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Pregled bibliografske jedinice broj: 325308

How to reconcile contradicting forecasts in the coastal ocean?


Rixen, M.; Carta, A.; Grandi, L.; Gualdesi, L.; Ranelli, P.; Book, J.; Martin, P.; Preller, R.; Oddo, P.; Pinardi, N. et al.
How to reconcile contradicting forecasts in the coastal ocean? // Proceedings of the 2008 Ocean Sciences Meeting : From the Watershed to the Global Ocean
Orlando, SAD, 2008. (poster, međunarodna recenzija, sažetak, znanstveni)


Naslov
How to reconcile contradicting forecasts in the coastal ocean?

Autori
Rixen, M. ; Carta, A. ; Grandi, L. ; Gualdesi, L. ; Ranelli, P. ; Book, J. ; Martin, P. ; Preller, R. ; Oddo, P. ; Pinardi, N. ; Guarnieri, A. ; Chiggiato, J. ; Carniel, S. ; Russo, Aleksandar ; Orlić, Mirko ; Tudor, Martina ; Vandenbulcke, L. ; DART Consortium

Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, sažetak, znanstveni

Izvornik
Proceedings of the 2008 Ocean Sciences Meeting : From the Watershed to the Global Ocean / - , 2008

Skup
2008 Ocean Sciences Meeting

Mjesto i datum
Orlando, SAD, 02.-07.03.2008

Vrsta sudjelovanja
Poster

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Coastal ocean; forecast; DART

Sažetak
Multi-model Super-Ensembles (SE) aiming 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 and limited reliability of operational models so far prevented the proper 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 an experiment in a coastal area in the Adriatic Sea. Kalman filter and Particle filter based methods which allow for dynamic evolution of weights and associated uncertainty show increased skill (+10%) as compared to single models. The latter method copes with non Gaussian error statistics and reduces the uncertainty by a further 30%.

Izvorni jezik
Engleski

Znanstvena područja
Geologija



POVEZANOST RADA


Projekt / tema
004-1193086-3036 - Oluje i prirodne katastrofe u Hrvatskoj (Branka Ivančan-Picek, )
119-1193086-3085 - Utjecaj atmosfere i topografske varijabilnosti na procese u moru (Mirko Orlić, )

Ustanove
Državni hidrometeorološki zavod,
Prirodoslovno-matematički fakultet, Zagreb