The observation-based source terms available in the third-generation wave model WAVEWATCH III (i.e., the ST6 package for parameterizations of wind input, wave breaking, and swell dissipation terms) are recalibrated and verified against a series of academic and realistic simulations, including the fetch/duration-limited test, a Lake Michigan hindcast, and a 1-yr global hindcast. The updated ST6 not only performs well in predicting commonly used bulk wave parameters (e.g., significant wave height and wave period) but also yields a clearly improved estimation of high-frequency energy level (in terms of saturation spectrum and mean square slope). In the duration-limited test, we investigate the modeled wave spectrum in a detailed way by introducing spectral metrics for the tail and the peak of the omnidirectional wave spectrum and for the directionality of the two-dimensional frequency–direction spectrum. The omnidirectional frequency spectrum E ( f ) from the recalibrated ST6 shows a clear transition behavior from a power law of approximately f ⁻⁴ to a power law of about f ⁻⁵ , comparable to previous field studies. Different solvers for nonlinear wave interactions are applied with ST6, including the Discrete Interaction Approximation (DIA), the more expensive Generalized Multiple DIA (GMD), and the very expensive exact solutions [using the Webb–Resio–Tracy method (WRT)]. The GMD-simulated E ( f ) is in excellent agreement with that from WRT. Nonetheless, we find the peak of E ( f ) modeled by the GMD and WRT appears too narrow. It is also shown that in the 1-yr global hindcast, the DIA-based model overestimates the low-frequency wave energy (wave period T > 16 s) by 90%. Such model errors are reduced significantly by the GMD to ~20%.

Twenty years (1996–2015) of satellite observations were used to study the climatology and trends of oceanic winds and waves in the Arctic Ocean in the summer season (August–September). The Atlantic-side seas, exposed to the open ocean, host more energetic waves than those on the Pacific side. Trend analysis shows a clear spatial (regional) and temporal (interannual) variability in wave height and wind speed. Waves in the Chukchi Sea, Beaufort Sea (near the northern Alaska), and Laptev Sea have been increasing at a rate of 0.1–0.3 m decade−1, found to be statistically significant at the 90% level. The trend of waves in the Greenland and Barents Seas, on the contrary, is weak and not statistically significant. In the Barents and Kara Seas, winds and waves initially increased between 1996 and 2006 and later decreased. Large-scale atmospheric circulations such as the Arctic Oscillation and Arctic dipole anomaly have a clear impact on the variation of winds and waves in the Atlantic sector. Comparison between altimeter observations and ERA-Interim shows that the reanalysis winds are on average 1.6 m s−1 lower in the Arctic Ocean, which translates to a low bias of significant wave height (−0.27 m) in the reanalysis wave data.

The sea state of the Beaufort and Chukchi seas is controlled by the wind forcing and the amount of ice-free water available to generate surface waves. Clear trends in the annual duration of the open water season and in the extent of the seasonal sea ice minimum suggest that the sea state should be increasing, independent of changes in the wind forcing. Wave model hindcasts from four selected years spanning recent conditions are consistent with this expectation. In particular, larger waves are more common in years with less summer sea ice and/or a longer open water season, and peak wave periods are generally longer. The increase in wave energy may affect both the coastal zones and the remaining summer ice pack, as well as delay the autumn ice-edge advance. However, trends in the amount of wave energy impinging on the ice-edge are inconclusive, and the associated processes, especially in the autumn period of new ice formation, have yet to be well-described by in situ observations. There is an implicit trend and evidence for increasing wave energy along the coast of northern Alaska, and this coastal signal is corroborated by satellite altimeter estimates of wave energy

Global wave hindcasts are developed using the third generation spectral wave model WAVEWATCH III with the observation-based source terms (ST6) and a hybrid rectilinear-curvilinear, irregular-regular-irregular grid system (approximately at ). Three distinct global hindcasts are produced: i) a long-term hindcast (1979-2019) forced by the ERA5 conventional winds and ii) two short-term hindcasts (2011-2019) driven by the NCEP CFSv2 and the ERA5 neutral winds , respectively. The input field for ice is sourced from the OSI SAF sea-ice concentration climate data records. These wave simulations, together with the driving wind forcing, are validated against extensive in-situ observations and satellite altimeter records. The performance of the ST6 wave hindcasts shows promising results across multiple wave parameters, including the conventional wave characteristics (e.g., wave height and wave period) and high-order spectral moments (e.g., the surface Stokes drift and mean square slope). The ERA5-based simulations generally present lower random errors, but the CFS-based run represents extreme sea states (e.g., m) considerably better. Novel wave parameters available in our hindcasts, namely the dominant wave breaking probability, wave-induced mixed layer depth, freak wave indexes and wave-spreading factor, are further described and briefly discussed. Inter-comparisons of from the long-term (41 yr) wave hindcast, buoy measurements and two different calibrated altimeter datasets highlight the inconsistency in these altimeter records arising from different calibration methodology. Significant errors in the low-frequency bins (period s) for both wave energy and directionality call for further model development.

Hai Yang-2 (HY-2) satellite altimeter measurements of significant wave height ( ) are analyzed over the period from 1 October 2011 to 6 December 2014. They are calibrated and validated against in situ buoys and other concurrently operating altimeters: Jason-2, CryoSat-2, and Satellite with Argos and ALtiKa (SARAL). In general, the HY-2 altimeter measurements agree well with buoy measurements, with a bias of −0.22 m and a root-mean-square error (RMSE) of 0.30 m. When the reduced major axis (RMA) regression procedure was applied to the entire period, the RMSE was reduced by 33% to 0.2 m. A further comparison with other satellite altimeters, however, revealed two additional features of HY-2 estimates over this period. First, a noticeable mismatch is present between HY-2 and the other satellite altimeters for high seas ( > 6 m). Second, a jump increase in HY-2 values was detected starting in April 2013, which was associated with the switch to backup status of the HY-2 sensors and the subsequent update of its data processing software. Although reported by previous studies, these two deficiencies had not been accounted for in calibrations. Therefore, the HY-2 wave height records are now subdivided into two phases (time periods pre- and post-April 2013) and a two-branched calibration is proposed for each phase. These revised calibrations, validated throughout the range of significant wave heights of 1–9 m, are expected to improve the practical applicability of HY-2 measurements significantly.