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| Titel |
On the predictability of extremes: does the butterfly effect ever decrease? |
| VerfasserIn |
Alef Sterk, David Stephenson, Mark Holland, Ken Mylne |
| Konferenz |
EGU General Assembly 2016
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| Medientyp |
Artikel
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| Sprache |
en
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 18 (2016) |
| Datensatznummer |
250122854
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| Publikation (Nr.) |
 EGU/EGU2016-1985.pdf |
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| Zusammenfassung |
| We investigate whether predictability always decreases for more extreme events.
Predictability is measured by the Mean Squared Error (MSE), which is estimated from the
difference of pairs of ensemble forecasts, conditioned on one of the forecast variables (the
“pseudo-observation”) exceeding a threshold.
Using an exchangeable linear regression model for pairs of forecast variables, we show
that the MSE can be decomposed into the sum of three terms: a threshold-independent
constant, a mean term that always increases with threshold, and a variance term that can
either increase, decrease, or stay constant with threshold. Using the Generalised Pareto
Distribution to model wind speed excesses over a threshold, we show that MSE always
increases with threshold at sufficiently high threshold. However, MSE can be a decreasing
function of threshold at lower thresholds but only if the forecasts have finite upper
bounds.
The methodology is illustrated by application to daily wind speed forecasts for London
made using the 24 member Met Office Global and Regional Ensemble Prediction System
from 1 January 2009 to 31 May 2011. For this example, the mean term increases faster than
the variance term decreases with increasing threshold, and so predictability decreases for
more extreme events. |
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