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ETD Dept., NURC
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- PublicationRestrictedA preliminary analysis of in situ and remotely sensed environmental variables in the coastal region of the Portofino Marine Protected Area(2008-06)
; ; ; ; ; ; ; ; ; ; ;Manca Zeichen, M.; Central Institute for Marine Research, Rome ;Finoia, M. G.; Central Institute for Marine Research, Rome ;Locritani, M.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Roma2, Roma, Italia ;Ruggieri, N.; University of Genoa ;Tunesi, L.; Central Institute for Marine Research, Rome ;Gasparini, G. P.; CNR ISMAR ;Bassetti, M.; ETD Dept., NURC ;Grandi, V.; ETD Dept., NURC ;Cattaneo-Vietti, R.; University of Genoa ;Povero, P.; University of Genoa; ; ; ; ; ; ; ; ; Coastal marine environment is a complex system and its management requires adequate information. Marine Protected Areas (MPAs) are considered pilot sites useful to define innovative tools for the Integrated Coastal Zone Management (ICZM). Their management however requires acquaintance with the relationships between the protected site and the status of the coastal neighbouring areas in order to assess mutual effects and influences. There is the need of monitoring systems capable of highlighting physical and biological phenomena, and possible oceanographic anomalies at local scale, to assess possible existing differences between MPAs and their neighbouring unprotected zones. The present study proposes an integrated analysis of data sets coming from in situ and remote-sensing data to evaluate the reliability of satellite sensors for coastal zone monitoring and to better understand the short-term environmental dynamics on a coastal area centred on the Portofino MPA (Ligurian Sea).768 40 - PublicationRestrictedImproved ocean prediction skill and reduced uncertainty in the coastal region from multi-model super-ensembles(2009)
; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ;; ; ; ; ; ; ; ;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.61 1 - PublicationOpen AccessANALISI INTEGRATA DELLE VARIABILI AMBIENTALI NELLE ACQUE DELL’AREA MARINA(2006-11-14)
; ; ; ; ; ; ; ; ; ;Manca Zeichen, M.; ICRAM ;Locritani, M.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Roma2, Roma, Italia ;Bassetti, M.; NURC ;Ruggieri, N.; UNIGE ;Tunesi, L.; ICRAM ;Grandi, V.; NURC ;Gasparini, G. P.; CNR-ISMAR ;Cattaneo-Vietti, R.; UNIGE ;Povero, P.; UNIGE; ; ; ; ; ; ; ; ; CoNISMaL’ambiente marino costiero è un sistema complesso la cui gestione richiede il coinvolgimento di differenti discipline e la notevole capacità di integrazione fra osservazioni molto eterogenee. E’ in fase di messa a punto di un sistema di osservazione dell’ambiente marino nell’AMP di Portofino. L’idea è quella di sviluppare un monitoraggio dai costi contenuti, che sia in grado di evidenziare le fenomenologie prevalenti sia di tipo fisico che biologico e permetta di cogliere eventuali situazioni anomale rispetto ad una climatologia di riferimento. L’acquisizione dei dati si avvale di differenti piattaforme sia locali che remote e di differenti strategie di campionamento ed elaborazione.189 127