%0 Journal Article
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%@holdercode {isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S}
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%@resumeid 8JMKD3MGP5W/3C9JH2E
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%3 martins_influence.pdf
%X Cloud cover index (CCI) obtained from satellite images contains information on cloud amount and their optical thickness. It is the chief climate data for the assessment of solar energy resources in most radiative transfer models, particularly for the model BRASIL-SR that is currently operational at CPTEC. The wide range of climate environments in Brazil turns CCI determination into a challenging activity and great effort has been directed to develop new methods and procedures to improve the accuracy of these estimations from satellite images (Martins 2001; Martins et al. 2003a; Ceballos et al. 2004). This work demonstrates the influence of CCI determination methods on estimates of surface solar irradiances obtained by the model BRASIL-SR comparing deviations among ground data and model results. Three techniques using visible and=or thermal infrared images of GOES-8 were employed to generate the CCI for input into the model BRASIL-SR. The groundtruth data was provided by the solar radiation station located at Caico=PE, in Brazilian Northeast region, which is part of the UNEP=GEF project SWERA (Solar and Wind Energy Resources Assessment). Results have shown that the application of the bi-spectral techniques have reduced mean bias error up to 66% and root mean square error up to 50% when compared to the usual technique for CCI determination based on the straightforward determination of month-by-month extremes for maximum and minimum cloud states.
%8 Apr.
%N 3-4
%@secondarydate 2007
%T The influence of cloud cover index on the accuracy of solar irradiance model estimates
%@secondarytype PRE PI
%K satellite data, physical model, surface, radiation, land.
%@visibility shown
%@group DMA-CPT-INPE-MCT-BR
%@group DMA-CPT-INPE-MCT-BR
%@group DMA-CPT-INPE-MCT-BR
%@e-mailaddress atus@cptec.inpe.br
%@secondarykey INPE--PRE/
%@issn 0177-7971
%2 sid.inpe.br/mtc-m15@80/2006/08.03.14.31.51
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE), Centro de Previsão de Tempo e Estudos Climáticos (CPTEC)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE), Centro de Previsão de Tempo e Estudos Climáticos (CPTEC)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE), Centro de Previsão de Tempo e Estudos Climáticos (CPTEC)
%B Meteorology and Atmospheric Physics
%P 169-180
%4 sid.inpe.br/mtc-m15@80/2006/08.03.14.31.50
%D 2008
%V 99
%@doi 10.1007/s00703-007-0272-5
%O DOI 10.1007/s00703-007-0272-5
%A Martins, Fernando Ramos,
%A Silva, Sheila de Araujo Bandeira,
%A Pereira, Enio Bueno,
%@dissemination WEBSCI; PORTALCAPES; COMPENDEX.
%@area MET