Can radio occultation be used to discern

long-term tropopause trends?

Paul Staten and Thomas Reichler

University of Utah

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

Radio Occultation

• How RO works

• The good news– No calibration– No instrument drift– Global coverage– Kuo et al., 2005

• The bad news– Engeln, 2006 - processing

RO Timeline

1995… …1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

Radiosondes

GPS/MET

CHAMP (Post Processed)

COSMIC

SAC-C

CHAMP

COSMIC Self Comparison

vs.

Image Courtesy Orbital Sciences Corporation

• Pointwise comparison• Simulates a comparison between years

Rocken et al.Hajj et al.

This study

RMS Temperature Error (K)

RMS Temperature ErrorBoreal Winter, Tropics

Rocken et al. 2 – 3 K global above 10 km GPSMET vs radiosondesHajj et al. 1.06 K global 5 – 15 km CHAMP vs SACCThis Study 1.79 K tropical LRT COSMIC vs COSMIC

Rocken et al.This study

Hajj et al.

(Shading = Contours)

Number of Pairs

RMS Temperature Error

RMS Temperature Error Number of Pairs

Boreal Spring

Confidence IntervalsCOSMIC, 2006.111 to 2007.149, Zonal Mean, Time Mean

Seidel et al., 2001: -0.5 K decade-1 Seidel et al., 2001: +20 m decade-1

Gettelman & Forster, 2001: +50 m decade-1*

0.04K

> 0.04 K is significant > 11 m is significant

* for CPT

11m

Temperature Geopotential HeightNumber of Pairs Number of Pairs

3-degree bins

48-degree bins

3-degree bins

48-degree bins

COSMIC vs. CHAMP

vs.

© GFZ-Potsdam, GermanyOrbital Sciences Corporation

Mean and Confidence Interval

Mean TCOSMIC - TCHAMP

95% Confidence IntervalNumber of Pairs-0.05

0.14

• Compare to -0.5 K decade-1 (Seidel)

• For tropics, trend in < 5 years (no overlap)

2006.221-2007.149

compare to ~2000 pairsfor COSMIC

Conclusions

• Radio occultation– Provides an abundance of tropopause data– Allows precise characterization of tropopause

across times scales– Can detect climate trends with confidence

Future Work

• Investigate processing effect

• Validate against radiosonde data

• Produce 12-year time series

Thank You.

Post – Processing

CHAMP (PP) – CHAMP

CHAMP (PP) – COSMIC

CHAMP - COSMIC

• Blue shows post processing

• Most bias is due to post processing

Boreal Fall

RMS Temperature Error

RMS Temperature Error Number of Comparisons

• Higher variability than in tropics• Steeper slope (~7m/s) than in tropics

Boreal Winter, SH Subtropics

COSMIC DISTRIBUTION

Occultation Locations for COSMIC, 6 S/C, 6 Planes, 24 Hrs

Illustration by Bill Schreiner, UCAR

References

• Gettelman, A. and P. M. de F Forster (2002): A Climatology of the Tropical Tropopause Layer, JMSJ, Vol. 80, 911-924.

• 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, 29849-29866.

• 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:10.1029/2006GL027767.