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[1] A combined high-resolution atmospheric downscaling and wave hindcast based on the ERA-40 reanalysis covering the Norwegian Sea, the North Sea, and the Barents Sea is presented. The period covered is from September 1957 to August 2002. The dynamic atmospheric downscaling is performed as a series of short prognostic runs initialized from a blend of ERA-40 and the previous prognostic run to preserve the fine-scale surface features from the high-resolution model while maintaining the large-scale synoptic field from ERA-40. The nested WAM wave model hindcast consists of a coarse 50 km model covering the North Atlantic forced with ERA-40 winds and a nested 10-11 km resolution model forced with downscaled winds. A comparison against in situ and satellite observations of wind and sea state reveals significant improvement in mean values and upper percentiles of wind vectors and the significant wave height over ERA-40. Improvement is also found in the mean wave period. ERA-40 is biased low in wind speed and significant wave height, a bias which is not reproduced by the downscaling. The atmospheric downscaling also reproduces polar lows, which cannot be resolved by ERA-40, but the lows are too weak and short-lived as the downscaling is not capable of capturing their full life cycle.

Trends in marine wind speed and significant wave height are investigated using the global reanalysis ERAInterim over the period 1979-2012, based on monthly-mean and monthly-maximum data. Besides the traditional reanalysis, the authors include trends obtained at different forecast range, available up to 10 days ahead. Any model biases that are corrected differently over time are likely to introduce spurious trends of variable magnitude. However, at increased forecast range the model tends to relax, being less affected by assimilation. Still, there is a trade-off between removing the impact of data assimilation at longer forecast range and getting a lower level of uncertainty in the predictions at shorter forecast range. Because of the sheer amount of assimilations made in ERA-Interim, directly and indirectly affecting the data, it is difficult, if not impossible, to distinguish effects imposed by all updates. Here, special emphasis is put on the introduction of wave altimeter data in August 1991, the only type of data directly affecting the wave field. From this, it is shown that areas of higher model bias introduce quite different trends depending on forecast range, most apparent in the North Atlantic and eastern tropical Pacific. Results are compared with 23 in situ measurements, Envisat altimeter winds, and two stand-alone ECMWF operational wave model (EC-WAM) runs with and without wave altimeter assimilation. Here, the 48-h forecast is suggested to be a better candidate for trend estimates of wave height, mainly due to the step change imposed by altimeter observations. Even though wind speed seems less affected by undesirable step changes, the authors believe that the 24-48-h forecast more effectively filters out any unwanted effects.

The objective of this study is to compute 100-yr return value estimates of significant wave height using a new hindcast developed by the Norwegian Meteorological Institute. This regional hindcast covers the northeast Atlantic and spans the period 1958-2009.The return value estimates are based upon three different stationary models commonly applied in extreme value statistics: the generalized extreme value (GEV) distribution, the joint GEV distribution for the r largest-order statistic (rLOS), and the generalized Pareto (GP) distribution. Here, the qualitative differences between the models and their corresponding confidence intervals are investigated.