Using ensemble prediction methods to examine regional climate variation under global warming scenarios

The fate of the North Atlantic thermohaline circulation (THC) is of great significance for regional climate prediction. Research based on both numerical modelling and paleoclimate data has suggested that the THC might be intrinsically bistable, and could have the potential to switch rapidly between...

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Published in:Ocean Modelling
Main Authors: Hargreaves, J.C., Annan, J.D.
Format: Article in Journal/Newspaper
Language:unknown
Published: Elsevier 2006
Subjects:
Online Access:http://nora.nerc.ac.uk/id/eprint/530/
https://doi.org/10.1016/j.ocemod.2004.12.004
id ftnerc:oai:nora.nerc.ac.uk:530
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spelling ftnerc:oai:nora.nerc.ac.uk:530 2024-06-09T07:48:16+00:00 Using ensemble prediction methods to examine regional climate variation under global warming scenarios Hargreaves, J.C. Annan, J.D. 2006 http://nora.nerc.ac.uk/id/eprint/530/ https://doi.org/10.1016/j.ocemod.2004.12.004 unknown Elsevier Hargreaves, J.C.; Annan, J.D. 2006 Using ensemble prediction methods to examine regional climate variation under global warming scenarios. Ocean Modelling, 11 (1-2). 174-192. https://doi.org/10.1016/j.ocemod.2004.12.004 <https://doi.org/10.1016/j.ocemod.2004.12.004> Marine Sciences Publication - Article PeerReviewed 2006 ftnerc https://doi.org/10.1016/j.ocemod.2004.12.004 2024-05-15T08:39:04Z The fate of the North Atlantic thermohaline circulation (THC) is of great significance for regional climate prediction. Research based on both numerical modelling and paleoclimate data has suggested that the THC might be intrinsically bistable, and could have the potential to switch rapidly between its stable modes. Using a low-resolution intermediate complexity model, we investigate the predictability of the response of the THC to anthropogenic forcing in the medium (100 years) and longer term. Using an ensemble Kalman filter we can efficiently tune the climate of ensemble members by varying multiple parameters simultaneously, and flux adjustments are not required to prevent unreasonable model drift. However, some biases remain, and we demonstrate that the common approach of subtracting the bias from a model forecast can result in substantial errors when the model state is close to a nonlinear threshold. Over 100 years of 1% per annum atmospheric CO2 enrichment, the THC drops significantly but steadily by about 4 or 5 Sv, a result that appears robust over a wide range of scenarios. In the longer term, the THC can collapse entirely, or recover to its original state, and small changes in the present uncertainties can have a large effect on the future outcomes. We conclude that generating reliable forecasts over the next century should be achievable, but the long term behaviour remains highly unpredictable. Article in Journal/Newspaper North Atlantic North atlantic Thermohaline circulation Natural Environment Research Council: NERC Open Research Archive Ocean Modelling 11 1-2 174 192
institution Open Polar
collection Natural Environment Research Council: NERC Open Research Archive
op_collection_id ftnerc
language unknown
topic Marine Sciences
spellingShingle Marine Sciences
Hargreaves, J.C.
Annan, J.D.
Using ensemble prediction methods to examine regional climate variation under global warming scenarios
topic_facet Marine Sciences
description The fate of the North Atlantic thermohaline circulation (THC) is of great significance for regional climate prediction. Research based on both numerical modelling and paleoclimate data has suggested that the THC might be intrinsically bistable, and could have the potential to switch rapidly between its stable modes. Using a low-resolution intermediate complexity model, we investigate the predictability of the response of the THC to anthropogenic forcing in the medium (100 years) and longer term. Using an ensemble Kalman filter we can efficiently tune the climate of ensemble members by varying multiple parameters simultaneously, and flux adjustments are not required to prevent unreasonable model drift. However, some biases remain, and we demonstrate that the common approach of subtracting the bias from a model forecast can result in substantial errors when the model state is close to a nonlinear threshold. Over 100 years of 1% per annum atmospheric CO2 enrichment, the THC drops significantly but steadily by about 4 or 5 Sv, a result that appears robust over a wide range of scenarios. In the longer term, the THC can collapse entirely, or recover to its original state, and small changes in the present uncertainties can have a large effect on the future outcomes. We conclude that generating reliable forecasts over the next century should be achievable, but the long term behaviour remains highly unpredictable.
format Article in Journal/Newspaper
author Hargreaves, J.C.
Annan, J.D.
author_facet Hargreaves, J.C.
Annan, J.D.
author_sort Hargreaves, J.C.
title Using ensemble prediction methods to examine regional climate variation under global warming scenarios
title_short Using ensemble prediction methods to examine regional climate variation under global warming scenarios
title_full Using ensemble prediction methods to examine regional climate variation under global warming scenarios
title_fullStr Using ensemble prediction methods to examine regional climate variation under global warming scenarios
title_full_unstemmed Using ensemble prediction methods to examine regional climate variation under global warming scenarios
title_sort using ensemble prediction methods to examine regional climate variation under global warming scenarios
publisher Elsevier
publishDate 2006
url http://nora.nerc.ac.uk/id/eprint/530/
https://doi.org/10.1016/j.ocemod.2004.12.004
genre North Atlantic
North atlantic Thermohaline circulation
genre_facet North Atlantic
North atlantic Thermohaline circulation
op_relation Hargreaves, J.C.; Annan, J.D. 2006 Using ensemble prediction methods to examine regional climate variation under global warming scenarios. Ocean Modelling, 11 (1-2). 174-192. https://doi.org/10.1016/j.ocemod.2004.12.004 <https://doi.org/10.1016/j.ocemod.2004.12.004>
op_doi https://doi.org/10.1016/j.ocemod.2004.12.004
container_title Ocean Modelling
container_volume 11
container_issue 1-2
container_start_page 174
op_container_end_page 192
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