Dear colleagues, I am very happy that this paper got accepted in PNAS:
The paper is not very well organized but it contains some important results:
- the spectra of swell forerunners (defined as those that exceed the peak period in the storm) have always the same shape that is close to f^17 for 0.5 fp < f < 0.9 fp , consistent with exact Snl calculations of energy transfer in the storm
- this spectral shape gives a distinctive d^-9 decay of the swell height away from the storm that is observed by SWOT
- The usual Pierson-Moscowitz and JONSWAP spectral shape are too broad at low frequencies, and not consistent with exact Snl calculation. (it is not in this paper but numerical models have the same problem unless they use an exact Snl calculation, for which I recommend you use the GQM method available in TOMAWAC or WAVEWATCH III (thanks to Michel Benoit).
- Storm “Eddie” (peaked on 21 December 2024 in the North Pacific) was the most severe storm of the past 10 years, with a measured Hs at 19.7 m +/- 0.3 m (the largest ever altimeter measurement) and a peak period at the location of max Hs of 20.2+/- 0.6 s. (by the way, we can follow that swell over 24,000 km, maybe a new record: SWOT-CALVAL )
- altimeters generally miss the peak of storms and make it difficult to estimate storm intensity from Hs alone. Using swells resolved in SWOT sea level data can probably provide a comprehensive and accurate census of all storms that have Hs > 16 m or so.
Future work will include revisiting the swell dissipation problem, now for longer periods (Tp > 18 s) and with much more accurate data, as well as linking the swell radiation pattern to the wave directional spectra in the storm. Work underway includes a detailed analysis of various trade-offs in numerical wave modelling to be able to reproduce these swell properties, and an analysis of swell attenuation across individual atolls and chains of islands (to be presented in Santander by Taina Postec).
More about extreme storms: YouTube animations of modeled long period energy and location of SWOT tracks: https://youtu.be/VeSV2cuiABk
