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  • The 1st NOAA Workshop on Leveraging AI in the Exploitation of Satellite Earth Observations & Numerical Weather Prediction x
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Noah D. Brenowitz, Tom Beucler, Michael Pritchard, and Christopher S. Bretherton

). The goal of the NN parameterization ( Rasp et al. 2018 ; Gentine et al. 2018 ) is to emulate how the embedded SAM models vertically redistribute temperature (approximately Q 1 ) and water vapor (approximately Q 2 ) in response to given coarse-grained conditions from the host model’s primitive equation dynamical predictions (i.e., temperature profile, water vapor profile, meridional velocity profile, surface pressure, insolation, surface sensible heat flux, and surface latent heat flux; all

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

numerous processes that contribute to TC intensification. Many of these processes are inherently thermodynamic (such as latent heat flux from high sea surface temperatures; Kaplan and DeMaria 2003 ) and not well represented by the dynamic weather models used in operational forecasts ( Kotroni and Lagouvardos 2004 ; Klemp 2006 ; Mercer et al. 2013 ). Kinematic factors relevant to TC intensity change are frequently noisy (e.g., 200-hPa divergence; Leroux 2016 ) or require sufficient vertical

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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

1. Introduction Soil moisture (SM) is an essential component of the Earth system. It affects the variability of the coupled energy (latent and sensible heat fluxes) and water fluxes (runoff and evapotranspiration) by modifying the partitioning of water and energy across the land–atmosphere interface ( Seneviratne et al. 2010 ). The effects of SM on evapotranspiration also impact temperature variability and may intrigue persistent heatwaves ( Fischer et al. 2007 ; Hirschi et al. 2011

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

– 753 , . 10.1175/JAS-D-13-0163.1 Ben Daoud , A. , E. Sauquet , G. Bontron , C. Obled , and M. Lang , 2016 : Daily quantitative precipitation forecasts based on the analogue method: Improvements and application to a French large river basin . Atmos. Res. , 169 , 147 – 159 , . 10.1016/j.atmosres.2015.09.015 Berbery , E. H. , and E. A. Collini , 2000 : Springtime precipitation and water vapor flux

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