%0 Journal Article
%4 sid.inpe.br/mtc-m21b/2017/10.05.16.20
%2 sid.inpe.br/mtc-m21b/2017/10.05.16.20.18
%@doi 10.15446/rfna.v70n3.61805
%@issn 0304-2847
%T Evaluación de las estimaciones de precipitaciones por satélite TRMM (Algoritmos 3B42 V7 y RT) en Santo Antônio (Goiás, Brasil)
%D 2017
%9 journal article
%A Quirino, D. T.,
%A Casaroli, D.,
%A Jucá Oliveira, Rômulo Augusto,
%A Mesquita, M.,
%A Pego Evangelista, A. W.,
%A Alves Júnior, J.,
%@affiliation Universidade Federal de Goiás (UFG)
%@affiliation Centro de Investigación en Recursos para el Clima y el Agua del Cerrado (NUCLIRH)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Centro de Investigación en Recursos para el Clima y el Agua del Cerrado (NUCLIRH)
%@affiliation Centro de Investigación en Recursos para el Clima y el Agua del Cerrado (NUCLIRH)
%@affiliation Centro de Investigación en Recursos para el Clima y el Agua del Cerrado (NUCLIRH)
%@electronicmailaddress
%@electronicmailaddress
%@electronicmailaddress romulo.augusto@cptec.inpe.br
%B Revista Facultad Nacional de Agronomia
%V 70
%N 3
%P 8251-8261
%K Precipitation, Remote sensing, TRMM, Uncertainty quantification.
%X The rainfall has a direct influence on the agricultural productivity, being indispensable the knowledge of its spatiotemporal behavior in order to establish trends that will assist in the management of water resources, agricultural planning, hydrological monitoring and prevention of natural disasters. Thus, this work aimed to evaluate the accuracy of the TRMM satellite precipitation estimates in relation to the gauge-recorded precipitation. For this, the rainfall data from the weather station located in the municipality of Santo Antônio de Goiás-GO were used, being compared to the TRMM satellite datasets, especially, the algorithms 3B42 Version 7 (V7) and Real Time (RT), during the period from January 1998 to October 2015. The comparison of the TRMM satellite data showed that the ten-day and monthly precipitation records of the 3B42 V7 algorithm showed correlation values of 0.69 and 0.65, respectively, during the rainy season; in the dry season, the correlations were of 0.80 and 0.73. The ten-day concordance index ranged from 0.68 to 0.98 and the monthly concordance index ranged from 0.83 to 0.99. The algorithm 3B42 RT presented lower statistical results when compared to the 3B42 V7. The satellite precipitation estimates showed both trends of over estimation and underestimation; however, the satellite data can help research in the absence of information on the rainfall in the region.
%@language en