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Journal Articles Monthly Weather Review Year : 2005

A cyclogenesis evolving into two distinct scenarios and its implications for short-term ensemble forecasting

Abstract

In a nonlinear quasigeostrophic model with uniform potential vorticity, an idealized initial state sharing some features with atmospheric low-predictability situations is built. Inspired by previous work on idealized cyclogenesis, two different cyclogenesis scenarios are obtained as a result of a small change of the initial location of one structure. This behavior is interpreted by analyzing the baroclinic interaction between upper- and lower-level anomalies. The error growth mechanism is nonlinear; it does not depend on the linear stability properties of the jet, which are the same in both evolutions. The ability of ensemble forecasts to capture these two possible evolutions is then assessed given some realistic error bounds in the knowledge of the initial conditions. First, a reference statistical distribution of each of the evolutions is obtained by means of a large Monte Carlo ensemble. Smaller ensembles with size representative of what is available in current operational implementations are then built and compared to the Monte Carlo reference: several singular-vector-based ensembles, a small Monte Carlo ensemble, and a “coherent structure”-based ensemble. This new technique relies on a sampling of the errors on the precursors of the cyclogenesis: amplitude and position errors. In this context, the precursors are handled as coherent structures that may be amplified or moved within realistic error bounds. It is shown that the singular vector ensemble fails to reproduce the bimodal distribution of the variability if the ensemble is not initially constrained, whereas it is accessible at a relatively low cost to the new coherent structures initialization.
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Dates and versions

meteo-00195293 , version 1 (12-02-2021)

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Matthieu Plu, Philippe Arbogast. A cyclogenesis evolving into two distinct scenarios and its implications for short-term ensemble forecasting. Monthly Weather Review, 2005, 133 (7), pp.2016--2029. ⟨10.1175/MWR2955.1⟩. ⟨meteo-00195293⟩
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