A downscaling exercise for the coastal ocean with the perfect model approach: a study for the Adriatic Sea

This PhD thesis proposes a downscaling exercise with the perfect model approach. A large domain high resolution experiment covering the entire Adriatic Sea, referred to as the “truth”, is used as a benchmark for assessing downscaling configurations for a small nested domain, the Northern Adriatic Sea. A set of experimental setup with different nesting strategies have been performed based on the NEMO ocean model, where child experiments are finally compared with the truth reference. The downscaling performance of each strategy was estimated by kinetic energy spectral analysis. Overall, the child experiments were able to regenerate small scale features and recover the energy not present at the boundaries. A downscaling ratio of 1:3 has proven to be suitable for allowing regeneration of kinetic energy in the inner domain. At larger ratios (i.e. 1:5), drawbacks associated with the lateral open boundaries are propagated resulting in overshooting of energy at specific frequencies. The analyses of local physical processes (dense water formation) and extreme events (marine heat waves) served the scope of judging the capability of reproducing the thermohaline variability of the Northern Adriatic Sea by looking at the effects of local drivers at small scales and/or remote drivers at large scales. The perfect model approach underscores that when remote drivers are missed by the parent model, i.e. the salt water inflow through the Otranto Strait during the cyclonic phase of the Northern Ionian Gyre, the child model may fail the reproducibility of local dense water formation. A final methodology is proposed based on the spectral nudging technique, proven to be a suitable tool for coastal ocean modelling application. The resulting inner domain circulation evolved with better representation of water inflow at the Otranto Strait and thermohaline properties also at remote shallow coastal areas of the Northern Adriatic subdomain.