Analysis of Using Different Microphysics Schemes for the Cloud-Resolving Ensemble forecasts during SoWMEX-IOP8

• Main Authors: Chin-Hung Chen, 陳勁宏
• Other Authors: Kao-Shen Chung
• Format: Others
• Language: en_US
• Published: 2018
• Online Access: http://ndltd.ncl.edu.tw/handle/5t2a3n

碩士 === 國立中央大學 === 大氣科學學系 === 106 === In this study, we aim to understand the effects of different microphysics (MP)schemes [including single- (SM) and double-moment (DM)] on the ensemble spread under the framework of ensemble forecasts in the cloud-resolving model. We first analyze the basic features of these schemes through the deterministic forecasts then using the ensemble method to focus on the comparison of the ensemble-based error structures and investigate the sensitivity of the initial conditions to different MP schemes. The simulation for the heavy rainfall event during the Southwest Monsoon Experiment on June 16, 2008 (SoWMEX-IOP8) is examined with the WRF model. In all ensemble experiments, the initial conditions are obtained from the regional data assimilation system (WRF-LETKF). Four different MP schemes were selected for analysis, including GCE, MOR, WSM6, and WDM6 schemes. Results show that the DM schemes (MOR, WDM6) do not necessarily produce a larger ensemble spread than the SM schemes (GCE, WSM6). Different MP schemes have great differences in the distribution of hydrometeors, especially with the icerelated variables. Results show that GCE has a relatively large spread in almost every variable. This is mainly because GCE has a relatively strong and variable vertical velocity associated with the efficient phase transition results in the spread of latent heat release increases and further affect the spread of larger-scale temperature and wind fields. The benefits of the DM scheme are only apparent when comparing similar MP schemes (WSM6, WDM6). Especially in the rainwater and cloud water, even if the two methods use similar ice processes, it seems that the spread caused by the DM treatment in the warm rain processes will further affect the spread of ice-related variables. Therefore, if the ensemble is established by the multi-MP method, the results of this study show that the combination of GCE and WDM6 schemes would be more effective in increasing the overall ensemble spread to represent the forecast error in different aspects. Finally, we found that the ice-related processes are handled very differently with different MP scheme developers and these difference will affect the pattern of latent heat release which in turn affect larger-scale temperature and wind fields.