Adjoint‐Based Climate Model Tuning: Application to the Planet Simulator

Abstract The adjoint method is used to calibrate the medium complexity climate model “Planet Simulator” through parameter estimation. Identical twin experiments demonstrate that this method can retrieve default values of the control parameters when using a long assimilation window of the order of 2...

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Main Authors: Guokun Lyu, Armin Köhl, Ion Matei, Detlef Stammer
Format: Article
Language:English
Published: American Geophysical Union (AGU) 2018-01-01
Series:Journal of Advances in Modeling Earth Systems
Subjects:
Online Access:https://doi.org/10.1002/2017MS001194
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spelling doaj-52f67ec48bc944c896a73a9dbc799f3c2020-11-24T20:57:18ZengAmerican Geophysical Union (AGU)Journal of Advances in Modeling Earth Systems1942-24662018-01-0110120722210.1002/2017MS001194Adjoint‐Based Climate Model Tuning: Application to the Planet SimulatorGuokun Lyu0Armin Köhl1Ion Matei2Detlef Stammer3Institute of Oceanography, Center for Earth System Research and Sustainability (CEN), University of HamburgHamburg GermanyInstitute of Oceanography, Center for Earth System Research and Sustainability (CEN), University of HamburgHamburg GermanyInstitute of Oceanography, Center for Earth System Research and Sustainability (CEN), University of HamburgHamburg GermanyInstitute of Oceanography, Center for Earth System Research and Sustainability (CEN), University of HamburgHamburg GermanyAbstract The adjoint method is used to calibrate the medium complexity climate model “Planet Simulator” through parameter estimation. Identical twin experiments demonstrate that this method can retrieve default values of the control parameters when using a long assimilation window of the order of 2 months. Chaos synchronization through nudging, required to overcome limits in the temporal assimilation window in the adjoint method, is employed successfully to reach this assimilation window length. When assimilating ERA‐Interim reanalysis data, the observations of air temperature and the radiative fluxes are the most important data for adjusting the control parameters. The global mean net longwave fluxes at the surface and at the top of the atmosphere are significantly improved by tuning two model parameters controlling the absorption of clouds and water vapor. The global mean net shortwave radiation at the surface is improved by optimizing three model parameters controlling cloud optical properties. The optimized parameters improve the free model (without nudging terms) simulation in a way similar to that in the assimilation experiments. Results suggest a promising way for tuning uncertain parameters in nonlinear coupled climate models.https://doi.org/10.1002/2017MS001194parameter estimationadjoint methodchaos synchronizationclimate modeling
collection DOAJ
language English
format Article
sources DOAJ
author Guokun Lyu
Armin Köhl
Ion Matei
Detlef Stammer
spellingShingle Guokun Lyu
Armin Köhl
Ion Matei
Detlef Stammer
Adjoint‐Based Climate Model Tuning: Application to the Planet Simulator
Journal of Advances in Modeling Earth Systems
parameter estimation
adjoint method
chaos synchronization
climate modeling
author_facet Guokun Lyu
Armin Köhl
Ion Matei
Detlef Stammer
author_sort Guokun Lyu
title Adjoint‐Based Climate Model Tuning: Application to the Planet Simulator
title_short Adjoint‐Based Climate Model Tuning: Application to the Planet Simulator
title_full Adjoint‐Based Climate Model Tuning: Application to the Planet Simulator
title_fullStr Adjoint‐Based Climate Model Tuning: Application to the Planet Simulator
title_full_unstemmed Adjoint‐Based Climate Model Tuning: Application to the Planet Simulator
title_sort adjoint‐based climate model tuning: application to the planet simulator
publisher American Geophysical Union (AGU)
series Journal of Advances in Modeling Earth Systems
issn 1942-2466
publishDate 2018-01-01
description Abstract The adjoint method is used to calibrate the medium complexity climate model “Planet Simulator” through parameter estimation. Identical twin experiments demonstrate that this method can retrieve default values of the control parameters when using a long assimilation window of the order of 2 months. Chaos synchronization through nudging, required to overcome limits in the temporal assimilation window in the adjoint method, is employed successfully to reach this assimilation window length. When assimilating ERA‐Interim reanalysis data, the observations of air temperature and the radiative fluxes are the most important data for adjusting the control parameters. The global mean net longwave fluxes at the surface and at the top of the atmosphere are significantly improved by tuning two model parameters controlling the absorption of clouds and water vapor. The global mean net shortwave radiation at the surface is improved by optimizing three model parameters controlling cloud optical properties. The optimized parameters improve the free model (without nudging terms) simulation in a way similar to that in the assimilation experiments. Results suggest a promising way for tuning uncertain parameters in nonlinear coupled climate models.
topic parameter estimation
adjoint method
chaos synchronization
climate modeling
url https://doi.org/10.1002/2017MS001194
work_keys_str_mv AT guokunlyu adjointbasedclimatemodeltuningapplicationtotheplanetsimulator
AT arminkohl adjointbasedclimatemodeltuningapplicationtotheplanetsimulator
AT ionmatei adjointbasedclimatemodeltuningapplicationtotheplanetsimulator
AT detlefstammer adjointbasedclimatemodeltuningapplicationtotheplanetsimulator
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