Using the AerChemMIP experiments to calculate radiative forcing from aerosols and chemically reactive gases
- 1University of Reading, Dept of Meteorology, Reading, United Kingdom (g.thornhill@reading.ac.uk)
- 2Climate and Radiation Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD 20771,USA
- 3Universities Space Research Association, 7178 Columbia Gateway Drive, Columbia, MD 21046, USA
- 4Norwegian Meteorological Institute, Oslo, Norway
- 5CICERO – Centre for International Climate and Environmental Research Oslo, Oslo, Norway
The effective radiative forcing (ERF) from aerosols and chemically reactive gases is calculated for several of the models that contributed to the CMIP6 project. The design of the experiments allowed for the calculation of the ERF due to each individual aerosol and gas, although where the aerosol and chemistry were modelled as interactive processes additional diagnostics were used to understand how these processes contributed to the overall ERF. The control used was the emission or concentration of the species in 1850 (considered the pre-industrial baseline for these experiments), with the perturbation using a specified emission or concentration of the species based on 2014 values as the present-day value. The experiments were run over a period of 30 years, with sea-surface temperatures held constant, and the ERF was obtained as the net change in TOA radiative flux between the perturbed and control run.
The aerosols considered were black carbon (BC), organic carbon (OC), SO2 and NH3, and the combination of these constituents in was modelled in the ‘aer’ experiment.
The chemically-reactive gases included methane, nitrous oxide (N2O), and the ozone precursors nitrogen oxides (NOx) and volatile organic compounds (VOC) as well as ozone (O3).
For some models we were able to use radiative kernels to find the relative importance of rapid adjustments such as cloud changes, atmospheric temperature and water vapour in the overall value of the ERF. We also used double-calls, where the effect of the aerosol or gas was removed from the radiative transfer calculations in the model, to examine the relative contributions of aerosol-cloud interactions and direct radiative effects.
The spread of the results between models is also considered, and the differences attributed to how the models represent different processes, e.g. aerosol-cloud interactions, and the complexity of the atmospheric chemistry modelling. The multi-model means are given below.
Table 1 Multi-model means for ERF for aerosols
| ERF Wm-2 | aer | BC | OC | SO2 | NH3 |
| Multimodel Mean | -1.01 | 0.15 | -0.25 | -1.03 | -0.07 |
| S.D. | 0.25 | 0.17 | 0.09 | 0.37 | 0.01 |
Table 2 Multi-model means for ERF for chemically reactive gases
| ERF Wm-2 | CH4 | HC | N2O | NTCF | O3 | NOx | VOC |
| Multi-model mean | 0.67 | 0.12 | 0.26 | -0.86 | 0.20 | 0.14 | 0.09 |
| S.D. | 0.17 | 0.21 | 0.07 | 0.18 | 0.07 | 0.13 | 0.14 |
We find the overall aerosol ERF (aer in Table 1) is consistent with previous work, although the results for black carbon (BC) show adjustments that are generally weaker than in previous studies. We also found that cloud effects can have a large impact on the overall ERF, including for the chemically-reactive gases.
The impact of other processes, especially atmospheric chemistry on the overall results is also discussed.
How to cite: Thornhill, G., Collins, W., Kramer, R., Olivie, D., and Skeie, R.: Using the AerChemMIP experiments to calculate radiative forcing from aerosols and chemically reactive gases, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7757, https://doi.org/10.5194/egusphere-egu21-7757, 2021.
