Atmospheric Motion Vectors Derived from an Infrared Window Channel of a Geostationary Satellite Using Particle Image Velocimetry

• Published in: Journal of applied meteorology and climatology 2019-02, Vol.58 (2), p.199-211
• Main Authors: Chuang, Wei-Liang, Chou, Chien-Ben, Chang, Kuang-An, Chang, Yu-Cheng, Chin, Hsin-Lung
• Format: Article
• Language: English
• Subjects: Accuracy; Algorithms; Atmosphere; Atmospheric circulation; Atmospheric motion; Bias; Carbon dioxide; Civil engineering; Fluid mechanics; Fluids; Height; Infrared imagery; Infrared windows; Interrogation; Kalman filters; Meteorological satellites; Methods; Particle image velocimetry; Pattern recognition; Radiosondes; Satellite imagery; Satellites; Spatial discrimination; Spatial resolution; Typhoons; Vectors; Velocity; Velocity measurement; Weather; Weather forecasting; Wind; Wind fields; Wind speed
• ISSN: 1558-8424; 1558-8432
• DOI: 10.1175/JAMC-D-18-0105.1

As the new-generation geostationary satellite Himawari-8 provides a greater frequency and more observation channels than its predecessor, the Multifunctional Transport Satellite series (e.g., MTSAT-2), an opportunity arises to generate atmospheric motion vectors (AMVs) with an increased accuracy and extensive distribution over eastern Asia. In this work AMVs were derived from consecutive images of an infrared-window channel (IR1) of the Himawari-8 satellite using particle image velocimetry (PIV) based on the theory of cross-correlation schemes. A multipass scheme and an adaptive interrogation scheme were also employed to increase spatial resolution and accuracy. For height assignment, an infrared-window method was applied for opaque cloud, while an H2O-intercept method was employed for semitransparent cloud. Validation was conducted by comparing the PIV-derived AMVs with wind fields obtained from NWP analysis, radiosonde observations, and the operational system from the Meteorological Satellite Center (MSC) of the Japan Meteorological Agency (JMA) or JMA/MSC. The comparison of wind velocity maps with the NWP data shows that the PIV-derived AMVs are capable of quantitatively depicting full-field wind field maps and strong jets in atmospheric circulation. Through comparisons with radiosonde observations, the root-mean-square error and wind speed bias (4.29 and −1.05 m s−1) of the PIV-derived AMVs are comparable to, although slightly greater than, that of the NWP data (3.88 and −0.26 m s−1). Based on comparison between the PIV-derived AMVs and wind fields obtained from the JMA/MSC operational system, the PIV-derived AMVs are again comparable, producing a slightly lower error but a larger wind speed bias (−1.05 vs 0.20 m s−1). This also implies that a better height assignment algorithm is necessary.