Alexey Yu. Karpechko

Stratosphere-troposphere coupling and annular mode variability in chemistry-climate models

The internal variability and coupling between the stratosphere and troposphere in CCMValA¢Â�Â�2 chemistryA¢Â�Â�climate models are evaluated through analysis of the annular mode patterns of variability. Computation of the annular modes in long data sets with secular trends requires refinement of the standard definition of the annular mode, and a more robust procedure that allows for slowly varying trends is established and verified. The spatial and temporal structure of the modelsA¢Â�Â� annular modes is then compared with that of reanalyses. As a whole, the models capture the key features of observed intraseasonal variability, including the sharp vertical gradients in structure between stratosphere and troposphere, the asymmetries in the seasonal cycle between the Northern and Southern hemispheres, and the coupling between the polar stratospheric vortices and tropospheric midlatitude jets. It is also found that the annular mode variability changes little in time throughout simulations of the 21st century. There are, however, both common biases and significant differences in performance in the models. In the troposphere, the annular mode in models is generally too persistent, particularly in the Southern Hemisphere summer, a bias similar to that found in CMIP3 coupled climate models. In the stratosphere, the periods of peak variance and coupling with the troposphere are delayed by about a month in both hemispheres. The relationship between increased variability of the stratosphere and increased persistence in the troposphere suggests that some tropospheric biases may be related to stratospheric biases and that a wellA¢Â�Â�simulated stratosphere can improve simulation of tropospheric intraseasonal variability.

Evaluation of radiation scheme performance within chemistry climate models

[1] This paper evaluates global mean radiatively important properties of chemistry climate models (CCMs). We evaluate stratospheric temperatures and their 1980–2000 trends, January clear sky irradiances, heating rates, and greenhouse gas radiative forcings from an offline comparison of CCM radiation codes with line‐by‐line models, and CCMs’ representation of the solar cycle. CCM global mean temperatures and their change can give an indication of errors in radiative transfer codes and/or atmospheric composition. Biases in the global temperature climatology are generally small, although five out of 18 CCMs show biases in their climatology that likely indicate problems with their radiative transfer codes. Temperature trends also generally agree well with observations, although one model shows significant discrepancies that appear to be due to radiation errors. Heating rates and estimated temperature changes from CO2, ozone, and water vapor changes are generally well modeled. Other gases (N2O, CH4, and CFCs) have only played a minor role in stratospheric temperature change, but their heating rates have large fractional errors in many models. Models that do not account for variations in the spectrum of solar irradiance cannot properly simulate solar‐induced variations in stratospheric temperature. The combined long‐lived greenhouse gas global annual mean instantaneous net radiative forcing at the tropopause is within 30% of line‐by‐line models for all CCM radiation codes tested. Problems remain in simulating radiative forcing for stratospheric water vapor and ozone changes with errors between 3% and 200% compared to line by line models. The paper makes recommendations for CCM radiation code developers and future intercomparisons.

Climate Impacts of the Southern Annular Mode Simulated by the CMIP3 Models

The southern annular mode (SAM) has a well-established impact on climate in the Southern Hemisphere. The strongest response in surface air temperature (SAT) is observed in the Antarctic, but the SAMs area of influence extends much farther, with statistically significant effects on temperature and precipitation being detected as far north as 20°S. Here the authors quantify the ability of the Coupled Model Intercomparison Project, phase 3 (CMIP3) coupled climate models to simulate the observed SAT, total precipitation, sea surface temperature (SST), and sea ice concentration responses to the SAM. The models are able to simulate the spatial pattern of response in SAT reasonably well; however, all models underestimate the magnitude of the response over Antarctica, both at the surface and in the free troposphere. This underestimation of the temperature response has implications for prediction of the future temperature changes associated with expected changes in the SAM. The models possess reasonable skill in simulating patterns of precipitation and SST response; however, some considerable regional deviations exist. The simulated precipitation and SST responses are less constrained by the observations than the SAT response, particularly in magnitude, as significant discrepancies are detected between the responses in the reference datasets. The largest problems are identified in simulating the sea ice response to the SAM, with some models even simulating a response that is negatively correlated with that observed.

