Development of a surface assimilation scheme in a Variational Doppler Radar Analysis System for improving the model analysis and forecast skill

• Main Authors: I-Han Chen, 陳依涵
• Other Authors: Yu-Chieng Liou
• Format: Others
• Language: zh-TW
• Published: 2016
• Online Access: http://ndltd.ncl.edu.tw/handle/25238251607974230276

碩士 === 國立中央大學 === 大氣科學學系 === 104 === The purpose of this study is to implement a surface assimilation scheme to the Variational Doppler Radar Analysis System (VDRAS) for further improving the model analysis and forecast skill. Due to the lack of low-elevation radar observations caused by standard Plan Position Indicator (PPI) scans and/or beam-blockage, the accuracy of low level analysis after data assimilation process could be significantly reduced. An observation system simulation experiments (OSSE) and a real case study are conducted to investigate the feasibility of the new surface data assimilation scheme and how it impacts the convective system. Surface observations including rainwater mixing ratio, liquid water potential temperature and horizontal wind components are selected to be assimilated into VDRAS. The results show that assimilation of low level wind information significantly improves the analysis and forecast. Assimilation of only rain water mixing ratio has negative impact on the accuracy of the analysis fields. However, errors can be corrected by assimilating low level wind field. The vertical structure of the analysis field demonstrates that the modification of surface observation can be spread to higher levels through model dynamics and smoothness terms embedded in the cost function. Application in a real case indicates that this data assimilation scheme successfully retrieves the low level convergence line with reduction of the wind speed inland, and helps to recover the low level temperature structure.