1. Storm surge modelling in the Mediterranean Sea with focus on the Italian coast Christian Ferrarin 1.2. Georg Umgiesser 1. Andrea Cucco 2. Marco Bajo 1 1. ISMAR-CNR. Venice. Italy. 2. IAMC-CNR. Oristano. Italy. Christian Ferrarin : c.ferrarin@ismar.cnr.itc.ferrarin@ismar.cnr.it

2. The goal of this research is to describe/predict the storm surge in the Mediterranean Sea with focus on the Italian coast, through the application of high resolution numerical models. Objective The TOTAL WATER LEVEL is given by: Tidal Oscillation Meteorological Surge Wave set-up / set-down

3. Finite element tide-surge-wave modelling system Meteorological Model Hydrodynamic Model Spectral Wave Model STORM SURGE MODEL FRAMEWORK

4. SHYFEM Model Shallow water HYdrodynamic Finite Element Model  = water level H = water depth g = gravity f = Coriolis parameter U.,V = velocities A h = hor. diff. coeff. p a = atm. pressure η = equilibrium tide α = Love number β = loading factor Potential tide Loading tide Wave Radiation stress Wind stress Pressure gradient Bottom stress

5. Operator Splitting Methods (OSM)  1 st and 2 nd Step – Spectral part  2 nd Step – Geographical space  3 rd Step – Integration of the source terms Finite element wave model WWM Finite element wave model based on the spectral action balance equation (Hsu et al. 2005): N = wave action density S = source term

6. Model domain 646218 nodes 117714 elements Resolution: open sea 15-20 km coast 5 km Italian coast 1.5 km

7. Model set up FORCING: ECMWF wind & pressure FES2004 tide at Gibraltar Strait Body + earth + load tides 4 diurnal (K1, O1, P1, Q1) 4 semidiurnal (M2, S2, N2, K2) 3 long term (Mf, Mm, Ssa) Hydrodynamic: 2D borotropic Smith & Banke formulation Time step: 300 s (adaptive) Wave: 18 directions 18 frequency [0.05... 0.5] Time step = 600 s

8. Model results 1: tide

9. Model results 2: Residual differences Station RMSE [cm]CORRBIAS [cm]SI IDName 1Trieste0.110.70-0.021.07 2Venezia0.120.76-0.070.98 3Ravenna0.090.750.000.86 4Ancona0.120.780.091.35 5Ortona0.150.720.121.61 6Vieste0.190.640.171.91 7Bari0.220.670.202.02 8Otranto0.300.570.292.34 9Taranto0.260.560.252.27 10Crotone0.240.490.222.22 11Reggio Cal.0.250.550.242.30 12Palinuro0.170.560.162.06 13Salerno0.190.530.182.15 14Napoli0.160.550.152.01 15Civitav0.100.570.071.58 16Livorno0.090.650.061.39 17Genova0.070.68-0.041.02 18Imperia0.060.67-0.010.92 19Messina0.110.590.091.74 20Palermo0.080.59-0.061.19 21Porto Emp.0.100.480.081.79 22Catania0.060.660.011.05 23Lampedusa0.080.50-0.041.24 24Cagliari0.160.53-0.141.80 25Carloforte0.130.57-0.111.62 26Porto Torres0.120.60-0.111.46 AVERAGE0.140.610.071.61

10. Model results 2: Residual differences Line = median Box = 25th to 75th percentile Wisker = 1.5 * IQR Star = average value