A comprehensive evaluation of the satellite precipitation products across Iran |
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Author: | Dehaghani, Asieh Mousavi1; Gohari, Alireza1; Zareian, Mohammad Javad2; |
Organizations: |
1Department of Irrigation, College of Agriculture, Isfahan University of Technology, Isfahan 84156-83111, Iran 2Department of Water Resources Study and Research, Water Research Institute (WRI), Ministry of Energy, Tehran, Iran 3Water, Energy and Environmental Engineering Research Unit, University of Oulu, P.O. Box 4300, FIN-90014 Oulu, Finland |
Format: | article |
Version: | published version |
Access: | open |
Online Access: | PDF Full Text (PDF, 8.4 MB) |
Persistent link: | http://urn.fi/urn:nbn:fi-fe20230928137733 |
Language: | English |
Published: |
Elsevier,
2023
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Publish Date: | 2023-09-28 |
Description: |
AbstractStudy region: Iran Study focus: This study evaluated three satellite precipitation products, including PERSIANN-CCS and TRMM-3B42RT V7 (near real-time satellites) and CMOROH (post real-time satellite), on hourly, daily, monthly, and annual time scales in 52 synoptic stations over Iran. This study aims to evaluate the accuracy of satellite- precipitation products over different return periods and durations as well as their performance in different climates and altitudes. The Pearson’s correlation coefficient (Rp), Relative Root Mean Square Error (RRMSE), and Relative Bias (RBias) as well as three probability indices including Probability of Detection (POD), False Alarm Ratio (FAR), and Critical Success Index (CSI) were applied to evaluate the accuracy of these products. In addition, the sub-daily IDF curves (6, 12, 18, and 24 h) were derived to evaluate the studied satellites precipitation for 5, 10-, 20-, 50-, and 100-year return periods. New hydrological insights for the region: The results showed that the modification method could significantly improve all satellites’ performance in precipitation estimation. The IDF curves derived from the CMORPH satellite as post real-time satellite precipitation product, showed the highest accuracy compared to synoptic stations. The TRMM and CMORPH underestimated precipitation by 56% and 8%, respectively, while PERSIANN-CCS overestimated precipitation by 143%. However, PERSIANN-CCS performed better in detecting the occurrence and non-occurrence of precipitation than other products. For Northeastern and Southwestern Iran, all products showed the same performance in accurately detecting occurrence and precipitation. see all
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Series: |
Journal of hydrology. Regional studies |
ISSN: | 2214-5818 |
ISSN-E: | 2214-5818 |
ISSN-L: | 2214-5818 |
Volume: | 46 |
Article number: | 101360 |
DOI: | 10.1016/j.ejrh.2023.101360 |
OADOI: | https://oadoi.org/10.1016/j.ejrh.2023.101360 |
Type of Publication: |
A1 Journal article – refereed |
Field of Science: |
1172 Environmental sciences 1171 Geosciences |
Subjects: | |
Funding: |
The study was supported by Maa- ja vesitekniikan tuki ry (Reference no. 41878). |
Copyright information: |
© 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
https://creativecommons.org/licenses/by/4.0/ |