10:45 AM - 11:00 AM
[AAS10-07] Detection and Analysis of Line-shaped MCS Along the Baiu Front
★Invited Papers
Keywords:mesoscale meteorology, Line-shaped mesoscale convective system, radar data analysis
Band- or line-shaped mesoscale convective systems (LS-MCSs) are a significant weather phenomenon in Japan, often leading to localized heavy rainfall, particularly along the Baiu front. This study focuses on the LS-MCSs observed in Japan, extracting them and statistically analyzing the favorable environmental conditions. The precipitation features of these LS-MCSs are identified through a process that involves Binarization, cluster analyses, and principle component analyses using radar-based data. The internal structures of larger-scale LS-MCSs are then analyzed by combining accumulated precipitation data and Instantaneous radar images.
First, we analyzed larger-scale LS-MCSs along the Baiu front. The horizontal scale of the LS-MCSs is around 100-300 km. The LS-MCSs had been classified into Type-A, -B, and -C. Type-A clearly showed a line or band shape. Type-B and -C showed line- or band-shape only for the accumulated precipitation data but did not show in the instantaneous radar images. From a scientific viewpoint, the LS-MCSs should not be determined only by the accumulated precipitation data. Type-A was generated under more water vapor environments in the lower atmosphere and unstable vertical stratifications. Type-A was divided into Type-I and -II. Type-I showed mostly line shapes, which were classified into broken line or back-building types. Type-II showed a line shape on the upwind side and spread to the band shape on the downwind side. The LS-MCS consisted of internal small-scale MCSs. The orientation direction of the inner LS-MCSs had an orthogonal component to that of the outer LS-MCS. There are no significant differences in vertical stratifications between Type-I and -II. However, the orthogonal components of the low-level winds were significantly larger for Type-II than for Type-I. Therefore, the favorable conditions for the LS-MCSs depend on Types.
Second, small-scale LS-MCSs will be focused on identifying the back-building types, but the details are explained in the presentation. Linear structures are first identified using 3-hour accumulated precipitation and finally determined using radar images within the accumulation period. They are identified based on the overlap rate and direction differences of the LS-MCSs between accumulated precipitation and radar images. When the proportion of time that a linear structure is seen exceeds a threshold value, a small-scale LS-MCS is identified.
First, we analyzed larger-scale LS-MCSs along the Baiu front. The horizontal scale of the LS-MCSs is around 100-300 km. The LS-MCSs had been classified into Type-A, -B, and -C. Type-A clearly showed a line or band shape. Type-B and -C showed line- or band-shape only for the accumulated precipitation data but did not show in the instantaneous radar images. From a scientific viewpoint, the LS-MCSs should not be determined only by the accumulated precipitation data. Type-A was generated under more water vapor environments in the lower atmosphere and unstable vertical stratifications. Type-A was divided into Type-I and -II. Type-I showed mostly line shapes, which were classified into broken line or back-building types. Type-II showed a line shape on the upwind side and spread to the band shape on the downwind side. The LS-MCS consisted of internal small-scale MCSs. The orientation direction of the inner LS-MCSs had an orthogonal component to that of the outer LS-MCS. There are no significant differences in vertical stratifications between Type-I and -II. However, the orthogonal components of the low-level winds were significantly larger for Type-II than for Type-I. Therefore, the favorable conditions for the LS-MCSs depend on Types.
Second, small-scale LS-MCSs will be focused on identifying the back-building types, but the details are explained in the presentation. Linear structures are first identified using 3-hour accumulated precipitation and finally determined using radar images within the accumulation period. They are identified based on the overlap rate and direction differences of the LS-MCSs between accumulated precipitation and radar images. When the proportion of time that a linear structure is seen exceeds a threshold value, a small-scale LS-MCS is identified.