Abstract
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.
Highlights
Rainfall is critical for dryland agriculture, domestic water supply, groundwater recharge, and the overall health of the ecosystem of any region
The results indicated that the local topography and rainfall intensities significantly impacted the satellite-based rainfall products (SRPs) performance, which was consistent with previous research [37,38]
The main findings of the present study are: (1) the performances of the CHIRPS-2.0 and SM2RAIN-ASCAT products outperformed the PERSIANN-CCS and PERSIANN-CDR products in terms of skill to represent the spatial distribution of the observed rainfall over Punjab Province
Summary
Rainfall is critical for dryland agriculture, domestic water supply, groundwater recharge, and the overall health of the ecosystem of any region. As a consequence of the ongoing global warming, the amount, intensity, and spatial–temporal rainfall patterns have all changed worldwide [1,2]. These shifts have had altered the water budgets of various geographical regions. Ground-based rainfall measurement instruments such as rain gauges and radars are considered as reliable data sources for rainfall estimation [3,4,5]. Ground-based instruments are available in certain developed countries, their unavailability or scarcity in developing countries causes ambiguities in the measurements of rainfall quantities and intensities
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