Extreme sea level events, such as storm surges, pose a threat to coastlines around the globe. Many tide gauges have been measuring sea level and recording these extreme events for decades, some for over a century. The data from these gauges often serve as the basis for evaluating the extreme sea level statistics, which are used to extrapolate sea levels that serve as design values for coastal protection. Hydrodynamic models often have difficulty in correctly reproducing extreme sea levels and, consequently, extreme sea level statistics and trends.
In this study, we generate a 13-member hind-cast ensemble for the non-tidal Baltic Sea from 1979 to 2018 using the coastal ocean model GETM (General Estuarine Transport Model). In order to cope with mean biases in maximum water levels in the simulations, we include both simulations with and without wind speed adjustments in the ensemble. We evaluate the uncertainties in the extreme value statistics and recent trends of annual maximum sea levels. Although the ensemble mean shows good agreement with observations regarding return levels and trends, we still find large variability and uncertainty within the ensemble (95% confidence levels up to 60 cm for the 30-year return level).
We argue that biases and uncertainties in the atmospheric reanalyses, e.g.\ variability in the representation of storms, translate directly into uncertainty within the ensemble. The translation of the variability of the 99th percentile wind speeds into the sea level elevation is in the order of the variability of the ensemble spread of the modelled maximum sea levels. Our results emphasise that 13 members are insufficient and that regionally large ensembles should be created to minimise uncertainties. This should improve the ability of the models to correctly reproduce the underlying extreme value statistics and thus provide robust estimates of climate change-induced changes in the future.
The Total Exchange Flow analysis framework computes consistent bulk values quantifying the estuarine exchange flow using salinity coordinates since salinity is the main contributor to density in estuaries and the salinity budget is entirely controlled by the exchange flow.
For deeper and larger estuaries temperature may contribute equally or even more to the density. That is why we included potential temperature as a second coordinate to the Total Exchange Flow analysis framework which allows gaining insights in the potential temperature-salinity structure of the exchange flow as well as to compute consistent bulk potential temperature and therefore heat exchange values with the ocean.
We applied this theory to the exchange flow of the Persian Gulf, a shallow, semi-enclosed marginal sea, where dominant evaporation leads to the formation of hyper-saline and dense Gulf water. This drives an inverse estuarine circulation which is analyzed with special interest on the seasonal cycle of the exchange flow. The exchange flow of the Persian Gulf is numerically simulated with the General Estuarine Transport Model (GETM) from 1993 to 2016 and validated against observations. Results show that a clear seasonal cycle exists with stronger exchange flow rates in the first half of the year. Furthermore, the composition of the outflowing water is investigated using passive tracers which mark different surface waters. The results show that in the first half of the year, most outflowing water comes from the southern coast, while in the second half most water originates from the north-western region.