ASSIMILATION OF GNSS-R DELAY-DOPPLER MAPS INTO WEATHER MODELS

被引：0
|
作者：
Huang, Feixiong [1 ]
Garrison, James L. [1 ]
Leidner, S. Mark [2 ]
Annane, Bachir [3 ]
Grieco, Giuseppe [4 ]
Stoffelen, Ad [4 ]
Hoffman, Ross N. [2 ]
机构：
[1] Purdue Univ, W Lafayette, IN 47907 USA
[2] Atmospher & Environm Res, Lexington, MA USA
[3] Cooperat Inst Marine & Atmospher Studies, Miami, FL USA
[4] Royal Netherlands Meteorol Inst, De Bilt, Netherlands
来源：
IGARSS 2020 - 2020 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM | 2020年
关键词：
GPS; GNSS-R; DDM; ocean wind; data assimilation; NWP; SCATTERING;
D O I：
10.1109/IGARSS39084.2020.9324128
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Global Navigation Satellite System Reflectometry (GNSS-R) observations from the Cyclone Global Navigation Satellite System (CYGNSS) mission are expected to improve numerical weather prediction (NWP) models. Level 1 GNSS-R observables, delay-Doppler maps (DDMs), contain information that is lost in producing the Level 2 wind speed retrievals at the specular point. DDMs could, therefore, prove to be a better observable for data assimilation. In this study, assimilation of GNSS-R DDMs into both global and regional NWP models is demonstrated. In the global case, DDM assimilation shows improvements on the European Centre for Medium-Range Weather Forecasts (ECMWF) background for one month of data. In the regional case, DDM assimilation shows its impact on the hurricane structure and intensity. Results using a two-dimensional variation analysis method (VAM) are presented. A plan for an Observation System Experiment (OSE) experiment is proposed.
引用
收藏
页码：5313 / 5316
页数：4
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