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. The
altimeter can only measure the nadir wave height and other information,
and the scatterometer can obtain the wind field with a wide swath. In
this paper, a deep learning approach is applied to produce a wide swath
SWH data through the wind field from the scatterometer and the nadir
wave height from altimeter. 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.