4.6 Article

Global Wave Hindcasts Using the Observation-Based Source Terms: Description and Validation

Journal

Publisher

AMER GEOPHYSICAL UNION
DOI: 10.1029/2021MS002493

Keywords

global wave hindcasts; spectral wave modeling; WAVEWATCH III

Funding

  1. DISI Australia-China Centre [ACSRF48199]
  2. Office of Naval Research Global [N62909-20-1-2080]
  3. Research Computing Services of the University of Melbourne

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Global wave hindcasts were developed using WAVEWATCH III model, showing promising results in validation. Three distinct hindcast datasets were produced and showed different characteristics based on wave parameters. Novel wave parameters were described and discussed in the study.
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 degrees x0.25 degrees). Three distinct global hindcasts are produced: (a) a long-term hindcast (1979-2019) forced by the ERA5 conventional winds U10 and (b) two short-term hindcasts (2011-2019) driven by the NCEP climate forecast system (CFS)v2 U10 and the ERA5 neutral winds U10,neu, 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 Hs 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., Hs>10 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 Hs 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>15 s) for both wave energy and directionality call for further model development.

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