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    Assessing changes in risk of amplified planetary waves in a warming world
    (Hoboken, NJ : Wiley, 2019) Huntingford, Chris; Mitchell, Dann; Kornhuber, Kai; Coumou, Dim; Osprey, Scott; Allen, Myles
    Summer weather extremes are often associated with high-amplitude atmospheric planetary waves (Petoukhov et al., 2013). Such conditions lead to stationary weather patterns, triggering heat waves and sometimes prolonged intense rainfall. These wave events, referred to as periods of Quasi-Resonant Amplification (QRA), are relatively rare though and hence provide only a few data points in the meteorological record to analyse. Here, we use atmospheric models coupled to boundary conditions that have evolved slowly (i.e., climate), to supplement measurements. Specifically we assess altered probabilities of resonant episodes by employing a unique massive ensemble of atmosphere-only climate simulations to populate statistical distributions of event occurrence. We focus on amplified waves during the two most extreme European heat waves on record, in years 2003 and 2015 (Russo et al., 2015). These years are compared with other modelled recent years (1987–2011), and critically against a modelled world without climate change. We find that there are differences in the statistical characteristics of wave event likelihood between years, suggesting a strong dependence on the known and prescribed Sea Surface Temperature (SST) patterns. The differences are larger than those projected to have occurred under climate change since the pre-industrial period. However, this feature of small differences since pre-industrial is based on single large ensembles, with members consisting of a range of estimates of SST adjustment from pre-industrial to present. Such SST changes are from projections by a set of coupled atmosphere–ocean (AOGCM) climate models. When instead an ensemble for pre-industrial estimates is subdivided into simulations according to which AOGCM the SST changes are based on, we find differences in QRA occurrence. These differences suggest that to reliably estimate changes to extremes associated with altered amplification of planetary waves, and under future raised greenhouse gas concentrations, likely requires reductions in any spread of future modelled SST patterns. © 2019 The Authors. Atmospheric Science Letters published by John Wiley & Sons Ltd on behalf of the Royal Meteorological Society.
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    Half a degree additional warming, prognosis and projected impacts (HAPPI): Background and experimental design
    (München : European Geopyhsical Union, 2017) Mitchell, Daniel; AchutaRao, Krishna; Allen, Myles; Bethke, Ingo; Beyerle, Urs; Ciavarella, Andrew; Forster, Piers M.; Fuglestvedt, Jan; Gillett, Nathan; Haustein, Karsten; Ingram, William; Iversen, Trond; Kharin, Viatcheslav; Klingaman, Nicholas; Massey, Neil; Fischer, Erich; Schleussner, Carl-Friedrich; Scinocca, John; Seland, Øyvind; Shiogama, Hideo; Shuckburgh, Emily; Sparrow, Sarah; Stone, Dáithí; Uhe, Peter; Wallom, David; Wehner, Michael; Zaaboul, Rashyd
    The Intergovernmental Panel on Climate Change (IPCC) has accepted the invitation from the UNFCCC to provide a special report on the impacts of global warming of 1.5°C above pre-industrial levels and on related global greenhouse-gas emission pathways. Many current experiments in, for example, the Coupled Model Inter-comparison Project (CMIP), are not specifically designed for informing this report. Here, we document the design of the half a degree additional warming, projections, prognosis and impacts (HAPPI) experiment. HAPPI provides a framework for the generation of climate data describing how the climate, and in particular extreme weather, might differ from the present day in worlds that are 1.5 and 2.0°C warmer than pre-industrial conditions. Output from participating climate models includes variables frequently used by a range of impact models. The key challenge is to separate the impact of an additional approximately half degree of warming from uncertainty in climate model responses and internal climate variability that dominate CMIP-style experiments under low-emission scenarios. Large ensembles of simulations (> 50 members) of atmosphere-only models for three time slices are proposed, each a decade in length: the first being the most recent observed 10-year period (2006–2015), the second two being estimates of a similar decade but under 1.5 and 2°C conditions a century in the future. We use the representative concentration pathway 2.6 (RCP2.6) to provide the model boundary conditions for the 1.5°C scenario, and a weighted combination of RCP2.6 and RCP4.5 for the 2°C scenario.