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 0.25 0.25 ). Three distinct global hindcasts are produced: (a) a long-term hindcast forced by the ERA5 conventional winds 10 U and (b) two short-term hindcasts (2011)(2012)(2013)(2014)(2015)(2016)(2017)(2018)(2019) driven by the NCEP climate forecast system (CFS)v2 10 U and the ERA5 neutral winds 10,neu U, respectively. The input field for ice is sourced from the Ocean and Sea Ice Satellite Application Facility (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 s H 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., 10 s H 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 wavespreading factor, are further described and briefly discussed. Inter-comparisons of s H from the long-term (41 years) wave hindcast, buoy measurements and two different calibrated altimeter data sets highlight the inconsistency in these altimeter records arising from different calibration methodology. Significant errors in the low-frequency bins (period T s) for both wave energy and directionality call for further model development.Plain Language Summary Ocean surface waves are fundamentally important for ocean engineering design, ship navigation, air-sea exchange of gas, heat, momentum and energy, upper ocean dynamics, and remote sensing of the ocean. Spectral wave modeling is an indispensable tool to estimate sea state information. In this study, we present new global wave hindcasts developed using the stateof-the-art model physics and numerics and the modern reanalysis winds and satellite sea ice records. It is demonstrated through validation against in-situ observations and altimeter records that the global wave hindcasts perform well across multiple parameters. Meanwhile, intercomparisons of wave height from the long-term hindcast, buoys, and altimeters reveal inconsistency and potential inhomogeneity in these different data sets. The wave hindcasts we developed, in combination with global wave databases published previously, will form a large ensemble of realizations of historical evolution of sea states simulated with distinct wave physics and wind forcing, which will help quantify sea states in real oceans more accurately. LIU ET AL.
Quality control measures for ocean waves observations are necessary to give confidence of their accuracy. It is common practice to detect anomalies or outliers in surface displacement observations by applying a standard deviation threshold. Besides being a purely statistical method, this quality control procedure is likely to flag extreme wave events erroneously, thereby impacting higher order descriptions of the wave field. In this paper we extend the use of the statistical phase-space threshold, an established outlier detection method in the field of turbulence, to detect anomalies in a wave record. We show that a wave record in phase-space (here defined as a diagram of displacement against acceleration) can be enclosed by a predictable ellipse where the major and minor axis are defined by the spectral properties of the wave field. By using the parameterized ellipse in phase-space as a threshold to identify wave anomalies, this is a semi-physical filtering method. Wave buoy data obtained from a mooring deployed near King George Island, Antarctica (as part of the Antarctic Modeling Observation System, ATMOS) and laser altimeter data obtained at the Northwest Shelf of Australia were used to demonstrate the functioning of the filtering methodology in identifying wave anomalies. Synthetic data obtained using a high-order spectral model is used to identify how extreme waves are positioned in phase-space.
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