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Grid box-level evaluation of IMERG over Brazil at various space and time scales

André N. Gadelha, Victor Hugo R. Coelho, Alexandre C. Xavier, Luís Romero Barbosa, Davi C.D. Melo, Yunqing Xuan Orcid Logo, George J. Huffman, Walt A. Petersen, Cristiano das N. Almeida

Atmospheric Research, Volume: 218, Pages: 231 - 244

Swansea University Author: Yunqing Xuan Orcid Logo

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Abstract

This study evaluates the performance of the Integrated Multi-satellitE Retrievals for GPM (IMERG) Final Run product over Brazil by means of multi-temporal and -spatial analyses. The assessment of the IMERG Final Run product is based on six statistics obtained for the period between January-December...

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Published in: Atmospheric Research
ISSN: 0169-8095
Published: 2019
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URI: https://cronfa.swan.ac.uk/Record/cronfa47941
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spelling 2021-01-15T10:29:27.8478437 v2 47941 2018-12-12 Grid box-level evaluation of IMERG over Brazil at various space and time scales 3ece84458da360ff84fa95aa1c0c912b 0000-0003-2736-8625 Yunqing Xuan Yunqing Xuan true false 2018-12-12 CIVL This study evaluates the performance of the Integrated Multi-satellitE Retrievals for GPM (IMERG) Final Run product over Brazil by means of multi-temporal and -spatial analyses. The assessment of the IMERG Final Run product is based on six statistics obtained for the period between January-December 2016 (daily, monthly, and annual basis). The analysis consisted of comparing the satellite-based estimates against a ground-based gridded rainfall product created using daily records from 4,911 rain gauges distributed throughout Brazil. Overall, the results show that the IMERG product can effectively capture the spatial patterns of rainfall across Brazil. However, the IMERG product presents a slight tendency in overestimating the ground-based rainfall at all timescales. Furthermore, the performance of the satellite product varies throughout the region. The higher errors and biases are found in the North and Central-West regions, but the low density of rain gauges in those regions can be a source of large deviations between IMERG estimates and observations. A large underestimation of the IMERG data is evident along the coastal zone of the Northeast region, probably due to the inability of the passive microwave and infrared sensors to detect warm-rain processes over land. This study shows that the IMERG product can be a good source of rainfall data to complement the ground precipitation measurements in most of Brazil, although some uncertainties are found and need to be further studied. Journal Article Atmospheric Research 218 231 244 0169-8095 Gridded rainfall, Global precipitation measurement, Final run, Performance 1 4 2019 2019-04-01 10.1016/j.atmosres.2018.12.001 COLLEGE NANME Civil Engineering COLLEGE CODE CIVL Swansea University 2021-01-15T10:29:27.8478437 2018-12-12T13:41:57.0131507 André N. Gadelha 1 Victor Hugo R. Coelho 2 Alexandre C. Xavier 3 Luís Romero Barbosa 4 Davi C.D. Melo 5 Yunqing Xuan 0000-0003-2736-8625 6 George J. Huffman 7 Walt A. Petersen 8 Cristiano das N. Almeida 9 47941__12156__4e7caa674baa4b8c9ccaf1859a29ec8b.pdf ATMOSRES_2018_980_preprint.pdf 2018-12-12T14:14:06.5200000 Output 12578252 application/pdf Accepted Manuscript true 2019-12-12T00:00:00.0000000 Released under the terms of a Creative Commons Attribution Non-Commercial No Derivatives License (CC-BY-NC-ND). true eng
title Grid box-level evaluation of IMERG over Brazil at various space and time scales
spellingShingle Grid box-level evaluation of IMERG over Brazil at various space and time scales
Yunqing Xuan
title_short Grid box-level evaluation of IMERG over Brazil at various space and time scales
title_full Grid box-level evaluation of IMERG over Brazil at various space and time scales
title_fullStr Grid box-level evaluation of IMERG over Brazil at various space and time scales
title_full_unstemmed Grid box-level evaluation of IMERG over Brazil at various space and time scales
title_sort Grid box-level evaluation of IMERG over Brazil at various space and time scales
author_id_str_mv 3ece84458da360ff84fa95aa1c0c912b
author_id_fullname_str_mv 3ece84458da360ff84fa95aa1c0c912b_***_Yunqing Xuan
author Yunqing Xuan
author2 André N. Gadelha
Victor Hugo R. Coelho
Alexandre C. Xavier
Luís Romero Barbosa
Davi C.D. Melo
Yunqing Xuan
George J. Huffman
Walt A. Petersen
Cristiano das N. Almeida
format Journal article
container_title Atmospheric Research
container_volume 218
container_start_page 231
publishDate 2019
institution Swansea University
issn 0169-8095
doi_str_mv 10.1016/j.atmosres.2018.12.001
document_store_str 1
active_str 0
description This study evaluates the performance of the Integrated Multi-satellitE Retrievals for GPM (IMERG) Final Run product over Brazil by means of multi-temporal and -spatial analyses. The assessment of the IMERG Final Run product is based on six statistics obtained for the period between January-December 2016 (daily, monthly, and annual basis). The analysis consisted of comparing the satellite-based estimates against a ground-based gridded rainfall product created using daily records from 4,911 rain gauges distributed throughout Brazil. Overall, the results show that the IMERG product can effectively capture the spatial patterns of rainfall across Brazil. However, the IMERG product presents a slight tendency in overestimating the ground-based rainfall at all timescales. Furthermore, the performance of the satellite product varies throughout the region. The higher errors and biases are found in the North and Central-West regions, but the low density of rain gauges in those regions can be a source of large deviations between IMERG estimates and observations. A large underestimation of the IMERG data is evident along the coastal zone of the Northeast region, probably due to the inability of the passive microwave and infrared sensors to detect warm-rain processes over land. This study shows that the IMERG product can be a good source of rainfall data to complement the ground precipitation measurements in most of Brazil, although some uncertainties are found and need to be further studied.
published_date 2019-04-01T04:00:35Z
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