Key Questions to Answer on Storm Simulation Xiangdong Zhang International Arctic Research Center University of Alaska Fairbanks, Fairbanks, AK 99775, USA.

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Presentation transcript:

Key Questions to Answer on Storm Simulation Xiangdong Zhang International Arctic Research Center University of Alaska Fairbanks, Fairbanks, AK 99775, USA Jing Zhang, and Jeremy R. Krieger Geophysical Institute University of Alaska Fairbanks, Fairbanks, AK 99775, USA Arctic System Model Workshop, August 6-7, 2007

Why ASM? 1. Capture high resolution features that GCM could not resolve well.

Why ASM? 1. Capture high resolution features that GCM could not resolve well.

Why ASM? 1. Capture high resolution features that GCM could not resolve well. 2. Capture realistic physical processes or feedbacks that GCM could not simulate well.

Why Storm? 1. Primary weather system and could have high impact in mid- and high-latitudes. 2. Enhancing atmosphere-sea ice-ocean interactions and may leave fingerprints on climate variability and change.

Zhang, J., et al. 2007: Modeling Study of an Arctic Storm Process and Associated Atmosphere-Sea Ice-Ocean Interactions by Using a Coupled Regional Model. under revision.

Yang et al. 2004

Why Storm? 1. Primary weather system and could have high impact in mid- and high-latitudes. 2. Enhancing atmosphere-sea ice-ocean interactions and may leave fingerprints on climate variability and change. 3. Storm activity has intensified in Arctic and storm track has shifted poleward, highly associated with large scale climate variability and change.

 Trends and variability: Arctic CAI The integrative index CAI (Cyclone Activity Index) represents a combination of information of cyclone trajectory count, duration and intensity. Zhang, X., et al. 2004: Climatology and interannual variability of Arctic cyclone activity, J. Climate, 17,

 Relationship to mid-latitudes: Poleward shift Both the intensity and trajectory count show increasing trends; The increase was dramatically amplified around There are more and stronger cyclones originating southern 60N entering the Arctic, particularly around Zhang, X., et al. 2004: Climatology and interannual variability of Arctic cyclone activity, J. Climate, 17,

Flux Exchanges Atmosphere (MM5) Land Ocean & Sea Ice Arctic MM5: Regional Weather & Climate Model One more step forward: Zhang, J., et al. 2007: Modeling Study of an Arctic Storm Process and Associated Atmosphere-Sea Ice-Ocean Interactions by Using a Coupled Regional Model. under revision. taking atmosphere-sea ice-ocean coupling process into account

Flux Exchanges Atmosphere (MM5) Land Ocean & Sea Ice Arctic MM5: Regional Weather & Climate Model One more step forward: Dynamic Downscaling Glacier Mass Balance Zhang, J., et al. 2007: Response of glaciers in northwestern North America to future climate change: an atmosphere/glacier hierarchical modeling approach. Annals of Glaciology, 46, taking atmosphere-sea ice-ocean coupling process into account Zhang, J., et al. 2007: Climate downscaling for estimating glacier mass balance in Northwestern North America: Validation with USGS index glacier. Geophy. Res. Lett., submitted.

Arctic MM5 Storm Simulation: Model Domain

Arctic MM5 Storm Simulation: Initial Condition

Arctic MM5 Storm Simulation: 2m Air Temperature

Arctic MM5 Storm Simulation: Cloudiness

Arctic MM5 Storm Simulation: Ocean Temperature

Arctic MM5 Storm Simulation: Sea Ice Thickness

Flux Exchanges Atmosphere (WRF) Land Ocean & Sea Ice Transition: Arctic MM5  Arctic WRF

WRF Simulation: Model Domain

WRF Simulation: Surface Pressure

WRF Simulation: 2 m Air Temperature

WRF Simulation: 2 m Mixing Ratio

WRF Simulation: 10 m Windspeed

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