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Prøveforelesning
The Ensemble Kalman filter, and its use in data assimilation in ensemble forecasting
Kreeringssammendrag
Værvarsel for timer eller dager fremover beregnes i numeriske modeller. Når de er publisert eller utstedt til sluttbruker blir værvarselet vanligvis ikke oppdatert. Imidlertid kan feil i værvarselet bli tydelig etter at noen få observasjoner er registrert. Dette doktorgradsarbeidet foreslår en ny teknikk 'Rapid Adjustment of Forecast Trajectories' som oppdaterer værvarsler ved hjelp av statistisk etterbehandling, noe som gir vesentlig forbedrede prediksjoner som også gir merverdi for sluttbrukeren.
Hovedfunn
Populærvitenskapelig artikkel om Schuhens avhandling:
Statistical post-processing of weather forecast ensembles: obtaining optimal deterministic and probabilistic predictions at multiple time scales
Weather forecasts are produced by complex numerical models, issued to end users and then updated after a certain period of time, usually at least several hours. During this time, it might become obvious that the current forecasts are somehow flawed and of little use. Nonetheless, they are not changed until being replaced by a new batch from the most recent run of the model. This work proposes a new statistical post-processing method, Rapid Adjustment of Forecast Trajectories, that improves the quality of predictions even after they have been issued and thus increases their potential value to customers.
The inherent correlation between errors at different forecast times allows for adjustments being applied to future predictions based on very recent observations. Thus, both fast-developing and systematic forecast errors can be corrected in a flexible and swift manner. It complements other, conventional statistical post-processing and results in a significant gain in forecast quality. In fact, adjusted predictions from older runs of the numerical model can become more skilful than those from the newest run. This novel technique can be applied to any forecast time range, from a few hours to several days and weeks, while being very economical and versatile.
Foto og annen informasjon:
Pressefoto: Nina Schuhen, portrett; 500px. Foto: Privat
