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Huihui Zhang, Hugo A. Loáiciga, Da Ha, and Qingyun Du

1. Introduction Precipitation plays a significant role in hydrological, meteorological, and agricultural research ( Li and Shao 2010 ; Wu and Chen 2012 ). Conventional observations from rain gauge stations generally provide direct and accurate measurements at local stations ( Duan et al. 2016 ). It remains a challenge to acquire accurate precipitation over underdeveloped and mountainous regions due to the sparsity of rain gauge networks ( Xu et al. 2015 ). The development of advanced

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Dwi Prabowo Yuga Suseno and Tomohito J. Yamada

1. Introduction Geostationary satellites make frequent observations with continuous spatial coverage, providing useful information for rainfall monitoring and the early warning of storms ( Feidas and Cartalis 2001 ; Wardah et al. 2008 ). Thermal infrared data (TIR) centered at 10.8 μm are commonly used to detect cloud-top temperature for use in rainfall estimation ( Haile et al. 2010 ). Lower temperatures are assumed to correspond to relatively cold and thick clouds, which tend to produce high

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Muattar Saydi, Guoping Tang, Yan Qin, Hong Fang, and Xiaohua Chen

radar retrievals from ground platforms (i.e., single or dual polarization radar) ( Ryzhkov and Zrnić 1998 ; Schuur et al. 2012 ) and spaceborne platforms (i.e., passive or active microwave sensors) ( Field and Heymsfield 2015 ; Kongoli et al. 2015 ; Kulie et al. 2016 ) based on the different radiative properties of snow flakes and rain droplets ( Dai 2008 ; Harpold et al. 2017a ). Precipitation phase at ground can be observed using regular meteorological observations and is primarily controlled

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Ji-Qin Zhong, Bing Lu, Wei Wang, Cheng-Cheng Huang, and Yang Yang

://www.fao.org/soils-portal/soil-survey/soil-maps-and-databases/faounesco-soil-map-of-the-world/en/ . Gao , Y. , and Coauthors , 2008 : Enhancement of land surface information and its impact on atmospheric modeling in the Heihe River Basin, northwest China . J. Geophys. Res. , 113 , D20S90 , https://doi.org/10.1029/2008JD010359 . 10.1029/2008JD010359 Hallikainen , M. T. , F. T. Ulaby , M. C. Dobson , M. A. El-Rayes , and L.-K. Wu , 1985 : Microwave dielectric behavior of wet soil—Part I: Empirical models and experimental observations . IEEE Trans. Geosci. Remote Sens. , 23

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Dazhi Xi, Ning Lin, and James Smith

climatology models have been developed to efficiently generate synthetic storms under large-scale climate projections ( Emanuel 2006 ; Lee et al. 2018 ; Jing and Lin 2020 ). Various proposed TC rainfall models ( Tuleya et al. 2007 ; Lonfat et al. 2007 ; Langousis and Veneziano 2009a ; Zhu et al. 2013 ) can be used to evaluate TC rainfall climatology based on the generated synthetic storms. Based on satellite observations, Tuleya et al. (2007) developed a statistical model to simulate TC rainfall

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J. C. Albert C. Peralta, Gemma Teresa T. Narisma, and Faye Abigail T. Cruz

Type 2 with annual rainfall comparable to Type 3 but more or less evenly distributed over all the months. However, the profile resembles that of Type 2 because of a similar absence of a pronounced dry season. This classification is a good survey of Philippine rainfall variability as the majority of the features described were also present when an objective clustering method was applied to rainfall data from recent station and satellite-based observations ( Corporal-Lodangco and Leslie 2017 ). It is

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Sheng Chen, Jonathan J. Gourley, Yang Hong, P. E. Kirstetter, Jian Zhang, Kenneth Howard, Zachary L. Flamig, Junjun Hu, and Youcun Qi

Aviation Administration's Aviation Weather Research Program. The system assimilates different observational networks, including “raw” level-2 data from the NEXRAD network, model hourly analyses from the Rapid Update Cycle (RUC) model ( Benjamin et al. 2004 ) and rain gauge observations from the Hydrometeorological Automated Data System (HADS). Similar to the Stage II radar-only product, computations are first computed in polar coordinates on grids centered on each WSR-88D site. Hybrid scan reflectivity

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Michael D. Dettinger

of drought-busting storms was categorized as AR versus non-AR events on the basis of combinations of 1) integrated water vapor content (IWC) fields from the twice-daily Special Sensor Microwave Imager (SSM/I) imagery, available since October 1998, and 2) daily integrated vapor transport (IVT) fields from the NCEP–NCAR 40-Year Reanalysis Project ( Kalnay et al. 1996 , and updates thereto), available since 1948. The procedure for, and results of, using the recent IWC data to identify West Coast

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Massimiliano Ignaccolo and Carlo De Michele

) used to make the plot is 0.1: only bins with at least 10 observations in it were considered. Finally, we show in Fig. 3 how the Eq. (2) is not dependent on the particular type of rain considered. The distinction between stratiform and convective, made according to the presence or absence of bright band, regards the Darwin dataset (DRW) as in Williams (2009) . Similarly, the distinction between stratiform and orographic made according to the presence or absence of bright band regards the

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Jessica C. A. Baker, Dayana Castilho de Souza, Paulo Y. Kubota, Wolfgang Buermann, Caio A. S. Coelho, Martin B. Andrews, Manuel Gloor, Luis Garcia-Carreras, Silvio N. Figueroa, and Dominick V. Spracklen

Intercomparison Project (CMIP) phase 5 (CMIP5) models analyzed, and 10 out of 26 CMIP6 models, simulated a water-limited evaporative regime over the Amazon, rather than a radiation-limited regime as indicated by observations (Baker et al. 2020, manuscript submitted to Environ. Res. Lett .). The authors showed that the direction of interactions influenced whether future changes in climate were likely to be amplified or moderated. These examples illustrate the importance of evaluating model representation of

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