How to reconcile contradicting forecasts in the coastal ocean? (CROSBI ID 533678)
Prilog sa skupa u zborniku | sažetak izlaganja sa skupa | međunarodna recenzija
Podaci o odgovornosti
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
engleski
How to reconcile contradicting forecasts in the coastal ocean?
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%.
coastal ocean; forecast; DART
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Podaci o prilogu
2008.
objavljeno
Podaci o matičnoj publikaciji
Proceedings of the 2008 Ocean Sciences Meeting : From the Watershed to the Global Ocean
Podaci o skupu
2008 Ocean Sciences Meeting
poster
02.03.2008-07.03.2008
Orlando (FL), Sjedinjene Američke Države