Wind storm research at HZG long-term changes from numerical models
Matthias Zahn
Coordination of storm themes (Frauke Feser)
Institute of Coastal Research
Helmholtz-Zentrum Geesthacht matthias.zahn@hzg.de
April 1, 2014
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Focus: wind storm climate worldwide
Specifically
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◮ most extreme fraction of storms: polar lows, medicanes, extra tropical storms, typhoons, hurricanes, etc.
climatologies, trends, statistics link to driving conditions impacts past decades and future climate scenarios
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Tools of research: numerical models low-res global-domain
Simulation
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◮ different types of atmosphere/ocean models dynamical downscaling re-analysis data to RCM domain spectral nudging
❄ high-res RCM-domain
Detection
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◮ automated storm detection methods applied methods based on scale separation
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Why models?
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◮ homogeneity spatially extended information sufficiently long in time future scenarios are possible
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Example for recent research: polar lows
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◮ diameter
<
1000 km strong winds
>
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9 m s heavy precipitation poleward Polar Fronts in winter spiral cloud and cloud free core (Arctic Hurricane) rapid development c Dundee Satellite Receiving Station
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Reproducibility of one polar low
15 Oct 1993, 6:00, The Swan
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Detection, band-pass filtered MSLP
200-600km retained, PLs as distinct minima
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Annual numbers of PLs (1949-2005)
Number of PLs per Polar Low Season (PLS), one PLS from July until June next year
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Future projection of PL frequency
Zahn and von Storch, Nature (2010)
Under GHG warmed atmosphere (IPCC):
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◮ number of annual PLs almost halves proxy for favourable development conditions decreases large inter model bias, but same direction of change
Left: number polar lows per PLS and scenario.
Right: Area and time-averaged ice free
SST − T
500 hPa over northern North Atlantic.
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Spatial genesis distribution and its end of C21 change
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C20-B1
20˚ 20˚ 20˚ 20˚
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C20-A1B
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C20-A2
20˚ 20˚ 20˚ 20˚
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Further example: medicanes
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N
W 5
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W 0
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NCEP
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1950 locations of genesis
1960 1970 1980 1990 number per season
Cavicchia (2013), NCEP downscaled to 10km resolution with CLM
2000 2010
40 E
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Further example: typhoons typhoons in A1B scenario, different detection configurations, same trend
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CONTINUATIVE APPROACH: global downscaling low-res global-domain
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◮ apply a global ECHAM6 dynamical downscaling to global domain (M. Schubert-Frisius) spectral nudging
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◮ which nudging configuration?
how well are storms simulated?
determination currently underway high-res global-domain
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TOKAGE under different nudging configurations
110˚
60˚
BEST Track Storm
NCEP values
EH6_n1_T05_av_05dv
EH6_n1_T05_av_09dv
EH6_n1_T11_av_001dv
EH6_n1_T11_av_01dv
EH6_n1_T11_av_05dv
EH6_n1_T11_av_09dv
EH6_n1_av_001dv
EH6_n1_av_005dv
EH6_n1_av_01dv
EH6_n1_av_05dv
EH6_n1_av_09dv
EH6_n1_dvw_005dv
EH6_n1_dvw_echam6_dv
EH6_n1_ev_005dv
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Summary
At HZG, different types of storms:
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◮ are simulated using dynamical downscaling are detected with spatial filters will be simulated using global downscaling
Some of our results (shown here):
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◮ no past change of polar low/medicane activity significant decrease in a warmed future
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http://coast.hzg.de/staff/zahn/
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