1 / 21

Revisiting Ocean Warming Rates

Revisiting Ocean Warming Rates. Susan Wijffels CSIRO Marine and Atmospheric Research with contributions from Catia Domingues, Ann Thresher, Neil White, John Church, Paul Barker, Achuo Rao, Peter Gleckler, Ken Ridgway Thanks to Bruce Ingleby and Matt Palmer for access to EN3.

dyanne
Download Presentation

Revisiting Ocean Warming Rates

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Revisiting Ocean Warming Rates Susan Wijffels CSIRO Marine and Atmospheric Research with contributions from Catia Domingues, Ann Thresher, Neil White, John Church, Paul Barker, Achuo Rao, Peter Gleckler, Ken Ridgway Thanks to Bruce Ingleby and Matt Palmer for access to EN3

  2. Contribution to Global Mean Sea Level (GMSL) XBT Fall-rate workshop, Miami, 2008

  3. Comparison of IPCC AR4 Climate Models with and without Volcanic Forcing with Observational Estimates Even with volcanic forcing, decadal model variability is less than in observational estimates. XBT Fall-rate workshop, Miami, 2008

  4. - Sparse observations- Changing coverage- Changing mix of platforms XBT’s Research Vessels Argo XBT Fall-rate workshop, Miami, 2008

  5. The Changing Ocean Observing System Latitude Year Technology changes and bias issues are now being recognised – - Gouretski and Koltermann, 2007: warm bias in XBT’s - Lyman et al, 2007: ‘spurious recent ocean cooling’ XBT Fall-rate workshop, Miami, 2008

  6. Analysis based on ENSEMBLES EN3 • XBTs as clearly identified by WOD05 and GTSPP • All profiles returned to H95 fall-rate where fall-rate was ‘known’ • All unknown profiles assumed to be S65 and returned to H95 • Reference data set is bottles and CTDs XBT Fall-rate workshop, Miami, 2008

  7. Bias in XBT data compared to CTD/bottle data Difference of climatological fit for 1985 for two independent data sets: + local LOESS + spatial polynomials + temporal annual, semiannual sinusoids and linear 50 year trend XBT Fall-rate workshop, Miami, 2008

  8. Global and Basin Temperature Bias XBT Fall-rate workshop, Miami, 2008

  9. XBT ‘warm bias’ is actually an overestimation of depth XBT Fall-rate workshop, Miami, 2008

  10. But the bias changes in time! Is this hopeless? Gouretski and Koltermann, 2007 XBT Fall-rate workshop, Miami, 2008

  11. Depth Error for ‘shallow XBTs’ XBT Fall-rate workshop, Miami, 2008

  12. Depth Error for Deep XBTs XBT Fall-rate workshop, Miami, 2008

  13. A correction is possible as a fraction of depth Time-variable bias arises from small changes at the XBT factory affecting the speed at which an XBT falls through the water 80% of XBT’s deployed are manufactured by one company: Sippican Lockheed Martin, USA. XBT Fall-rate workshop, Miami, 2008

  14. Corroboration? Altimetric Pseudo-profiles XBT Fall-rate workshop, Miami, 2008

  15. Comparison with archive results XBT Fall-rate workshop, Miami, 2008

  16. Comparison with in situ measurements depth = A*time + B*time^2 where time is in seconds XBT Fall-rate workshop, Miami, 2008

  17. (5-yr run. mean) Comparison with Previous Observational Estimates Higher rate of rise during 1961-2001. Magnitude of decadal variability about 5 mm, less than previous estimates. XBT Fall-rate workshop, Miami, 2008

  18. Comparison of IPCC AR4 Climate Models with Volcanic Forcing with Observational Estimates Variability in models that include volcanic forcing are in better agreement with our new observational estimate ... XBT Fall-rate workshop, Miami, 2008

  19. Conclusions • There is a time dependent warm bias in 70% of ocean temperature profiles, but it is largely correctable at a 2 year resolution • With the above correction and better spatial interpolation techniques, upper ocean temperature changes and associated thermosteric sea level rise are 50% larger than past estimates • The new estimates agree better with models – removal of spurious decadal variability and the ‘volcano signal’ is now evident for the first time XBT Fall-rate workshop, Miami, 2008

  20. Future – more questions than answers • Challenging! • This idea needs to be confirmed – rework past CTD/XBT data sets • Revisit fall rate equation – early acceleration, acquisition delay, ???? • continue to exploit altimetry - is the basin divergence in deep XBTs after 2000 real or a meta-data problem? • Can we do better using ocean reanalyses – remove possible biasing of decadal signals into bias estimates (especially for regionally dominated data sets such as TSK probes • What to do about future fall-rate changes? Can we piggy back on CLIVAR/Carbon lines to ‘batch’ calibrate? But what is a batch? XBT Fall-rate workshop, Miami, 2008

  21. Contact Us Phone: 1300 363 400 or +61 3 9545 2176 Email: enquiries@csiro.au Web: www.csiro.au Thank you This work is part of the Australian Climate Change Science Program, supported by the Australian Greenhouse Office and CSIRO’s Wealth from Oceans Flagship. Susan Wijffels CSIRO Marine and Atmospheric Research Email: Susan.Wijffels@csiro.au XBT Fall-rate workshop, Miami, 2008

More Related