Statistical Analysis of Extreme Wind in Regional Climate Model Simulations
Future projections in extreme wind statistics over Europe
description
Transcript of Future projections in extreme wind statistics over Europe
![Page 1: Future projections in extreme wind statistics over Europe](https://reader036.fdocuments.us/reader036/viewer/2022062409/5681498a550346895db6d2e8/html5/thumbnails/1.jpg)
Future projections in extreme wind statistics over Europe
Grigory Nikulin, Erik Kjellström and Colin Jones
Rossby Centre Swedish Meteorological and Hydrological Institute
![Page 2: Future projections in extreme wind statistics over Europe](https://reader036.fdocuments.us/reader036/viewer/2022062409/5681498a550346895db6d2e8/html5/thumbnails/2.jpg)
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)
![Page 3: Future projections in extreme wind statistics over Europe](https://reader036.fdocuments.us/reader036/viewer/2022062409/5681498a550346895db6d2e8/html5/thumbnails/3.jpg)
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
![Page 4: Future projections in extreme wind statistics over Europe](https://reader036.fdocuments.us/reader036/viewer/2022062409/5681498a550346895db6d2e8/html5/thumbnails/4.jpg)
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
![Page 5: Future projections in extreme wind statistics over Europe](https://reader036.fdocuments.us/reader036/viewer/2022062409/5681498a550346895db6d2e8/html5/thumbnails/5.jpg)
Projected change in warm extremes
Moving GEV: 50yr ret. val. of T2max (ONDJFM )
common gradual increase
role of drivingGCMs
![Page 6: Future projections in extreme wind statistics over Europe](https://reader036.fdocuments.us/reader036/viewer/2022062409/5681498a550346895db6d2e8/html5/thumbnails/6.jpg)
Climate change in precipitation extremes
Moving GEV: 50yr ret. val. of winter max precipitation
a tendency to intensification of precipitation extremes
role of drivingGCMs
![Page 7: Future projections in extreme wind statistics over Europe](https://reader036.fdocuments.us/reader036/viewer/2022062409/5681498a550346895db6d2e8/html5/thumbnails/7.jpg)
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
![Page 8: Future projections in extreme wind statistics over Europe](https://reader036.fdocuments.us/reader036/viewer/2022062409/5681498a550346895db6d2e8/html5/thumbnails/8.jpg)
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
![Page 9: Future projections in extreme wind statistics over Europe](https://reader036.fdocuments.us/reader036/viewer/2022062409/5681498a550346895db6d2e8/html5/thumbnails/9.jpg)
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 ?
![Page 10: Future projections in extreme wind statistics over Europe](https://reader036.fdocuments.us/reader036/viewer/2022062409/5681498a550346895db6d2e8/html5/thumbnails/10.jpg)
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 ?
![Page 11: Future projections in extreme wind statistics over Europe](https://reader036.fdocuments.us/reader036/viewer/2022062409/5681498a550346895db6d2e8/html5/thumbnails/11.jpg)
Climate change in wind extremes
Different RCMs RCA3 RACMO2 REMO
some similarities between RCA3 and REMO
noisy patterns for RACMO2
![Page 12: Future projections in extreme wind statistics over Europe](https://reader036.fdocuments.us/reader036/viewer/2022062409/5681498a550346895db6d2e8/html5/thumbnails/12.jpg)
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";
![Page 13: Future projections in extreme wind statistics over Europe](https://reader036.fdocuments.us/reader036/viewer/2022062409/5681498a550346895db6d2e8/html5/thumbnails/13.jpg)
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