Uncertainty Quantification of Ocean Parameterizations: Application to the K‐Profile‐Parameterization for Penetrative Convection

Autor:	Andre Souza, Valentin Churavy, Alan Edelman, B. Allen, Chris Hill, Glenn R. Flierl, Jean-Michel Campin, Raffaele Ferrari, Ali Ramadhan, James Schloss, Gregory L. Wagner, John Marshall
Rok vydání:	2020
Předmět:	Convection Work (thermodynamics) ComputerSystemsOrganization_COMPUTERSYSTEMIMPLEMENTATION 010504 meteorology & atmospheric sciences Meteorology media_common.quotation_subject Bayesian probability Fidelity Climate change 01 natural sciences GeneralLiterature_MISCELLANEOUS Physics::Geophysics 010305 fluids & plasmas Physics::Fluid Dynamics lcsh:Oceanography 0103 physical sciences Environmental Chemistry lcsh:GC1-1581 Uncertainty quantification lcsh:Physical geography Physics::Atmospheric and Oceanic Physics ComputingMethodologies_COMPUTERGRAPHICS 0105 earth and related environmental sciences media_common Global and Planetary Change Turbulence General Earth and Planetary Sciences Environmental science lcsh:GB3-5030
Zdroj:	Journal of Advances in Modeling Earth Systems, Vol 12, Iss 12, Pp n/a-n/a (2020)
ISSN:	1942-2466
Popis:	Parameterizations of unresolved turbulent processes often compromise the fidelity of large‐scale ocean models. In this work, we argue for a Bayesian approach to the refinement and evaluation of turbulence parameterizations. Using an ensemble of large eddy simulations of turbulent penetrative convection in the surface boundary layer, we demonstrate the method by estimating the uncertainty of parameters in the convective limit of the popular “K‐Profile Parameterization.” We uncover structural deficiencies and propose an alternative scaling that overcomes them.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bb922d8ce402eb173acd68e652e79498 https://doi.org/10.1029/2020ms002108 Zobrazit plný text záznamu Plný text