Acquisition of the Wide Swath Significant Wave Height From HY-2C Through
Deep Learning
Abstract
The significant wave height (SWH) is of great importance in industries
such as ocean engineering, marine resource development, shipping and
transportation. Haiyang-2C (HY-2C), the 2nd operational satellite of
China’s marine dynamic exploration series, can provide all-weather,
all-day, global observations of wave height, wind, and temperature. In
this paper, a deep learning approach is applied to build a wide swath
model based on the SWH from the altimeter and the wind speed from the
scatterometer of HY-2C. Two validation sets, 1-month data at 6-minute
intervals and 1-day data with an interval of 10 s, are fed into the
trained model. Experiments indicate that the extending nadir SWH yields
a real-time wide swath grid product along track, which can be offered as
support for oceanographic study, and it is superior to take the swell
characteristics of ERA5 into account as the input of wide swath SWH
model. In conclusion, the verification results demonstrate the
effectiveness and feasibility of the wide swath SWH model.