A Comparison of Surface Air Temperature Variability in Three 1000-Yr Coupled Ocean–Atmosphere Model Integrations

Ronald J. Stouffer NOAA/Geophysical Fluid Dynamics Laboratory, Princeton, New Jersey

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Gabriele Hegerl University of Washington, Joint Institute for the Study of the Atmosphere and Ocean, Seattle, Washington

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Simon Tett Hadley Centre for Climate Prediction and Research, Bracknell, United Kingdom

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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 1000-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 modes 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. This indicates that the results of the detection of climate change and its attribution to different external forcings may differ when unperturbed climate variability in surface air temperature is estimated using different coupled models. Assuming that the simulation of variability of the global mean SAT is as realistic on longer timescales as it is for the shorter timescales, then the observed warming of more than 0.5 K of the SAT in the last 110 yr is not likely to be due to internally generated variability of the coupled atmosphere–ocean–sea ice system. Instead, the warming is likely to be due to changes in the radiative forcing of the climate system, such as the forcing associated with increases in greenhouse gases.

Corresponding author address: Mr. Ronald J. Stouffer, Geophysical Fluid Dynamics Laboratory/NOAA, Forrestal Campus, Forrestal Road/U.S. Route 1, P.O. Box 308, Princeton, NJ 08542.

Email: rjs@gfdl.gov

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 1000-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 modes 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. This indicates that the results of the detection of climate change and its attribution to different external forcings may differ when unperturbed climate variability in surface air temperature is estimated using different coupled models. Assuming that the simulation of variability of the global mean SAT is as realistic on longer timescales as it is for the shorter timescales, then the observed warming of more than 0.5 K of the SAT in the last 110 yr is not likely to be due to internally generated variability of the coupled atmosphere–ocean–sea ice system. Instead, the warming is likely to be due to changes in the radiative forcing of the climate system, such as the forcing associated with increases in greenhouse gases.

Corresponding author address: Mr. Ronald J. Stouffer, Geophysical Fluid Dynamics Laboratory/NOAA, Forrestal Campus, Forrestal Road/U.S. Route 1, P.O. Box 308, Princeton, NJ 08542.

Email: rjs@gfdl.gov

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