Investigate Deep Convections and their Environmental Factors in the MC and SCS by using CloudSat and ECMWF analysis

• Main Authors: Yi-Jing Wu, 吳宜靜
• Other Authors: Chian-Yi Liu
• Format: Others
• Language: en_US
• Published: 2019
• Online Access: http://ndltd.ncl.edu.tw/handle/a9k4bp

碩士 === 國立中央大學 === 遙測科技碩士學位學程 === 107 === Deep convection has great influence on the earth’s radiation budget and hydrologic cycle. South China Sea- Maritime Continent (SCS-MC) is one of the most convective areas in the world. Deep convection in this area interacts with multiscale weather/climate systems and has influence on global climate. However, it remains a great challenge for models to capture the timing, location, and intensity of deep convection. As a result, the aim of this study is to take the advantage of CloudSat and composite ECMWF reanalysis data to investigate general features of DCC and analyze ingredient elements for deep convection, including TPW, LTS, CAPE, T2m, SHF and LHF. The results suggest that deep convective cores (DCCs) feature apparent diurnal variation on geospatial distribution. Higher probabilities of DCC are on ocean and coastal region in daytime (~1330 LT), but there are more inland DCC in nighttime (~0130 LT). Generally, the occurrence of DCC in nighttime is higher than daytime. The thermodynamic condition in nighttime is not suitable for DCC development. Therefore, DCC in nighttime might be sustained from the other mechanism. On the other hand, vertical structure of DCC shows difference between daytime and nighttime. In the daytime, maximum echo (~20 dBZ) extends from 6 km to 14 km owing to strong convective updraft. In the nighttime, maximum echo extends from 6 km to 12 km only result from relative stable thermodynamic environment. The analysis of thermodynamic environmental factors in SCS and MC reveal the relationship to each individual factor. There are specific intervals of T2m and LTS that are favorable to DCC. TPW has positive correlation with DCC probability, while CAPE shows less sensitivity to DCC probability. The environment of SCS and MC are unstable all the time, so the increase of CAPE value has little impact on DCC probability. Over the SCS region, all the factors have sensitivity except CAPE. In the contrast, T2m, TPW and SHF have sensitivity to DCC in the MC region. In this study, thermodynamic factors for DCC development are investigated. We expect to have a combination and intercomparison for thermodynamic and dynamic factors and further analyze the life cycle of deep convection. We look forward to a better understanding of deep convection mechanism, and the results can provide a positive feedback to improve the simulation of cumulus cloud in NWP models.