A Machine Learning-Based Method for Wind Fields Forecasting Utilizing GNSS Radio Occultation Data
Author:
Affiliation:
1. School of Civil and Resource Engineering, University of Science and Technology Beijing, Beijing, China
2. National Space Science Center, Chinese Academy of Sciences (NSSC/CAS), Beijing, China
Funder
Youth Cross Team Scientific Research Project of the Chinese Academy of Sciences
National Natural Science Foundation of China
Feng Yun 3 (FY-3) Global Navigation Satellite System Occultation Sounder (GNOS and GNOS II) Development and Manufacture Project led by the National Space Science Center, Chinese Academy of Sciences
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science
Link
http://xplorestaging.ieee.org/ielx7/6287639/9668973/09736142.pdf?arnumber=9736142
Reference58 articles.
1. Global climatology of planetary boundary layer top obtained from multi-satellite GPS RO observations
2. A robust method to determine global distribution of atmospheric boundary layer top from COSMIC GPS RO measurements
3. Assimilation of global navigation satellite radio occultation observations in GRAPES: Operational implementation
4. Improving capabilities of broadband differential satellite navigation systems via radio occultation technology
5. Analysis of the temporal-spatial distribution of ionosphere scale height based on COSMIC occultation data
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