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Observational determination of surface radiative forcing by CO2 from 2000 to 2010


The climatic impact of CO2 and other greenhouse gases is usually quantified in terms of radiative forcing1, calculated as the difference between estimates of the Earth’s radiation field from pre-industrial and present-day concentrations of these gases. Radiative transfer models calculate that the increase in CO2 since 1750 corresponds to a global annual-mean radiative forcing at the tropopause of 1.82 ± 0.19 W m−2 (ref. 2). However, despite widespread scientific discussion and modelling of the climate impacts of well-mixed greenhouse gases, there is little direct observational evidence of the radiative impact of increasing atmospheric CO2. Here we present observationally based evidence of clear-sky CO2 surface radiative forcing that is directly attributable to the increase, between 2000 and 2010, of 22 parts per million atmospheric CO2. The time series of this forcing at the two locations—the Southern Great Plains and the North Slope of Alaska—are derived from Atmospheric Emitted Radiance Interferometer spectra3 together with ancillary measurements and thoroughly corroborated radiative transfer calculations4. The time series both show statistically significant trends of 0.2 W m−2 per decade (with respective uncertainties of ±0.06 W m−2 per decade and ±0.07 W m−2 per decade) and have seasonal ranges of 0.1–0.2 W m−2. This is approximately ten per cent of the trend in downwelling longwave radiation5,6,7. These results confirm theoretical predictions of the atmospheric greenhouse effect due to anthropogenic emissions, and provide empirical evidence of how rising CO2 levels, mediated by temporal variations due to photosynthesis and respiration, are affecting the surface energy balance.

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Figure 1: AERI spectrum and residual features.
Figure 2: Measured and modelled spectral trends for 2000–2010.
Figure 3: Distributions of residual rms values in 2010.
Figure 4: Time-series of surface forcing.


  1. Ramaswamy, V. et al. in Climate Change 2001: The Scientific Basis. Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change (eds Houghton, J. T. et al.) 349–416 (Cambridge Univ. Press, 2001)

  2. Myhre, G. et al. Anthropogenic and natural radiative forcing. In Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (eds Stocker, T. F. et al.) 661 (Cambridge Univ. Press, 2013)

  3. Knuteson, R. O. et al. Atmospheric emitted radiance interferometer. Part I: Instrument design. J. Atmos. Ocean. Technol. 21, 1763–1776 (2004)

    ADS  Article  Google Scholar 

  4. Oreopoulos, L. et al. The continual intercomparison of radiation codes: results from phase I. J. Geophys. Res. 117, D06118 (2012)

    ADS  Article  Google Scholar 

  5. Prata, F. The climatological record of clear-sky longwave radiation at the Earth's surface: evidence for water vapour feedback? Int. J. Remote Sens. 29, 5247–5263 (2008)

    ADS  Article  Google Scholar 

  6. Wild, M., Grieser, J. & Schär, C. Combined surface solar brightening and increasing greenhouse effect support recent intensification of the global land-based hydrological cycle. Geophys. Res. Lett. 35, L17706 (2008)

    ADS  Article  Google Scholar 

  7. Wang, K. & Liang, S. Global atmospheric downward longwave radiation over land surface under all-sky conditions from 1973 to 2008. J. Geophys. Res. 114, D19101 (2009)

    ADS  Article  Google Scholar 

  8. Harries, J. E., Brindley, H. E., Sagoo, P. J. & Bantges, R. J. Increases in greenhouse forcing inferred from the outgoing longwave radiation spectra of the Earth in 1970 and 1997. Nature 410, 355–357 (2001)

    CAS  ADS  Article  Google Scholar 

  9. Jiang, Y., Aumann, H. H., Wingyee-Lau, M. & Yung, Y. L. Climate change sensitivity evaluation from AIRS and IRIS measurements. Proc. SPIE 8153, XVI, (2011)

    Google Scholar 

  10. Rothman, L. S. et al. The HITRAN2012 molecular spectroscopic database. J. Quant. Spectrosc. Radiat. 130, 4–50 (2013)

    CAS  ADS  Article  Google Scholar 

  11. Kochel, J.-M., Hartmann, J.-M., Camy-Peyret, C., Rodrigues, R. & Payan, S. Influence of line mixing on absorption by CO2 Q branches in atmospheric balloon-borne spectra near 13 µm. J. Geophys. Res. 102 (D11). 12891–12899 (1997)

