A systematic approach to identify the sources of tropical SST errors in coupled models using the adjustment of initialised experiments
A systematic approach to identify the sources of tropical SST errors in coupled models using the adjustment of initialised experiments
Understanding the sources of systematic errors in climate models is challenging because of coupled feedbacks and errors compensation. The developing seamless approach proposes that the identification and the correction of short term climate model errors have the potential to improve the modeled climate on longer time scales. In previous studies, initialised atmospheric simulations of a few days have been used to compare fast physics processes (convection, cloud processes) among models. The present study explores how initialised seasonal to decadal hindcasts (re-forecasts) relate transient week-to-month errors of the ocean and atmospheric components to the coupled model long-term pervasive SST errors. A protocol is designed to attribute the SST biases to the source processes. It includes five steps: (1) identify and describe biases in a coupled stabilized simulation, (2) determine the time scale of the advent of the bias and its propagation, (3) find the geographical origin of the bias, (4) evaluate the degree of coupling in the development of the bias, (5) find the field responsible for the bias. This strategy has been implemented with a set of experiments based on the initial adjustment of initialised simulations and exploring various degrees of coupling. In particular, hindcasts give the time scale of biases advent, regionally restored experiments show the geographical origin and ocean-only simulations isolate the field responsible for the bias and evaluate the degree of coupling in the bias development. This strategy is applied to four prominent SST biases of the IPSLCM5A-LR coupled model in the tropical Pacific, that are largely shared by other coupled models, including the Southeast Pacific warm bias and the equatorial cold tongue bias. Using the proposed protocol, we demonstrate that the East Pacific warm bias appears in a few months and is caused by a lack of upwelling due to too weak meridional coastal winds off Peru. The cold equatorial bias, which surprisingly takes 30 years to develop, is the result of an equatorward advection of midlatitude cold SST errors. Despite large development efforts, the current generation of coupled models shows only little improvement. The strategy proposed in this study is a further step to move from the current random ad hoc approach, to a bias-targeted, priority setting, systematic model development approach.
GCMs errors, Seasonal forecasts, Tropical Pacific, Cold tongue bias
2261-2282
Vannière, Benoît
fd9185a0-60c2-4130-ad43-16d235d0b888
Guilyardi, Eric
7a596a3f-7c16-4d5b-8fa8-13848959694d
Toniazzo, Thomas
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Madec, Gurvan
ffb28deb-4bbd-4a4c-914f-492f813e4864
Woolnough, Steve
8498b5e9-7476-490b-a693-833460d9f2e6
October 2014
Vannière, Benoît
fd9185a0-60c2-4130-ad43-16d235d0b888
Guilyardi, Eric
7a596a3f-7c16-4d5b-8fa8-13848959694d
Toniazzo, Thomas
9cf23d70-0dd5-4bdd-ab3b-26a9243e36e9
Madec, Gurvan
ffb28deb-4bbd-4a4c-914f-492f813e4864
Woolnough, Steve
8498b5e9-7476-490b-a693-833460d9f2e6
Vannière, Benoît, Guilyardi, Eric, Toniazzo, Thomas, Madec, Gurvan and Woolnough, Steve
(2014)
A systematic approach to identify the sources of tropical SST errors in coupled models using the adjustment of initialised experiments.
Climate Dynamics, 43 (7-8), .
(doi:10.1007/s00382-014-2051-6).
Abstract
Understanding the sources of systematic errors in climate models is challenging because of coupled feedbacks and errors compensation. The developing seamless approach proposes that the identification and the correction of short term climate model errors have the potential to improve the modeled climate on longer time scales. In previous studies, initialised atmospheric simulations of a few days have been used to compare fast physics processes (convection, cloud processes) among models. The present study explores how initialised seasonal to decadal hindcasts (re-forecasts) relate transient week-to-month errors of the ocean and atmospheric components to the coupled model long-term pervasive SST errors. A protocol is designed to attribute the SST biases to the source processes. It includes five steps: (1) identify and describe biases in a coupled stabilized simulation, (2) determine the time scale of the advent of the bias and its propagation, (3) find the geographical origin of the bias, (4) evaluate the degree of coupling in the development of the bias, (5) find the field responsible for the bias. This strategy has been implemented with a set of experiments based on the initial adjustment of initialised simulations and exploring various degrees of coupling. In particular, hindcasts give the time scale of biases advent, regionally restored experiments show the geographical origin and ocean-only simulations isolate the field responsible for the bias and evaluate the degree of coupling in the bias development. This strategy is applied to four prominent SST biases of the IPSLCM5A-LR coupled model in the tropical Pacific, that are largely shared by other coupled models, including the Southeast Pacific warm bias and the equatorial cold tongue bias. Using the proposed protocol, we demonstrate that the East Pacific warm bias appears in a few months and is caused by a lack of upwelling due to too weak meridional coastal winds off Peru. The cold equatorial bias, which surprisingly takes 30 years to develop, is the result of an equatorward advection of midlatitude cold SST errors. Despite large development efforts, the current generation of coupled models shows only little improvement. The strategy proposed in this study is a further step to move from the current random ad hoc approach, to a bias-targeted, priority setting, systematic model development approach.
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Published date: October 2014
Keywords:
GCMs errors, Seasonal forecasts, Tropical Pacific, Cold tongue bias
Organisations:
Marine Systems Modelling
Identifiers
Local EPrints ID: 370754
URI: http://eprints.soton.ac.uk/id/eprint/370754
ISSN: 0930-7575
PURE UUID: e1f19c31-4be1-41fd-ab6d-55e9dcb53668
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Date deposited: 05 Nov 2014 17:17
Last modified: 14 Mar 2024 18:21
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Contributors
Author:
Benoît Vannière
Author:
Eric Guilyardi
Author:
Thomas Toniazzo
Author:
Gurvan Madec
Author:
Steve Woolnough
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