Options
Nittis, K.
Loading...
2 results
Now showing 1 - 2 of 2
- PublicationOpen AccessMediterranean Forecasting System: forecast and analysis assessment through skill scores(2009-12-07)
; ; ; ; ; ; ; ; ;Tonani, M.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Bologna, Bologna, Italia ;Pinardi, N.; University of Bologna, Corso di Scienze Ambientali, Ravenna, Italy ;Fratianni, C.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Bologna, Bologna, Italia ;Pistoia, J.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Bologna, Bologna, Italia ;Dobricic, S.; Centro euro-Mediterraneo per i Cambiamenti Climatici, Bologna, Italy ;Pensieri, S.; Consiglio Nazionale delle Ricerche-ISSIA, Genova, Italy ;de Alfonso, M.; Puertos del Estado, Madrid, Spain ;Nittis, K.; Hellenic Centre for Marine Research, Athens, Greece; ; ; ; ; ; ; This paper describes the first evaluation of the quality of the forecast and analyses produced at the basin scale by the Mediterranean ocean Forecasting System (MFS) (http://gnoo.bo.ingv.it/mfs). The system produces short-term ocean forecasts for the following ten days. Analyses are produced weekly using a daily assimilation cycle. The analyses are compared with independent data from buoys, where available, and with the assimilated data before the data are inserted. In this work we have considered 53 ten days forecasts produced from 16 August 2005 to 15 August 2006. The forecast skill is evaluated by means of root mean square error (rmse) differences, bias and anomaly correlations at different depths for temperature and salinity, computing differences between forecast and analysis, analysis and persistence and forecast and persistence. The Skill Score (SS) is defined as the ratio of the rmse of the difference between analysis and forecast and the rmse of the difference between analysis and persistence. The SS shows that at 5 and 30m the forecast is always better than the persistence, but at 300m it can be worse than persistence for the first days of the forecast. This result may be related to flow adjustments introduced by the data assimilation scheme. The monthly variability of SS shows that when the system variability is high, the values of SS are higher, therefore the forecast has higher skill than persistence. We give evidence that the error growth in the surface layers is controlled by the atmospheric forcing inaccuracies, while at depth the forecast error can be interpreted as due to the data insertion procedure. The data, both in situ and satellite, are not homogeneously distributed in the basin; therefore, the quality of the analyses may be different in different areas of the basin.386 185 - PublicationOpen AccessMarine Environment and Security for the European Area (MERSEA) - Towards operational oceanography(2006)
; ; ; ; ; ; ; ;Johannessen, P. Y.; Nansen Environmental and Remote Sensing Center, and Geophysical Institute, University of Bergen, Bergen, Norway ;Le Traon, I.; Institute Francais de Recherche pour l’Exploitation de la Mer, Brest, France ;Robinson, K.; Southampton Oceanography Centre, University of Southampton, Southampton, United Kingdom ;Nittis, K.; Hellenic Centre for Marine Research, Athens, Greece ;Bell, M. J.; Met Office, Exeter, United Kingdom ;Pinardi, N.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Bologna, Bologna, Italia ;Bahurel, P.; MERCATOR OCEAN, Toulouse, France; ; ; ; ; ; An assessment of the present European operational marine monitoring and forecasting systems shows how observations, atmospheric forcing fields and ocean models combine to make useful oceanographic products possible.142 295