Mapping the daily rainfall over an ungauged tropical micro-watershed: a downscaling algorithm using gpm data
In this study, half-hourly Global Precipitation Mission (GPM) satellite precipitation data were downscaled to produce high-resolution daily rainfall data for tropical coastal micro-watersheds (100-1000 ha) without gauges or with rainfall data conflicts. Currently, daily-scale satellite rainfall down...
Saved in:
Main Authors: | , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020
|
Subjects: | |
Online Access: | http://eprints.utm.my/id/eprint/86588/1/MohdRizaludinMahmud2020_MappingtheDailyRainfalloveranUngaugedTropical.pdf http://eprints.utm.my/id/eprint/86588/ https://dx.doi.org/10.3390/W12061661 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
id |
my.utm.86588 |
---|---|
record_format |
eprints |
spelling |
my.utm.865882020-09-30T08:43:53Z http://eprints.utm.my/id/eprint/86588/ Mapping the daily rainfall over an ungauged tropical micro-watershed: a downscaling algorithm using gpm data Mahmud, M. R. Yusof, A. A. M. Reba, M. Hashim, M. GE Environmental Sciences In this study, half-hourly Global Precipitation Mission (GPM) satellite precipitation data were downscaled to produce high-resolution daily rainfall data for tropical coastal micro-watersheds (100-1000 ha) without gauges or with rainfall data conflicts. Currently, daily-scale satellite rainfall downscaling techniques rely on rain gauge data as corrective and controlling factors, making them impractical for ungauged watersheds or watersheds with rainfall data conflicts. Therefore, we used high-resolution local orographic and vertical velocity data as proxies to downscale half-hourly GPM precipitation data (0.1°) to high-resolution daily rainfall data (0.02°). The overall quality of the downscaled product was similar to or better than the quality of the raw GPM data. The downscaled rainfall dataset improved the accuracy of rainfall estimates on the ground, with lower error relative to measured rain gauge data. The average error was reduced from 41 to 27 mm/d and from 16 to 12 mm/d during the wet and dry seasons, respectively. Estimates of localized rainfall patterns were improved from 38% to 73%. The results of this study will be useful for production of high-resolution satellite precipitation data in ungauged tropical micro-watersheds. MDPI AG 2020-06 Article PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/86588/1/MohdRizaludinMahmud2020_MappingtheDailyRainfalloveranUngaugedTropical.pdf Mahmud, M. R. and Yusof, A. A. M. and Reba, M. and Hashim, M. (2020) Mapping the daily rainfall over an ungauged tropical micro-watershed: a downscaling algorithm using gpm data. Water (Switzerland), 12 (6). ISSN 2073-4441 https://dx.doi.org/10.3390/W12061661 DOI:10.3390/W12061661 |
institution |
Universiti Teknologi Malaysia |
building |
UTM Library |
collection |
Institutional Repository |
continent |
Asia |
country |
Malaysia |
content_provider |
Universiti Teknologi Malaysia |
content_source |
UTM Institutional Repository |
url_provider |
http://eprints.utm.my/ |
language |
English |
topic |
GE Environmental Sciences |
spellingShingle |
GE Environmental Sciences Mahmud, M. R. Yusof, A. A. M. Reba, M. Hashim, M. Mapping the daily rainfall over an ungauged tropical micro-watershed: a downscaling algorithm using gpm data |
description |
In this study, half-hourly Global Precipitation Mission (GPM) satellite precipitation data were downscaled to produce high-resolution daily rainfall data for tropical coastal micro-watersheds (100-1000 ha) without gauges or with rainfall data conflicts. Currently, daily-scale satellite rainfall downscaling techniques rely on rain gauge data as corrective and controlling factors, making them impractical for ungauged watersheds or watersheds with rainfall data conflicts. Therefore, we used high-resolution local orographic and vertical velocity data as proxies to downscale half-hourly GPM precipitation data (0.1°) to high-resolution daily rainfall data (0.02°). The overall quality of the downscaled product was similar to or better than the quality of the raw GPM data. The downscaled rainfall dataset improved the accuracy of rainfall estimates on the ground, with lower error relative to measured rain gauge data. The average error was reduced from 41 to 27 mm/d and from 16 to 12 mm/d during the wet and dry seasons, respectively. Estimates of localized rainfall patterns were improved from 38% to 73%. The results of this study will be useful for production of high-resolution satellite precipitation data in ungauged tropical micro-watersheds. |
format |
Article |
author |
Mahmud, M. R. Yusof, A. A. M. Reba, M. Hashim, M. |
author_facet |
Mahmud, M. R. Yusof, A. A. M. Reba, M. Hashim, M. |
author_sort |
Mahmud, M. R. |
title |
Mapping the daily rainfall over an ungauged tropical micro-watershed: a downscaling algorithm using gpm data |
title_short |
Mapping the daily rainfall over an ungauged tropical micro-watershed: a downscaling algorithm using gpm data |
title_full |
Mapping the daily rainfall over an ungauged tropical micro-watershed: a downscaling algorithm using gpm data |
title_fullStr |
Mapping the daily rainfall over an ungauged tropical micro-watershed: a downscaling algorithm using gpm data |
title_full_unstemmed |
Mapping the daily rainfall over an ungauged tropical micro-watershed: a downscaling algorithm using gpm data |
title_sort |
mapping the daily rainfall over an ungauged tropical micro-watershed: a downscaling algorithm using gpm data |
publisher |
MDPI AG |
publishDate |
2020 |
url |
http://eprints.utm.my/id/eprint/86588/1/MohdRizaludinMahmud2020_MappingtheDailyRainfalloveranUngaugedTropical.pdf http://eprints.utm.my/id/eprint/86588/ https://dx.doi.org/10.3390/W12061661 |
_version_ |
1680321067898372096 |
score |
13.18916 |