CLIMATOLOGICAL STUDY OF THE WIND IN PIEDMONT

The object of the following study is to individualize the common anemological features in the Piemonte region. The executed analysis avails itself of a multiannual sample of wind data (from 1990 to 2000) collected by 59 ARPA-Piemonte monitoring network. The wind statistical analyses have followed different phases: - analyses of wind frequency and wind directions and spotting of the anemological basins; - annual and monthly average of wind directions; - annual monthly and hourly average of the wind force with spotting of breezes; - analyses of daily and hourly wind calm; - analyses of the strongest windblasts with records of critical cases; - analyses of the number of days of föhn and types of weather (Borghi-Giuliacci method)

CLIMATOLOGICAL STUDY OF THE WIND IN PIEDMONT

The object of the following study is to individualize the common anemological features in the Piemonte region. The executed analysis avails itself of a multiannual sample of wind data (from 1990 to 2000) collected by 59 ARPA-Piemonte monitoring network. The wind statistical analyses have followed different phases: - analyses of wind frequency and wind directions and spotting of the anemological basins; - annual and monthly average of wind directions; - annual monthly and hourly average of the wind force with spotting of breezes; - analyses of daily and hourly wind calm; - analyses of the strongest windblasts with records of critical cases; - analyses of the number of days of föhn and types of weather (Borghi-Giuliacci method)

Forecast and analysis assessment through skill scores

International audienceThis paper describes a first comprehensive evaluation of the quality of the ten days ocean forecasts produced by the Mediterranean ocean Forecasting System (MFS). Once a week ten days forecasts are produced. The forecast starts on Tuesday at noon and the prediction is released on Wednesday morning with less then 24 hr delay. In this work we have considered 22 ten days forecasts produced from the 16 August 2005 to the 10 January 2006. All the statistical scores have been done for the Mediterranean basin and for 13 regions in which the Mediterranean sea has been subdivided. The forecast evaluation is given here in terms of root mean square (rms) values. The main skill score is computed as the root mean square of the difference between forecast and analysis (FA) and forecast and persistence (FP), where the persistence is defined as the average of the day of the analysis corresponding to the first day of the forecast. A second skill score (SSP) is defined as the ratio between rms of FA and FP, giving the percentage of accuracy of the forecast with respect to the persistence (Murphy 1993). The rms of FA is always better than FP and the FP rms error is double than the rms of FA. It is found that in the surface layers the error growth is controlled mainly by the atmospheric forcing inaccuracies while at depth the forecast errors could be due to adjustments of the data assimilation scheme to the data insertion procedure. The predictability limit for our ocean forecast seems to be 5?6 days connected to atmospheric forcing inaccuracies and to the data availability for assimilation

A high resolution free surface model of the Mediterranean Sea

International audienceThis study describes a new model implementation for the Mediterranean Sea which has the presently highest vertical resolution over the Mediterranean basin. The resolution is of 1/16°×1/16° in horizontal and 71 unevenly spaced vertical levels. This model has been developed in the frame of the EU-MFSTEP project and it is the operational forecast model presently used at the basin scale. For the first time in the Mediterranean, the model considers an implicit free surface and this characteristics enhances the model capability to simulate the sea surface height variability. In this study we show the calibration/validation experiments done before and after the model has been used for forecasting. The first experiment consist of six years of a simulation forced by a perpetual year forcing and the other experiment is a simulation from January 1997 to December 2004, forcing the model with 6 h atmospheric forcing fields from ECMWF. For the first time the model Sea Level Anomaly is compared with SLA and with ARGO data to provide evidence of the quality of the simulation. The results show that this model is capable to reproduce most of the variability of the general circulation in the Mediterranean Sea even if some basic model inadequacies stand out and should be corrected in the near future

Forecast and analysis assessment through skill scores

This paper describes a first comprehensive evaluation of the quality of the ten days ocean forecasts produced by the Mediterranean ocean Forecasting System (MFS). Once a week ten days forecasts are produced. The forecast starts on Tuesday at noon and the prediction is released on Wednesday morning with less then 24 hr delay. 5 In this work we have considered 22 ten days forecasts produced from the 16 August 2005 to the 10 January 2006. All the statistical scores have been done for the Mediterranean basin and for 13 regions in which the Mediterranean sea has been subdivided. The forecast evaluation is given here in terms of root mean square (rms) values. 10 The main skill score is computed as the root mean square of the difference between forecast and analysis (FA) and forecast and persistence (FP), where the persistence is defined as the average of the day of the analysis corresponding to the first day of the forecast. A second skill score (SSP) is defined as the ratio between rms of FA and FP, giving the percentage of accuracy of the forecast with respect to the persistence 15 (Murphy 1993). The rms of FA is always better than FP and the FP rms error is double than the rms of FA. It is found that in the surface layers the error growth is controlled mainly by the atmospheric forcing inaccuracies while at depth the forecast errors could be due to adjustments of the data assimilation scheme to the data insertion procedure. The pre20 dictability limit for our ocean forecast seems to be 5–6 days connected to atmospheric forcing inaccuracies and to the data availability for assimilation