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 The bad news No calibration No instrument drift Global coverage Kuo et al., 2005 The bad news Engeln, 2006 - processing

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 …

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

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. 1.06 K global 5 – 15 km CHAMP vs SACC This Study 1.79 K tropical LRT COSMIC vs COSMIC

RMS Temperature Error Boreal Spring RMS Temperature Error Number of Pairs

COSMIC, 2006.111 to 2007.149, Zonal Mean, Time Mean Confidence Intervals COSMIC, 2006.111 to 2007.149, 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

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

Mean and Confidence Interval 2006.221-2007.149 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)

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 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

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

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

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.