Pregled bibliografske jedinice broj: 435504
Improved ocean prediction skill and reduced uncertainty in the coastal region from multi-model super-ensembles
Improved ocean prediction skill and reduced uncertainty in the coastal region from multi-model super-ensembles // Journal of Marine Systems, 78 (2009), Suppl. 1; 282-289 doi:10.1016/j.jmarsys.2009.01.014 (međunarodna recenzija, članak, znanstveni)
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Naslov
Improved ocean prediction skill and reduced uncertainty in the coastal region from multi-model super-ensembles
Autori
Rixen, Michel ; Book, Jeffrey W. ; Carta, Alessandro ; Grandi, Vittorio ; Gualdesi, Lavinio ; Stoner, Richard ; Ranelli, Peter ; Cavanna, Andrea ; Zanasca, Pietro ; Baldasserini, Gisella ; Trangeled, Alex ; Lewis, Craig ; Trees, Chuck ; Grasso, Rafaelle ; Giannechini, Simone ; Fabiani, Alessio ; Merani, Diego ; Berni, Alessandro ; Leonard, Michel ; Martin, Paul ; Rowley, Clark ; Hulbert, Mark ; Quaid, Andrew ; Goode, Wesley ; Preller, Ruth ; Pinardi, Nadia ; Oddo, Paolo ; Guarnieri, Antonio ; Chiggiato, Jacopo ; Carniel, Sandro ; Russo, Aniello ; Tudor, Martina ; Lenartz, Fabian ; Vandenbulcke, Luc
Izvornik
Journal of Marine Systems (0924-7963) 78
(2009), Suppl. 1;
282-289
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
Ocean prediction skill; Uncertainties; Multi model super-ensembles; Coastal environments; Kalman Filter; Particle Filter
Sažetak
The use of Multi-model Super-Ensembles (SE) which optimally combine different models, has been shown to significantly improve atmospheric weather and climate predictions. In the highly dynamic coastal ocean, the presence of small-scales processes, the lack of real-time data, and the limited skill of operational models at the meso-scale have so far limited the application of SE methods. Here, we report results from state-of-the-art super-ensemble techniques in which SEPTR (a trawl-resistant bottom mounted instrument platform transmitting data in near real-time) temperature profile data are combined with outputs from eight ocean models run in a coastal area during the Dynamics of the Adriatic in Real-Time (DART) experiment in 2006. New Kalman filter and particle filter based SE methods, which allow for dynamic evolution of weights and associated uncertainty, are compared to standard SE techniques and numerical models. Results show that dynamic SE are able to significantly improve prediction skill. In particular, the particle filter SE copes with non-Gaussian error statistics and provides robust and reduced uncertainty estimates.
Izvorni jezik
Engleski
Znanstvena područja
Fizika
Napomena
Coastal Processes: Challenges for Monitoring and Prediction Edited by Michel Rixen, Jeffrey W. Book and Mirko Orlic
POVEZANOST RADA
Projekti:
004-1193086-3036 - Oluje i prirodne katastrofe u Hrvatskoj (Ivančan-Picek, Branka, MZOS ) ( CroRIS)
Ustanove:
Državni hidrometeorološki zavod
Profili:
Martina Tudor
(autor)
Citiraj ovu publikaciju:
Časopis indeksira:
- Current Contents Connect (CCC)
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus