13th Conference on Mountain Meteorology

3.5

An observational comparison of microphysical representations in WRF

Robert S. Hahn, University of Washington, Seattle, WA; and C. F. Mass and B. F. Smull

This research investigates shortcomings of the microphysics schemes used in the numerical weather prediction in regions of complex terrain. The IMPROVE-2 field campaign provides a high-resolution dataset, co-located with Oregon's Cascade Mountains, that is suitable for testing the parameterizations used in mesoscale models. The 13-14 December IMPROVE-2 event was selected due to prior study using MM5 and Reisner-II microphysics and the quality of observational data assets throughout the vigorous frontal passage. The current study utilizes three-dimensional Weather Research and Forecasting (WRF) model simulations from the 13-14 December IMPROVE-II case, building upon the prior work to include analysis of forecasts using the latest microphysics schemes: (1) Woods' (2006) modification of the Reisner-Thompson scheme in order to predict the habit composition of the snow field, including seven prognostic equations, each of which predicts the mixing ratio of snow of a particular crystal type, (2) the Thompson scheme—the only scheme that uses both ice water content and temperature to assume snow size distributions, which it represents as a sum of exponential and gamma distributions (Thompson et al., 2006), and (3) NCAR's WSM 6 Class scheme with graupel.

Model output for each microphysics scheme will be compared against aircraft data, including crystal data in regions of orographically forced ascent (from the 2D-C probe), cloud liquid water (from the King probe), and dual-doppler derived reflectivity and wind fields. Additional consideration of microphysics schemes in the context of recent numerical insights will also be presented.

wrf recording  Recorded presentation

Session 3, Weather Forecasting III
Monday, 11 August 2008, 1:30 PM-3:00 PM, Rainbow Theatre

Previous paper  Next paper

Browse or search entire meeting

AMS Home Page