Journal
CLIMATE DYNAMICS
Volume 43, Issue 7-8, Pages 2167-2184Publisher
SPRINGER
DOI: 10.1007/s00382-013-2041-0
Keywords
ROMS; Non-tidal residuals; Storm surge; Trends; Numerical modelling; Satellite validation
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Funding
- Spanish government [CTM2010-15009, BIA2011-29031-C02-00]
- FP7 European Project CoCoNet [287844]
- FP7 European Project Theseus [ENV.2009-1, n244104]
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Two sets of 62-year (1948-2009) and 21-year (1989-2009) high-resolution hindcasts of the meteorological sea level component have been developed for Southern Europe using the Regional Ocean Model System (ROMS) of Rutgers University. These new databases, named GOS 1.1 and GOS 2.1, are a valuable tool for a wide variety of studies, such as those related to a better understanding of sea level variability, flooding risk and coastal engineering studies. The model domain encloses Southern Europe, including the Mediterranean Sea and the Atlantic coast, with a horizontal resolution of 1/8A degrees (similar to 14 km). In order to study the effect of the atmospheric forcing resolution, ROMS is driven with two different regional atmospheric forcings: SeaWind I (30 km of horizontal resolution) and SeaWind II (15 km of horizontal resolution). Both are the result of a dynamical downscaling from global atmospheric reanalysis: NCEP global reanalysis and ERA-Interim global reanalysis, respectively. As a result, two surge data sets are obtained: GOS 1.1 (forced with SeaWind I) and GOS 2.1 (forced with SeaWind II). Surge elevations calculated by ROMS are compared with in situ measurements from tide gauges in coastal areas and with open ocean satellite observations. The validation procedure, testing outcomes from GOS 1.1 and GOS 2.1 against observations, shows the capability of the model to simulate accurately the sea level variation induced by the meteorological forcing. A description of the surge in terms of seasonality and long term trends is also made. The climate variability analysis reveals clear seasonal patterns in the Mediterranean Sea basins. A long-term negative trend for the period 1948-2009 is found, whilst positive trends are computed for the last 20 years (GOS 2.1).
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