    CAS  ADS  Article  Google Scholar 

  12. Niro, F., Jucks, K. & Hartmann, J.-M. Spectra calculations in central and wing regions of CO2 IR bands. IV: Software and database for the computation of atmospheric spectra. J. Quant. Spectrosc. Radiat. 95, 469–481 (2005)

    CAS  ADS  Article  Google Scholar 

  13. Alvarado, M. J. et al. Performance of the Line-By-Line Radiative Transfer Model (LBLRTM) for temperature, water vapor, and trace gas retrievals: recent updates evaluated with IASI case studies. Atmos. Chem. Phys. 13, 6687–6711 (2013)

    CAS  ADS  Article  Google Scholar 

  14. Iacono, M. J. et al. Radiative forcing by long-lived greenhouse gases: calculations with the AER radiative transfer models. J. Geophys. Res. 113, D13103 (2008)

    ADS  Article  Google Scholar 

  15. Stephens, G. L. et al. An update on Earth’s energy balance in light of the latest global observations. Nature Geosci. 5, 691–696 (2012)

    CAS  ADS  Article  Google Scholar 

  16. Manabe, S. & Wetherald, R. T. Thermal equilibrium of the atmosphere with a given distribution of relative humidity. J. Atmos. Sci. 24, 241–259 (1967)

    CAS  ADS  Article  Google Scholar 

  17. Stokes, G. M. & Schwartz, S. E. The Atmospheric Radiation Measurement (ARM) program: programmatic background and design of the cloud and radiation test bed. Bull. Am. Meteorol. Soc. 75, 1201–1221 (1994)

    ADS  Article  Google Scholar 

  18. Clough, S. A. et al. Atmospheric radiative transfer modeling: a summary of the AER codes. J. Quant. Spectrosc. Radiat. 91, 233–244 (2005)

    CAS  ADS  Article  Google Scholar 

  19. Turner, D. D. et al. Ground-based high spectral resolution observations of the entire terrestrial spectrum under extremely dry conditions. Geophys. Res. Lett. 39, L10801 (2012)

    ADS  Google Scholar 

  20. Peters, W. et al. An atmospheric perspective on North American carbon dioxide exchange: CarbonTracker. Proc. Natl Acad. Sci. USA 104, 18925–18930 (2007)

    CAS  ADS  Article  Google Scholar 

  21. Bruhwiler, L. M. et al. CarbonTracker-CH4: an assimilation system for estimating emissions of atmospheric methane. Atmos. Chem. Phys. 14, 8269–8293 (2014)

    ADS  Article  Google Scholar 

  22. Rienecker, M. M. et al. MERRA: NASA’s Modern-Era Retrospective Analysis for Research and Applications. J. Clim. 24, 3624–3648 (2011)

    ADS  Article  Google Scholar 

  23. Gero, P. J. & Turner, D. D. Long-term trends in downwelling spectral infrared radiance over the U.S. Southern Great Plains. J. Clim. 24, 4831–4843 (2011)

    ADS  Article  Google Scholar 

  24. Clothiaux, E. E. et al. Objective determination of cloud heights and radar reflectivities using a combination of active remote sensors at the ARM CART sites. J. Appl. Meteorol. 39, 645–665 (2000)

    ADS  Article  Google Scholar 

  25. Weatherhead, E. C. et al. Factors affecting the detection of trends: statistical considerations and applications to environmental data. J. Geophys. Res. 103 (D14). 17149–17161 (1998)

    ADS  Article  Google Scholar 

  26. Haskins, R. D., Goody, R. M. & Chen, L. A statistical method for testing a general circulation model with spectrally resolved satellite data. J. Geophys. Res. 102, 16563–16581 (1997)

    ADS  Article  Google Scholar 

  27. Huang, Y. et al. Separation of longwave climate feedbacks from spectral observations. J. Geophys. Res. 115, D07104 (2010)

    ADS  Google Scholar 

  28. Philipona, R., Dürr, B., Ohmura, A. & Ruckstuhl, C. Anthropogenic greenhouse forcing and strong water vapor feedback increase temperature in Europe. Geophys. Res. Lett. 32, L19809 (2005)

    ADS  Article  Google Scholar 

  29. Dessler, A. E. et al. Water-vapor climate feedback inferred from climate fluctuations, 2003–2008. Geophys. Res. Lett. 35, L20704 (2008)

