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Noah D. Brenowitz, Tom Beucler, Michael Pritchard, and Christopher S. Bretherton

continuous elliptical vertical differential operator defined by Aw = (∂/∂ z )[(1/ ρ 0 )(∂/∂ z )( ρ 0 w )]. When endowed with rigid-lid boundary conditions, w (0) = w ( H ) = 0, this linear operator can be inverted to give A −1 . In practice, we discretize these continuous operators using finite differences so that these operations can be performed with matrix algebra. Since we are focused on free-tropospheric dynamics, we have neglected the virtual effect of water vapor and approximated the buoyancy

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Kyle A. Hilburn, Imme Ebert-Uphoff, and Steven D. Miller

thunderstorms with abundant cloud water concentrations (e.g., Williams et al. 2005 ) that produce large anvils that obscure the convective cores in infrared imagery. While these conditions also lead to very high lightning rates, Rutledge et al. (2020) show these conditions also produce storms for which the lighting flash height is relatively low, making for large optical paths between the lightning source and the upper cloud boundary along the GLM sensor line of sight (both in general and for this

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Andrew E. Mercer, Alexandria D. Grimes, and Kimberly M. Wood

episodes meet this threshold ( Kaplan et al. 2010 ). Additionally, the exact physical processes governing RI remain poorly understood ( Wang and Wu 2004 ; Grimes and Mercer 2014 ), an issue compounded by the relative lack of boundary layer observations within the TC environment and heavy reliance on global operational dynamic forecast models to fill these observational gaps. Recent work has improved our understanding of processes governing the RI of Atlantic Ocean TCs. The probability of RI increases

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Eric D. Loken, Adam J. Clark, Amy McGovern, Montgomery Flora, and Kent Knopfmeier

are derived using a blend of Global Ensemble Forecast System (GEFS) and SREF analyses. Lateral boundary conditions (LBCs) are from the GFS and GEFS members. Convective parameterizations include the Kain–Fritsch (KF; Kain 2004 ), Grell (1993) , Betts–Miller–Janjić (BMJ; Betts 1986 ; Janjić 1994 ), and simplified Arakawa–Schubert ( Han and Pan 2011 ) schemes. Planetary boundary layer (PBL) schemes include the Yonsei University (YSU; Hong et al. 2006 ), Mellor–Yamada–Nakanishi–Niino (MYNN

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Sid-Ahmed Boukabara, Vladimir Krasnopolsky, Jebb Q. Stewart, Eric S. Maddy, Narges Shahroudi, and Ross N. Hoffman

lower cost, and mass and power requirements. This will improve analyses close to the surface (in the lower atmospheric boundary layer) where existing observations are not optimal. Fig . 1. Growth in annual mean number of satellite observations (millions) per 0000 UTC cycle (a) available and (b) used by the NCEP DA system for different data types (colors). The data are grouped into the following types: atmospheric motion vector, ocean surface wind, solar backscatter ozone, radio occultation, and

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Imme Ebert-Uphoff and Kyle Hilburn

. Pattern complexity is very difficult to evaluate for several reasons: 1) patterns can only be evaluated after NN training is completed; 2) techniques for discovering patterns, such as feature visualization ( Olah et al. 2017 , 2018 ), to date only provide limited answers; and 3) feature visualization is even more challenging for meteorological imagery, because it tends to have amorphous boundaries (e.g., clouds, atmospheric rivers, ocean eddies) ( Karpatne et al. 2019 ) rather than the crisp

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Yaling Liu, Dongdong Chen, Soukayna Mouatadid, Xiaoliang Lu, Min Chen, Yu Cheng, Zhenghui Xie, Binghao Jia, Huan Wu, and Pierre Gentine

water demand, and thus SM could also be a crucial factor affecting socioeconomic conditions. Despite the criticality of SM in the Earth system, accurate estimation of large-scale soil moisture is still a challenge, mainly due to its rapid fluctuations and the lack of sufficient ground truth observations. Currently, most large-scale SM products are either retrieved from satellite data or produced from land surface models (LSMs). As an example of product derived from satellites, the European Space

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Hanoi Medina, Di Tian, Fabio R. Marin, and Giovanni B. Chirico

to spatial inconsistencies at the boundaries between tiles ( Hamill and Whitaker 2006 ; Hamill et al. 2006 ). However, this is not an issue present in this study. Leave-one-out cross validation are carried out by excluding the current year from the list of potential analogs. For a detailed description and theoretical basis of the analog method, the readers can refer to Hamill and Whitaker (2006) . 2) Logistic regression method In the logistic regression (LR) method a nonlinear function is

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