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A new roughness length parameterization accounting for wind-wave (mis)alignment
Porchetta, S.; Temel, O.; Muñoz-Esparza, D.; Reuder, J.; Monbaliu, J.; van Beeck, J.; van Lipzig, N. (2019). A new roughness length parameterization accounting for wind-wave (mis)alignment. Atmos. Chem. Phys. 19(10): 6681-6700. https://dx.doi.org/10.5194/acp-19-6681-2019
In: Atmospheric Chemistry and Physics. Copernicus Publ: Göttingen. ISSN 1680-7316; e-ISSN 1680-7324, meer
Is gerelateerd aan:
Porchetta, S.; Temel, O.; Muñoz-Esparza, D.; Reuder, J.; Monbaliu, J.; van Beeck, J.; van Lipzig, N. (2019). Corrigendum to “A new roughness length parameterization accounting for wind–wave (mis)alignment” published in Atmos. Chem. Phys., 19, 6681–6700, 2019. Atmos. Chem. Phys. 19, meer
Peer reviewed article  
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  • Porchetta, S., meer
  • Temel, O., meer
  • Muñoz-Esparza, D.
  • Reuder, J.
  • Monbaliu, J., meer
  • van Beeck, J., meer
  • van Lipzig, N.
Abstract
    Two-way feedback occurs between offshore wind and waves. However, the influence of the waves on the wind profile remains understudied, in particular the momentum transfer between the sea surface and the atmosphere. Previous studies showed that for swell waves it is possible to have increasing wind speeds in case of aligned wind-wave directions. However, the opposite is valid for opposed wind-wave directions, where a decrease in wind velocity is observed. Up to now, this behavior has not been included in most numerical models due to the lack of an appropriate parameterization of the resulting effective roughness length. Using an extensive data set of offshore measurements in the North Sea and the Atlantic Ocean, we show that the wave roughness length affecting the wind is indeed dependent on the alignment between the wind and wave directions. Moreover, we propose a new roughness length parameterization, taking into account the dependence on alignment, consisting of an enhanced roughness length for increasing misalignment. Using this new roughness length parameterization in numerical models might facilitate a better representation of offshore wind, which is relevant to many applications including offshore wind energy and climate modeling.
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