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Accountability and error in ensemble prediction of baroclinic flows

Smith, Leonard A. (1995) Accountability and error in ensemble prediction of baroclinic flows. In: Seminar on Predictability, 4-8 September 1995. ECMWF seminar proceedings. European Centre for Medium-Range Weather Forecasts, Reading, UK, pp. 351-368.

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Forecast evaluation based on single predictions, each determined from an imperfectly observed initial state, is incomplete; observational uncertainty implies that an ensemble of initial states of the system is consistent with a given observation. In a nonlinear system, this initial distribution will develop a non- Gaussian structure, even if the forecast model is perfect. A perfect prediction (that is, forecasting {\it the} future state of the system) from an uncertain initial observation, is not possible even with a perfect model. Yet this irreducible uncertainty is accountable, in that it is distinct from model error. Ensemble prediction of nonlinear systems reveals shortcomings in the traditional evaluation of forecastverification pairs with least-squared error cost functions; an alternative evaluation of imperfect models through their ability to shadow uncertain observations is discussed. Difficulties surrounding the construction of an ensemble of initial conditions are considered, the implications of imperfect ensembles are noted, and the use of breeding vectors and singular vectors is contrasted in low-dimensional systems.

Item Type: Book Section
Official URL:
Additional Information: © 1995 ECMWF
Divisions: Statistics
Centre for Analysis of Time Series
Subjects: H Social Sciences > HA Statistics
Date Deposited: 22 Feb 2011 13:47
Last Modified: 15 Sep 2023 08:45

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