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| Titel |
Robust multiscale prediction of Po River discharge using a twofold AR-NN approach |
| VerfasserIn |
Silvia Alessio, Carla Taricco, Sara Rubinetti, Davide Zanchettin, Angelo Rubino, Salvatore Mancuso |
| Konferenz |
EGU General Assembly 2017
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| Medientyp |
Artikel
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| Sprache |
en
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 19 (2017) |
| Datensatznummer |
250149273
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| Publikation (Nr.) |
 EGU/EGU2017-13607.pdf |
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| Zusammenfassung |
| The Mediterranean area is among the regions most exposed to hydroclimatic changes, with a
likely increase of frequency and duration of droughts in the last decades and potentially
substantial future drying according to climate projections. However, significant decadal
variability is often superposed or even dominates these long-term hydrological trend as
observed, for instance, in North Italian precipitation and river discharge records. The
capability to accurately predict such decadal changes is, therefore, of utmost environmental
and social importance.
In order to forecast short and noisy hydroclimatic time series, we apply a twofold statistical
approach that we improved with respect to previous works [1]. Our prediction strategy
consists in the application of two independent methods that use autoregressive models
and feed-forward neural networks. Since all prediction methods work better on
clean signals, the predictions are not performed directly on the series, but rather on
each significant variability components extracted with Singular Spectrum Analysis
(SSA).
In this contribution, we will illustrate the multiscale prediction approach and its application to
the case of decadal prediction of annual-average Po River discharges (Italy). The
discharge record is available for the last 209 years and allows to work with both
interannual and decadal time-scale components. Fifteen-year forecasts obtained with
both methods robustly indicate a prominent dry period in the second half of the
2020s.
We will discuss advantages and limitations of the proposed statistical approach in the light of
the current capabilities of decadal climate prediction systems based on numerical
climate models, toward an integrated dynamical and statistical approach for the
interannual-to-decadal prediction of hydroclimate variability in medium-size river
basins.
[1] Alessio et. al., Natural variability and anthropogenic effects in a Central Mediterranean
core, Clim. of the Past, 8, 831-839, 2012. |
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