“Climate response functions” for the Arctic Ocean: a proposed coordinated modelling experiment

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...

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Bibliographic Details
Published in:Geoscientific Model Development
Main Authors: Marshall, John, Scott, Jeffery, Proshutinsky, Andrey
Format: Article in Journal/Newspaper
Language:English
Published: Copernicus Publications 2017
Subjects:
Online Access:https://doi.org/10.5194/gmd-10-2833-2017
https://noa.gwlb.de/receive/cop_mods_00009547
https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00009504/gmd-10-2833-2017.pdf
https://gmd.copernicus.org/articles/10/2833/2017/gmd-10-2833-2017.pdf
Description
Summary: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.