Journal article 925 views 330 downloads
Grid box-level evaluation of IMERG over Brazil at various space and time scales
Atmospheric Research, Volume: 218, Pages: 231 - 244
Swansea University Author: Yunqing Xuan
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DOI (Published version): 10.1016/j.atmosres.2018.12.001
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...
Published in: | Atmospheric Research |
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ISSN: | 0169-8095 |
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2019
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URI: | https://cronfa.swan.ac.uk/Record/cronfa47941 |
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2023-02-14T16:25:15.3516917 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 ACEM 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 Aerospace, Civil, Electrical, and Mechanical Engineering COLLEGE CODE ACEM Swansea University 2023-02-14T16:25:15.3516917 2018-12-12T13:41:57.0131507 Faculty of Science and Engineering School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Civil Engineering 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 |
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3ece84458da360ff84fa95aa1c0c912b |
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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 |
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Atmospheric Research |
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218 |
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Swansea University |
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0169-8095 |
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10.1016/j.atmosres.2018.12.001 |
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Faculty of Science and Engineering |
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School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Civil Engineering{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Civil Engineering |
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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 |
2019-04-01T19:43:11Z |
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1822160628314275840 |
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11.048453 |