21 research outputs found

    Beyond equilibrium climate sensitivity

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    ISSN:1752-0908ISSN:1752-089

    Evaluation of CMIP6 AMIP climate simulations with the ACCESS-AM2 model

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    The most recent version of the ACCESS-AM2 atmosphere-only climate model is introduced with results from the CMIP6 Atmospheric Model Intercomparison Project (AMIP) experiments configured with two land-surface models: CABLE and JULES. AMIP simulations are required as part of the CMIP6 core experiments. They are forced by prescribed time-varying observed sea surface temperature and sea-ice variations as well as variations in natural and anthropogenic external forcings. We evaluate the performance of the two configurations using three historical realisations for each. Model biases are estimated both globally and for the Australian region. The model shows close agreement with observed interannual variations of global-mean temperature across the latitude range 65°N–65°S. This is also true for the land-only temperature for 65°N–65°S, and a more stringent test of the model is driven by specified observed sea surface temperatures. Patterns of mean precipitation are simulated reasonably well, although there are biases in the amount and distribution of precipitation, typical of longstanding problems in representing this aspect of the climate. Selected features of the atmospheric circulation are discussed, including air temperatures and wind speeds. For the Australian region, in addition to examining the climatological patterns of temperature and precipitation, important drivers of climate variability are reviewed: El Niño-Southern Oscillation, the Indian Ocean Dipole and the Southern Annular Mode. In general, the correlation patterns for precipitation simulated by ACCESS-AM2 are somewhat weaker than in observations, although the ensemble means show better agreement than individual ensemble members. Overall, the two different land-surface schemes perform similarly. ACCESS-AM2 has reduced root mean square errors for both temperature and precipitation of around 15–20% at the global scale compared to the older CMIP5 versions of the model: ACCESS 1.0 and ACCESS 1.3

    Refining global warming projections

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    Accurately determining the warming associated with scenarios of greenhouse gas emissions remains an overarching aim of climate modelling. Research now shows that contemporary measurements significantly reduce uncertainty bounds and indicate that some more extreme warming predictions may be less likel

    Uncertainty in temperature projections reduced using carbon cycle and climate observations

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    The future behaviour of the carbon cycle is a major contributor to uncertainty in temperature projections for the twenty-first century1,2. Using a simplified climate model3, we show that, for a given emission scenario, it is the second most important contributor to this uncertainty after climate sensitivity, followed by aerosol impacts. Historical measurements of carbon dioxide concentrations4 have been used along with global temperature observations5 to help reduce this uncertainty. This results in an increased probability of exceeding a 2 °C global–mean temperature increase by 2100 while reducing the probability of surpassing a 6 °C threshold for non-mitigation scenarios such as the Special Report on Emissions Scenarios A1B and A1FI scenarios6, as compared with projections from the Fourth Assessment Report7 of the Intergovernmental Panel on Climate Change. Climate sensitivity, the response of the carbon cycle and aerosol effects remain highly uncertain but historical observations of temperature and carbon dioxide imply a trade–off between them so that temperature projections are more certain than they would be considering each factor in isolation. As well as pointing out the promise from the formal use of observational constraints in climate projection, this also highlights the need for an holistic view of uncertainty
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