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Stephen E. Lang and Wei-Kuo Tao

great importance, LH is hard to measure directly. However, the launch of the Tropical Rainfall Measuring Mission satellite (TRMM; Simpson et al. 1996 ; Kummerow et al. 2000 ) in November of 1997 made it possible to obtain quantitative precipitation measurements over the global tropics and, as a consequence of their close connection, estimates of tropical LH as well. In support of this effort, five different LH algorithms were developed to retrieve profiles of LH using TRMM rainfall products

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Sarah Ringerud, Christa Peters-Lidard, Joe Munchak, and Yalei You

ocean. Over ocean, the multispectral emission and scattering characteristics of hydrometeors can be used in algorithms for microwave imagers such as the 13-channel GPM Microwave Imager (GMI), whereas over land, retrievals typically reduce to looking for an ice scattering signal associated with precipitation ( Levizzani et al. 2020 ; You et al. 2017 ; Petty and Krajewski 1996 ). Additionally, the passive microwave (PMW) brightness temperatures (Tbs) are sensitive to the column integrated

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Lisa Milani, Mark S. Kulie, Daniele Casella, Pierre E. Kirstetter, Giulia Panegrossi, Veljko Petkovic, Sarah E. Ringerud, Jean-François Rysman, Paolo Sanò, Nai-Yu Wang, Yalei You, and Gail Skofronick-Jackson

precipitation retrievals up to the Arctic and Antarctic Circles. Detecting snowfall is one of the critical GPM mission requirements. Both DPR and GMI have shown snowfall detection capabilities ( Adhikari et al. 2018 ; Casella et al. 2017 ; Ebtehaj and Kummerow 2017 ; Panegrossi et al. 2017 ; Rysman et al. 2018 ; You et al. 2017 ; Petersen et al. 2020 ). However, different sampling strategies, sensor sensitivities, phase classification, and other algorithm assumptions strongly influence global snowfall

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Clément Guilloteau, Antonios Mamalakis, Lawrence Vulis, Phong V. V. Le, Tryphon T. Georgiou, and Efi Foufoula-Georgiou

.1002/(SICI)1097-0088(199902)19:2<169:AID-JOC356>3.0.CO;2-Y . 10.1002/(SICI)1097-0088(199902)19:2<169::AID-JOC356>3.0.CO;2-Y Proakis , J. G. , 2001 : Nonparametric methods for power spectrum estimation. Digital Signal Processing: Principles, Algorithms and Applications , Pearson Education India, 908–919. Reynolds , R. W. , T. M. Smith , C. Liu , D. B. Chelton , K. S. Casey , and M. G. Schlax , 2007 : Daily high-resolution-blended analyses for sea surface temperature . J. Climate

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Abby Stevens, Rebecca Willett, Antonios Mamalakis, Efi Foufoula-Georgiou, Alejandro Tejedor, James T. Randerson, Padhraic Smyth, and Stephen Wright

covariances to constrain the model via a GTV regularization term. The covariance matrix is estimated based on the output of climate models and subjected to a hard thresholding (see section 3c ) to increase the consistency of the dependency among predictors for improved performance of the GTV algorithm. a. Predictive performance of the GTV model The GTV model [Eq. (6) ] was fitted in the training period (from 1940/41 to 1989/90) and the optimal threshold value θ * and optimal parameter values ( λ 1

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Clément Guilloteau and Efi Foufoula-Georgiou

1. Introduction Since the first experimental algorithms developed for the SMMR (see appendix A for all acronyms used in this article) imager in the 1980s, the algorithms performing the retrieval of precipitation from passive microwave imagers in orbit have been continuously evolving and improving ( Wilheit and Chang 1980 ; Spencer 1986 ; Spencer et al. 1989 ; Wilheit et al. 1991 ; Liu and Curry 1992 ; Kummerow and Giglio 1994 ; Petty 1994 ; Ferraro and Marks 1995 ; Kummerow et al

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

the net flux of the condensed water at the bottom of this profile as seen from space and is arguably one of the quantities that the TB is least directly sensitive to ( Haddad et al. 2017 ). Furthermore, precipitation that falls near the surface is a manifestation of its associated vertical precipitation structure nearby and above. This implies that a more representative passive MW algorithm would have an ability to jointly estimate the vertical structure and the surface precipitation. Some of the

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Phu Nguyen, Mohammed Ombadi, Vesta Afzali Gorooh, Eric J. Shearer, Mojtaba Sadeghi, Soroosh Sorooshian, Kuolin Hsu, David Bolvin, and Martin F. Ralph

; Kidd and Levizzani 2011 ). Thus, IR-based precipitation estimation products have the advantage of providing higher spatiotemporal resolutions with a minimum latency that meet the requirements for many near-real-time applications ( Arkin and Meisner 1987 ). More commonly, satellite-based algorithms take advantage of information from both IR and PMW sources ( Behrangi et al. 2009 ; Joyce et al. 2004 ; Turk et al. 2000 ; Miller et al. 2001 ; Sorooshian et al. 2000 ; Hsu et al. 1997 ; Levizzani

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Shruti A. Upadhyaya, Pierre-Emmanuel Kirstetter, Jonathan J. Gourley, and Robert J. Kuligowski

global coverage at very high spatiotemporal and spectral resolutions ( ). With this significant progress in GEO sensor technology, the next generation of precipitation retrieval algorithms must follow suit. Recently, several attempts to utilize these datasets aimed at improving the precipitation retrievals (e.g., Kirstetter et al. 2018 ; Kuligowski et al. 2016 ; Ma et al. 2018 ; Meyer et al. 2016 ; Thies et al. 2008 ). The Self

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Veljko Petković, Marko Orescanin, Pierre Kirstetter, Christian Kummerow, and Ralph Ferraro

especially pronounced in satellite observations. Since the first spaceborne passive microwave instruments were launched in early 1970s, satellite precipitation retrievals have exploited the link between upwelling radiation and state of atmospheric column. Leveraging decades of ever-improving algorithms, coverage, and data latency, the Global Precipitation Measurement (GPM) mission ( Skofronick-Jackson et al. 2018 ; Hou et al. 2014 ) represents the most advance satellite precipitation project to date

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