The mesoscale heavy rainfall, “Senjo-Kousuitai” (SK), often causes severe disasters. This study utilizes a regional reanalysis dataset for Japan (RRJ-Conv; hourly data from 1976 to 2020 with a horizontal resolution of 5 km) to extract and analyze SK events across Japan and its surrounding area. By applying an objective extraction method, we identified 6760 SK events. They are mostly oriented southwest–northeast or west–east and more frequently appear between June and October and in the morning. These characteristics of their occurrences agree with those in observations. While RRJ-Conv does not reproduce all observed SK events, the vast number of SK samples is useful for statistical analysis of their characteristics and environmental conditions. The present study demonstrates that the SK orientations have the strongest correlation with wind directions at 600 hPa with a slight clockwise deviation from the wind direction at this altitude. The environmental winds exhibit veering, whose magnitude decreases after onsets of SK.

 This study statistically investigated the occurrence environment of the Muroto Line, a south–north oriented orographic quasi-stationary convective band (QSCB) that appears from the Muroto Peninsula in the eastern part of Shikoku, Japan. We objectively identified the Muroto Lines that occurred between 2004 and 2022. We focused on cases dominated by relatively shallow (Low-top case, 12 cases) and deep convective clouds (High-top case, 6 cases) and compared their occurrence environments. The results revealed similarities and differences in the occurrence environments of orographic QSCBs at different convective cloud depths.

 In all cases, tropical cyclones (TCs) were located within 1500 km west of the Muroto Lines. The Low-top cases occurred between the TC and the North Pacific Subtropical High (NPSH), which was favorable for strong southerly geostrophic winds, whereas the peripheral flow of the NPSH prevailed in Shikoku during the High-top cases. In both types, horizontal wind direction ranged from east-southeasterly to south-southeasterly near the surface and southerly above 1.5 km in height, with warm-moist and conditionally unstable thermodynamic environment. Compared to the High-top cases, the Low-top cases occurred under less conditionally unstable atmosphere, higher low- and mid-level wind speeds, larger low-level water vapor flux, and stronger vertical wind shear.

This study introduces an object-based approach for assessing the prediction accuracy of quasi-stationary band-shaped precipitation systems (QSBPSs), known as “Senjo-Kousuitai.” Unlike a conventional grid-based verification approach, the proposed method integrates the unique characteristics of QSBPSs, including their shape, size, and duration, to provide a comprehensive evaluation of forecast accuracy. Quantitative prediction verification was performed by analyzing the features of QSBPSs based on the error between the observation and numerical weather prediction using the operational forecast model. The proposed approach was applied to Japan and its surrounding areas from June to September 2024, during which 41 QSBPSs cases were identified based on observational data. A total of 157 QSBPSs cases, including multiple forecasts of the same observed events, were detected using the local forecast model operated by the Japan Meteorological Agency with a 2 km horizontal resolution and 18-hour forecasts eight times daily. The proposed approach was applied to these observed and predicted cases to evaluate prediction accuracy. In addition, a new index, the “SCS: Senjo-Kousuitai (QSBPSs) Composite Score,” was introduced to evaluate forecast performance across the entire period. The preliminary results obtained by applying this method indicate its effectiveness in quantitatively assessing the accuracy of numerical weather predictions for QSBPSs.