Date: 26 January 2022, 12.00pm (GMT)
Speakers: David Sexton (Met Office), Nick Leach (University of Oxford) and Nigel Arnell (University of Reading)
Chair: Simon Brown (Met Office)
See links to a video of the webinar and presentation slides below
Recent extreme weather in the UK highlights the need to understand the potential for more extreme events in the present-day, and how such events may change with global warming. We present a methodology for more efficiently sampling extremes in future climate projections. As a proof-of-concept, we use the UK’s most recent set of national Climate Projections (UKCP18). UKCP18 includes a 15-member perturbed parameter ensemble (PPE) of coupled global simulations, providing a range of climate projections incorporating uncertainty in both internal variability and forced response. However, this ensemble is too small to adequately sample extremes with return periods over 100 years, which are of interest to policy-makers and adaptation planners. To better understand the statistics of these events, we use distributed computing to run three ~1000-member initial-condition ensembles with the atmosphere-only HadAM4 model at 60km resolution on volunteers’ computers, taking boundary conditions from future extreme winters within the UKCP18 ensemble. This experimental setup allows us to explore the uncertainty surrounding these rare extreme events in UKCP18 more completely, which includes determining whether they were genuinely exceptional events, or if they could have been even greater extremes.
We find that every UKCP18 extreme winter is captured within our ensembles, and that two of the three ensembles are conditioned towards producing extremes by the boundary conditions. The ensemble contains physically, spatially and temporally coherent information for several extremes that would only be expected to be sampled by a UKCP18 PPE of over 500 members, which would be prohibitively expensive with current supercomputing resource. The most extreme winters simulated lie above those for UKCP18 by 0.85K for daily maximum temperature and 37% of the present-day average for UK precipitation. Therefore, the ensembles form a prototype product for use in impacts studies that require large samples
David Sexton is a Science Manager of the Ensemble Climate Projection team at the Met Office Hadley Centre and leads the production and evaluation of the climate simulations used for informing climate adaptation. The most recent notable set of projections are the “Global Projections” for UKCP18. David also developed and led the production of the probabilistic climate projections in UKCP09, using a Bayesian methodology to quantify the risk using observations and a variety of climate simulations generated at the Met Office and other climate centres around the world. In 2008, David received the LG Groves prize for Meteorology for this work.
Nick Leach is a PhD student on the Environmental Research Doctoral Training Partnership at Oxford University in his fourth and final year. He resides in the Predictability of Weather and Climate research group, supervised by Antje Weisheimer and Myles Allen. His research explores the use of operational weather forecasting models within the field of extreme event attribution, with a particular focus on heat events. This work touches on themes of numerical weather prediction, attribution of climate change, meteorological drivers of extreme weather and extreme value statistics.