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Title: A comparison of surface air temperature variability in three 1000-Yr. coupled ocean-atmosphere model integrations

Abstract

This study compares the variability of surface air temperature in three long coupled ocean-atmosphere general circulation model integrations. It is shown that the annual mean climatology of the surface air temperatures (SAT) in all three models is realistic and the linear trends over the 1,000-yr integrations are small over most areas of the globe. Second, although there are notable differences among the models, the models' SAT variability is fairly realistic on annual to decadal timescales, both in terms of the geographical distribution and of the global mean values. A notable exception is the poor simulation of observed tropical Pacific variability. In the HadCM2 model, the tropical variability is overestimated, while in the GFDL and HAM3L models, it is underestimated. Also, the ENSO-related spectral peak in the globally averaged observed SAT differs from that in any of the models. The relatively low resolution required to integrate models for long time periods inhibits the successful simulation of the variability in this region. On timescales longer than a few decades, the largest variance in the models is generally located near sea ice margins in high latitudes, which are also regions of deep oceanic convection and variability related to variations in the thermohaline circulation.more » However, the exact geographical location of these maxima varies from model to model. The preferred patterns of interdecadal variability that are common to all three coupled models can be isolated by computing empirical orthogonal functions (EOFs) of all model data simultaneously using the common EOF technique. A comparison of the variance each model associated with these common EOF patterns shows that the models generally agree on the most prominent patterns of variability. However, the amplitudes of the dominant models of variability differ to some extent between the models and between the models and observations. For example, two of the models have a mode with relatively large values of the same sign over most of the Northern Hemisphere midlatitudes. This mode has been shown to be relevant for the separation of the temperature response pattern due to sulfate aerosol forcing from the response to greenhouse gas forcing.« less

Authors:
; ;
Publication Date:
Research Org.:
National Oceanic and Atmospheric Administration, Princeton, NJ (US)
OSTI Identifier:
20020693
Resource Type:
Journal Article
Journal Name:
Journal of Climate
Additional Journal Information:
Journal Volume: 13; Journal Issue: 3; Other Information: PBD: 1 Feb 2000; Journal ID: ISSN 0894-8755
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; AMBIENT TEMPERATURE; CLIMATIC CHANGE; GREENHOUSE GASES; H CODES; G CODES; SULFATES; ENVIRONMENTAL IMPACTS; COMPARATIVE EVALUATIONS

Citation Formats

Stouffer, R J, Hegerl, G, and Tett, S. A comparison of surface air temperature variability in three 1000-Yr. coupled ocean-atmosphere model integrations. United States: N. p., 2000. Web. doi:10.1175/1520-0442(2000)013<0513:ACOSAT>2.0.CO;2.
Stouffer, R J, Hegerl, G, & Tett, S. A comparison of surface air temperature variability in three 1000-Yr. coupled ocean-atmosphere model integrations. United States. https://doi.org/10.1175/1520-0442(2000)013<0513:ACOSAT>2.0.CO;2
Stouffer, R J, Hegerl, G, and Tett, S. 2000. "A comparison of surface air temperature variability in three 1000-Yr. coupled ocean-atmosphere model integrations". United States. https://doi.org/10.1175/1520-0442(2000)013<0513:ACOSAT>2.0.CO;2.
@article{osti_20020693,
title = {A comparison of surface air temperature variability in three 1000-Yr. coupled ocean-atmosphere model integrations},
author = {Stouffer, R J and Hegerl, G and Tett, S},
abstractNote = {This study compares the variability of surface air temperature in three long coupled ocean-atmosphere general circulation model integrations. It is shown that the annual mean climatology of the surface air temperatures (SAT) in all three models is realistic and the linear trends over the 1,000-yr integrations are small over most areas of the globe. Second, although there are notable differences among the models, the models' SAT variability is fairly realistic on annual to decadal timescales, both in terms of the geographical distribution and of the global mean values. A notable exception is the poor simulation of observed tropical Pacific variability. In the HadCM2 model, the tropical variability is overestimated, while in the GFDL and HAM3L models, it is underestimated. Also, the ENSO-related spectral peak in the globally averaged observed SAT differs from that in any of the models. The relatively low resolution required to integrate models for long time periods inhibits the successful simulation of the variability in this region. On timescales longer than a few decades, the largest variance in the models is generally located near sea ice margins in high latitudes, which are also regions of deep oceanic convection and variability related to variations in the thermohaline circulation. However, the exact geographical location of these maxima varies from model to model. The preferred patterns of interdecadal variability that are common to all three coupled models can be isolated by computing empirical orthogonal functions (EOFs) of all model data simultaneously using the common EOF technique. A comparison of the variance each model associated with these common EOF patterns shows that the models generally agree on the most prominent patterns of variability. However, the amplitudes of the dominant models of variability differ to some extent between the models and between the models and observations. For example, two of the models have a mode with relatively large values of the same sign over most of the Northern Hemisphere midlatitudes. This mode has been shown to be relevant for the separation of the temperature response pattern due to sulfate aerosol forcing from the response to greenhouse gas forcing.},
doi = {10.1175/1520-0442(2000)013<0513:ACOSAT>2.0.CO;2},
url = {https://www.osti.gov/biblio/20020693}, journal = {Journal of Climate},
issn = {0894-8755},
number = 3,
volume = 13,
place = {United States},
year = {Tue Feb 01 00:00:00 EST 2000},
month = {Tue Feb 01 00:00:00 EST 2000}
}