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

Nature volume 519, pages 339–343 (2015)Cite this article

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Abstract

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.

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Acknowledgements

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

  1. Earth Sciences Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, MS 74R-316C, Berkeley, California 94720, USA,

    D. R. Feldman, W. D. Collins & M. S. Torn

  2. Department of Earth and Planetary Science, University of California-Berkeley, 307 McCone Hall, MC 4767, Berkeley, California 94720, USA,

    W. D. Collins

  3. University of Wisconsin-Madison, Space Science and Engineering Center, 1225 W. Dayton Street, Madison, Wisconsin 53706, USA,

    P. J. Gero

  4. University of California-Berkeley, Energy and Resources Group, Berkeley, 310 Barrows Hall, MC 3050, California 94720, USA,

    M. S. Torn

  5. Atmospheric and Environmental Research, Inc., 131 Hartwell Avenue, Lexington, Massachusetts 02141, USA,

    E. J. Mlawer

  6. Pacific Northwest National Laboratory, Fundamental and Computational Sciences, 902 Battelle Boulevard, Richland, Washington 99354, USA,

    T. R. Shippert

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Contributions

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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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). https://doi.org/10.1038/nature14240

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