Assimilation of significant wave height from distributed ocean wave sensors.

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Date
2021Author
Smit, P.B.
Houghton, I.A.
Jordanova, K.
Portwood, T.
Shapiro, E.
Clark, D.
Sosa, M.
Janssen, T.T.
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In-situ ocean wave observations are critical to improve model skill and validate remote sensing wave measurements. Historically, such observations are extremely sparse due to the large costs and complexity of traditional wave buoys and sensors. In this work, we present a recently deployed network of free-drifting satellite-connected surface weather buoys that provide long-dwell coverage of surface weather in the northern Pacific Ocean basin. To evaluate the leading-order improvements to model forecast skill using this distributed sensor network, we implement a widely-used data assimilation technique and compare forecast skill to the same model without data assimilation. Even with a basic assimilation strategy as used here, we find remarkable improvements to forecast accuracy from the incorporation of wave buoy observations, with a 27% reduction in root-mean-square error in significant waveheights overall. For an extreme event, where forecast accuracy is particularly relevant, we observ.....
Journal
Ocean ModellingVolume
159Issue
Article 101738Page Range
10pp.Document Language
enSustainable Development Goals (SDG)
14.aEssential Ocean Variables (EOV)
Sea stateDOI Original
https://doi.org/10.1016/j.ocemod.2020.101738Citation
Smit,P.B., Houghton, I.A., Jordanova, K. et al (2021) Assimilation of significant wave height from distributed ocean wave sensors, Ocean Modelling, 159:101738, 10pp. DOI: https://doi.org/10.1016/j.ocemod.2020.101738.Collections
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