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		<isbn>978-85-17-0076-8</isbn>
		<label>807</label>
		<citationkey>MoraisTeix:2015:VaEsPa</citationkey>
		<title>Variabilidade espaço-temporal do padrão de ventos do setor oeste do oceano Atlântico Sul Equatorial</title>
		<format>Internet</format>
		<year>2015</year>
		<secondarytype>PRE CN</secondarytype>
		<numberoffiles>1</numberoffiles>
		<size>632 KiB</size>
		<author>Morais, Pedro Henrique Lima Silva,</author>
		<author>Teixeira, Carlos Eduardo Peres,</author>
		<electronicmailaddress>ocpmorais@gmail.com</electronicmailaddress>
		<editor>Gherardi, Douglas Francisco Marcolino,</editor>
		<editor>Aragão, Luiz Eduardo Oliveira e Cruz de,</editor>
		<e-mailaddress>wanderf@dsr.inpe.br</e-mailaddress>
		<conferencename>Simpósio Brasileiro de Sensoriamento Remoto, 17 (SBSR)</conferencename>
		<conferencelocation>João Pessoa</conferencelocation>
		<date>25-29 abr. 2015</date>
		<publisher>Instituto Nacional de Pesquisas Espaciais (INPE)</publisher>
		<publisheraddress>São José dos Campos</publisheraddress>
		<pages>4107-4114</pages>
		<booktitle>Anais</booktitle>
		<organization>Instituto Nacional de Pesquisas Espaciais (INPE)</organization>
		<transferableflag>1</transferableflag>
		<abstract>The winds are one key forcing for oceanographic applications, as they are a major determinant of ocean circulation. In addition, the winds are key to understanding the flow of energy, mass and gases between the atmosphere and oceans. In this sense, the objective of this study is to determine the spatial and temporal variability of the wind in the western portion of the Equatorial Atlantic Ocean (4° N - 6.7° S, 52° W - 32.3° W). Twenty-five years (1987-2011) of wind speed and direction from the Cross-Calibrated Multi-Platform Ocean Surface Wind Vector (CCMP) with 5 days temporal and 25 km spatial resolution were used. The CCMP is derived from measurements collected by various satellites, weather stations and data from numerical modeling. In this project the methodology of harmonic analysis will be used to quantify the annual variability inter and intranual data. Overall CCMP represented correctly variability timeline of winds in the area because when compared with in situ data from the PIRATA project, we obtained a good correlation in the behavior of speeds and directions throughout the study period. Based on the results, we can infer that the annual cycle is mainly responsible for the variability of the pattern of meridional winds in the region. As for zonal wind, the adjustment of the annual model is not satisfactory with small values of R². Considering the values of intranual variability are larger than annual, it is concluded that these are the main periods of variability of zonal winds in the region.</abstract>
		<area>SRE</area>
		<type>Oceanografia</type>
		<language>pt</language>
		<targetfile>p0807.pdf</targetfile>
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		<url>http://marte2.sid.inpe.br/rep-/sid.inpe.br/marte2/2015/06.15.15.36</url>
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