Influence of ozone recovery and greenhouse gas increases on Southern Hemisphere circulation

Stratospheric ozone depletion has significantly influenced the tropospheric circulation and climate of the Southern Hemisphere (SH) over recent decades, the largest trends being detected in summer. These circulation changes include acceleration of the extratropical tropospheric westerly jet on its poleward side and lowered Antarctic sea level pressure. It is therefore expected that ozone changes will continue to influence climate during the 21st century when ozone recovery is expected. Here we use two contrasting future ozone projections from two chemistryA¢Â�Â�climate models (CCMs) to force 21st century simulations of the HadGEM1 coupled atmosphereA¢Â�Â�ocean model, along with A1B greenhouse gas (GHG) concentrations, and study the simulated response in the SH circulation. According to several studies, HadGEM1 simulates present tropospheric climate better than the majority of other available models. When forced by the larger ozone recovery trends, HadGEM1 simulates significant deceleration of the tropospheric jet on its poleward side in the upper troposphere in summer, but the trends in the lower troposphere are not significant. In the simulations with the smaller ozone recovery trends the zonal mean zonal wind trends are not significant throughout the troposphere. The response of the SH circulation to GHG concentration increases in HadGEM1 includes an increase in poleward eddy heat flux in the stratosphere and positive sea level pressure trends in southeastern Pacific. The HadGEM1A¢Â�Â�simulated zonal wind trends are considerably smaller than the trends simulated by the CCMs, both in the stratosphere and in the troposphere, despite the fact that the zonal mean ozone trends are the same between these simulations.

Sensitivity of the southern annular mode to greenhouse gas emission scenarios

The leading mode of southern hemisphere (SH) climatic variability, the southern annular mode (SAM), has recently seen a shift towards its positive phase due to stratospheric ozone depletion and increasing greenhouse gas (GHG) concentrations. Here we examine how sensitive the SAM (defined as the leading empirical orthogonal function of SH sea level pressure anomalies) is to future GHG concentrations. We determine its likely evolution for three intergovernmental panel on climate change (IPCC) special report on emission scenarios (SRES) for austral summer and winter, using a multi-model ensemble of IPCC fourth assessment report models which resolve stratospheric ozone recovery. During the period of summer ozone recovery (2000–2050), the SAM index exhibits weakly negative, statistically insignificant trends due to stratospheric ozone recovery which offsets the positive forcing imposed by increasing GHG concentrations. Thereafter, positive SAM index trends occur with magnitudes that show sensitivity to the SRES scenario utilised, and thus future GHG emissions. Trends are determined to be strongest for SRES A2, followed by A1B and B1, respectively. The winter SAM maintains a similar dependency upon GHG as summer, but over the entire twenty-first century and to a greater extent. We also examine the influence of ozone recovery by comparing results to models that exclude stratospheric ozone recovery. Projections are shown to be statistically different from the aforementioned results, highlighting the importance of ozone recovery in governing SAM-evolution. We therefore demonstrate that the future SAM will depend both upon GHG emissions and stratospheric ozone recovery.

Mixed Layer Temperature Response to the Southern Annular Mode: Mechanisms and Model Representation

Abstract Previous studies have shown that simulated sea surface temperature (SST) responses to the southern annular mode (SAM) in phase 3 of the Coupled Model Intercomparison Project (CMIP3) climate models compare poorly to the observed response. The reasons behind these model inaccuracies are explored. The ocean mixed layer heat budget is examined in four of the CMIP3 models and by using observations–reanalyses. The SST response to the SAM is predominantly driven by sensible and latent heat flux and Ekman heat transport anomalies. The radiative heat fluxes play a lesser but nonnegligible role. Errors in the simulated SST responses are traced back to deficiencies in the atmospheric response to the SAM. The models exaggerate the surface wind response to the SAM leading to large unrealistic Ekman transport anomalies. During the positive phase of the SAM, this results in excessive simulated cooling in the 40°–65°S latitudes. Problems with the simulated wind stress responses, which relate partly to errors in ...

Constraining Future Summer Austral Jet Stream Positions in the CMIP5 Ensemble by Process-Oriented Multiple Diagnostic Regression*

