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Τρίτη 19 Ιανουαρίου 2016

On the use of a coupled ocean–atmosphere–wave model during an extreme cold air outbreak over the Adriatic Sea

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Publication date: 15 May–1 June 2016
Source:Atmospheric Research, Volumes 172–173
Author(s): Antonio Ricchi, Mario Marcello Miglietta, Pier Paolo Falco, Alvise Benetazzo, Davide Bonaldo, Andrea Bergamasco, Mauro Sclavo, Sandro Carniel
An intense cold air outbreak affected the northern Adriatic Sea during winter 2012, determining an exceptional persistence of northeasterly Bora wind over the basin, which lasted for about 3weeks. The cold air coming from the Balkans produced icing in the Venice lagoon and very intense snowfall in the Apennines Mountains and even near the coasts.In order to understand the importance and role of air–sea interactions for the evolution of the atmospheric fields, simulations with the Weather Research and Forecasting (WRF) model encompassing the whole period have been performed using sea surface temperature (SST) fields with an increasing level of complexity. Starting from a large-scale static sea temperature, the SST in the initial and boundary conditions has been progressively made more realistic. First, a more refined field, retrieved from a satellite radiometer was used; then, the same field was updated every 6h. Next, the effect of including a simplified 1D ocean model reproducing the Oceanic Mixed Layer (OML) evolution has been tested. Finally, the potential improvements coming from a coupled description of atmosphere–ocean and atmosphere–ocean–waves interactions have been explored within the Coupled Ocean–Atmosphere–Wave Sediment Transport (COAWST) modeling system.Results highlight that the energy exchange between air and sea does not significantly impact the atmospheric fields, in particular 10m wind and 2m temperature, also because of the geography of the basin and the predominance of synoptic-scale flow in intense events of Bora, in the northern Adriatic. However, when sensible and latent heat fluxes, which are dependent on atmospheric and oceanic variables, are analyzed, the more realistic representation of SST drastically improves the model performances.



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