2024 : 11 : 21
Mohammad Darand

Mohammad Darand

Academic rank: Professor
ORCID:
Education: PhD.
ScopusId: 26664517400
HIndex:
Faculty: Faculty of Natural Resources
Address: سنندج، دانشگاه کردستان، دانشکده منابع طبیعی، گروه آب و هواشناسی
Phone: 08736620551

Research

Title
Evaluation of Tropical Rainfall Measuring Mission, Integrated Multi‐satellite Retrievals for GPM, Climate Hazards Centre InfraRed Precipitation with Station data, and European Centre for Medium‐Range Weather Forecasts Reanalysis v5 data in estimating precipitation and capturing meteorological droughts over Iran
Type
JournalPaper
Keywords
Iran, meteorological drought, precipitation products
Year
2022
Journal INTERNATIONAL JOURNAL OF CLIMATOLOGY
DOI
Researchers Mohammad Sadegh Keikhosravi Kiany ، Seied Abolfazl Masudian ، Robert C. Balling Jr ، Mohammad Darand

Abstract

Satellite remote-sensing products with high spatial and temporal resolution are viable sources of precipitation information, especially for data-sparse and remote regions. The aim of this study is to examine the performance of four precipitation products including Integrated Multi-satellite Retrievals for GPM (GPM IMERG), Tropical Rainfall Measuring Mission (TRMM 3B43), Climate Hazards Centre InfraRed Precipitation with Station data (CHIRPS), and European Centre for Medium-Range Weather Forecasts Reanalysis v5 (ERA5) in estimating precipitation and capturing meteorological droughts over Iran for the time span from 2001 to 2019. For this aim, a ground-based gridded precipitation dataset was constructed over the country using a dense network of quality-controlled rain gauges as a reference dataset. Different statistical metrics including the correlation coefficient (CC), the bias, the relative bias, and the root mean square error (RMSE) were applied to evaluate the performance of the products. The results suggest that GPM IMERG and TRMM 3B43 outperform CHIRPS and ERA5 in capturing the spatial distribution of precipitation and meteorological drought events across the country. The estimates of precipitation from the four products are seasonally influenced, with the least accurate precipitation estimates during summer season over the southern shores of the Caspian Sea. The GPM IMERG and TRMM 3B43, with higher CC and lower RMSE, show better performance in detecting drought events at both short and long time scales while the CHIRPS demonstrates the least accuracy. Spatially, all of the products show the best performance in identifying drought events over western and southwestern regions.