1. Can radio occultation be used to discern long-term tropopause trends?
Paul Staten and Thomas Reichler
University of Utah

2. Outline Brief RO overview
Describe precision of tropopause measurements
Discuss errors in day-to-day tropopause measurements
Demonstrate fitness of RO for tropopause climate studies

3. Radio Occultation How RO works The good news The bad news
No calibration
No instrument drift
Global coverage
Kuo et al., 2005
The bad news
Engeln, processing

4. CHAMP (Post Processed)
RO Timeline
Radiosondes
GPS/MET
CHAMP (Post Processed)
CHAMP
SAC-C
COSMIC …
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007 …

5. COSMIC Self Comparison
vs.
Image Courtesy Orbital Sciences Corporation
Pointwise comparison
Simulates a comparison between years

6. RMS Temperature Error (K)
Boreal Winter, Tropics
RMS Temperature Error (K)
Number of Pairs
Rocken et al.
Hajj et al.
This study
Rocken et al.
This study
Hajj et al.
Emphasize precision
Rocken et al. 2 – 3 K global above 10 km GPSMET vs radiosondes
(Shading = Contours)
Hajj et al K global 5 – 15 km CHAMP vs SACC
This Study 1.79 K tropical LRT COSMIC vs COSMIC

7. RMS Temperature Error Boreal Spring RMS Temperature Error
Number of Pairs

8. COSMIC, 2006.111 to 2007.149, Zonal Mean, Time Mean
Confidence Intervals
COSMIC, to , Zonal Mean, Time Mean
Temperature
Number of Pairs
Number of Pairs
Geopotential Height
3-degree bins
3-degree bins
48-degree bins
48-degree bins
11m
0.04K
Seidel et al., 2001: -0.5 K decade-1
Seidel et al., 2001: +20 m decade-1
Gettelman & Forster, 2001: +50 m decade-1*
> 0.04 K is significant
> 11 m is significant
* for CPT

9. COSMIC vs. CHAMP vs. Orbital Sciences Corporation
© GFZ-Potsdam, Germany

10. Mean and Confidence Interval
compare to ~2000 pairs for COSMIC
95% Confidence Interval
Number of Pairs
-0.05
Mean TCOSMIC - TCHAMP
0.14
Compare to -0.5 K decade-1 (Seidel)
For tropics, trend in < 5 years (no overlap)

11. Conclusions Radio occultation Provides an abundance of tropopause data
Allows precise characterization of tropopause across times scales
Can detect climate trends with confidence

12. Future Work Investigate processing effect
Validate against radiosonde data
Produce 12-year time series

13. Thank You.

14. Post – Processing Blue shows post processing
Boreal Fall
CHAMP (PP) – CHAMP
CHAMP (PP) – COSMIC
CHAMP - COSMIC
Blue shows post processing
Most bias is due to post processing

15. Boreal Winter, SH Subtropics
RMS Temperature Error
Boreal Winter, SH Subtropics
RMS Temperature Error
Number of Comparisons
Emphasize precision
Higher variability than in tropics
Steeper slope (~7m/s) than in tropics

16. Occultation Locations for COSMIC, 6 S/C, 6 Planes, 24 Hrs
COSMIC DISTRIBUTION
Occultation Locations for COSMIC, 6 S/C, 6 Planes, 24 Hrs
Illustration by Bill Schreiner, UCAR

17. References
Gettelman, A. and P. M. de F Forster (2002): A Climatology of the Tropical Tropopause Layer, JMSJ, Vol. 80,
Kuo, Y., C. Rocken, and R. Anthens (2005): Use of GPS radio occultation data for climate monitoring, 16th Conference on Climate Variability and Change, San Diego, CA, Amer. Meteor. Soc.
Rocken, C., et al. (1997): Analysis and validation of GPS/MET data in the neutral atmosphere, J. Geophys. Res., 102,
Seidel, D. J., R. J. Ross, J. K. Angell, and G. C. Reid (2001): Climatological characteristics of the tropical tropopause as revealed by radiosondes, J. Geophys. Res., 106, 7857– 7878.
von Engeln, A. (2006): A first test of climate monitoring with radio occultation instruments: Comparing two processing centers, Geophys. Res. Lett., 33, L22705, doi: /2006GL