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Md. Abul Ehsan Bhuiyan, Efthymios I. Nikolopoulos, and Emmanouil N. Anagnostou

morphing technique (CMORPH) of the National Oceanic and Atmospheric Administration (NOAA) depends on passive microwave (PMW) satellite precipitation fields propagated by motion vectors calculated from infrared (IR) observations ( Joyce et al. 2004 ). Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN) connects IR observations to PMW rainfall estimates through a neutral network ( Sorooshian et al. 2000 ). Tropical Rainfall Measuring Mission (TRMM

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M. Petracca, L. P. D’Adderio, F. Porcù, G. Vulpiani, S. Sebastianelli, and S. Puca

1. Introduction The Global Precipitation Measurement (GPM) Core Observatory has been collecting data by both the passive GPM Microwave Imager (GMI; Draper et al. 2015 ) and the Dual-Frequency Precipitation Radar (DPR; Furukawa et al. 2015 ) for more than 3 years ( Neeck et al. 2014 ). The DPR consists of a Ku-band (13.6 GHz) precipitation radar, similar to the Precipitation Radar (PR) on board the Tropical Rainfall Measuring Mission (TRMM) satellite ( Kummerow et al. 1998 ), and an

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Jiaying Zhang, Liao-Fan Lin, and Rafael L. Bras

information of temperature. Section 4 discusses the robustness of the results. Section 5 provides conclusions. 2. Data and methods a. IMERG early- and final-run products This study uses version 5 IMERG early- and final-run products. The IMERG level 3 multisatellite precipitation product combines precipitation estimates from all passive microwave sensors from the GPM constellation, infrared observations from geosynchronous satellites, and monthly gauge measurements ( Huffman et al. 2015 ). IMERG covers

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Jackson Tan, Walter A. Petersen, Pierre-Emmanuel Kirstetter, and Yudong Tian

scale suitable to their purposes. 2. Data a. IMERG IMERG is a gridded precipitation product that merges measurements from a network of satellites in the GPM constellation ( Huffman et al. 2015 ). IMERG uses the GPM Core Observatory satellite, which has a dual-frequency precipitation radar and a 13-channel passive microwave imager, as a reference standard to intercalibrate and merge precipitation estimates from individual passive microwave (PMW) satellites in the constellation ( Hou et al. 2014

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Hooman Ayat, Jason P. Evans, Steven Sherwood, and Ali Behrangi

. Kalogiros , D. Casella , A. C. Marra , G. Panegrossi , and P. Sano , 2018 : Passive microwave rainfall error analysis using high-resolution X-band dual-polarization radar observations in complex terrain . IEEE Trans. Geosci. Remote Sens. , 56 , 2565 – 2586 , https://doi.org/10.1109/TGRS.2017.2763622 . 10.1109/TGRS.2017.2763622 Derin , Y. , and Coauthors , 2019 : Evaluation of GPM-era global satellite precipitation products over multiple complex terrain regions . Remote Sens. , 11

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