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Ensemble Sensitivity Tools for Assessing Extratropical Cyclone Intensity and Track Predictability

Ensemble Sensitivity Tools for Assessing Extratropical Cyclone Intensity and Track Predictability This paper applies ensemble sensitivity analysis to a U.S. East Coast snowstorm on 26–28 December 2010 in a way that may be beneficial for an operational forecaster to better understand the forecast uncertainties. Sensitivity using the principal components of the leading empirical orthogonal functions (EOFs) on the 50-member European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble identifies the sensitive regions and weather systems at earlier times associated with the cyclone intensity and track uncertainty separately. The 5.5-day forecast cyclone intensity uncertainty in the ECMWF ensemble is associated with trough and ridge systems over the northeastern Pacific and central United States, respectively, while the track uncertainty is associated with a short-wave trough over the southern Great Plains. Sensitivity based on the ensemble mean sea level pressure difference between two run cycles also suggests that the track's shift between the two cycles is linked with the initial errors in the short-wave trough over the southern Great Plains. The sensitivity approach is run forward in time using forward ensemble regression based on short-range forecast errors, which further confirms that the short-term error over the southern plains trough was associated with the shift in cyclone position between the two forecast cycles. A coherent Rossby wave packet originated from the central North Pacific 6 days before this snowstorm event. The sensitivity signals behave like a wave packet and exhibit the same group velocity of ~29° longitude per day, indicating that Rossby wave packets may have also amplified uncertainty in both the cyclone amplitude and track forecast. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Weather and Forecasting American Meteorological Society

Ensemble Sensitivity Tools for Assessing Extratropical Cyclone Intensity and Track Predictability

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Publisher
American Meteorological Society
Copyright
Copyright © 2012 American Meteorological Society
ISSN
0882-8156
eISSN
1520-0434
DOI
10.1175/WAF-D-12-00132.1
Publisher site
See Article on Publisher Site

Abstract

This paper applies ensemble sensitivity analysis to a U.S. East Coast snowstorm on 26–28 December 2010 in a way that may be beneficial for an operational forecaster to better understand the forecast uncertainties. Sensitivity using the principal components of the leading empirical orthogonal functions (EOFs) on the 50-member European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble identifies the sensitive regions and weather systems at earlier times associated with the cyclone intensity and track uncertainty separately. The 5.5-day forecast cyclone intensity uncertainty in the ECMWF ensemble is associated with trough and ridge systems over the northeastern Pacific and central United States, respectively, while the track uncertainty is associated with a short-wave trough over the southern Great Plains. Sensitivity based on the ensemble mean sea level pressure difference between two run cycles also suggests that the track's shift between the two cycles is linked with the initial errors in the short-wave trough over the southern Great Plains. The sensitivity approach is run forward in time using forward ensemble regression based on short-range forecast errors, which further confirms that the short-term error over the southern plains trough was associated with the shift in cyclone position between the two forecast cycles. A coherent Rossby wave packet originated from the central North Pacific 6 days before this snowstorm event. The sensitivity signals behave like a wave packet and exhibit the same group velocity of ~29° longitude per day, indicating that Rossby wave packets may have also amplified uncertainty in both the cyclone amplitude and track forecast.

Journal

Weather and Forecasting – American Meteorological Society

Published: Dec 18, 2012

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