Results of adjoint-based climate model tuning: application to the Planet Simulator

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 non-linear coupled climate models.

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Lyu, Guokun, Köhl, Armin, Matei, Ion, Stammer, Detlef (2018). Dataset: Results of adjoint-based climate model tuning: application to the Planet Simulator. https://doi.org/10.1594/PANGAEA.884574

DOI retrieved: 2018

Additional Info

Field Value
Imported on November 30, 2024
Last update November 30, 2024
License CC-BY-3.0
Source https://doi.org/10.1594/PANGAEA.884574
Author Lyu, Guokun
Given Name Guokun
Family Name Lyu
More Authors
Köhl, Armin
Matei, Ion
Stammer, Detlef
Source Creation 2018
Publication Year 2018
Subject Areas
Name: Atmosphere

Related Identifiers
Title: Adjoint-Based Climate Model Tuning: Application to the Planet Simulator
Identifier: https://doi.org/10.1002/2017MS001194
Type: DOI
Relation: References
Year: 2018
Source: Journal of Advances in Modeling Earth Systems
Authors: Lyu Guokun , Köhl Armin , Matei Ion , Stammer Detlef .