An improved one-dimensional ocean wave description based on SWIM observations

Abstract. The one-dimensional ocean wave spectra (1D spectra) describing the total energy of the ocean waves are vital for providing ocean surface roughness information in remote sensing simulations. Most existing wave spectrum models deviate from real ocean surface descriptions due to limitations of observation methods and approximation in theories applied to generating them. In this research, the widely applied Goda and Elfouhaily spectra in their 1D form are compared with the remote sensing products from the Surface Waves Investigation and Monitoring instrument (SWIM) on-board the China France Oceanography Satellite (CFOSAT). Differences between models and the measurements are addressed, and the causes are analysed before concluded in terms of sea states. Then, a Combined spectrum (C spectrum) considering varied sea states is proposed as a closer model to the observations of the real sea, where parameterization of the spectral peak enhancement factor (γ) is achieved by the inverse wave age and wave steepness for multiple sea states. Then the specific values of the all-state sea are obtained from SWIM observations. The validation of the C spectrum is achieved by comparisons with SWIM measurements not utilized during the model establishment, and with buoy measurements. The difference index (DI) and the R-squared (R2), are calculated for evaluation of the results, indicating that the C spectrum demonstrates closer fitting to the SWIM and buoy measurements than both Goda and Elfouhaily spectra. The DI and R2 for the C spectrum are compared to the Goda spectrum, which is closer to SWIM measurements than E spectrum. Results suggest the C spectrum is suitable for providing information required for remote sensing applications.

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Publication Details

Journal
Atmospheric measurement techniques
Published
2025-11-06
DOI
https://doi.org/10.5194/amt-18-6329-2025
Primary Topic
Ocean Waves and Remote Sensing
Type
article
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article

An improved one-dimensional ocean wave description based on SWIM observations

Yihui Wang, Zhimin Dong, Xingou Xu
Atmospheric measurement techniques
Ocean Waves and Remote Sensing
article

An improved one-dimensional ocean wave description based on SWIM observations

Yihui Wang, Zhimin Dong, Xingou Xu
article en

Abstract

Abstract. The one-dimensional ocean wave spectra (1D spectra) describing the total energy of the ocean waves are vital for providing ocean surface roughness information in remote sensing simulations. Most existing wave spectrum models deviate from real ocean surface descriptions due to limitations of observation methods and approximation in theories applied to generating them. In this research, the widely applied Goda and Elfouhaily spectra in their 1D form are compared with the remote sensing products from the Surface Waves Investigation and Monitoring instrument (SWIM) on-board the China France Oceanography Satellite (CFOSAT). Differences between models and the measurements are addressed, and the causes are analysed before concluded in terms of sea states. Then, a Combined spectrum (C spectrum) considering varied sea states is proposed as a closer model to the observations of the real sea, where parameterization of the spectral peak enhancement factor (γ) is achieved by the inverse wave age and wave steepness for multiple sea states. Then the specific values of the all-state sea are obtained from SWIM observations. The validation of the C spectrum is achieved by comparisons with SWIM measurements not utilized during the model establishment, and with buoy measurements. The difference index (DI) and the R-squared (R2), are calculated for evaluation of the results, indicating that the C spectrum demonstrates closer fitting to the SWIM and buoy measurements than both Goda and Elfouhaily spectra. The DI and R2 for the C spectrum are compared to the Goda spectrum, which is closer to SWIM measurements than E spectrum. Results suggest the C spectrum is suitable for providing information required for remote sensing applications.

Atmospheric measurement techniquesVol. 18(21)
Openalex Percentile: Top 67%
Ocean Waves and Remote Sensing
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