| 英文摘要: | State-of-the-art climate models now include more climate processes simulated at higher spatial resolution than ever1. Nevertheless, some processes, such as atmospheric chemical feedbacks, are still computationally expensive and are often ignored in climate simulations1, 2. Here we present evidence that the representation of stratospheric ozone in climate models can have a first-order impact on estimates of effective climate sensitivity. Using a comprehensive atmosphere–ocean chemistry–climate model, we find an increase in global mean surface warming of around 1 °C (∼20%) after 75 years when ozone is prescribed at pre-industrial levels compared with when it is allowed to evolve self-consistently in response to an abrupt 4×CO2 forcing. The difference is primarily attributed to changes in long-wave radiative feedbacks associated with circulation-driven decreases in tropical lower stratospheric ozone and related stratospheric water vapour and cirrus cloud changes. This has important implications for global model intercomparison studies1, 2 in which participating models often use simplified treatments of atmospheric composition changes that are consistent with neither the specified greenhouse gas forcing scenario nor the associated atmospheric circulation feedbacks3, 4, 5. Starting from pre-industrial conditions, an instantaneous quadrupling of the atmospheric CO2 mixing ratio is a standard climate change experiment (referred to as abrupt4×CO2) in model intercomparison projects such as the Coupled Model Intercomparison Project phase 5 (CMIP5; ref. 1) or the Geoengineering Model Intercomparison Project2 (GeoMIP). One aim of these initiatives is to offer a quantitative assessment of possible future climate change, with the range of projections from participating models commonly used as a measure of uncertainty6. Within such projects, stratospheric chemistry, and therefore stratospheric ozone, is treated differently in individual models. In CMIP5 and GeoMIP, most participating models did not explicitly calculate stratospheric ozone changes2, 4. For abrupt4×CO2 experiments, modelling centres thus often prescribed stratospheric ozone at pre-industrial levels2, 5. For transient CMIP5 experiments, it was instead recommended to use an ozone field derived from the averaged projections of 13 chemistry–climate models3. This multi-model mean ozone data set was obtained from the Chemistry–Climate Model Validation activity phase 2 (CCMVal-2) projections run under the Special Report on Emissions Scenarios (SRES) A1b scenario for well-mixed greenhouse gases, in contrast to the representative concentration pathway (RCP) scenarios used in CMIP5. So far, research on the impacts of contrasting representations of stratospheric ozone has focused on regional effects, such as the influence of possible future Antarctic ozone recovery on the position of the Southern Hemisphere mid-latitude jet4, 7. However, its potential effect on the magnitude of projected global warming has not received much attention. Here, we present evidence that highlights that stratospheric chemistry–climate feedbacks can exert a more significant influence on global warming projections than has been suggested8. For a specific climate change experiment, we show that the choice of how to represent key stratospheric chemical species alone can result in a 20% difference in simulated global mean surface warming. Therefore, a treatment of ozone that is not internally consistent with a particular model or greenhouse gas scenario, as is the case for some CMIP5 simulations, could introduce a significant bias into climate change projections. The model used here is the HadGEM3-AO configuration of the UK Met Office’s Unified Model9 coupled to the United Kingdom Chemistry and Aerosols (UKCA) stratospheric chemistry scheme10 (see Methods). This comprehensive model set-up allows us to study complex feedback effects between the atmosphere, land surface, ocean and sea ice. Figure 1 shows the evolution of global and annual mean surface temperature anomalies (ΔTsurf) from eight different climate integrations, two of which were carried out with interactive stratospheric chemistry and six with different prescribed monthly mean fields of the following chemically and radiatively active gases: ozone, methane and nitrous oxide (see Table 1 for details). Experiments labelled A are pre-industrial control runs. Experiment B is an abrupt4×CO2 run with fully interactive chemistry, and experiments labelled C are non-interactive abrupt4×CO2 runs in which the chemical fields were prescribed at pre-industrial levels. We conducted two versions of each non-interactive experiment to test the effect of using zonal mean fields (label 2, for example, A2) instead of full three-dimensional (3D) fields (label 1, for example, A1). The time development of ΔTsurf shows a clear difference of nearly 20% between the abrupt4×CO2 experiments B and C1/C2, indicating a much larger global warming in C1/C2 as a consequence of missing composition feedbacks. The primary driver of these differences is changing ozone, with methane and nitrous oxide making much smaller contributions (see below). Fields averaged over the final 50 years of the interactive experiment B were imposed from the beginning in the abrupt4×CO2 experiments B1 and B2. These simulations show a close agreement with experiment B in terms of ΔTsurf, implying that the global mean energy budget can be comparatively well reproduced with this treatment of composition changes, despite the neglect of transient changes in their abundances.
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