ИСТИНА

Human activities and environmental evolution in coastal zones go by in the face to coastal erosion. In case of coasts composed by loose material coastal erosion may reach from several centimetres up to ten meters per year. The driving factor of coastal erosion is the energy of waves coming to the shoreline. Wave energy, in turn, depends heavily on wind and storm activity and the exposure of coast to waves – open water season duration. Modern gridded wind and sea ice data products (like reanalyses) can be used as the input data for WE calculation, as they are of wide spatial and temporal cover and in regular grid. But the resulting WE estimations may vary with the data source change-over. This work is aimed to estimate the WE series characteristics (mean value, evolution and trend) uncertainties provoked by the scatter of the input data. We vary the sea ice concentration (and open water season start and end dates) within 6 datasets: 2 satellite products NSIDC and OSI SAF, 4 reanalyses (CFSR, MERRA2, JRA55 and ERA-5) and also wind data within 3 reanalyses (CFSR, MERRA2 and ERA-5) and then calculate trend, RMSE and mean values scatter of the resulting WE series for the 1979-2017 period. The research is conducted over 2 sites in the Kara Sea (Popova and Marresalya stations) and 3 sites at the Far East (Lorino at Chukotka peninsula and Shishmarev and Kivalina at Alyaska). The WE is calculated with the Popova-Sovershaev method. The GEBCO digital relief model as used for bathymetry and wave-dangerous directions detection. It occurred that, despite of the intensively changing climate, there is no significant trend in WE series since 1979 and all the datasets are consistent with each other in this fact. The great variability of WE from year to year is still the dominant factor of WE evolution: the standard deviation accounts for 0.3-0.7 of long-term mean value. Herewith the switch of data source (wind or ice) may reverse the trend direction to the opposite: the 38-years increment, calculated through linear trend building, may scatter negligible (about 0.06 σ) or range significantly up to 2 σ. The fluctuating wind data provide the greater (than ice) WE instability in terms of RMSE and correlation which account for 0.41-0.57 σ (vs 0.02-0.1) and 85-91% (vs 93-99%) correspondingly. Among the CFSR, MERRA2, ERA5 reanalyses there is no one of the preferred wind-representation quality. For the ice conditions the NSIDC may by the dataset of choice for wave energy assessment in coastal zone as it shows the best convergence with ensemble and observation series. The CFSR dataset (and in some cases JRA55) should not be used without any additional data, as they may demonstrate spurious negative tendency of open water season duration (and, hence, WE).