Reliability and discrepancies of rainfall and temperatures from remote sensing and Brazilian ground weather stations

Insufficient ground meteorological stations limit agricultural research in wide geographic areas, but high-quality data from remote sensing may decrease information gaps, when surface stations are scarce. This study compared meteorological datasets, estimated from satellite and ground meteorological...

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Bibliographic Details
Published in:Remote sensing applications 2020-04, Vol.18, p.100301, Article 100301
Main Authors: Teixeira de Aguiar, Jordene, Lobo, Murillo
Format: Article
Language:English
Subjects:
Agriculture
Climatology
Decision-support
Modelling
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Summary:Insufficient ground meteorological stations limit agricultural research in wide geographic areas, but high-quality data from remote sensing may decrease information gaps, when surface stations are scarce. This study compared meteorological datasets, estimated from satellite and ground meteorological stations in latitudes from 0 to 33 °S, to support agricultural research in Brazil. The dataset comprised 3600 records of monthly temperatures and rainfall from 01 Jan 2004 to 31 Dec 2014 in 30 Brazilian municipalities distributed in six regions, labeled according to their precipitation homogeneity. Climatic records from NASA's Prediction of Worldwide Energy Resource (POWER) online database were compared with data from Brazilian surface stations managed by National Institute of Meteorology (INMET). Monthly rainfall data showed satisfactory correlation coefficients for almost all locations, between 0.75 and 0.95 (p 
ISSN:2352-9385
2352-9385
DOI:10.1016/j.rsase.2020.100301