Determining Longwave Forcing and Feedback Using Infrared Spectra and GNSS Radio Occultation

Abstract The authors investigate whether combining a data type derived from radio occultation (RO) with the infrared spectral data in an optimal detection method improves the quantification of longwave radiative forcing and feedback. Signals derived from a doubled-CO2 experiment in a theoretical study are used. When the uncertainties in both data types are conservatively estimated, jointly detecting the feedbacks of tropospheric temperature and water vapor, stratospheric temperature, and high-level cloud from the two data types should reduce the mean errors by more than 50%. This improvement is achieved because the RO measurement helps disentangle the radiance signals that are ambiguous in the infrared spectrum. The result signifies the complementary information content in infrared spectral and radio occultation data types, which can be effectively combined in optimal detection to accurately quantify the longwave radiative forcing and feedback. The results herein show that the radiative forcing of CO2 and...

[1]  M. Webb,et al.  A quantitative performance assessment of cloud regimes in climate models , 2009 .

[2]  Gerald R. North,et al.  Testing climate models : An approach , 1998 .

[3]  Stephen S. Leroy,et al.  Measurement of geopotential heights by GPS radio occultation , 1997 .

[4]  R. Haskins,et al.  Radiance Covariance and Climate Models , 1999 .

[5]  Yi Huang,et al.  Separation of longwave climate feedbacks from spectral observations , 2010 .

[6]  Qiang Fu,et al.  A strict test in climate modeling with spectrally resolved radiances: GCM simulation versus AIRS observations , 2007 .

[7]  V. Ramaswamy,et al.  Evolution and Trend of the Outgoing Longwave Radiation Spectrum , 2009 .

[8]  kwang-yul kim,et al.  Detection of Forced Climate Signals. Part 1: Filter Theory , 1995 .

[9]  John A. Dykema,et al.  Testing climate models using GPS radio occultation: A sensitivity analysis , 2006 .

[10]  L. J. Cox.  Optical Properties of the Atmosphere , 1979 .

[11]  Gerald R. North,et al.  The Application of COSMIC Data to Global Change Research , 2000 .

[12]  James G. Anderson,et al.  Optimal Detection of Regional Trends Using Global Data , 2010 .

[13]  Brian J. Soden,et al.  An investigation of the sensitivity of the clear‐sky outgoing longwave radiation to atmospheric temperature and water vapor , 2007 .

[14]  Ernest K. Smith,et al.  The Constants in the Equation for Atmospheric Refractive Index at Radio Frequencies , 1953, Proceedings of the IRE.

[15]  Thomas L. Bell,et al.  Theory of Optimal Weighting of Data to Detect Climatic Change. , 1986 .

[16]  Klaus Hasselmann,et al.  Multi-pattern fingerprint method for detection and attribution of climate change , 1997 .

[17]  Clive D Rodgers,et al.  Inverse Methods for Atmospheric Sounding: Theory and Practice , 2000 .

[18]  S. Manabe,et al.  Cloud Feedback Processes in a General Circulation Model , 1988 .

[19]  Lawrence S. Bernstein,et al.  Very Narrow Band Model Calculations of Atmospheric Fluxes and Cooling Rates , 1996 .

[20]  S. Bony,et al.  How Well Do We Understand and Evaluate Climate Change Feedback Processes , 2006 .

[21]  J. Schofield,et al.  Observing Earth's atmosphere with radio occultation measurements using the Global Positioning System , 1997 .

[22]  M. Webb,et al.  The spectral signature of global warming , 1997 .

[23]  J. Kiehl.  Satellite Detection of Effects Due to Increased Atmospheric Carbon Dioxide , 1983, Science.

[24]  John A. Dykema,et al.  Testing Climate Models Using Thermal Infrared Spectra , 2008 .