Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Spatio-Temporal Evaluation of GPM-IMERGV6.0 Final Run Precipitation Product in Capturing Extreme Precipitation Events across Iran
Extreme precipitation events such as floods and droughts have occurred with higher frequency over the recent decades as a result of the climate change and anthropogenic activities. To understand and mitigate such events, it is crucial to investigate their spatio-temporal variations globally or regionally. Global precipitation products provide an alternative way to the in situ observations over such a region. In this study, we have evaluated the performance of the latest version of the Global Precipitation Measurement-Integrated Multi-satellitE Retrievals (GPM-IMERGV6.0 Final Run (GPM-IMERGF)). To this end, we have employed ten most common extreme precipitation indices, including maximum indices (Rx1day, Rx5day, CDD, and CWD), percentile indices (R95pTOT and R99pTOT), and absolute threshold indices (R10mm, R20mm, SDII, and PRCPTOT). Overall, the spatial distribution results for error metrics showed that the highest and lowest accuracy for GPM-IMERGF were reported for the absolute threshold indices and percentile indices, respectively. Considering the spatial distribution of the results, the highest accuracy of GPM-IMERGF in capturing extreme precipitations was observed over the western highlands, while the worst results were obtained along the Caspian Sea regions. Our analysis can significantly contribute to various hydro-metrological applications for the study region, including identifying drought and flood-prone areas and water resources planning.
Spatio-Temporal Evaluation of GPM-IMERGV6.0 Final Run Precipitation Product in Capturing Extreme Precipitation Events across Iran
Extreme precipitation events such as floods and droughts have occurred with higher frequency over the recent decades as a result of the climate change and anthropogenic activities. To understand and mitigate such events, it is crucial to investigate their spatio-temporal variations globally or regionally. Global precipitation products provide an alternative way to the in situ observations over such a region. In this study, we have evaluated the performance of the latest version of the Global Precipitation Measurement-Integrated Multi-satellitE Retrievals (GPM-IMERGV6.0 Final Run (GPM-IMERGF)). To this end, we have employed ten most common extreme precipitation indices, including maximum indices (Rx1day, Rx5day, CDD, and CWD), percentile indices (R95pTOT and R99pTOT), and absolute threshold indices (R10mm, R20mm, SDII, and PRCPTOT). Overall, the spatial distribution results for error metrics showed that the highest and lowest accuracy for GPM-IMERGF were reported for the absolute threshold indices and percentile indices, respectively. Considering the spatial distribution of the results, the highest accuracy of GPM-IMERGF in capturing extreme precipitations was observed over the western highlands, while the worst results were obtained along the Caspian Sea regions. Our analysis can significantly contribute to various hydro-metrological applications for the study region, including identifying drought and flood-prone areas and water resources planning.
Spatio-Temporal Evaluation of GPM-IMERGV6.0 Final Run Precipitation Product in Capturing Extreme Precipitation Events across Iran
Aydin Bakhtar (Autor:in) / Akbar Rahmati (Autor:in) / Afshin Shayeghi (Autor:in) / Javad Teymoori (Autor:in) / Navid Ghajarnia (Autor:in) / Peyman Saemian (Autor:in)
2022
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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A hierarchical Bayesian spatio‐temporal model for extreme precipitation events
| Online Contents | 2011
| Elsevier | 2022