GPS Solutions

, Volume 12, Issue 4, pp 227–235 | Cite as

Variational data assimilation for deriving global climate analyses from GNSS radio occultation data

Review Article
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Abstract

A comprehensive global navigation satellite system (GNSS) based radio occultation (RO) data set is available for meteorology and climate applications since the start of GNSS RO measurements aboard the CHAllenging Mini-satellite Payload (CHAMP) satellite in February 2001. Global coverage, all-weather capability, long-term stability and accuracy not only makes this innovative use of GNSS signals a valuable supplement to the data set assimilated into numerical weather prediction (NWP) systems but also an excellent candidate for global climate monitoring. We present a 3D variational data assimilation (3D-Var) scheme developed to derive consistent global analysis fields of temperature, specific humidity, and surface pressure from GNSS RO data. The system is based on the assimilation of RO data within 6 h time windows into European Centre for Medium-Range Weather Forecasts (ECMWF) short-term (24 h, 30 h) forecasts, to derive climatologic monthly mean fields. July 2003 was used as a test-bed for assessing the system’s performance. The results show good agreement with climatologies derived from RO data only and recent NWP impact studies. These findings are encouraging for future developments to apply the approach for longer term climatologic analyses, validation of other data sets, and atmospheric variability studies.

Keywords

GPS GNSS Radio occultation Climatology Champ Climate change Climate variability Climate monitoring Climate maps Variational optimization Assimilation 3D-Var Data fusion Recursive filters Atmospheric studies 

Notes

Acknowledgments

The authors thank U. Foelsche, A. Gobiet, and M. Borsche (WegCenter, University. of Graz) for providing processed CHAMP profiles, A.K. Steiner (WegCenter) for discussions on CHAMP error characteristics, GFZ Potsdam (Germany) for the basic CHAMP phase delay data, and M. Fisher (ECWMF Reading) for providing ECMWF analysis error characteristics. S.B. Healy (ECMWF), A. von Engeln and C. Marquardt (EUMETSAT Darmstadt), and X.-Y. Huang (NCAR Boulder) are thanked for providing important stimuli for some parts of the work. A. Löscher received financial support from the START research award of G. Kirchengast funded under Program No. Y103-N03 of the Austrian Science Fund.

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Copyright information

© Springer-Verlag 2008

Authors and Affiliations

  1. 1.European Space Agency/European Space Research and Technology Centre (ESA/ESTEC)NoordwijkThe Netherlands
  2. 2.Wegener Center for Climate and Global Change (WegCenter), Institute for Geophysics, Astrophysics, and Meteorology (IGAM)University of GrazGrazAustria
  3. 3.EOP-SF, ESTECNoordwijkThe Netherlands

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