Title
Precipitation diurnal cycle assessment of satellite-based estimates over Brazil
Date Issued
01 July 2020
Access level
open access
Resource Type
journal article
Author(s)
Afonso J.M.d.S.
Vila D.A.
Gan M.A.
Quispe D.P.
Barreto N.d.J.d.C.
Huaman Chinchay, Joao Henry
Palharini R.S.A.
Publisher(s)
Multidisciplinary Digital Publishing Institute (MDPI)
Abstract
The main objective of this study is to assess the ability of several high-resolution satellite-based precipitation estimates to represent the Precipitation Diurnal Cycle (PDC) over Brazil during the 2014-2018 period, after the launch of the Global Precipitation Measurement satellite (GPM). The selected algorithms are the Global Satellite Mapping of Precipitation (GSMaP), The Integrated Multi-satellitE Retrievals for GPM (IMERG) and Climate Prediction Center (CPC) MORPHing technique (CMORPH). Hourly rain gauge data from different national and regional networks were used as the reference dataset after going through rigid quality control tests. All datasets were interpolated to a common 0.1° × 0.1° grid every 3 h for comparison. After a hierarchical cluster analysis, seven regions with different PDC characteristics (amplitude and phase) were selected for this study. The main results of this research could be summarized as follow: (i) Those regions where thermal heating produce deep convective clouds, the PDC is better represented by all algorithms (in term of amplitude and phase) than those regions driven by shallow convection or low-level circulation; (ii) the GSMaP suite (GSMaP-Gauge (G) and GSMaP-Motion Vector Kalman (MVK)), in general terms, outperforms the rest of the algorithms with lower bias and less dispersion. In this case, the gauge-adjusted version improves the satellite-only retrievals of the same algorithm suggesting that daily gauge-analysis is useful to reduce the bias in a sub-daily scale; (iii) IMERG suite (IMERG-Late (L) and IMERG-Final (F)) overestimates rainfall for almost all times and all the regions, while the satellite-only version provide better results than the final version; (iv) CMORPH has the better performance for a transitional regime between a coastal land-sea breeze and a continental amazonian regime. Further research should be performed to understand how shallow clouds processes and convective/stratiform classification is performed in each algorithm to improve the representativity of diurnal cycle.
Volume
12
Issue
14
Language
English
OCDE Knowledge area
Meteorología y ciencias atmosféricas
Subjects
Scopus EID
2-s2.0-85088642533
Source
Remote Sensing
ISSN of the container
20724292
Sponsor(s)
Acknowledgments: The authors express their sincere thanks to the scientists responsible for the development of GSMaP, CMORPH and IMERG algorithms. They also acknowledge the National Institute for Space Research (INPE) for the rain gauge data database utilized in this study. The authors are thankful to the Ministry of Telecommunications, Information Technology, and Social Communication of Angola for sponsoring the publication of this article. The second author would like to acknowledge the São Paulo Research Foundation (FAPESP) for supporting this study through the project “Hydrometeorological Monitoring System (HMS) Based on Remote Sensing Products—2018/11160-2”.
Funding: This study was financed in part by and Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) and Coordenação de Aperfeiçoamento de Pessoal de Nível Superior Brazil (CAPES)—Finance Code 001.
This study was financed in part by and Conselho Nacional de Desenvolvimento Cient?fico e Tecnol?gico (CNPq) and Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior Brazil (CAPES)-Finance Code 001. The authors express their sincere thanks to the scientists responsible for the development of GSMaP, CMORPH and IMERG algorithms. They also acknowledge the National Institute for Space Research (INPE) for the rain gauge data database utilized in this study. The authors are thankful to the Ministry of Telecommunications, Information Technology, and Social Communication of Angola for sponsoring the publication of this article. The second author would like to acknowledge the S?o Paulo Research Foundation (FAPESP) for supporting this study through the project "Hydrometeorological Monitoring System (HMS) Based on Remote Sensing Products-2018/11160-2".
Sources of information:
Directorio de Producción Científica
Servicio Nacional de Meteorología e Hidrología del Perú