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SUMMARY:Assessing seasonal predictability from stratospheric variability i
 n a seasonal prediction system - Daniela Domeisen\, Institute of Oceanogra
 phy\, University of Hamburg
DTSTART:20140226T130000Z
DTEND:20140226T140000Z
UID:TALK51057@talks.cam.ac.uk
CONTACT:36891
DESCRIPTION:The predictability arising from stratospheric variability is a
 nalyzed in a seasonal prediction system including a high top atmosphere mo
 del and a full ocean. Stratospheric variability is suggested to enhance tr
 opospheric predictive skill through the downward influence of Sudden Strat
 ospheric Warmings as well as the remote influence of El Niño pathways thr
 ough the stratosphere. Here\, we aim to quantify predictive skill on seaso
 nal timescales with a focus on the extratropical Northern Hemisphere. We u
 se a seasonal prediction model based on the MPI-ESM coupled climate model 
 system (as used for the CMIP5/IPCC-AR5 simulations) initialized from reana
 lysis data for the atmosphere\, ocean\, and for sea ice. Hindcast ensemble
  runs are performed for the satellite era 1981 to 2011\, with start dates 
 every May and November.\n\nStratospheric variability is reproduced well in
  the hindcast runs with a realistic frequency of sudden warmings\, with th
 e ensemble spread representing the variability of reanalysis data. ENSO va
 riability is captured in the tropical Pacific with a high predictive skill
  for 5 months. The suggested relationship between El Niño and stratospher
 ic polar cap temperatures is reproduced. We also investigate predictive sk
 ill in the North Atlantic / European sector as a function of stratospheric
  variability.\n\nWhile the North Atlantic / Europe sector traditionally ex
 hibits little skill in seasonal prediction models\, our analysis of a seas
 onal forecast system presents a promising step towards assessing the influ
 ence of stratospheric variability on the predictability of tropospheric va
 riability on seasonal timescales.
LOCATION:MR12\, Centre for Mathematical Sciences
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