中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
STUDY OF BENDING ANGLE RESIDUAL IONOSPHRIC ERROR IN REAL RO DATA

文献类型:会议论文

作者Liu, Congliang; Kirchengast, Gottfried; Sun, Yueqiang; Bai, Weihua; Du, Qifei; Wang, Xianyi; Meng, Xiangguang; Wang, Dongwei; Cai, Yuerong; Wu, Di
出版日期2016
会议名称36th IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
会议日期JUL 10-15, 2016
会议地点Beijing, PEOPLES R CHINA
关键词residual ionopheric error (RIE) bending angle GNSS RO
页码4171-4174
通讯作者Liu, CL (reprint author), Chinese Acad Sci, Natl Space Sci Ctr, Beijing Key Lab Space Environm Explorat, Beijing, Peoples R China.
英文摘要With the development of global navigation satellite system (GNSS) remote sensing, radio occultation (RO) has become an important atmospheric observation technique that mainly be used for numerical weather prediction (NWP) and global climate monitoring (GCM). However, residual ionopheric error (RIE) can still be significant after an ionospheric error elimination by linear combination of dual-frequency RO bending angles. Lots of quantification and analysis of RO bending angle RIEs has been conducted by using quasirealistic end-to-end simulations. In this study, the RIEs in RO observations have been investigated by comparative analysis of COSMIC RO measurements and ECMWF model data. The results illustrate that the RIE is a major source of the bending angle in lower mesosphere and upper stratosphere, and its bias has a clear negative tendency that in line with our empirical studies based on simulation RO data. This study helps to inform future RIE mitigation schemes for ensuring benchmark quality stratospheric RO data.
收录类别CPCI
会议录2016 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS)
语种英语
ISSN号2153-6996
ISBN号978-1-5090-3332-4
源URL[http://ir.nssc.ac.cn/handle/122/5798]  
专题国家空间科学中心_空间环境部
推荐引用方式
GB/T 7714
Liu, Congliang,Kirchengast, Gottfried,Sun, Yueqiang,et al. STUDY OF BENDING ANGLE RESIDUAL IONOSPHRIC ERROR IN REAL RO DATA[C]. 见:36th IEEE International Geoscience and Remote Sensing Symposium (IGARSS). Beijing, PEOPLES R CHINA. JUL 10-15, 2016.

入库方式: OAI收割

来源:国家空间科学中心

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