50 / 2023-07-24 15:08:07

Accurate Mean Wave Period Retrieved from SWIM Instrument On-Board CFOSAT

CFOSAT, SWIM, Empirical Algorithm

The Surface Waves Investigation and Monitoring (SWIM) instrument onboard the China–France Oceanography Satellite (CFOSAT) can provide wave spectra using its off-nadir beams. Although SWIM shows a reasonable performance for capturing spectral peaks, the accuracy of mean wave periods (MWPs) computed directly from the SWIM spectra is not satisfying due to parasitic peaks induced by the high noise level of the spectra, especially at low frequencies. SWIM can also provide good-quality simultaneous nadir wind speed (U10) and significant wave height (SWH) like an altimeter. The MWP can also be estimated using a U10-SWH look-up table presented in previous studies. However, the accuracy of this method is also limited as the U10-SWH look-up table is only applicable for wind-sea-dominated conditions. The two MWP retrieval methods are independent of each other, and their error properties are complementary to each other. Therefore, this study further presents a merged MWP retrieval model combining the nadir U10-SWH and the MWP from the off-nadir spectrum of SWIM using a deep neural network. To train such a deep learning model, a large amount of “ground truths” of MWP, i.e., measurements from buoys, are needed to be collocated with the observations from SWIM. However, SWIM can only obtain ~400 collocations with open-ocean deep-water buoys per year using a typical 50-km collocation window due to its narrow swath. To solve this problem, a “dynamic collocation” method was used to increase the number of effective collocations between SWIM and buoys by enlarging the collocation window to 150 km with the help of a numerical wave model. This yielded a number of collocations of ~3000 per year. After training against some buoy data, the model reaches unprecedented accuracy for MWP retrievals from space-borne remote sensing, demonstrating the usefulness of SWIM in the studies of ocean waves.