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  4. 'Climate Response Functions' for the Arctic Ocean: a proposedcoordinated modeling experiment

'Climate Response Functions' for the Arctic Ocean: a proposedcoordinated modeling experiment

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Author(s)
Proshutinsky, Andrey
•
Marshall, John C
•
Scott, Jeremy
Date Issued
July 2017
Journal
Geoscientific Model Development Discussions
Publisher
Copernicus GmbH
Citation
Marshall, John et al. “‘Climate Response Functions’ for the Arctic Ocean: a Proposed Coordinated Modeling Experiment.” Geoscientific Model Development Discussions 10 (January 2017): 2833-2848 © 2017 Author(s)
Version
Final published version
Abstract
A coordinated set of Arctic modelling experiments, which explore how the Arctic responds to changes in external forcing, is proposed. Our goal is to compute and compare “climate response functions” (CRFs) – the transient response of key observable indicators such as sea-ice extent, freshwater content of the Beaufort Gyre, etc. – to abrupt “step” changes in forcing fields across a number of Arctic models. Changes in wind, freshwater sources, and inflows to the Arctic basin are considered. Convolutions of known or postulated time series of these forcing fields with their respective CRFs then yield the (linear) response of these observables. This allows the project to inform, and interface directly with, Arctic observations and observers and the climate change community. Here we outline the rationale behind such experiments and illustrate our approach in the context of a coarse-resolution model of the Arctic based on the MITgcm. We conclude by summarizing the expected benefits of such an activity and encourage other modelling groups to compute CRFs with their own models so that we might begin to document their robustness to model formulation, resolution, and parameterization.
MIT Department
Massachusetts Institute of Technology. Department of Earth, Atmospheric, and Planetary Sciences
Terms of Use
Creative Commons Attribution 3.0 Unported license
http://creativecommons.org/licenses/by/3.0/
Persistent DSpace Link
http://hdl.handle.net/1721.1/115217
DOI of Published Version
https://doi.org/10.5194/GMD-2016-316
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