Journal of Meteorological Research

, Volume 28, Issue 6, pp 1061–1074

Assimilation of global navigation satellite radio occultation observations in GRAPES: Operational implementation

Articles

DOI: 10.1007/s13351-014-4028-0

Cite this article as:
Liu, Y. & Xue, J. J Meteorol Res (2014) 28: 1061. doi:10.1007/s13351-014-4028-0

Abstract

This paper presents the design of an observation operator for assimilation of global navigation satellite system (GNSS) radio occultation (RO) refractivity and the related operational implementation strategy in the global GRAPES variational data assimilation system. A preliminary assessment of the RO data assimilation effect is performed. The results show that the RO data are one of the most important observation types in GRAPES, as they have a significant positive impact on the analysis and forecast at all ranges, especially in the Southern Hemisphere and the global stratosphere where in-situ measurements are lacking. The GRAPES model error cannot be controlled in the Southern Hemisphere without RO data being assimilated. In addition, it is found that the RO data play a key role in the stable running of the GRAPES global assimilation and forecast system. Even in a relatively simple global data assimilation experiment, in which only the conventional and RO data are assimilated, the system is able to run for more than nine months without drift compared with NCEP analyses. The analysis skills in both the Northern and Southern Hemispheres are still relatively comparable even after nine-month integration, especially in the stratosphere where the number of conventional observations decreases and RO observations with a uniform global coverage dominate gradually.

Key words

global navigation satellite system (GNSS) radiation occultation (RO) refractivity data assimilation GRAPES 

Copyright information

© The Chinese Meteorological Society and Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.Numerical Weather Prediction CenterChina Meteorology AdministrationBeijingChina
  2. 2.State Key Laboratory of Severe Weather, Chinese Academy of Meteorological SciencesChina Meteorology AdministrationBeijingChina

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