Medium-Range Ensemble Sensitivity Analysis of Two Extreme Pacific Extratropical Cyclones

Author:

Chang Edmund K. M.1,Zheng Minghua1,Raeder Kevin2

Affiliation:

1. School of Marine and Atmospheric Sciences, Stony Brook University, Stony Brook, New York

2. CISL/IMAGe/Data Assimilation Research Section, National Center for Atmospheric Research, Boulder, Colorado

Abstract

Abstract In this study, ensemble sensitivity analysis has been applied to examine the evolution of two extreme extratropical cyclones over the Pacific. Sensitivity using, as forecast metrics, forecast cyclone minimum pressure and location, as well as principal components (PCs) of the leading EOFs in forecast SLP variations near the cyclone center, has been computed for medium-range forecasts of up to 7.5 days. Results presented here show that coherent sensitivity patterns can be tracked from the forecast validation time back in time to at least day −6, with the sensitivity signal exhibiting downstream development characteristics in most cases. Comparing the different forecast metrics, sensitivity patterns derived from the PCs of the leading EOFs in forecast SLP variations are apparently more coherent than those derived from cyclone parameters. To test whether the linear sensitivity analyses provide quantitatively accurate guidance under the highly nonlinear evolution of the atmospheric flow, perturbed initial condition experiments have been conducted using initial condition perturbations derived based on ensemble sensitivity. Results of this study suggest that in the medium range, perturbations derived from cyclone parameters are quite effective in modifying the evolution of the cyclones out to 5.5 days, but are largely ineffective for 7.5-day forecasts. On the other hand, perturbations derived based on the PCs of the leading EOFs are still quite effective in modifying forecast cyclone location out to 7.5 days. These results suggest that EOF-based sensitivities perform better than cyclone parameter-based sensitivities in the medium range.

Publisher

American Meteorological Society

Subject

Atmospheric Science

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