an analysis of uncertainties and skill in forecasts of winter storm losses
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2016
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Abstract
This paper describes an approach to derive probabilistic predictions of local
winter storm damage occurrences from a global medium-range ensemble
prediction system (EPS). Predictions of storm damage occurrences are subject
to large uncertainty due to meteorological forecast uncertainty (typically
addressed by means of ensemble predictions) and uncertainties in modelling
weather impacts. The latter uncertainty arises from the fact that local
vulnerabilities are not known in sufficient detail to allow for a
deterministic prediction of damages, even if the forecasted gust wind speed
contains no uncertainty. Thus, to estimate the damage model uncertainty, a
statistical model based on logistic regression analysis is employed, relating
meteorological analyses to historical damage records. A quantification of the
two individual contributions (meteorological and damage model uncertainty) to
the total forecast uncertainty is achieved by neglecting individual
uncertainty sources and analysing resulting predictions. Results show an
increase in forecast skill measured by means of a reduced Brier score if both
meteorological and damage model uncertainties are taken into account. It is
demonstrated that skilful predictions on district level (dividing the area of
Germany into 439 administrative districts) are possible on lead times of
several days. Skill is increased through the application of a proper ensemble
calibration method, extending the range of lead times for which skilful
damage predictions can be made.
| Reference Key |
pardowitz2016naturalan
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|---|---|
| Authors | ;T. Pardowitz;T. Pardowitz;R. Osinski;T. Kruschke;U. Ulbrich |
| Journal | anziam journal |
| Year | 2016 |
| DOI |
10.5194/nhess-16-2391-2016
|
| URL | |
| Keywords |
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