Analysis of Precipitation Systems By Using MP-PAWR

Multi-parameter phased array weather radar (MP-PAWR), which was developed in 2018, is available to observe 3-dimensional observations within 30 s. Therefore MP-PAWR will allow analysis of the wind field (dual-Doppler analysis without time gap) and estimation of precipitation particle types in the 3D structure of rapidly changing cumulus clouds, as well as Velocity Azimuth Display (VAD) with various elevation angles, and continuous vertical pointing data. In the study, we demonstrate the analysis results of isolated cumulus clouds and relatively large precipitation systems associated with typhoons.

For the former, the objective is to provide a more detailed structural characterization of the internal structure of isolated cumulus clouds during the life cycle aiming to understand the fundamental processes of cumulonimbus. The analysis cases were six isolated cumulus clouds observed in Tokyo on August 2, 2018 from 3:00 p.m. to 5:00 p.m. (hereafter referred to as Cases 1-6), with Cases 3-6 occurring continuously over a narrow area of approximately 7 km x 7 km, and Cases 1 and 4 having heavier precipitation at the ground than the other cases. The time variation of the precipitation cores (area of >30 dBZ) was compared, and the precipitation cores in Cases 1 and 4 existed longer than those in the other cases. Hydrometeor type classification using MP-PAWR and temperature data from sounding data showed that wet snow appeared at 4-5 km altitude in the early stage of the cloud, followed by wet snow in the upper layers, wet hail in the middle layers, and rain in the middle and lower layers, with an increasing trend. The volume of rain and drizzle increased as the echo top altitude decreased. In addition, single Doppler analysis was performed using Doppler velocity data, focusing on the low-level divergence. The results showed that strong divergence appeared near the surface as the strongest echo region approaching to the ground in Cases 1 and 4, whereas strong divergence occurred when the precipitation initiation at the ground for other cases. In addition, Case 4 occurred south of the strong divergence in the lower layer of Case 3 and Case 5 occurred north of the strong divergence in the lower layer of Case 4, suggesting that the divergence in the lower layers of the previous cases may have contributed to the occurrence of Cases 3 through 5, respectively. In addition, the three-dimensional wind velocity field was estimated by dual Doppler analysis of PAWR (owned by JRC company) and MP-PAWR, and the temporal changes in the vertical air motion during the life cycle were compared, showing differences in the trends of the vertical air motion in the middle layer during the early stages and in the upper and middle layers from development to dissipating stage. This comparison of several cases suggests that there may be several different patterns of wind field within cumulus clouds and associated formation of precipitation particles during the life cycle of isolated cumulus clouds.

Estimation of the vertical air motion within precipitation clouds is important for understanding the development and maintenance processes of precipitation systems, and VAD method using multiple elevation angle, and vertical pointing Doppler velocity data from MP-PAWR is important method as well as the dual-Doppler analysis by MP-PAWR and PAWR. Here, we analyze a stratiform and convective precipitation system associated with a typhoon, which was observed by MP-PAWR from July 27 to 29, 2018. In order to estimate the vertical air motion from vertical pointing Doppler velocity observations, the information of the fall velocity of precipitation particles is necessary. On the other hand, the VAD method is effective for estimating vertical air motion from divergence if we use low elevation angle data because the effect of fall velocity can be negligible and it can be used to evaluate vertical velocity in the lower altitude, but a large observation radius is required to estimate to high altitudes. The VAD method using a high elevation angle is expected to calculate vertical air motion that can be compared with vertical pointing data, but estimation of the fall velocity is also the issue. In this analysis, vertical air motion can be estimated by the VAD method that gives wind direction, wind speed, and vertical component (divergence + vertical air motion + fall velocity), and the vertical air motion can be estimated iteratively by assuming the particle fall velocity. The vertical air motion estimated from the vertical pointing Doppler velocity cannot be obtained near the ground. Therefore, it is necessary to use the VAD method to compensate. We are currently analyzing the formation process of precipitation particles using the hydrometeor classification method using MP-PAWR data.