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Published byIrene Brooks Modified over 9 years ago
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Snapshots of WRF activities in the GFI/Iceland groups
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DLR / Bernadett Weinzierl Layering Observations from DLR research aircraft near Eyjafjallajökull
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Lidar from the DLR flight across the plume on its way from Eyjafjallajökull to Scotland Strong stratification (layering)
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WRF with horizontal resolution of 9 km FLOW
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WRF with horizontal resolution of 3 km Hálfdán Ágústsson and Haraldur Ólafsson, 2010.
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Permanent lowering of the flow level Vertical mixing in a 3000 m deep layer Vertical mixing at higher levels due to mountain waves FLOW None of these important features are visible at dx=9km, or at resolutions of many current forecast models! WRF with horizontal resolution of 1 km Hálfdán Ágústsson and Haraldur Ólafsson, 2010.
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The model underestimates the sharpness of the inversion, and all smaller details above it MODEL OBSERVATIONS Keflavík http://belgingur.is
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High concentrations of ash occures several times in Reykjavík, after the end of the eruption
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Very clear source
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Simulated surface flow http://belgingur.is
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Simulations of winds at the source of the dust (ash) m/s at the source Horizontal resolution (km)
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1) 2) 3) 4) The FLOHOF field experiment
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1) 2) 3) 4) By far largest errors: Downslope winds Jonassen et al
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The the horizontal extension of the downslope winds is highly non-stationary
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The SUMO model aircraft for meteorological observations Photo: Haraldur Ólafsson
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No extra observations With in-situ obs. with a model aircraft A major difference in flow pattern extending far above mountain top level 23 km Wind speed, ranging from 0 to 12 m/s Vertical section of simulated flow across mountain
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1) 2) 3) 4) A study of turbulent fluxes inn Spitzbergen (Kilpelainen et al., Tellus – in press)
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Dynamics of extreme precipitation in Central Norway (Steenesen et al. subm. to Tellus)
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Tveita et al. MAP, in rev. 19 Case studies Dynamics of mesoscale winds WSP10m (CTRL-NOGREEN) +24h 5 March 2000 18UTC Frontal jet off shore Cape Tobin jet Pattern NE of Iceland Wake Prominent features
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Using the WRF fields to calculate the surface gusts by the Brasseur method Ágústsson & Ólafsson, MAP, 2009
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Predictability studies: Analysis of the dynamics of forecast errrors Tveita, Olafsson, Sandvik & Hagen, MAP – in revision Hagen, Olafsson, Sandvik & Tveita, MAP – in revision Steenesen, Olafsson & Jonassen, Tellus, submitted
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RESULTS - FORECASTING C: LEAD TIME increased lead time => decrease in forecast quality the decrease is quite regular for all the four cases and for most steps however, some steps are larger than the others, e.g. 72 h lead time to 96 h lead time for the 10 November 2006 case.
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~5 K warmer in GOOD than in BAD Temperature difference =>difference in mean sea level pressure DIFF (GOOD-BAD) MSLP GOOD: 0h BAD: +24h Black line: track of slp anomaly originating east of Hudson Bay Red line: track of another slp anomaly DIFF (GOOD-BAD) in θ 850 RESULTS - FORECASTING
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