    ADS  Article  Google Scholar 

  30. Haywood, J. M. et al. The roles of aerosol, water vapor and cloud in future global dimming/brightening. J. Geophys. Res. 116, D20203 (2011)

    ADS  Article  Google Scholar 

  31. Best, F. A. et al. Traceability of absolute radiometric calibration for the Atmospheric Emitted Radiance Interferometer (AERI). In Conf. on Characterization and Radiometric Calibration for Remote Sensing (Space Dynamics Laboratory, Utah State Univ.. , 15–18 Sept) (2003)

  32. Knuteson, R. O. et al. Atmospheric Emitted Radiance Interferometer. Part II: Instrument performance. J. Atmos. Ocean. Technol. 21, 1777–1789 (2004)

    ADS  Article  Google Scholar 

  33. Masarie, K. A. et al. Impact of CO2 measurement bias on CarbonTracker surface flux estimates. J. Geophys. Res. 116, D17305 (2011)

    ADS  Article  Google Scholar 

  34. Bakwin, P. S., Tans, P. P., Zhao, C., Ussler, W. & Quesnell, E. Measurements of carbon dioxide on a very tall tower. Tellus B. 47, 535–549 (1995)

    ADS  Article  Google Scholar 

  35. Bakwin, P. S., Tans, P. P., Hurst, D. F. & Zhao, C. Measurements of carbon dioxide on very tall towers: results of the NOAA/CMDL program. Tellus B. 50, 401–415 (1998)

    ADS  Article  Google Scholar 

  36. Biraud, S. C. et al. A multi-year record of airborne CO2 observations in the US Southern Great Plains. Atmos. Meas. Technol. 6, 751–763 (2013)

    CAS  Article  Google Scholar 

  37. Wang, J. et al. Corrections of humidity measurement errors from the Vaisala RS80 radiosonde—application to TOGA COARE data. J. Atmos. Ocean. Technol. 19, 981–1002 (2002)

    ADS  Article  Google Scholar 

  38. Liljegren, J. C. in Microwave Radiometry and Remote Sensing of the Earth’s Surface and Atmosphere (eds Pampaloni, P. & Paloscia, S. ) 433–443 (VSP Press, 1999)

    Google Scholar 

  39. Cimini, D., Westwater, E. R., Han, Y. & Keihm, S. J. Accuracy of ground-based microwave radiometer and balloon-borne measurements during the WVIOP2000 field experiment. IEEE Trans. Geosci. Rem. Sens. 41, 2605–2615 (2003)

    ADS  Article  Google Scholar 

  40. Clothiaux, E. E. et al. The ARM Millimeter Wave Cloud Radars (MMCRs) and the Active Remote Sensing of Clouds (ARSCL) Value Added Product (VAP) DOE Tech. Memo. ARM VAP-002.1, (US Department of Energy, 2001)

  41. Li, J. Gaussian quadrature and its application to infrared radiation. J. Atmos. Sci. 57, 753–765 (2000)

    ADS  Article  Google Scholar 

  42. Mlawer, E. J. et al. The broadband heating rate profile (BBHRP) VAP. Proc. 12th ARM Sci. Team Meet. ARM-CONF-2002 (US Department of Energy, 2002)

  43. McFarlane, S., Shippert, T. & Mather, J. Radiatively Important Parameters Best Estimate (RIPBE): an ARM value-added product. DOE Tech. Rep. SC-ARM/TR-097 (US Department of Energy, 2011)

  44. Andrews, T., Forster, P. M., Boucher, O., Bellouin, N. & Jones, A. Precipitation, radiative forcing and global temperature change. Geophys. Res. Lett. 37, L14701 (2010)

    ADS  Article  Google Scholar 

  45. Collins, W. D. et al. Radiative forcing by well-mixed greenhouse gases: estimates from climate models in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4). J. Geophys. Res. 111, D14317 (2006)

    ADS  Article  Google Scholar 

  46. Anderson, G. P. et al. AFGL atmospheric constituent profiles (0–120 km). AFGL-TR_86-0110, (Hanscom Air Force Base, Air Force Geophysics Laboratory, 1986)

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This material is based upon work supported by the US Department of Energy, Office of Science, Office of Biological and Environmental Research, Climate and Environmental Science Division, of the US Department of Energy under Award Number DE-AC02-05CH11231 as part of the Atmospheric System Research Program and the Atmospheric Radiation Measurement (ARM) Climate Research Facility Southern Great Plains. We used resources of the National Energy Research Scientific Computing Center (NERSC) under that same award. I. Williams, W. Riley, and S. Biraud of the Lawrence Berkeley National Laboratory, and D. Turner of the National Severe Storms Laboratory also provided feedback. The Broadband Heating Rate Profile (BBHRP) runs were performed using Pacific Northwest National Laboratory (PNNL) Institutional Computing at PNNL, with help from K. Cady-Pereira of Atmospheric Environmental Research, Inc., L. Riihimaki of PNNL, and D. Troyan of Brookhaven National Laboratory.

