Characteristics of Himawari-8 Rapid Scan Atmospheric Motion Vectors Utilized in Mesoscale Data Assimilation

Abstract

Rapid scan atmospheric motion vectors (RS-AMVs) were derived using an algorithm developed by the Meteorological Satellite Center of the Japan Meteorological Agency (JMA) from Himawari-8 rapid scan imagery over the area around Japan. They were computed every 10 min for seven different channels, namely, the visible channel (VIS), near infrared and infrared channels (IR), three water vapor absorption channels (WV), and CO2 absorption channel (CO2), from image triplets with time intervals of 2.5 min for VIS and 5 min for the other six channels. In June 2016, the amount of data was increased by more than 20 times compared to the number of routinely used AMVs. To exploit these high-resolution data in mesoscale data assimilation for the improvement of short-range forecasts, data verification, and assimilation experiments were conducted. The RS-AMVs were of sufficiently good quality for assimilation and consistent overall with winds from JMA’s mesoscale analyses, radiosonde, and wind profiler observations. Errors were slightly larger in WV than in VIS and IR channels. Significant negative biases relative to sonde winds were seen at high levels in VIS, IR, and CO2, whereas slightly positive biases were noticeable in WV at midto high levels. Data assimilation experiments with the JMA’s nonhydrostatic model based Variational Data Assimilation System (JNoVA) on a cold vortex event in June 2016 were conducted using RS-AMVs from seven channels. The wind forecasts improved slightly in early forecast hours before 12 hours in northern Japan, over which the vortex passed during the assimilation period. They also showed small improvements at low levels when averaged over the whole forecast period. The results varied slightly depending on the channels used for assimilation, which might be caused by different error characteristics of RS-AMVs in different channels. ©The Author(s) 2018. This is an open access article published by the Meteorological Society of Japan under a Creative Commons Attribution 4.0 International (CC BY 4.0) license (http://creativecommons.org/license/by/4.0). Corresponding author: Michiko Otsuka, Forecast Department, Meteorological Research Institute, 1-1 Nagamine, Tsukuba, Ibaraki 305-0052, Japan E-mail: motsuka@mri-jma.go.jp 1 Present affiliation: Numerical Prediction Division, Japan Meteorological Agency, Tokyo, Japan 2 Present affiliation: Meteorological Satellite Center, Japan Meteorological Agency, Kiyose, Japan J-stage Advance Published Date: 23 March 2018 Journal of the Meteorological Society of Japan, Vol. 96B, pp. 111−131, DOI:10.2151/jmsj.2018-034, 2018 Special Issue on Meteorology and Climate Change Studies by Using the Geostationary Meteorological Satellite Himawari-8 Journal of the Meteorological Society of Japan Vol. 96B 112