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Assessment of PERSIANN-CCS, PERSIANN-CDR, SM2RAIN-ASCAT, and CHIRPS-2.0 Rainfall Products over a Semi-Arid Subtropical Climatic Region

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Department of Land and Water Conservation Engineering, Faculty of Agricultural Engineering and Technology, PMAS-Arid Agriculture University, Rawalpindi 46000, Pakistan
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Data Driven Smart Decision Platform, PMAS-Arid Agriculture University, Rawalpindi 46000, Pakistan
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Electrical Engineering Department, College of Engineering, Najran University Saudi Arabia, Najran 61441, Saudi Arabia
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Department of Civil Engineering, Ghulam Ishaq Khan Institute of Engineering and Technology, Topi 23460, Pakistan
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Faculty of Agriculture and Environmental Sciences, University of Rostock, 18059 Rostock, Germany
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Department of Mechanical Engineering Technology, National Skills University, Islamabad 44000, Pakistan
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Department of Civil Engineering, College of Engineering, Najran University Saudi Arabia, Najran 61441, Saudi Arabia
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Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
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Author to whom correspondence should be addressed.
Academic Editor: Fi-John Chang
Water 2022, 14(2), 147; https://doi.org/10.3390/w14020147
Received: 7 November 2021 / Revised: 19 December 2021 / Accepted: 31 December 2021 / Published: 7 January 2022
(This article belongs to the Section Hydrology)
This study compares the performance of four satellite-based rainfall products (SRPs) (PERSIANN-CCS, PERSIANN-CDR, SM2RAIN-ASCAT, and CHIRPS-2.0) in a semi-arid subtropical region. As a case study, Punjab Province of Pakistan was considered for this assessment. Using observations from in-situ meteorological stations, the uncertainty in daily, monthly, seasonal, and annual rainfall estimates of SRPs at pixel and regional scales during 2010–2018 were examined. Several evaluation indices (Correlation Coefficient (CC), Root Mean Square Error (RMSE), Bias, and relative Bias (rBias), as well as categorical indices (Probability of Detection (POD), Critical Success Index (CSI), and False Alarm Ration (FAR)) were used to assess the performance of the SRPs. The following findings were found: (1) CHIRPS-2.0 and SM2RAIN-ASCAT products were capable of tracking the spatiotemporal variability of observed rainfall, (2) all SRPs had higher overall performances in the northwestern parts of the province than the other parts, (3) all SRP estimates were in better agreement with ground-based monthly observations than daily records, and (4) on the seasonal scale, CHIRPS-2.0 and SM2RAIN-ASCAT were better than PERSIANN-CCS and PERSIANN. In all seasons, CHIRPS-2.0 and SM2RAIN-ASCAT outperformed PERSIANN-CCS and PERSIANN-CDR. Based on our findings, we recommend that hydrometeorological investigations in Pakistan’s Punjab Province employ monthly estimates of CHIRPS-2.0 and SM2RAIN-ASCAT products. View Full-Text
Keywords: satellite rainfall; performance evaluation; CHIRPS-2.0; SM2Rain-ASCAT; PERSIANN-CDR; PERSIANN-CCS satellite rainfall; performance evaluation; CHIRPS-2.0; SM2Rain-ASCAT; PERSIANN-CDR; PERSIANN-CCS
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MDPI and ACS Style

Anjum, M.N.; Irfan, M.; Waseem, M.; Leta, M.K.; Niazi, U.M.; ur Rahman, S.; Ghanim, A.; Mukhtar, M.A.; Nadeem, M.U. Assessment of PERSIANN-CCS, PERSIANN-CDR, SM2RAIN-ASCAT, and CHIRPS-2.0 Rainfall Products over a Semi-Arid Subtropical Climatic Region. Water 2022, 14, 147. https://doi.org/10.3390/w14020147

AMA Style

Anjum MN, Irfan M, Waseem M, Leta MK, Niazi UM, ur Rahman S, Ghanim A, Mukhtar MA, Nadeem MU. Assessment of PERSIANN-CCS, PERSIANN-CDR, SM2RAIN-ASCAT, and CHIRPS-2.0 Rainfall Products over a Semi-Arid Subtropical Climatic Region. Water. 2022; 14(2):147. https://doi.org/10.3390/w14020147

Chicago/Turabian Style

Anjum, Muhammad N., Muhammad Irfan, Muhammad Waseem, Megersa K. Leta, Usama M. Niazi, Saif ur Rahman, Abdulnoor Ghanim, Muhammad A. Mukhtar, and Muhammad U. Nadeem. 2022. "Assessment of PERSIANN-CCS, PERSIANN-CDR, SM2RAIN-ASCAT, and CHIRPS-2.0 Rainfall Products over a Semi-Arid Subtropical Climatic Region" Water 14, no. 2: 147. https://doi.org/10.3390/w14020147

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