During the southwest monsoon

Changes in the seasonal cycle of mean sea level (MSL) may affect the heights of storm surges and thereby flood risk in coastal areas. This study investigates the intra-and inter-annual variability of monthly MSL and its link to the North Atlantic Oscillation using records from 13 tide gauges located in the German Bight. The amplitudes of the seasonal MSL cycle are not regionally uniform and vary between 20 and 29 cm. Generally, the amplitudes are smaller at the southwestern stations, increasing as one travels to the northeastern part. The amplitudes, as well as the phase of the seasonal cycle, are characterized by a large inter-annual and inter-decadal variability, but no long-term trend could be detected. Nevertheless, in the last two decades annual maximum peaks more frequently occurred in January and February, whereas beforehand an accumulation was detected for the November and December period. These changes in phase in the various sea level time series are consistent with a shift in the annual cycle, which is, however, not significant. The changes are associated with strongly increasing trends in monthly MSL of the winter season (J-M), which are considerably higher compared to the remaining seasons. For the same season, the MSL and North Atlantic Oscillation (NAO) indices show strong similarities, resulting in statistically significant correlations (r ~ 0.7). Hence, these changes are linked with changing pressure conditions over the North Atlantic, which lead to a strong phase of positive values in the NAO index between the 1960's and 1990's.

No abstract

No abstract

Physical processes in coastal waters and estuaries extend their influences on many economic and ecological processes in the coastal regions and affect the safety of the coastal defences. In a context with the global climate change, these physical processes underlie also inherent modifications. In order to win an impression of such future changes and of the probability of their occurrence, physically consistent simulations of these processes are used to describe how wind-waves and currents interact. This paper presents an offline-coupled simulation using the models HAMSOM (HAMburg Shelf Ocean Model) and SWAN (Simulating Waves Nearshore). These stateof-the-art models excel by high computing speed, so that they offer an opportunity to simulate hydrological conditions and physical processes over longer time periods, e.g. decades. For the influence of currents on the waves, we estimate less influence on tidal flats, but stronger influence in the tidal channels. Improvements in parameter estimation that were achieved by the interaction of currents and waves are described and discussed; we estimate new drag-coefficients for the hydrodynamic simulation. Because long-term simulations need to be simplified, a method is examined and presented that bypasses the direct online-coupling of models. For the aim of long term simulation improvements of the surface drag coefficient are useful, because online-coupled wind-wave models overcome the available machine time for climate runs. Our method yields an optimization regarding computing economy and physical consistency of simulations.