Quantitative precipitation estimation of tropical cyclone in Southern Thailand using radar based reflectivity and numerical modeling

Abstract

This study focused on the quantitative precipitation estimation (QPE) in case of tropical cyclone in southern Thailand by investigating the characteristics of rainstorm, Radar precipitation estimate based on Z-R relationship and the quantitative precipitation forecast (QPF) based on WRF numerical model. The tropical cyclone PABUK was selected as the case study of heavy rainfall during 3 to 5 January 2019 (D1, D2, and D3) where the total rainfall reached 150-300 mm. across 14 provinces of southern Thailand. The widespread heavy rain, flash floods and strong winds caused the power system outages, communication systems failures, while the surface meteorological stations were damaged and a lot of data were lost. However, the Songkhla's radar system could work and continuously collected the information all three days of the case study. The study concentrated on the strengths of weather radar system that has become g ht s reserved an important data source for mesoscale weather analysis and forecasting. Therefore, the Thunderstorm Identification and Tracking Analysis and Nowcasting (TITAN) was used to analysis the data set of radar-based reflectivity for investigating the rainstorm properties of tropical cyclone PABUK including 5 variables of rainstorm duration, rainstorm area, rainstorm base, rainstorm reflectivity, and rainstorm speed. Based on the properties and frequency distribution of 2,557 rainstorms in D1, D2, and D3, rainstorms in D2 and D3 when PABUK made landfall over southern Thailand showed a longer lifetime, higher reflectivity, and larger rain-cells as well as it was found efficient in terms of rainfall amount than in D1. In addition, the estimated rainfall using weather radar provided important information of the rainfall distribution for the analysis of the rainstorm as well. These analyses provided a context for interpreting the feasible rainfall estimation based on Z-R relationship during tropical cyclone PABUK that produced extreme floods in southern Thailand. The Z-R relationship in the form Z = 104R!.5 provided acceptable statistical indicators, making it to be appropriate for Radar QPE in the case study presented of tropical storm PABUK. The simulation of Radar QPE by estimated heavy rainfall using Z=104RI.5 was exhibited the rainfall intensity (mm/hr) covering the both sides (east and west) of southern Thailand including 11 provinces consistently with the storm movement during the period of case study (D1 to D3).As the results from QPF analysis by performed simulations provided by WRF model as NoDA and DA-Sounding, it was found that the case of DA-Sounding performed better agreement than NoDA method, according to the results from the comparison of point verification and precipitation pattern among the WRF forecast, Radar QPE and observation fields. Moreover, the predicted precipitation obtained from the initialization of the WRF simulation on the date before the occurrence of the tropical cyclone PABUK (3 January 2019) in both of NoDA and DA-Sounding provides more precise results than other initialized date of 1 and 2 January 2019. It is confirmed that the rather strong dependence of QPF on the initialized date and number of predictive hours. Finally, the important finding in this study was to optimize the spinup time in the case of 8-11 hours showed the best consistency of heavy rainfall in the case study of PABUK. This investigation of spinup time should be especially useful for establishing the initialization process of WRF model producing the most accurate delay in case of tropical cyclone in southern Thailand.