[IPSL] Prochains seminaires du LMD/IPSL a l'ENS

[externe-ipsl at ipsl.jussieu.fr]

Les prochains séminaires du Laboratoire de Météorologie
Dynamique (IPSL) à l'Ecole Normale Supérieure auront lieu



le jeudi 5 octobre  à 14h30
en salle 316 (3ème étage, département TAO)

Bayesian Approach to Decision Making
  Using Ensemble Weather Forecasts

Rick KATZ

Institute for Study of Society and Environment,
NCAR, Boulder, USA


The economic value of ensemble-based weather or climate forecasts is
generally assessed by taking the ensembles at "face value." That is,
the forecast probability is estimated as the relative frequency of
occurrence of an event among a limited number of ensemble members.
Despite the economic value of probability forecasts being based on the
concept of decision-making under uncertainty, in effect, the decision
maker is assumed to ignore the uncertainty in estimating this
probability. Nevertheless, many users are certainly aware of the
uncertainty inherent in a limited ensemble size. Bayesian prediction
is used instead in the present paper, incorporating such additional
forecast uncertainty into the decision process.

The face-value forecast probability estimator would correspond to a
Bayesian analysis, with a prior distribution on the actual forecast
probability only appropriate if it were believed that the ensemble
prediction system produces perfect forecasts. For the cost/loss
decision-making model, the economic value of the face-value estimator
can be negative for small ensemble sizes from a prediction system
whose level of skill is not sufficiently high. Further, this economic
value has the counterintuitive property of sometimes decreasing as the
ensemble size increases. For a more plausible form of prior
distribution on the actual forecast probability (which could be viewed
as a "re-calibration" of face-value forecasts), the Bayesian estimator
does not exhibit this unexpected behavior. Moreover, it is established
that the effects of ensemble size on the reliability, skill, and
economic value have been exaggerated by using the face-value, instead
of the Bayesian, estimator.

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le jeudi 12 octobre  à 14h30
en salle 316, département TAO


Large-scale tropical atmospheric dynamics:
           waves or balance?

Jun-Ichi YANO

CNRM/GMME/MOANA, Météo-France, Toulouse


------------------------------------------------------------

le mercredi 18 octobre à 11h30
en salle 316, département TAO


Distribution spatiale des populations de plancton
           dans un fluide turbulent


Alexandra TZELLA

DAMTP, Cambridge, Royaume-Uni



--------------------
résumés et liste des prochains séminaires sur
http://www.lmd.ens.fr/Seminar/