Stochastic variability at the air‐sea interface on decadal timescales
Multiple integrations of an atmospheric general circulation model (AGCM) exhibit differences in the decadal mean of the surface heat flux, Q. The differences (typically 2–3 Wm−2) can be as large as 10 Wm−2 in places, which are shown to produce sea‐surface temperature (SST) changes up to approximatel...
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1995
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Online Access: | https://research.usq.edu.au/item/q6wz7/stochastic-variability-at-the-air-sea-interface-on-decadal-timescales https://doi.org/10.1029/95GL02655 |
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ftusqland:oai:research.usq.edu.au:q6wz7 2023-08-27T04:11:56+02:00 Stochastic variability at the air‐sea interface on decadal timescales Power, S. B. Tseitkin, F. Dix, M. Kleeman, R. Colman, R. Holland, D. 1995 https://research.usq.edu.au/item/q6wz7/stochastic-variability-at-the-air-sea-interface-on-decadal-timescales https://doi.org/10.1029/95GL02655 unknown https://doi.org/10.1029/95GL02655 Power, S. B., Tseitkin, F., Dix, M., Kleeman, R., Colman, R. and Holland, D. 1995. "Stochastic variability at the air‐sea interface on decadal timescales." Geophysical Research Letters. 22 (19), pp. 2593-2596. https://doi.org/10.1029/95GL02655 air-sea interface atmospheric circulation model decadal variability heat transfer sea surface temperature stochastic fluxes surface heat flux article PeerReviewed 1995 ftusqland https://doi.org/10.1029/95GL02655 2023-08-07T22:32:45Z Multiple integrations of an atmospheric general circulation model (AGCM) exhibit differences in the decadal mean of the surface heat flux, Q. The differences (typically 2–3 Wm−2) can be as large as 10 Wm−2 in places, which are shown to produce sea‐surface temperature (SST) changes up to approximately 0.5°C in a hybrid coupled atmosphere/ocean/sea‐ice model or HCM. This underscores a significant mechanism by which long‐lived SST anomalies can arise, independent of any internal ocean variability, for which there is very little predictive capability. Consequently, AGCM integrations using prescribed SSTs provide upper bounds on the predictability of atmospheric variability. The HCM is used to estimate the magnitude of the drift in the climatology of coupled models if flux adjustments are based on AGCM integrations of decadal duration. The random interannual fluctuations in Q averaged over the ocean are most closely associated with fluctuations in surface latent heating and long wave radiation to space. The same fluctuations are not associated with land surface variability. The impact of variability in other fluxes on SST in the HCM was also analysed. Changes due to wind‐stress were approximately half those due to heating, while changes due to freshwater forcing were relatively unimportant except at polar latitudes. Article in Journal/Newspaper Sea ice University of Southern Queensland: USQ ePrints Geophysical Research Letters 22 19 2593 2596 |
institution |
Open Polar |
collection |
University of Southern Queensland: USQ ePrints |
op_collection_id |
ftusqland |
language |
unknown |
topic |
air-sea interface atmospheric circulation model decadal variability heat transfer sea surface temperature stochastic fluxes surface heat flux |
spellingShingle |
air-sea interface atmospheric circulation model decadal variability heat transfer sea surface temperature stochastic fluxes surface heat flux Power, S. B. Tseitkin, F. Dix, M. Kleeman, R. Colman, R. Holland, D. Stochastic variability at the air‐sea interface on decadal timescales |
topic_facet |
air-sea interface atmospheric circulation model decadal variability heat transfer sea surface temperature stochastic fluxes surface heat flux |
description |
Multiple integrations of an atmospheric general circulation model (AGCM) exhibit differences in the decadal mean of the surface heat flux, Q. The differences (typically 2–3 Wm−2) can be as large as 10 Wm−2 in places, which are shown to produce sea‐surface temperature (SST) changes up to approximately 0.5°C in a hybrid coupled atmosphere/ocean/sea‐ice model or HCM. This underscores a significant mechanism by which long‐lived SST anomalies can arise, independent of any internal ocean variability, for which there is very little predictive capability. Consequently, AGCM integrations using prescribed SSTs provide upper bounds on the predictability of atmospheric variability. The HCM is used to estimate the magnitude of the drift in the climatology of coupled models if flux adjustments are based on AGCM integrations of decadal duration. The random interannual fluctuations in Q averaged over the ocean are most closely associated with fluctuations in surface latent heating and long wave radiation to space. The same fluctuations are not associated with land surface variability. The impact of variability in other fluxes on SST in the HCM was also analysed. Changes due to wind‐stress were approximately half those due to heating, while changes due to freshwater forcing were relatively unimportant except at polar latitudes. |
format |
Article in Journal/Newspaper |
author |
Power, S. B. Tseitkin, F. Dix, M. Kleeman, R. Colman, R. Holland, D. |
author_facet |
Power, S. B. Tseitkin, F. Dix, M. Kleeman, R. Colman, R. Holland, D. |
author_sort |
Power, S. B. |
title |
Stochastic variability at the air‐sea interface on decadal timescales |
title_short |
Stochastic variability at the air‐sea interface on decadal timescales |
title_full |
Stochastic variability at the air‐sea interface on decadal timescales |
title_fullStr |
Stochastic variability at the air‐sea interface on decadal timescales |
title_full_unstemmed |
Stochastic variability at the air‐sea interface on decadal timescales |
title_sort |
stochastic variability at the air‐sea interface on decadal timescales |
publishDate |
1995 |
url |
https://research.usq.edu.au/item/q6wz7/stochastic-variability-at-the-air-sea-interface-on-decadal-timescales https://doi.org/10.1029/95GL02655 |
genre |
Sea ice |
genre_facet |
Sea ice |
op_relation |
https://doi.org/10.1029/95GL02655 Power, S. B., Tseitkin, F., Dix, M., Kleeman, R., Colman, R. and Holland, D. 1995. "Stochastic variability at the air‐sea interface on decadal timescales." Geophysical Research Letters. 22 (19), pp. 2593-2596. https://doi.org/10.1029/95GL02655 |
op_doi |
https://doi.org/10.1029/95GL02655 |
container_title |
Geophysical Research Letters |
container_volume |
22 |
container_issue |
19 |
container_start_page |
2593 |
op_container_end_page |
2596 |
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1775355622089293824 |