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Nedjeljka Žagar, Koji Terasaki, and Hiroshi L. Tanaka


This paper deals with the large-scale inertio-gravity (IG) wave energy in the operational ECMWF analyses in July 2007. Energy percentages of the IG waves obtained from the standard-pressure-level data are compared to those derived from various discretizations of the model-level data. The results show a small albeit systematic increase of the IG energy percentage as the vertical level density increases from the standard-pressure levels toward the model-level density; the small relative change is explained by the sufficient vertical resolution to resolve the large-scale IG waves in the tropics that make the majority of the global IG energy on large scales. A relatively larger increase of the IG energy is obtained when the mesospheric model levels are included; however, the analyses at these levels in July 2007 are less reliable. Furthermore, two numerical methods for the normal-mode function (NMF) decomposition are shown to provide similar results. The decomposition of atmospheric analyses into the NMF series is proposed as a tool to analyze the spatial and temporal variations of the large-scale equatorial waves and their role in global energetics.

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Shunji Kotsuki, Kenta Kurosawa, Shigenori Otsuka, Koji Terasaki, and Takemasa Miyoshi


Over the past few decades, precipitation forecasts by numerical weather prediction (NWP) models have been remarkably improved. Yet, precipitation nowcasting based on spatiotemporal extrapolation tends to provide a better precipitation forecast at shorter lead times with much less computation. Therefore, merging the precipitation forecasts from the NWP and extrapolation systems would be a viable approach to quantitative precipitation forecast (QPF). Although the optimal weights between the NWP and extrapolation systems are usually defined as a global constant, the weights would vary in space, particularly for global QPF. This study proposes a method to find the optimal weights at each location using the local threat score (LTS), a spatially localized version of the threat score. We test the locally optimal weighting with a global NWP system composed of the local ensemble transform Kalman filter and the Nonhydrostatic Icosahedral Atmospheric Model (NICAM-LETKF). For the extrapolation system, the RIKEN’s global precipitation nowcasting system called GSMaP_RNC is used. GSMaP_RNC extrapolates precipitation patterns from the Japan Aerospace Exploration Agency (JAXA)’s Global Satellite Mapping of Precipitation (GSMaP). The benefit of merging in global precipitation forecast lasts longer compared to regional precipitation forecast. The results show that the locally optimal weighting is beneficial.

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Takumi Honda, Takemasa Miyoshi, Guo-Yuan Lien, Seiya Nishizawa, Ryuji Yoshida, Sachiho A. Adachi, Koji Terasaki, Kozo Okamoto, Hirofumi Tomita, and Kotaro Bessho


Japan’s new geostationary satellite Himawari-8, the first of a series of the third-generation geostationary meteorological satellites including GOES-16, has been operational since July 2015. Himawari-8 produces high-resolution observations with 16 frequency bands every 10 min for full disk, and every 2.5 min for local regions. This study aims to assimilate all-sky every-10-min infrared (IR) radiances from Himawari-8 with a regional numerical weather prediction model and to investigate its impact on real-world tropical cyclone (TC) analyses and forecasts for the first time. The results show that the assimilation of Himawari-8 IR radiances improves the analyzed TC structure in both inner-core and outer-rainband regions. The TC intensity forecasts are also improved due to Himawari-8 data because of the improved TC structure analysis.

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