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.