Abstract's details
Wave Spectra from SWOT: Overview of the New Level 3 Wind Wave Product
Event: 2025 SWOT Science Team Meeting
Session: Oceanography: Wind and Waves
Presentation type: Poster
The new SWOT KaRIn Level-3 Wind Wave product (L3_LR_WIND_WAVE) is an innovative dataset that provides wave spectra and related wave parameters derived from 250-meter KaRIn sea surface heights (based on the Unsmoothed L3_LR_SSH product: https://doi.org/10.24400/527896/a01-2024.003). This product is built upon the methodology developed by Ardhuin et al. (2024).
In this presentation, we introduce the SWOT KaRIn Level-3 Wind Wave product to the scientific community, detailing its main features, including processing algorithms, spatial coverage, data structure, and preliminary validation. The wave spectra provided in the product resolve wavelengths longer than approximately 500 meters, with centimeter-level precision (Ardhuin et al., 2024). These long waves are rare in the open ocean and entirely absent in marginal seas, yet they are closely associated with extreme storm events and play a critical role in coastal dynamics.
The spectral estimates are computed as power spectral densities (PSD) of sea surface height anomalies (SSHA), using a Welch (1967) method. This involves dividing SSHA “boxes” into smaller overlapping tiles, which are averaged to reduce spectral noise. Multiple configurations of box and tile sizes are available, allowing users to select a balance between spectral noise, spectral resolution, and wavelength range appropriate for their application. The product also includes a “swell mask” that identifies coherent wave systems (wave partitions) along with their integrated parameters: significant wave height (H18), dominant wavelength (L18), and direction (phi18). A correction is applied to the spectrum using an approximation of the KaRIn transfer function. This correction assumes linear processing and does not yet include all possible instrument or processing artifacts.
In parallel, alternative wave spectra partitioning methods without any a priori are considered, with a specific focus on the capability to retrieve longest swell signatures. These swell “forerunners” can only be seen by Karin but can help reviewing swell inversion methods and limitations from other sensors (e.g. S1, SWIM) to improve the processing of such low energetic swell.
Finally, we present preliminary examples and a limited validation of this first version of the product. Early comparisons with independent datasets suggest that the derived wave spectra and parameters are generally consistent with observations and models under favorable conditions, especially when KaRIn noise is low. However, this validation is exploratory, and further assessment is needed to better characterize the product’s accuracy and guide algorithm improvements. We encourage the scientific community to contribute to this effort by providing feedback and participating in future validation work. Understanding the properties of long-wavelength ocean waves is crucial for improving global wave forecasts, quantifying their impacts on coastal infrastructure, and advancing research in ocean-atmosphere interactions and seismology.
In this presentation, we introduce the SWOT KaRIn Level-3 Wind Wave product to the scientific community, detailing its main features, including processing algorithms, spatial coverage, data structure, and preliminary validation. The wave spectra provided in the product resolve wavelengths longer than approximately 500 meters, with centimeter-level precision (Ardhuin et al., 2024). These long waves are rare in the open ocean and entirely absent in marginal seas, yet they are closely associated with extreme storm events and play a critical role in coastal dynamics.
The spectral estimates are computed as power spectral densities (PSD) of sea surface height anomalies (SSHA), using a Welch (1967) method. This involves dividing SSHA “boxes” into smaller overlapping tiles, which are averaged to reduce spectral noise. Multiple configurations of box and tile sizes are available, allowing users to select a balance between spectral noise, spectral resolution, and wavelength range appropriate for their application. The product also includes a “swell mask” that identifies coherent wave systems (wave partitions) along with their integrated parameters: significant wave height (H18), dominant wavelength (L18), and direction (phi18). A correction is applied to the spectrum using an approximation of the KaRIn transfer function. This correction assumes linear processing and does not yet include all possible instrument or processing artifacts.
In parallel, alternative wave spectra partitioning methods without any a priori are considered, with a specific focus on the capability to retrieve longest swell signatures. These swell “forerunners” can only be seen by Karin but can help reviewing swell inversion methods and limitations from other sensors (e.g. S1, SWIM) to improve the processing of such low energetic swell.
Finally, we present preliminary examples and a limited validation of this first version of the product. Early comparisons with independent datasets suggest that the derived wave spectra and parameters are generally consistent with observations and models under favorable conditions, especially when KaRIn noise is low. However, this validation is exploratory, and further assessment is needed to better characterize the product’s accuracy and guide algorithm improvements. We encourage the scientific community to contribute to this effort by providing feedback and participating in future validation work. Understanding the properties of long-wavelength ocean waves is crucial for improving global wave forecasts, quantifying their impacts on coastal infrastructure, and advancing research in ocean-atmosphere interactions and seismology.
Contribution: ST2025OS4-Wave_Spectra_from_SWOT__Overview_of_the_New_Level_3_Wind_Wave_Product.pdf (pdf, 800 ko)
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