ubatuba (litoral) 15, 18, 28, 12, 11, 7 and 3 extreme events occurred, respectively (maximum wind higher than 20 ms-1 together with rainfall higher than 25 mm day-1). A case study of an episode of extreme event which occurred in Andradina on 15 October 2009 was examined. Heavy rainfall accompanied with high winds and strong divergence at 200 hPa and ascending motion were observed in the region due to intense convection along a cold front that moved fast over Sao Paulo State.
The identification of regions with strong winds and their relation with heavy precipitation must drive electrical energy generation and distribution what is important nowadays. So, the main importance of this research is its applicability to the energy sector.
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