Characteristics and Diurnal Cycle of GPM Rainfall Estimates over the Central Amazon Region

Studies that investigate and evaluate the quality, limitations and uncertainties of satellite rainfall estimates are fundamental to assure the correct and successful use of these products in applications, such as climate studies, hydrological modeling and natural hazard monitoring. Over regions of t...

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Main Authors: Rômulo Oliveira, Viviana Maggioni, Daniel Vila, Carlos Morales
Format: Article
Language:English
Published: MDPI AG 2016-06-01
Series:Remote Sensing
Subjects:
GPM
Online Access:http://www.mdpi.com/2072-4292/8/7/544
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spelling doaj-561edc56c5da4b33acde7addb4c963882020-11-24T23:07:03ZengMDPI AGRemote Sensing2072-42922016-06-018754410.3390/rs8070544rs8070544Characteristics and Diurnal Cycle of GPM Rainfall Estimates over the Central Amazon RegionRômulo Oliveira0Viviana Maggioni1Daniel Vila2Carlos Morales3Centro de Previsão de Tempo e Estudos Climáticos (CPTEC), Instituto Nacional de Pesquisas Espaciais (INPE), São Jos é dos Campos, SP 12227-010, BrazilDepartment of Civil, Environmental, and Infrastructure Engineering, George Mason University (GMU), Fairfax, VA 22030, USACentro de Previsão de Tempo e Estudos Climáticos (CPTEC), Instituto Nacional de Pesquisas Espaciais (INPE), São Jos é dos Campos, SP 12227-010, BrazilDepartamento de Ciências Atmosféricas (DCA), Instituto de Astronomia, Geofísica e Ciências Atmosféricas (IAG), Universidade de São Paulo (USP), São Paulo, SP 05508-900, BrazilStudies that investigate and evaluate the quality, limitations and uncertainties of satellite rainfall estimates are fundamental to assure the correct and successful use of these products in applications, such as climate studies, hydrological modeling and natural hazard monitoring. Over regions of the globe that lack in situ observations, such studies are only possible through intensive field measurement campaigns, which provide a range of high quality ground measurements, e.g., CHUVA (Cloud processes of tHe main precipitation systems in Brazil: A contribUtion to cloud resolVing modeling and to the GlobAl Precipitation Measurement) and GoAmazon (Observations and Modeling of the Green Ocean Amazon) over the Brazilian Amazon during 2014/2015. This study aims to assess the characteristics of Global Precipitation Measurement (GPM) satellite-based precipitation estimates in representing the diurnal cycle over the Brazilian Amazon. The Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) and the Goddard Profiling Algorithm—Version 2014 (GPROF2014) algorithms are evaluated against ground-based radar observations. Specifically, the S-band weather radar from the Amazon Protection National System (SIPAM), is first validated against the X-band CHUVA radar and then used as a reference to evaluate GPM precipitation. Results showed satisfactory agreement between S-band SIPAM radar and both IMERG and GPROF2014 algorithms. However, during the wet season, IMERG, which uses the GPROF2014 rainfall retrieval from the GPM Microwave Imager (GMI) sensor, significantly overestimates the frequency of heavy rainfall volumes around 00:00–04:00 UTC and 15:00–18:00 UTC. This overestimation is particularly evident over the Negro, Solimões and Amazon rivers due to the poorly-calibrated algorithm over water surfaces. On the other hand, during the dry season, the IMERG product underestimates mean precipitation in comparison to the S-band SIPAM radar, mainly due to the fact that isolated convective rain cells in the afternoon are not detected by the satellite precipitation algorithm.http://www.mdpi.com/2072-4292/8/7/544satellite rainfall estimatesradar rainfall estimatesGPMIMERGGPROFuncertainty quantificationGoAmazon
collection DOAJ
language English
format Article
sources DOAJ
author Rômulo Oliveira
Viviana Maggioni
Daniel Vila
Carlos Morales
spellingShingle Rômulo Oliveira
Viviana Maggioni
Daniel Vila
Carlos Morales
Characteristics and Diurnal Cycle of GPM Rainfall Estimates over the Central Amazon Region
Remote Sensing
satellite rainfall estimates
radar rainfall estimates
GPM
IMERG
GPROF
uncertainty quantification
GoAmazon
author_facet Rômulo Oliveira
Viviana Maggioni
Daniel Vila
Carlos Morales
author_sort Rômulo Oliveira
title Characteristics and Diurnal Cycle of GPM Rainfall Estimates over the Central Amazon Region
title_short Characteristics and Diurnal Cycle of GPM Rainfall Estimates over the Central Amazon Region
title_full Characteristics and Diurnal Cycle of GPM Rainfall Estimates over the Central Amazon Region
title_fullStr Characteristics and Diurnal Cycle of GPM Rainfall Estimates over the Central Amazon Region
title_full_unstemmed Characteristics and Diurnal Cycle of GPM Rainfall Estimates over the Central Amazon Region
title_sort characteristics and diurnal cycle of gpm rainfall estimates over the central amazon region
publisher MDPI AG
series Remote Sensing
issn 2072-4292
publishDate 2016-06-01
description Studies that investigate and evaluate the quality, limitations and uncertainties of satellite rainfall estimates are fundamental to assure the correct and successful use of these products in applications, such as climate studies, hydrological modeling and natural hazard monitoring. Over regions of the globe that lack in situ observations, such studies are only possible through intensive field measurement campaigns, which provide a range of high quality ground measurements, e.g., CHUVA (Cloud processes of tHe main precipitation systems in Brazil: A contribUtion to cloud resolVing modeling and to the GlobAl Precipitation Measurement) and GoAmazon (Observations and Modeling of the Green Ocean Amazon) over the Brazilian Amazon during 2014/2015. This study aims to assess the characteristics of Global Precipitation Measurement (GPM) satellite-based precipitation estimates in representing the diurnal cycle over the Brazilian Amazon. The Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) and the Goddard Profiling Algorithm—Version 2014 (GPROF2014) algorithms are evaluated against ground-based radar observations. Specifically, the S-band weather radar from the Amazon Protection National System (SIPAM), is first validated against the X-band CHUVA radar and then used as a reference to evaluate GPM precipitation. Results showed satisfactory agreement between S-band SIPAM radar and both IMERG and GPROF2014 algorithms. However, during the wet season, IMERG, which uses the GPROF2014 rainfall retrieval from the GPM Microwave Imager (GMI) sensor, significantly overestimates the frequency of heavy rainfall volumes around 00:00–04:00 UTC and 15:00–18:00 UTC. This overestimation is particularly evident over the Negro, Solimões and Amazon rivers due to the poorly-calibrated algorithm over water surfaces. On the other hand, during the dry season, the IMERG product underestimates mean precipitation in comparison to the S-band SIPAM radar, mainly due to the fact that isolated convective rain cells in the afternoon are not detected by the satellite precipitation algorithm.
topic satellite rainfall estimates
radar rainfall estimates
GPM
IMERG
GPROF
uncertainty quantification
GoAmazon
url http://www.mdpi.com/2072-4292/8/7/544
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