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

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Presentation transcript:

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, processing

RO Timeline 1995…… 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

RMS Temperature Error (K) RMS Temperature Error Boreal Winter, Tropics Rocken et al.2 – 3 Kglobalabove 10 kmGPSMET vs radiosondes Hajj et al.1.06 Kglobal5 – 15 kmCHAMP vs SACC This Study1.79 K tropicalLRTCOSMIC vs COSMIC Rocken et al. This study Hajj et al. (Shading = Contours)

RMS Temperature Error Number of Pairs Boreal Spring

Confidence Intervals COSMIC, to , 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 TemperatureGeopotential Height 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 T COSMIC - T CHAMP 95% Confidence Interval Number of Pairs Compare to -0.5 K decade -1 (Seidel) For tropics, trend in < 5 years (no overlap) compare to ~2000 pairs for 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 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, 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– 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