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Future projections in extreme wind statistics over Europe
Grigory Nikulin, Erik Kjellström and Colin Jones
Rossby Centre Swedish Meteorological and Hydrological Institute
Objectives
What is our confidence is the projected climate change in wind extremes compared to temperature and precipitation extremes ?
Sources of uncertainties in regional projections: different driving GCMs different RCMs natural variability
Starting point: regional climate projections in wind extremes is much more sensitive to driving GCMs than temperature and precipitation extremes (Nikulin et al., Tellus A 2011)
Ensembles of simulations
1. One RCM driven by different GCMs RCM: RCA3, SMHI (50 km) GCMs: ECHAM5-r3 (MPI, Germany) HadCM3-ref (MOHC, UK) BCM (NERSC, Norway) CCSM3 (NCAR, USA) CNRM (CNRM, France) IPSL (IPSL, France)
3. Natural variability - one RCM driven by one GCM with
different initial conditions RCM: RCA3, SMHI (50 km) GCMs: ECHAM5 (3 members: r1, r2, r3)
2. Different RCMs driven by one GCM RCMs: RCA3, SMHI; RACMO, KNMI; REMO, MPI; (25 km) GCM: ECHAM5-r3, MPI
Data and method
daily max 10m gust wind
Extreme events the 50-year return values of winter (October-March) maximum gust wind; the generalised extreme value (GEV) distribution fitting the GEV: stationary model, L-moments
30-yr time slices: 1961-1990, 2011-2040, 2041-2070, 2071-2100
30-yr moving GEV
1961-2100 (gust wind averaged over a region)
Confidence intervals
parametric bootstrap
Projected change in warm extremes
Moving GEV: 50yr ret. val. of T2max (ONDJFM )
common gradual increase
role of drivingGCMs
Climate change in precipitation extremes
Moving GEV: 50yr ret. val. of winter max precipitation
a tendency to intensification of precipitation extremes
role of drivingGCMs
strengthening of extreme gust winds over the Barents Sea (reduction in sea ice )
a tendency to strengthening of wind extremes over the Baltic Sea large spread among the simulations (magnitude, spatial patterns)
Climate change in wind extremes
Climate change in wind extremes
role of drivingGCMs
diverse behaviour of individual projectionsno common gradual increase; large decadal variability
Moving GEV: 50yr ret. val. of winter (ONDJFM) max gust wind
Climate change in wind extremes
role of natural variability: one driving ECHAM5 with different initial conditions
some tendency to an increase in wind extremes 2071-2100
natural variability or forced signal ?
Climate change in wind extremes
role of natural variability
Moving GEV: 50yr ret. val. of winter (ONDJFM) max gust wind
r2-3 show a large increase from 2060 but a small increase for r1 only natural variability or forced signal masked by natural variability ?
Are 3 members enough to conclude ?
Climate change in wind extremes
Different RCMs RCA3 RACMO2 REMO
some similarities between RCA3 and REMO
noisy patterns for RACMO2
Climate change in wind extremes
Moving GEV: 20yr ret. val. of winter max gust wind – (1975-2000)
different RCMs
difference in magnitude; time series are often not "synchronized";
Conclusions
Projected changes in Wind Extremes
Natural variability is very large and can easily mask the forced signal; 3 members with different initial conditions may not be enough to separate natural and forced signals
Driving GCMs very critically define the projected regional change in wind extremes: different magnitudes, diverse spatial patterns
RCMs: different parameterization of gust wind and internal RCM dynamics show a spread among the results comparable to the spread related to natural variability