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Remote Sens. 2018, 10(4), 577; https://doi.org/10.3390/rs10040577

Improving the Regional Applicability of Satellite Precipitation Products by Ensemble Algorithm

1
State Key Laboratory of Hydroscience and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China
2
Center of Excellence in Water Resource Engineering, University of Engineering and Technology, Lahore 54890, Pakistan
3
Department of Agricultural Engineering, University of Engineering and Technology, Peshawar 25120, Pakistan
*
Author to whom correspondence should be addressed.
Received: 11 January 2018 / Revised: 21 March 2018 / Accepted: 3 April 2018 / Published: 9 April 2018
(This article belongs to the Special Issue Satellite Remote Sensing for Water Resources in a Changing Climate)
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Abstract

Satellite-based precipitation products (e.g., Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (IMERG) and its predecessor, Tropical Rainfall Measuring Mission (TRMM)) are a critical source of precipitation estimation, particularly for a region with less, or no, hydrometric networking. However, the inconsistency in the performance of these products has been observed in different climatic and topographic diverse regions, timescales, and precipitation intensities and there is still room for improvement. Hence, using a projected ensemble algorithm, the regional precipitation estimate (RP) is introduced here. The RP concept is mainly based on the regional performance weights derived from the Mean Square Error (MSE) and the precipitation estimate from the TRMM product, that is, TRMM 3B42 (TR), real-time (late) (IT) and the research (post-real-time) (IR) products of IMERG. The overall results of the selected contingency table (e.g., Probability of detection (POD)) and statistical indices (e.g., Correlation Coefficient (CC)) signposted that the proposed RP product has shown an overall better potential to capture the gauge observations compared with the TR, IR, and IT in five different climatic regions of Pakistan from January 2015 to December 2016, at a diurnal time scale. The current study could be the first research providing preliminary feedback from Pakistan for global precipitation measurement researchers by highlighting the need for refinement in the IMERG. View Full-Text
Keywords: satellite observation; regional estimates; ensemble algorithm; TRMM satellite observation; regional estimates; ensemble algorithm; TRMM
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Muhammad, W.; Yang, H.; Lei, H.; Muhammad, A.; Yang, D. Improving the Regional Applicability of Satellite Precipitation Products by Ensemble Algorithm. Remote Sens. 2018, 10, 577.

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