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Alberto Ortolani, Francesca Caparrini, Samantha Melani, Luca Baldini, and Filippo Giannetti

the present experiments the results suggest that N = 100 is satisfactory, since a higher number ( N = 500) leads to similar errors (on the contrary, N = 50 gives poorer estimations). This is encouraging for the feasibility of the method, but further evaluation is needed when applied to larger domains with different configurations and real data. Other synthetic experiments have been performed, with the same cylindrical storm but changing true and modeled advection velocities, obtaining similar

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F. Joseph Turk, Sarah E. Ringerud, Yalei You, Andrea Camplani, Daniele Casella, Giulia Panegrossi, Paolo Sanò, Ardeshir Ebtehaj, Clement Guilloteau, Nobuyuki Utsumi, Catherine Prigent, and Christa Peters-Lidard

imager perspective: Observational analysis and precipitation retrieval evaluation . J. Atmos. Oceanic Technol. , 38 , 293 – 311 , . 10.1175/JTECH-D-20-0064.1 Mitrescu , C. , T. L’Ecuyer , J. Haynes , S. Miller , and F. J. Turk , 2010 : CloudSat precipitation profiling algorithm-model description . J. Appl. Meteor. Climatol. , 49 , 991 – 1003 , . 10.1175/2009JAMC2181.1 Mroz , K. , M. Montopoli

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Nobuyuki Utsumi, F. Joseph Turk, Ziad S. Haddad, Pierre-Emmanuel Kirstetter, and Hyungjun Kim

et al. 2007 ). Interestingly, on the other hand, GPROF shows overestimations for the same range (0.1–1 mm h −1 ) except for snow surfaces ( Table 1 ). The reason of the opposite biases of EPC and GPROF for weak precipitation range needs further investigation in the future study. Note that very light precipitation range (less than 0.1 mm h −1 ) is not included in the assessment ( Table 1 ). The performance evaluation for such very light range is more prone to the precipitation detection skill of

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Stephen E. Lang and Wei-Kuo Tao

. Zuluaga , and R. A. Houze Jr ., 2015 : Latent heating characteristics of the MJO computed from TRMM observations . J. Geophys. Res. Atmos. , 120 , 1322 – 1334 , . 10.1002/2014JD022530 Chern , J.-D. , W.-K. Tao , S. Lang , T. Matsui , J.-L. F. Li , K. Mohr , G. Skofronick-Jackson , and C. Peters-Lidard , 2016 : Performance of the Goddard multiscale modeling framework with Goddard ice microphysical schemes . J. Adv. Model. Earth

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Andrea Camplani, Daniele Casella, Paolo Sanò, and Giulia Panegrossi

water within the snowpack strongly enhances the absorption at the expense of the volume scattering ( Rott and Nagler 1995 ; Amlien 2008 ). Hewison and English (1999) developed a model representing the microwave emissivity spectra of sea ice and snow cover obtained by airborne measurements. Different behaviors have been observed for different types of snowpacks, with an evident decrease of the emissivity with increasing frequency (within MW) for dry snow, and a high and stable emissivity for fresh

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Chandra Rupa Rajulapati, Simon Michael Papalexiou, Martyn P. Clark, Saman Razavi, Guoqiang Tang, and John W. Pomeroy

model driven has utility in poorly gauged regions. Climate is also associated with data product performance in describing extremes. Thus, the question that naturally arises is “which product is the best for studying extremes?” The results presented here suggest that MSWEP performs better, yet there is no single global product that works best for all regions and climates. As such, it is still advisable to include multiple products in a study in order to gain some insights into the uncertainties in

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Clément Guilloteau and Efi Foufoula-Georgiou

uncertainty. The use of nonlocal parameters in a neighbor-search algorithm does not require defining explicit relations between TB patterns and precipitation; it is simply assumed that similar TB patterns correspond to similar precipitation systems and geometries. In particular, with this approach, it is not necessary to explicitly correct for the parallax shift as is done in Guilloteau et al. (2018) . The retrieval performance is evaluated over 6 million randomly sampled DPR profiles and collocated GMI

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