Skip to main content

Testing Climate Models Using Infrared Spectra and GNSS Radio Occultation

  • Chapter
  • First Online:
  • 614 Accesses

Abstract

The Climate Absolute Radiance and Refractivity Observatory will be a climate benchmarking mission intended to include instruments for measuring Earth’s atmospheric refractivity by GNSS radio occultation (RO), high spectral resolution thermal infrared spectra emitted from the Earth, and the spectrally resolved reflected shortwave spectrum. Climate benchmarking is necessary to establish a record that can be used to test climate models according to their predictive capability because other attempts at establishing trustworthy timeseries of satellite data have not been particularly successful. We have investigated how GNSS RO measurements and thermal infrared spectra can be used to test models’ predictive capability. GNSS RO provides a constraint on the transient sensitivity of the climate system. Infrared radiance spectra can quantify the individual longwave feedbacks of the climate system, including cloud-longwave feedbacks when used in conjunction with GNSS RO. At present, studies are limited to clear sky infrared radiation, so the next research steps should include cloudy sky infrared simulations and reflected shortwave simulations.

This is a preview of subscription content, log in via an institution.

References

  • Allen M, Gillett N, Kettleborough J, Hegerl G, Schnur R, Stott P, Boer G, Covey C, Delworth T, Jones G, Mitchell J, Barnett T (2006) Quantifying anthropogenic influence on recent near-surface temperature change. Surv Geophys 27:491–544

    Article  Google Scholar 

  • Bell T (1986) Theory of optimal weighting of data to detect climatic change. J Atmos Sci 43(16):1694–1710

    Article  Google Scholar 

  • Bony S, Colman R, Kattsov V, Allan R, Bretherton C, Dufresne J, Hall A, Hallegatte S, Holland M, Ingram W, Randall D, Soden B, Tselioudis G, Webb M (2006) How well do we understand and evaluate climate change feedback processes? J Climate 19(15):3445–3482

    Article  Google Scholar 

  • Cess R (1976) Climate change—Appraisal of atmospheric feedback mechanisms employing zonal climatology. J Atmos Sci 33(10):1831–1843

    Article  Google Scholar 

  • Colman R (2003) A comparison of climate feedbacks in general circulation models. Climate Dyn 20:865–873, doi:10.1007/s00382-003-0310-z

    Google Scholar 

  • Hasselmann K (1997) Multi-pattern fingerprint method for detection and attribution of climate change. Climate Dyn 13(9):601–611

    Article  Google Scholar 

  • Held I, Soden B (2000) Water vapor feedback and global warming. Ann Rev Energy Env 25:441–475

    Article  Google Scholar 

  • Huntingford C, Stott P, Allen M, Lambert F (2006) Incorporating model uncertainty into attribution of observed temperature change. Geophys Res Lett 33(L05710), doi:10.1029/2005GL024831

    Google Scholar 

  • Intergovernmental Panel on Climate Change (IPCC) (2000) Special Report on Emissions Scenarios. Cambridge University Press, Cambridge, UK

    Google Scholar 

  • Kirk-Davidoff D, Goody R, Anderson J (2005) Analysis of sampling errors for climate monitoring satellites. J Climate 18(6):810–822

    Article  Google Scholar 

  • Leroy S (1998) Detecting climate signals: Some bayesian aspects. J Climate 11(4):640–651

    Article  Google Scholar 

  • Leroy S, Anderson J, Dykema J (2006) Testing climate models using GPS radio occultation: A sensitivity analysis. J Geophys Res 111(D17105), doi:10.1029/2005JD006145

    Google Scholar 

  • Leroy S, Anderson J, Dykema J, Goody R (2008a) Testing climate models using thermal infrared spectra. J Climate 21(9):1863–1875, doi:10.1175/2007JCLI2061.1

    Google Scholar 

  • Leroy S, Anderson J, Ohring G (2008b) Climate signal detection times and constraints on climate benchmark accuracy requirements. J Climate 21(4):841–846

    Article  Google Scholar 

  • National Research Council, Committee on Earth Science and Applications from Space (2007) Earth Science and Applications from Space: National Imperatives for the Next Decade and Beyond. National Academies Press, Washington, DC

    Google Scholar 

  • North G, Kim K, Shen S, Hardin J (1995) Detection of forced climate signals: I. Filter theory. J Climate 8(3):401–408

    Article  Google Scholar 

  • Ohring G (ed) (2007) Achieving Satellite Instrument Calibration for Climate Change. National Oceanographic and Atmospheric Administration, Washington, DC, 155pp

    Google Scholar 

  • Soden B, Held I (2006) An assessment of climate feedbacks in coupled ocean-atmosphere models. J Climate 19(14):3354–3360

    Article  Google Scholar 

  • Wetherald R, Manabe S (1988) Cloud feedback processes in a general circulation model. J Atmos Sci 45(8):1397–1415

    Article  Google Scholar 

Download references

Acknowledgements

We acknowledge the modeling groups, the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and the WCRP’s Working Group on Coupled Modelling (WGCM) for their roles in making available the WCRP CMIP3 multi-model data set. Support of this data set is provided by the Office of Science, U.S. Department of Energy. This work was supported by grant ATM-0450288 of the U.S. National Science Foundation.

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Leroy, S., Dykema, J., Gero, P., Anderson, J. (2009). Testing Climate Models Using Infrared Spectra and GNSS Radio Occultation. In: Steiner, A., Pirscher, B., Foelsche, U., Kirchengast, G. (eds) New Horizons in Occultation Research. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00321-9_16

Download citation

Publish with us

Policies and ethics