Baseline evaluation of the impact of updates to the MIT Earth System Model on its model parameter estimates
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Published:2018-08-21
Issue:8
Volume:11
Page:3313-3325
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ISSN:1991-9603
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Container-title:Geoscientific Model Development
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language:en
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Short-container-title:Geosci. Model Dev.
Author:
Libardoni Alex G., Forest Chris E.ORCID, Sokolov Andrei P., Monier ErwanORCID
Abstract
Abstract. For over 20 years, the Massachusetts Institute of Technology Earth System
Model (MESM) has been used extensively for climate change research. The model
is under continuous development with components being added and updated. To
provide transparency in the model development, we perform a baseline
evaluation by comparing model behavior and properties in the newest version
to the previous model version. In particular, changes resulting from updates
to the land surface model component and the input forcings used in historical
simulations of climate change are investigated. We run an 1800-member
ensemble of MESM historical climate simulations where the model parameters
that set climate sensitivity, the rate of ocean heat uptake, and the net
anthropogenic aerosol forcing are systematically varied. By comparing model
output to observed patterns of surface temperature changes and the linear
trend in the increase in ocean heat content, we derive probability
distributions for the three model parameters. Furthermore, we run a
372-member ensemble of transient climate simulations where all model forcings
are fixed and carbon dioxide concentrations are increased at the rate of
1 % year−1. From these runs, we derive response surfaces for
transient climate response and thermosteric sea level rise as a function of
climate sensitivity and ocean heat uptake. We show that the probability
distributions shift towards higher climate sensitivities and weaker aerosol
forcing when using the new model and that the climate response surfaces are
relatively unchanged between model versions. Because the response surfaces
are independent of the changes to the model forcings and similar between
model versions with different land surface models, we suggest that the change
in land surface model has limited impact on the temperature evolution in the
model. Thus, we attribute the shifts in parameter estimates to the updated
model forcings.
Funder
Biological and Environmental Research
Publisher
Copernicus GmbH
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