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| Titel |
Assessing the drift of seasonal forecasts |
| VerfasserIn |
Rodrigo Manzanas, Jesús Fernández, Maria Eugenia Magariño, José Manuel Gutiérrez, Francisco José Doblas-Reyes, Grigory Nikulin, Carlo Buontempo |
| Konferenz |
EGU General Assembly 2014
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 16 (2014) |
| Datensatznummer |
250099564
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| Publikation (Nr.) |
 EGU/EGU2014-15360.pdf |
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| Zusammenfassung |
| The systematic drift (bias dependence on the forecast lead-time) present in state-of-the-art
coupled general circulation models is an inherent feature of global seasonal forecasts.
Usually, anomalies (relative to the model climatology) obtained from an ensemble of
hindcasts are used to correct this drift. However, this procedure has not been systematically
explored across different forecasting systems so far. Moreover, costly approaches for seasonal
impacts forecasting, such as dynamical downscaling, would benefit from drift removal
strategies involving smaller ensemble sizes.
The full thirty-year (1981-2010) hindcast of the System 4 ECWMF (in particular the
15-members seasonal experiment) was considered to address these issues over two
regions of interest for the EU project EUPORIAS, Europe and East Africa. The mean
climatology for each calendar month was computed at seven different lead-times (each
member was initialized the first of each month and was run for seven months).
For instance,the climatology of January was computed considering the forecasts
initialized the first of January (lead-month 0), December (lead-month 1) and so on
until July (lead-month 6). Results show important drifts for some cases. Moreover,
the differences between members are statistically not significant in general, what
suggests that considering a single member may be enough to robustly remove the
drift.
In the near future, additional forecasting systems involved in EUPORIAS will be
compared with System 4 in order to unveil possible commonalities in the drift climatology. |
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