気象集誌. 第2輯
Online ISSN : 2186-9057
Print ISSN : 0026-1165
ISSN-L : 0026-1165

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Verification of Forecasted Three-Hour Accumulated Precipitation Associated with “Senjo-Kousuitai” from Very-Short-Range Forecasting Operated by the JMA
HATSUZUKA DaisukeKATO RyoheiSHIMIZU ShingoSHIMOSE Ken-ichi
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ジャーナル オープンアクセス 早期公開
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論文ID: 2022-052

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 In recent years, “senjo-kousuitai”, characterized as band-shaped areas of heavy rainfall, have frequently caused river floods and landslides in Japan. Preventing and mitigating such disasters requires skillful forecasts of accumulated rainfall for several hours with an adequate lead time. The immediate very-short-range forecast of precipitation (VSRF) provided by the Japan Meteorological Agency (JMA) is well suited to this purpose, representing a blended forecast of hourly accumulated precipitation for up to 6 h ahead based on extrapolation and numerical weather prediction. This study examined the predictability of the VSRF for 3-h accumulated precipitation associated with 21 senjo-kousuitai events that occurred in Kyushu in 2019 and 2020. Predictability was evaluated based on forecast accuracy at each forecast time (1-6 h) using categorical and neighborhood verification techniques. Overall, the VSRF product was useful for heavy rainfall areas of ≥ 80 mm (3h)−1 up to a forecast time of 2 h at the original grid spacing of 1 km, but with large uncertainty in the accuracy of the forecasts. After that forecast time, it was not possible to obtain a useful precipitation forecast for the threshold of ≥ 80 mm (3h)−1, even if displacement errors at municipal or larger scale (15-31 km) were tolerated. Further analysis showed that the VSRF is less skillful in the stage of senjo-kousuitai formation at shorter forecast times (1-2 h) owing to limitations of the extrapolation forecasts. The poor skill during this period affects the timing of both issuance of warnings and decision-making regarding evacuation, representing major challenges for future development of forecasting methods and systems for senjo-kousuitai.

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© The Author(s) 2022. 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.
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