Ensemble sensitivity analysis of a severe downslope windstorm in complex terrain: implications for forecast predictability scales and targeted observing networks
Loading...
Authors
Homan, Paul B.
Subjects
Ensemble Sensitivity Analysis
Downslope Windstorm
Complex Terrain
Numerical Weather Prediction
Flow Separation
Breaking Waves
Vertically Propagating Waves
Trapped Waves
Data Assimilation
Targeted Observing
Forecast Predictability
Bulk Richardson Number
Mesoscale
Mesonet
Observing System Simulation Experiment
WRF
Mountain Waves.
Downslope Windstorm
Complex Terrain
Numerical Weather Prediction
Flow Separation
Breaking Waves
Vertically Propagating Waves
Trapped Waves
Data Assimilation
Targeted Observing
Forecast Predictability
Bulk Richardson Number
Mesoscale
Mesonet
Observing System Simulation Experiment
WRF
Mountain Waves.
Advisors
Hacker, Joshua P.
Date of Issue
2013-09
Date
Sep-13
Publisher
Monterey, California: Naval Postgraduate School
Language
Abstract
Multiple mesoscale numerical weather simulations are conducted to evaluate whether Ensemble Sensitivity Analysis (ESA) is a useful tool determining the sensitivity of a severe downslope windstorm (DSWS) in complex terrain to initial conditions and assimilated observations. A 96-member ensemble is implemented with 1.33 km grid spacing. Sensitive regions are found both upstream and downstream, based on a new forecast metric that indicates the potential for turbulence and strong winds reaching the Earths surface. Approximating the effects of assimilating a perfect observation at these sensitivity locations, then executing non-linear ensemble forecasts, shows the linear approximations in ESA are reasonable. We analyze the roles of upstream wind and stability structures, and leeside conditions, in determining the strength and propagation of winds down the mountain slope and onto the adjacent plains. Results suggest that ESA is a viable method to identify observation locations to improve forecasts of fine-scale, non-linear, high-impact events such as DSWS. Also, 14 severe DSWS identified by the High Wind Alert System located at the USAF Academy, CO are modeled utilizing a deterministic WRF configuration. Analysis shows that non-wave breaking events account for the strongest DSWS and propagate further away from the mountains than breaking events at this location.
Type
Thesis
Description
Series/Report No
Department
Meteorology
Organization
Identifiers
NPS Report Number
Sponsors
Funder
Format
Citation
Distribution Statement
Approved for public release; distribution is unlimited.
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.