3.1
Ensemble variability and predictability of mountain waves and downslope winds
P. Alexander Reinecke, University of Washington, Seattle, WA; and D. Durran
With the advancement of numerical weather prediction (NWP) models,
forecasting mesoscale phenomenon such as downslope wind storms and
mountain waves is becoming common place. While these models are
capable of producing realistic and plausible solutions, their ability
to produce valid a-priori forecasts of detailed mesoscale structures
is largely unknown. Cases from the TREX field campaign provide
several opportunities to investigate the predictability of such flows.
In this study we use an Ensemble Kalman Filter to generate a 70 member
ensemble at horizontal resolutions as fine as 1 km. Several
downslope-wind and mountain-wave events from the TREX campaign are
considered. The ensemble is used to demonstrate the variability
possible in a mesoscale forecast given typical synoptic-scale
uncertainty.
Despite relatively small synoptic-scale variability differences in the
downslope-wind response among the ensemble members can grow quite
large. For example, the difference in downslope-wind forecasts
between composites of the 10 weakest and 10 strongest ensemble members
exceed 30 m/s in a short 6-12 hour forecast. At the same time the
differences between the average crest-level wind speed in the strong
and weak composites is less than 5 m/s. Thus, at least in these
cases, the topography increases error growth and decreases
predictability. In addition to downslope-wind predictability, the
ability of models to accurately forecast mountain waves is explored.
Aircraft observations are used to verify individual ensemble members
for several events during TREX. While some members compare well with
observations, most of the members contain large errors in both
amplitude and phase. This suggests an inherent lack of predictability
in a-priori mountain-wave forecasts.
Session 3, Weather Forecasting III
Monday, 11 August 2008, 1:30 PM-3:00 PM, Rainbow Theatre
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