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Ground Validation of GPM IMERG Precipitation Products over Iran

Maghsood, Fatemeh LU ; Hashemi, Hossein LU orcid ; Hosseini, Seyyed Hasan LU and Berndtsson, Ronny LU orcid (2020) In Remote Sensing 12(1).
Abstract
Accurate estimation of precipitation is crucial for fundamental input to various hydrometeorological applications. Ground-based precipitation data suffer limitations associated with spatial resolution and coverage; hence, satellite precipitation products can be used to complement traditional rain gauge systems. However, the satellite precipitation data need to be validated before extensive use in the applications. Hence, we conducted a thorough validation of the Global Precipitation Measurement (GPM) Integrated Multi-satellite Retrievals (IMERG) product for all of Iran. The study focused on investigating the performance of daily and monthly GPM IMERG (early, late, final, and monthly) products by comparing them with ground-based... (More)
Accurate estimation of precipitation is crucial for fundamental input to various hydrometeorological applications. Ground-based precipitation data suffer limitations associated with spatial resolution and coverage; hence, satellite precipitation products can be used to complement traditional rain gauge systems. However, the satellite precipitation data need to be validated before extensive use in the applications. Hence, we conducted a thorough validation of the Global Precipitation Measurement (GPM) Integrated Multi-satellite Retrievals (IMERG) product for all of Iran. The study focused on investigating the performance of daily and monthly GPM IMERG (early, late, final, and monthly) products by comparing them with ground-based precipitation data at synoptic stations throughout the country (2014–2017). The spatial and temporal performance of the GPM IMERG was evaluated using eight statistical criteria considering the rainfall index at the country level. The rainfall detection ability index (POD) showed that the best IMERG product’s performance is for the spring season while the false alarm ratio (FAR) index indicated the inferior performance of the IMERG products for the summer season. The performance of the products generally increased from IMERG-Early to –Final according to the relative bias (rBIAS) results while, based on the quantile-quantile (Q-Q) plots, the IMERG-Final could not be suggested for the applications relying on extreme rainfall estimates compared to IMERG-Early and -Late. The results in this paper improve the understanding of IMERG product’s performance and open a door to future studies regarding hydrometeorological applications of these products in Iran. (Less)
Please use this url to cite or link to this publication:
author
; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
GPM IMERG, satellite precipitation, Iran, spatiotemporal analysis, statistical distribution, validation
in
Remote Sensing
volume
12
issue
1
article number
48
publisher
MDPI AG
external identifiers
  • scopus:85079679587
ISSN
2072-4292
DOI
10.3390/rs12010048
language
English
LU publication?
yes
id
14cb2dda-063a-4c03-a45d-df478f5e3980
date added to LUP
2020-01-20 11:08:07
date last changed
2023-10-07 22:54:01
@article{14cb2dda-063a-4c03-a45d-df478f5e3980,
  abstract     = {{Accurate estimation of precipitation is crucial for fundamental input to various hydrometeorological applications. Ground-based precipitation data suffer limitations associated with spatial resolution and coverage; hence, satellite precipitation products can be used to complement traditional rain gauge systems. However, the satellite precipitation data need to be validated before extensive use in the applications. Hence, we conducted a thorough validation of the Global Precipitation Measurement (GPM) Integrated Multi-satellite Retrievals (IMERG) product for all of Iran. The study focused on investigating the performance of daily and monthly GPM IMERG (early, late, final, and monthly) products by comparing them with ground-based precipitation data at synoptic stations throughout the country (2014–2017). The spatial and temporal performance of the GPM IMERG was evaluated using eight statistical criteria considering the rainfall index at the country level. The rainfall detection ability index (POD) showed that the best IMERG product’s performance is for the spring season while the false alarm ratio (FAR) index indicated the inferior performance of the IMERG products for the summer season. The performance of the products generally increased from IMERG-Early to –Final according to the relative bias (rBIAS) results while, based on the quantile-quantile (Q-Q) plots, the IMERG-Final could not be suggested for the applications relying on extreme rainfall estimates compared to IMERG-Early and -Late. The results in this paper improve the understanding of IMERG product’s performance and open a door to future studies regarding hydrometeorological applications of these products in Iran.}},
  author       = {{Maghsood, Fatemeh and Hashemi, Hossein and Hosseini, Seyyed Hasan and Berndtsson, Ronny}},
  issn         = {{2072-4292}},
  keywords     = {{GPM IMERG; satellite precipitation; Iran; spatiotemporal analysis; statistical distribution; validation}},
  language     = {{eng}},
  number       = {{1}},
  publisher    = {{MDPI AG}},
  series       = {{Remote Sensing}},
  title        = {{Ground Validation of GPM IMERG Precipitation Products over Iran}},
  url          = {{http://dx.doi.org/10.3390/rs12010048}},
  doi          = {{10.3390/rs12010048}},
  volume       = {{12}},
  year         = {{2020}},
}