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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Online Access: | https://doi.org/10.1002/2017MS001194 |
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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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1716788164232740864 |