Stratospheric ozone recovery and increasing greenhousegases are anticipated to have a large impact on the Southern Hemisphere extratropical circulation, shifting the jet stream and associated storm tracks. Models participating in phase 5 of the Coupled Model Intercomparison Project poorly simulate the austral jet, with a mean equatorward bias and 108 latitude spread in their historical climatologies, and project a wide range of future trends in response to anthropogenic forcing in the representative concentration pathway (RCP) scenarios. Here, the question is addressed whether the unweighted multimodel mean (uMMM) austral jet projection of the RCP4.5 scenario can be improved by applying a process-oriented multiple diagnostic ensemble regression (MDER). MDER links future projections of the jet position to processes relevant to its simulationunderpresent-dayconditions.MDERisfirsttargetedtoconstrainnear-term(2015‐34)projections of the austral jet position and selects the historical jet position as the most important of 20 diagnostics. The method essentially recognizes the equatorward bias in the past jet position and provides a bias correction of about1.58latitudesouthwardtofutureprojections. Whenthetargethorizonis extendedtomidcentury(2040‐ 59), the method also recognizes that lower-stratospheric temperature trends over Antarctica, a proxy for the intensity of ozone depletion, provide additional information that can be used to reduce uncertainty in the ensemble mean projection. MDER does not substantially alter the uMMM long-term position in jet position but reduces the uncertainty in the ensemble mean projection. This result suggests that accurate observational constraints on upper-tropospheric and lower-stratospheric temperature trends are needed to constrain projections of the austral jet position.

A model study of tropospheric impacts of the Arctic ozone depletion 2011

Record Arctic ozone loss in spring 2011 occurred in concert with record positive values of the tropospheric Northern Annular Mode (NAM) index raising the question about the role of stratospheric driver on this tropospheric climate event. A set of 50 years long simulations by atmospheric general circulation model European Centre/Hamburg version 5 (ECHAM5) is carried out and the responses of the model to observed anomalies in stratospheric ozone (O3) and sea surface temperatures (SST) separately and also the response to combined SST and O3 forcing (ALL) are analyzed. In all three experiments the response is characterized by a strengthening of stratospheric polar vortex in March–April. In the ALL experiment, this strengthening is followed by a significant, long-lasting shift of the tropospheric circulation toward a positive NAM phase and increased probability of occurrence of extremely positive NAM events. The combined effect of the O3 and SST forcings on the stratospheric circulation differs from the sum of the individual O3 and SST responses, most likely due to nonlinear effects, leading to a colder stratosphere in February–March. In the troposphere, the sum of the individual responses is comparable in magnitude to the ALL response, but the individual responses are delayed with respect to that in ALL. In summary, these results suggest that both ozone-induced stratospheric cooling and tropospheric forcing associated with the SST anomalies contributed to the record tropospheric climate anomalies observed in spring 2011.

Skilful seasonal predictions of Baltic Sea ice cover

The interannual variability in the Baltic Sea ice cover is strongly influenced by large scale atmospheric circulation. Recent progress in forecasting of the winter North Atlantic Oscillation (NAO) provides the possibility of skilful seasonal predictions of Baltic Sea ice conditions. In this paper we use a state-of-the-art forecast system to assess the predictability of the Baltic Sea annual maximum ice extent (MIE). We find a useful level of skill in retrospective forecasts initialized as early as the beginning of November. The forecast system can explain as much as 30% of the observed variability in MIE over the period 1993–2012. This skill is derived from the predictability of the NAO by using statistical relationships between the NAO and MIE in observations, while explicit simulations of sea ice have a less predictive skill. This result supports the idea that the NAO represents the main source of seasonal predictability for Northern Europe.

Improving Antarctic total ozone projections by a process-oriented multiple diagnostic ensemble regression

Accurate projections of stratospheric ozone are required because ozone changes affect exposure to ultraviolet radiation and tropospheric climate. Unweighted multimodel ensemble-mean (uMMM) projections from chemistry–climate models (CCMs) are commonly used to project ozone in the twenty-first century, when ozone-depleting substances are expected to decline and greenhouse gases are expected to rise. Here, the authors address the question of whether Antarctic total column ozone projections in October given by the uMMM of CCM simulations can be improved by using a process-oriented multiple diagnostic ensemble regression (MDER) method. This method is based on the correlation between simulated future ozone and selected key processes relevant for stratospheric ozone under present-day conditions. The regression model is built using an algorithm that selects those process-oriented diagnostics that explain a significant fraction of the spread in the projected ozone among the CCMs. The regression model with observed diagnostics is then used to predict future ozone and associated uncertainty. The precision of the authors’ method is tested in a pseudoreality; that is, the prediction is validated against an independent CCM projection used to replace unavailable future observations. The tests show that MDER has higher precision than uMMM, suggesting an improvement in the estimate of future Antarctic ozone. The authors’ method projects that Antarctic total ozone will return to 1980 values at around 2055 with the 95% prediction interval ranging from 2035 to 2080. This reduces the range of return dates across the ensemble of CCMs by about a decade and suggests that the earliest simulated return dates are unlikely.