Induced surface fluxes: a new framework for attributing Arctic sea ice volume balance biases to specific model errors

A new framework is presented for analysing the proximate causes of model Arctic sea ice biases, demonstrated with the CMIP5 model HadGEM2-ES (Hadley Centre Global Environment Model version 2 – Earth System). In this framework the Arctic sea ice volume is treated as a consequence of the integrated su...

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Published in:The Cryosphere
Main Authors: A. West, M. Collins, E. Blockley, J. Ridley, A. Bodas-Salcedo
Format: Article in Journal/Newspaper
Language:English
Published: Copernicus Publications 2019
Subjects:
Online Access:https://doi.org/10.5194/tc-13-2001-2019
https://www.the-cryosphere.net/13/2001/2019/tc-13-2001-2019.pdf
https://doaj.org/article/ce089c9d0d514fe89d5891abf5659783
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author A. West
M. Collins
E. Blockley
J. Ridley
A. Bodas-Salcedo
author_facet A. West
M. Collins
E. Blockley
J. Ridley
A. Bodas-Salcedo
author_sort A. West
collection Unknown
container_issue 7
container_start_page 2001
container_title The Cryosphere
container_volume 13
description A new framework is presented for analysing the proximate causes of model Arctic sea ice biases, demonstrated with the CMIP5 model HadGEM2-ES (Hadley Centre Global Environment Model version 2 – Earth System). In this framework the Arctic sea ice volume is treated as a consequence of the integrated surface energy balance, via the volume balance. A simple model allows the local dependence of the surface flux on specific model variables to be described as a function of time and space. When these are combined with reference datasets, it is possible to estimate the surface flux bias induced by the model bias in each variable. The method allows the role of the surface albedo and ice thickness–growth feedbacks in sea ice volume balance biases to be quantified along with the roles of model bias in variables not directly related to the sea ice volume. It shows biases in the HadGEM2-ES sea ice volume simulation to be due to a bias in spring surface melt onset date, partly countered by a bias in winter downwelling longwave radiation. The framework is applicable in principle to any model and has the potential to greatly improve understanding of the reasons for ensemble spread in the modelled sea ice state. A secondary finding is that observational uncertainty is the largest cause of uncertainty in the induced surface flux bias calculation.
format Article in Journal/Newspaper
genre albedo
Arctic
Sea ice
The Cryosphere
genre_facet albedo
Arctic
Sea ice
The Cryosphere
geographic Arctic
geographic_facet Arctic
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spelling fttriple:oai:gotriple.eu:oai:doaj.org/article:ce089c9d0d514fe89d5891abf5659783 2025-01-16T18:43:11+00:00 Induced surface fluxes: a new framework for attributing Arctic sea ice volume balance biases to specific model errors A. West M. Collins E. Blockley J. Ridley A. Bodas-Salcedo 2019-07-01 https://doi.org/10.5194/tc-13-2001-2019 https://www.the-cryosphere.net/13/2001/2019/tc-13-2001-2019.pdf https://doaj.org/article/ce089c9d0d514fe89d5891abf5659783 en eng Copernicus Publications doi:10.5194/tc-13-2001-2019 1994-0416 1994-0424 https://www.the-cryosphere.net/13/2001/2019/tc-13-2001-2019.pdf https://doaj.org/article/ce089c9d0d514fe89d5891abf5659783 undefined The Cryosphere, Vol 13, Pp 2001-2022 (2019) geo envir Journal Article https://vocabularies.coar-repositories.org/resource_types/c_6501/ 2019 fttriple https://doi.org/10.5194/tc-13-2001-2019 2023-01-22T19:23:33Z A new framework is presented for analysing the proximate causes of model Arctic sea ice biases, demonstrated with the CMIP5 model HadGEM2-ES (Hadley Centre Global Environment Model version 2 – Earth System). In this framework the Arctic sea ice volume is treated as a consequence of the integrated surface energy balance, via the volume balance. A simple model allows the local dependence of the surface flux on specific model variables to be described as a function of time and space. When these are combined with reference datasets, it is possible to estimate the surface flux bias induced by the model bias in each variable. The method allows the role of the surface albedo and ice thickness–growth feedbacks in sea ice volume balance biases to be quantified along with the roles of model bias in variables not directly related to the sea ice volume. It shows biases in the HadGEM2-ES sea ice volume simulation to be due to a bias in spring surface melt onset date, partly countered by a bias in winter downwelling longwave radiation. The framework is applicable in principle to any model and has the potential to greatly improve understanding of the reasons for ensemble spread in the modelled sea ice state. A secondary finding is that observational uncertainty is the largest cause of uncertainty in the induced surface flux bias calculation. Article in Journal/Newspaper albedo Arctic Sea ice The Cryosphere Unknown Arctic The Cryosphere 13 7 2001 2022
spellingShingle geo
envir
A. West
M. Collins
E. Blockley
J. Ridley
A. Bodas-Salcedo
Induced surface fluxes: a new framework for attributing Arctic sea ice volume balance biases to specific model errors
title Induced surface fluxes: a new framework for attributing Arctic sea ice volume balance biases to specific model errors
title_full Induced surface fluxes: a new framework for attributing Arctic sea ice volume balance biases to specific model errors
title_fullStr Induced surface fluxes: a new framework for attributing Arctic sea ice volume balance biases to specific model errors
title_full_unstemmed Induced surface fluxes: a new framework for attributing Arctic sea ice volume balance biases to specific model errors
title_short Induced surface fluxes: a new framework for attributing Arctic sea ice volume balance biases to specific model errors
title_sort induced surface fluxes: a new framework for attributing arctic sea ice volume balance biases to specific model errors
topic geo
envir
topic_facet geo
envir
url https://doi.org/10.5194/tc-13-2001-2019
https://www.the-cryosphere.net/13/2001/2019/tc-13-2001-2019.pdf
https://doaj.org/article/ce089c9d0d514fe89d5891abf5659783