Validation of rainfall data estimated by GPM satellite on Southern Amazon region

Revista Ambiente & Água

Nadja Gomes Machado¹  Marcelo Sacardi Biudes²  Luiz Octavio Fabricio dos Santos³  Aryanne Resende de Melo Moura³  Altemar Lopes Pedreira Junior³  Carlos Alexandre Santos Querino⁴  Juliane Kayse Albuquerque da Silva Querino⁴ 

[1] Instituto Federal de Educação, Ciência e Tecnologia de Mato Grosso (IFMT), Cuiabá, MT, Brasil Departamento de Ensino. Programa de Pós-Graduação em Física Ambiental (PPGFA). ;Universidade Federal de Mato Grosso (UFMT), Cuiabá, MT, Brasil Instituto de Física. Programa de Pós-Graduação em Física Ambiental (PPGFA).;Universidade Federal do Amazonas (UFAM), Humaitá, Amazonas, Brasil Instituto de Educação, Agricultura e Ambiente (IEAA). ;Universidade Federal do Amazonas (UFAM), Humaitá, Amazonas, Brasil Instituto de Educação, Agricultura e Ambiente (IEAA). Programa de Pós-graduação em Ciências Ambientais. ;

关键词: remote sensing;    statistical analysis;    weather monitoring;   

DOI  :  10.4136/ambi-agua.2249

来源: DOAJ

【 摘 要 】

Rainfall is a meteorological variable of great importance for hydric balance and for weather studies. Rainfall estimation, carried out by satellites, has increased the climatological dataset related to precipitation. However, the accuracy of these data is questionable. This paper aimed to validate the estimates done by the Global Precipitation Measurement (GPM) satellite for the mesoregion of Southern Amazonas State, Brazil. The surface data were collected by the National Water Agency – ANA and National Institute of Meteorology – INMET, and is available at both institutions’ websites. The satellite precipitation data were accessed directly from the NASA webpage. Statistical analysis of Pearson correlation was used, as well as the Willmott’s “d” index and errors from the MAE (Mean Absolute Error) and RMSE (Root Mean Square Error). The GPM satellite satisfactorily estimated the precipitation, once it had correlations above 73% and high Willmott coefficients (between 0.86 and 0.97). The MAE and RMSE showed values that varied from 36.50 mm to 72.49 mm and 13.81 mm to 71.76 mm, respectively. Seasonal rain variations are represented accordingly. In some cases, either an underestimation or an overestimation of the rain data was observed. In the yearly totals, a high rate of similarity between the estimated and measured values was observed. We concluded that the GPM-based multi-satellite precipitation estimates can be used, even though they are not 100% reliable. However, adjustments in calibration for the region are necessary and recommended.

【 授权许可】

Unknown