Deriving overlapped cloud motion vectors based on geostationary
satellite and its application on monitoring Typhoon Mulan
Abstract
We present a novel Overlapped Cloud Motion Vectors (OCMVs) deriving
algorithm using the Himawari-8 satellite. A multi-layer Cloud Top
Heights (CTHs) retrieving model based on multi-spectral observed
radiances is constructed using neural networks to reduce the substantial
uncertainty of CMVs over multi-layer clouds. The retrieved CTHs are
assigned to upper ice and lower water cloud layers, then they are used
as respective tracers for deriving OCMVs based on an optical flow
algorithm. OCMVs reveal the asymmetric kinematic structure of Typhoon
Mulan, particularly in the typhoon’s inner-core. The vortex center of
lower water CMVs is significantly closer to the typhoon center than that
of the upper ice CMVs. Additionally, the direction of CMVs in the lower
inner-core show excellent agreement with dropsonde observations. This
marks the first time that a geostationary satellite successfully
captured the lower layer CMVs of typhoons, providing a valuable
reference for the typhoon center identification.