The ability of a barotropic model to simulate sea level extremes of meteorological origin in the Mediterranean Sea, including those caused by explosive cyclones. Issue 11 (21st November 2014)

• Record Type: Journal Article
• Authors: Calafat, F. M.; Avgoustoglou, E.; Jordà, G.; Flocas, H.; Zodiatis, G.; Tsimplis, M. N.; Kouroutzoglou, J.
• Is Part Of: Journal of geophysical research. Volume 119:Issue 11(2014:Nov.)
• Page Start: 7840
• Page End: 7853
• Publication Date: 2014-11-21
• Subjects: Oceanography -- Periodicals; 551.4605
• DOI: 10.1002/2014JC010360
• Languages: English
• ISSNs: 2169-9275

Abstract

<abstract abstract-type="main"> <title>Abstract</title> <p>Storm surges are responsible for great damage to coastal property and loss of life every year. Coastal management and adaptation practices are essential to reduce such damage. Numerical models provide a useful tool for informing these practices as they simulate sea level with high spatial resolution. Here we investigate the ability of a barotropic version of the HAMSOM model to simulate sea level extremes of meteorological origin in the Mediterranean Sea, including those caused by explosive cyclones. For this purpose, the output of the model is compared to hourly sea level observations from six tide gauge records (Valencia, Barcelona, Marseille, Civitavecchia, Trieste, and Antalya). It is found that the model underestimates the positive extremes significantly at all stations, in some cases by up to 65%. At Trieste, the model can also sometimes overestimate the extremes significantly. The differences between the model and the residuals are not constant for extremes of a given height, which limits the applicability of the numerical model for storm surge forecasting because calibration is difficult. The 50 and 10 year return levels are reasonably well captured by the model at all stations except Barcelona and Marseille, where they are underestimated by over 30%. The number of exceedances of the 99.9th and 99.95% percentiles over a period of 25 years is severely underestimated by the model at all stations. The skill of the model for predicting the timing and value of the storm surges seems to be higher for the events associated with explosive cyclones at all stations.</p> </abstract>