首页 | 本学科首页   官方微博 | 高级检索  
     检索      


Impact of FORMOSAT-3/COSMIC radio occultation data on the prediction of super cyclone Gonu (2007): a case study
Authors:S K A V Prasad Rao Anisetty  Ching-Yuang Huang  Shu-Ya Chen
Institution:1. Department of Atmospheric Sciences, National Central University, No. 300, Jhongda Rd., Jhongli City, Taoyuan County, 32001, Taiwan
2. GPS Science and Application Research Center, National Central University, Jhongli City, Taiwan
3. University Corporation for Atmospheric Research, Boulder, CO, USA
Abstract:This study aims to present an encouraging example of prediction of super cyclone Gonu over the northern Indian Ocean in 2007. A series of experiments are conducted using the advanced Weather Research and Forecasting model with three-dimensional variational method to assimilate GPS RO refractivity from FORMOSAT-3/COSMIC (hereafter referred as GPS) and radiosonde sounding (GTS) to highlight the relative impact of GPS RO data on model prediction. Significant differences in cyclone track and intensity prediction are exhibited in various experiments with and without cyclic assimilations. Both cold-start (non-cyclic) and hot-start (cyclic) runs with GPS RO data exhibit improvement on later track prediction compared to the control run without data assimilation. GPS experiment outperforms other experiments including GTS in track prediction with the smallest cross-track error. Sensitivity tests were also conducted to identify which GPS RO sounding gives more impact on track prediction. We found that the sounding closest to the cyclone exhibits the largest contribution to track prediction. Assimilation of the RO soundings in the vicinity of Gonu cyclone appears to modify the environmental conditions that result in a later development of a couplet of high and low pressure, leading to a positive impact on track prediction. Sensitivity experiments indicate that the initial information retrieved by GPS data at upper levels that produce colder temperature increments indeed contributes more improvement to track prediction.
Keywords:
本文献已被 SpringerLink 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号