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		<isbn>978-85-17-00088-1</isbn>
		<label>60058</label>
		<citationkey>FagundesCorrPaiv:2017:AvDaPr</citationkey>
		<title>Avaliação dos dados de precipitação estimados pelo MSWEP para a bacia Amazônica</title>
		<format>Internet</format>
		<year>2017</year>
		<secondarytype>PRE CN</secondarytype>
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		<author>Fagundes, Hugo de Oliveira,</author>
		<author>Correa, Sly Wongchuig,</author>
		<author>Paiva, Rodrigo Cauduro Dias,</author>
		<electronicmailaddress>h.o.fagundes@hotmail.com</electronicmailaddress>
		<editor>Gherardi, Douglas Francisco Marcolino,</editor>
		<editor>Aragão, Luiz Eduardo Oliveira e Cruz de,</editor>
		<e-mailaddress>daniela.seki@inpe.br</e-mailaddress>
		<conferencename>Simpósio Brasileiro de Sensoriamento Remoto, 18 (SBSR)</conferencename>
		<conferencelocation>Santos</conferencelocation>
		<date>28-31 maio 2017</date>
		<publisher>Instituto Nacional de Pesquisas Espaciais (INPE)</publisher>
		<publisheraddress>São José dos Campos</publisheraddress>
		<pages>2027-2034</pages>
		<booktitle>Anais</booktitle>
		<organization>Instituto Nacional de Pesquisas Espaciais (INPE)</organization>
		<transferableflag>1</transferableflag>
		<abstract>Precipitation is one of the hydrological variables that has high difficulty level to estimate and has a greatimportance to many applications. Trying to solve this limitation, many products have been produced to estimate rainfall over quasi global coverage and usually used in places without data. The most recent of them is provided by Multi-Source Weighted-Ensemble Precipitation (MSWEP) database, with global coverage, 0.25º spatial and 3-hourly temporal resolution, which merged satellite imagery information, rain gauges and reanalysis data toprecipitations estimation. This paper therefore aims assess precipitations provided by MSWEP to Amazon basin,comparing them with in situ precipitations data provided by Brazilian Water National Agency (ANA). Themethodology used was a construction of monthly precipitation time series, with 25 years extension and after longterm average for each month. Also calculated cumulative average annual rainfall of long period with both MSWEPdata as to rain gauges, which they were spatially interpolated in order to obtain a grid of the same spatial resolution.From the calculation of absolute errors, it was noted that most of areas had good results considering errors between-50mm and 50mm. The cumulative average annual precipitation of long period also allowed us to observecharacteristic patterns of the Amazon basin, described by other authors, such as high values over Andes regions.</abstract>
		<area>SRE</area>
		<type>Hidrologia</type>
		<language>pt</language>
		<targetfile>60058.pdf</targetfile>
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