Agreement in late twentieth century Southern Hemisphere stratospheric temperature trends in observations and CCMVal‐2, CMIP3, and CMIP5 models. Issue 2 (31st January 2013) - Young, Paul J.; Butler, Amy H.; Calvo, Natalia; Haimberger, Leopold; Kushner, Paul J.; Marsh, Daniel R.; Randel, William J.; Rosenlof, Karen H.
Abstract : [1] We present a comparison of temperature trends using different satellite and radiosonde observations and climate (GCM) and chemistry‐climate model (CCM) outputs, focusing on the role of photochemical ozone depletion in the Antarctic lower stratosphere during the second half of the twentieth century. Ozone‐induced stratospheric cooling peaks during November at an altitude of approximately 100 hPa in radiosonde observations, with 1969 to 1998 trends in the range of −3.8 to −4.7 K/dec. This stratospheric cooling trend is more than 50% greater than the previously estimated value of −2.4 K/dec, which suggested that the CCMs were overestimating the stratospheric cooling, and that the less complex GCMs forced by prescribed ozone were matching observations better. Corresponding ensemble mean model trends are −3.8 K/dec for the CCMs, −3.5 K/dec for the CMIP5 GCMs, and −2.7 K/dec for the CMIP3 GCMs. Accounting for various sources of uncertainty—including sampling uncertainty, measurement error, model spread, and trend confidence intervals—observations and CCM and GCM ensembles are consistent in this new analysis. This consistency does not apply to each individual that makes up the GCM and CCM ensembles, and some do not show significant ozone‐induced cooling. Nonetheless, analysis of the joint ozone and temperature trends in the CCMs suggests that the modeled cooling/ozone‐depletion relationship is within the range of observations. Overall, this study emphasizes the need to use a wide range of observations for model validation as well as sufficient accounting of uncertainty in both models and measurements. Key Points: Models and observations agree within their uncertainties Observed trends are 50% stronger than previously calculated value Study emphasizes need to use a wide range of observations for model evaluation