Ensemble Forecasting of Severe
Weather in the 3-5 Days Range: Proposals, Validation and Open Questions
The design of ensemble methods for medium range forecasting ten years
ago has been aiming mainly at addressing the problem of limited predictability
of supra-synoptic weather regimes in the 6-10 days range. From this point of
view, it has been shown that the ensembles have delivered improved forecasts
compared to a purely deterministic approach, both by improving single-value
estimates (ensemble mean) and by providing both reliable and sharp estimates of
the probability distributions of large scale flow patterns such as given by 500
hPa height fields.
There is no reason why the provision of probability distributions for
parameters more directly related to the weather such as wind or precipitation
could not help decision-making processes in the early medium-range (3-5 days)
as well. Of particular interest for the users is to know if the ensembles are able
to detect severe weather. These are usually not seen by the models as the most
likely scenarios at these ranges, but forecasters have expressed an interest in
using even small probabilities of severe weather occurrence as a useful early
warnings that will help them focus their monitoring of the situation when the
severe weather eventually comes closer. Because the model resolution is a
serious limitation when addressing severe weather forecasting, a new method for
identifying model proxys for extreme events has been designed at ECMWF. It
involves first an estimate of monthly distributions of weather parameters at
the model resolution. A new index was then designed (the Extreme Forecast
Index) that scales the differences between EPS forecast distributions and the
model climate ones. Both the global climate and case studies showing how the
new index can help detecting severe weather conditions 3 to 5 days in advance
will be presented. Preliminary results showing objective verification in terms
of false alarms and hit rates will also be shown and discussed.
Finally, one of the most recent developments of ECMWF EPS has aimed at
improving the sampling of uncertainties in tropical environments. One of the
main objectives is to provide useful probabilistic guidance for tropical
cyclone forecasts up to 5 days in advance. New products such as Strike
Probability Maps derived from the ensemble forecasts will be presented,
together with some verification results.