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		<citationkey>CardosoSilv:2006:AsFoPe</citationkey>
		<title>Assessing Forecast Performance of the empirical model to forecast precipitation in the South and Southeast Regions of Brazil</title>
		<format>CD-ROM; On-line.</format>
		<year>2006</year>
		<secondarytype>PRE CI</secondarytype>
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		<author>Cardoso, Andrea de Oliveira,</author>
		<author>Silva Dias, Pedro Leite,</author>
		<group>DMD-INPE-MCT-BR</group>
		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<affiliation>Instituto de Astronomia Geofísica e Ciências Atmosféricas, Departamento de Ciências Atmosféricas, Universidade de São Paulo (IAG/ USP)</affiliation>
		<electronicmailaddress>andreaca@cptec.inpe.br</electronicmailaddress>
		<electronicmailaddress>pldsdias@model.iag.usp.br</electronicmailaddress>
		<editor>Vera, Carolina,</editor>
		<editor>Nobre, Carlos,</editor>
		<e-mailaddress>andreaca@cptec.inpe.br</e-mailaddress>
		<conferencename>International Conference on Southern Hemisphere Meteorology and Oceanography, 8 (ICSHMO).</conferencename>
		<conferencelocation>Foz do Iguaçu</conferencelocation>
		<date>24-28 Apr. 2006</date>
		<publisher>American Meteorological Society (AMS)</publisher>
		<publisheraddress>45 Beacon Hill Road, Boston, MA, USA</publisheraddress>
		<pages>517-520</pages>
		<booktitle>Proceedings</booktitle>
		<tertiarytype>Poster</tertiarytype>
		<organization>American Meteorological Society (AMS)</organization>
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		<keywords>SST, empirical model, forecast , precipitation, South Brazil, Southeast  Brazil.</keywords>
		<abstract>Empirical models can provide reliable forecasts through the knowledge of the conceptual relationship between the predictand and predictors. An empirical model of monthly precipitation forecast (predictand) in South and Southeast Brazilian is presented in this paper, based on estimates of the variability of the Atlantic Ocean (OA) and Pacific Ocean (OP) sea surface temperature (SST) as predictors. The data sets of SST and precipitation were reduced in dimension: (a) A cluster analysis defined the monthly precipitation regions with homogeneous characteristics and (b) The rotated principal component analysis allowed to reduce the dimension of SST time series. The empirical model, based on linear regression analysis, was designed to forecast the average precipitation in homogeneous regions based on the time series of the scores of the principal components of SST as predictors. Lagged forecasts up to 4 months were performed. The results indicate similarities in the skill of the empirical model using SST modes with different lags. The SST scores constitute a robust set of predictors of the precipitation mainly over the SE Brazil, pointing out a significant contribution of modes with high amplitudes in the tropical and subtropical OP, completed by the SST variations in the subtropical belt of the South Atlantic. The positive extreme values of precipitation were under-estimated by the empirical model in all homogeneous regions. In the case of the South Region of Brazil the precipitation also are over-estimated. The annual cycle and the low frequency variations are well captured by the empirical model.The best performance of the model is obtained in the Southeastern region of Brazil. The empirical model forecasts are better than the climatological forecasts in all rain categories in the homogeneous regions.</abstract>
		<area>MET</area>
		<type>Climate predictions</type>
		<language>en</language>
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