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Authors and Affiliations



D.R.F. implemented the study design, performed the analysis of all measurements from the ARM sites, and wrote the manuscript. W.D.C. proposed the study design and oversaw its implementation. P.J.G. is the AERI instrument mentor and ensured the proper use of spectral measurements and quality control. M.S.T. mentored the implementation of the study and oversaw its funding. E.J.M. and T.R.S. performed calculations and analysis to determine fair-weather bias. All authors discussed the results and commented on and edited the manuscript.

Corresponding author

Correspondence to D. R. Feldman.

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Competing interests

The authors declare no competing financial interests.

Extended data figures and tables

Extended Data Figure 1 Schematic.

Schematic of the derivation of surface forcing from AERI observations and calculations based on the atmospheric structure.

Extended Data Figure 2 AERI instrument stability.

Time series of the AERI-instrument-derived laser wavenumber around a nominal frequency of 15,799 cm−1.

Extended Data Figure 3 CarbonTracker profiles.

a, CT2011 profile time series of CO2 at the SGP site. b, CT2011 fossil fuel component of the CO2 profile. c, CT2011 biomass burning component of the CO2 profile. PGS, the ARM Precision Gas System Carbon Dioxide Mixing Ratio System.

Extended Data Figure 4 Microwave radiometer radiosonde scaling.

Distribution of microwave radiometer (MWR) precipitable water vapour to the precipitable water vapour derived from radiosondes for each year of the investigation at the ARM SGP site. Each count corresponds to the scaling between a collocated radiosonde and microwave radiometer retrieval.

Extended Data Figure 5 Thermodynamic trends.

a, Annual and seasonal clear-sky temperature (T) profile trends derived from radiosondes and ARSCL data for cloud-clearing at SGP from 2000 to 2010. b, Same as a but for water vapour (H2O) profile trends. c, As for a but temperature profile trends at NSA. d, As for b but for water vapour profile trends (in grams of water vapour per kilogram of air per decade) at NSA.

Extended Data Figure 6 Conversion from radiance to flux.

Histogram of zenith radiance to flux spectral conversion for AERI channel 1 spectral channels based on LBLRTM calculations based on the thermodynamic profiles from the ARM SGP site from 2000 to 2010. b, As for a but for the NSA site. ADM, Angular Distribution Model.

Extended Data Figure 7 Fair-weather bias.

a, Histogram of the difference in flux between BBHRP calculations with time-varying CO2 and calculations where CO2 = 370 ppmv for all profiles at 30-min resolution during 2010 at SGP. b, As for a but for the subset of data identified by the ARSCL as clear-sky.

Extended Data Figure 8 TOA and surface fluxes.

a, Occurrence frequency (in per cent) plot of tropopause versus surface forcing based on BBHRP calculations with time-varying CO2 and where CO2 = 370 ppmv for all profiles at 30-min resolution during 2010 at SGP for all-sky conditions as identified by ARSCL flags. b, As for a but for clear-sky conditions.

Extended Data Figure 9 Surface flux sensitivity to atmospheric profiles.

a, The sensitivity of the surface radiative flux (Fsurf) to the level of a 1°K perturbation in temperature for different model atmospheres including tropical, US standard (USSTD), mid-latitude summer (MLS), mid-latitude winter (MLW), sub-Arctic summer (SAS), and sub-Arctic winter (SAW)46. b, As for a but level perturbations are given as percentage H2O. c, As for a but level perturbations are 10 ppm CO2. d, As for a but level perturbations are 10% O3. e, As for a but level perturbations are 1 ppm CH4.

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Feldman, D., Collins, W., Gero, P. et al. Observational determination of surface radiative forcing by CO2 from 2000 to 2010. Nature 519, 339–343 (2015).

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