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An empirical ensemble mesoscale forecasting system

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Title: An empirical ensemble mesoscale forecasting system
Author: Hacker, Joshua P.
Degree Master of Science - MSc
Program Atmospheric Science
Copyright Date: 1997
Abstract: Seven short-term numerical weather prediction experiments test the feasibility of an ensemble mesoscale forecasting system that is designed to minimize the effects of analysis errors in the North Pacific. Each experiment consists of a five-member ensemble (4 + control) run once per day for eight days for the period 21-31 January 1990. The Mesoscale Compressible Community (MC2) model, run at Ax = 100 km over the North Pacific Ocean and western North America, serves as the experimental platform. Empirical perturbations called the Selective Introduction of Hazardous Modes (SIHM) define six of the experiments. The seventh experiment uses perturbations that are bred within the forecast cycle, and serves as a benchmark. Standard root mean square error (RMSE) statistics and surface cross sections are used for verification. SIHM perturbations are incipient cyclones that are added or subtracted from the initial analyses. Resolvable structures in the flow, such as low-level or stratospheric potential vorticity and jet-stream divergence, determine the locations of the perturbations. Perturbation size is set to match the most energetic wavelength in a particular latitude band, as derived from a spectral analysis. The strength of the incipient cyclones is designed to be within reasonable analysis errors published previously. One measure of the likely success of ensemble methods is the spread between different forecast members of the ensemble. The system lacks a desirable spread in RMSE development, and the curves converge at the end of many of the forecasts because of dominance of the common imposed boundary conditions. Spreads in sea-level pressure adequate to envelope most observations exist when the model predicts a storm system well. Precipitation consistently shows the most spread along the cross section. When the model completely misses an event, spreads are negligible.
URI: http://hdl.handle.net/2429/5785
Series/Report no. UBC Retrospective Theses Digitization Project [http://www.library.ubc.ca/archives/retro_theses/]

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