Brenowitz, N. D., Bretherton, C. S. (2018) Prognostic Validation of a Neural Network Unified Physics Parameterization. Geophysical Research Letters, 45 (12) 6289-6298 doi:10.1029/2018gl078510

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Reference Type	Journal (article/letter/editorial)
Title	Prognostic Validation of a Neural Network Unified Physics Parameterization
Journal	Geophysical Research Letters
Authors	Brenowitz, N. D.		Author
Authors	Bretherton, C. S.		Author
Year	2018 (June 28)	Volume	45
Issue	12
Publisher	American Geophysical Union (AGU)
DOI	doi:10.1029/2018gl078510Search in ResearchGate
	Generate Citation Formats
Mindat Ref. ID	856267	Long-form Identifier	mindat:1:5:856267:2
GUID	0
Full Reference	Brenowitz, N. D., Bretherton, C. S. (2018) Prognostic Validation of a Neural Network Unified Physics Parameterization. Geophysical Research Letters, 45 (12) 6289-6298 doi:10.1029/2018gl078510
Plain Text	Brenowitz, N. D., Bretherton, C. S. (2018) Prognostic Validation of a Neural Network Unified Physics Parameterization. Geophysical Research Letters, 45 (12) 6289-6298 doi:10.1029/2018gl078510
In	(2018, June) Geophysical Research Letters Vol. 45 (12) American Geophysical Union (AGU)

	Watt‐Meyer, Oliver, Brenowitz, Noah D., Clark, Spencer K., Henn, Brian, Kwa, Anna, McGibbon, Jeremy, Perkins, W. Andre, Harris, Lucas, Bretherton, Christopher S. (2024) Neural Network Parameterization of Subgrid‐Scale Physics From a Realistic Geography Global Storm‐Resolving Simulation. Journal of Advances in Modeling Earth Systems, 16 (2) doi:10.1029/2023ms003668
	Brenowitz, Noah D., Bretherton, Christopher S. (2019) Spatially Extended Tests of a Neural Network Parametrization Trained by Coarse‐Graining. Journal of Advances in Modeling Earth Systems, 11. 2728-2744 doi:10.1029/2019ms001711
	Miller, S. D., Stephens, G. L., Beljaars, A. C. M. (1999) A validation survey of the ECMWF prognostic cloud scheme using LITE. Geophysical Research Letters, 26 (10) 1417-1420 doi:10.1029/1999gl900263
	Watt‐Meyer, Oliver, Brenowitz, Noah D., Clark, Spencer K., Henn, Brian, Kwa, Anna, McGibbon, Jeremy, Perkins, W. Andre, Bretherton, Christopher S. (2021) Correcting Weather and Climate Models by Machine Learning Nudged Historical Simulations. Geophysical Research Letters, 48 (15) doi:10.1029/2021gl092555
	Rushley, S. S., Kim, D., Bretherton, C. S., Ahn, M.‐S. (2018) Reexamining the Nonlinear Moisture‐Precipitation Relationship Over the Tropical Oceans. Geophysical Research Letters, 45 (2) 1133-1140 doi:10.1002/2017gl076296
	Jiang, Guo-Qing, Xu, Jing, Wei, Jun (2018) A Deep Learning Algorithm of Neural Network for the Parameterization of Typhoon-Ocean Feedback in Typhoon Forecast Models. Geophysical Research Letters, 45 (8) 3706-3716 doi:10.1002/2018gl077004
	Roh, Soonyoung, Song, Hwan‐Jin (2020) Evaluation of Neural Network Emulations for Radiation Parameterization in Cloud Resolving Model. Geophysical Research Letters, 47 (21) doi:10.1029/2020gl089444
	Blossey, Peter N., Bretherton, Christopher S., Thornton, Joel A., Virts, Katrina S. (2018) Locally Enhanced Aerosols Over a Shipping Lane Produce Convective Invigoration but Weak Overall Indirect Effects in Cloud-Resolving Simulations. Geophysical Research Letters, 45 (17) 9305-9313 doi:10.1029/2018gl078682
	Perezhogin, Pavel; Adcroft, Alistair; Zanna, Laure (2025) Generalizable Neural‐Network Parameterization of Mesoscale Eddies in Idealized and Global Ocean Models. Geophysical Research Letters, 52 (19). doi:10.1029/2025gl117046
	Emori, S. (2005) Validation, parameterization dependence, and future projection of daily precipitation simulated with a high-resolution atmospheric GCM. Geophysical Research Letters, 32 (6) doi:10.1029/2004gl022306
	Bretherton, C. S., Blossey, P. N., Uchida, J. (2007) Cloud droplet sedimentation, entrainment efficiency, and subtropical stratocumulus albedo. Geophysical Research Letters, 34 (3) doi:10.1029/2006gl027648

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Brenowitz, N. D., Bretherton, C. S. (2018) Prognostic Validation of a Neural Network Unified Physics Parameterization. Geophysical Research Letters, 45 (12) 6289-6298 doi:10.1029/2018gl078510

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