Ensemble Sensitivity Analysis of a Severe Downslope Windstorm in Complex Terrain: Implications for Forecast Predictability Scales and Targeted Observing Networks

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 Earth s 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.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2013
Accession Number
ADA590058

Entities

People

  • Paul B. Homan

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Cyber
  • Energy and Power Technologies
  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Air Force
  • Aircrafts
  • Boundary Layer
  • Climate Change
  • Geography
  • Grids
  • Meteorology
  • Normal Distribution
  • Physics
  • Pressure Distribution
  • Pressure Gradients
  • Sea Level
  • Temperature Gradients
  • Turbulence
  • Two Dimensional
  • United States
  • Unmanned Aerial Vehicles

Fields of Study

  • Environmental science

Readers

  • Atmospheric Science / Meteorology, specifically Wind Wave Turbulence.
  • Atmospheric Science/Meteorology
  • Computational Modeling and Simulation

Technology Areas

  • Space