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Pregled bibliografske jedinice broj: 371116

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Autori: Rixen, M; Carta, A; Grandi V.; Gualdesi L., Ranelli, P.; Book, J.; Martin, P.J.; Preller, R; Oddo, P; Pinardi, N; Guarnieri, A.; Chiggiato, J.; Carniel, S.; Russo, Aleksandar; Orlić, Mirko; Tudor, Martina; Vandenbulcke, L.; Lenartz, F.; DART consortium
Naslov: Dynamics of the Adriatic in Real-Time (DART) : multi-model superensembles prediction in a coastal ocean regime
( Dynamics of the Adriatic in Real-Time (DART) : multi-model superensembles prediction in a coastal ocean regime )
Izvornik: Workshop Recent Advances in Adriatic Oceanography and Marine Meteorology : Book of abstracts / Orlić, Mirko ; Pasarić, MIroslava (ur.). - Zagreb : Andrija Mohorovičić Geophysical Institute, Faculty of Science, University of Zagreb , 2008. 51-51 (ISBN: 978-953-6076-18-5).
Skup: Workshop Recent Advances in Adriatic Oceanography and Marine Meteorology
Mjesto i datum: Dubrovnik, Hrvatska, 05-07.11.2008.
Ključne riječi: Adriatic; super-ensembles; models; prediction
( Adriatic; super-ensembles; models; prediction )
Sažetak:
Multi-model Super-Ensembles (SE) aimed at combining optimally different models have been shown to improve significantly atmospheric weather predictions. In the coastal ocean, complex, yet poorly understood dynamics, the presence of small-scales processes, the lack of real-time data at appropriate spatio-temporal resolution and limited reliability of operational models so far prevented the application of SE methods. Here, we report results from state-of-the-art super-ensemble techniques based on dynamic combinations of SEPTR (a trawl-resistant bottom mounted platform transmitting in near real-time) data and a series of eight operational models ran during the DART (Dynamics of the Adriatic in Real-Time) experiment in a coastal area. Kalman filter and particle filter SE-based methods which allow for dynamic evolution of weights and associated uncertainty show increased temperature prediction skill (+10%) as compared to single models. The latter method copes with non-Gaussian error statistics and reduces the forecast uncertainty by a further 30%.
Vrsta sudjelovanja: Predavanje
Vrsta prezentacije u zborniku: Sažetak
Vrsta recenzije: Nema recenziju
Projekt / tema: 119-1193086-3085, 004-1193086-3036
Izvorni jezik: eng
Kategorija: Znanstveni
Znanstvena područja:
Geologija
Upisao u CROSBI: mpavic@geolpmf.hr (mpavic@geolpmf.hr), 11. Stu. 2008. u 15:46 sati



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