Supplementary Information

Supplementary Information How shorter black carbon lifetime alters its climate effect Ø. Hodnebrog 1, *, G. Myhre 1, B. H. Samset 1 1 Center for International Climate and Environmental Research-Oslo (CICERO), Oslo, Norway Supplementary Figures Supplementary Figure 1. Modelled and observed BC concentration profiles. Same as Fig. 1 in main manuscript, but for different HIPPO regions. The plots show comparison between aircraft observations (black line), the AeroCom phase II model range (shaded area), the AeroCom phase II OsloCTM2 model result (dashed orange line), and various simulations with the OsloCTM2 model (coloured lines). The observations are from the HIPPO campaign 1. 1

(a) STANDARD (b) PERTBC_A / PERTBC_B / PERTBC_C / PERTBC (c) Absolute difference (d) Scaling factors Supplementary Figure 2. Black carbon emissions. Distribution of BC emissions (kt yr -1 ) used in the STANDARD and perturbation simulations (a-b) and the absolute difference between these two emissions fields (c). The factors applied to the emissions in STANDARD to obtain the scaled emissions in the perturbation runs are also shown (d) and have the values 1.5 (blue), 2 (green), 3 (yellow) and 4 (red). Scaling factors were applied to all BC emissions, except for aviation emissions. 2

STANDARD PERTBC Supplementary Figure 3. Results from OsloCTM2 simulations. Horizontal distribution of atmospheric BC burden (mg m -2 ) (top) and zonal mean of atmospheric BC concentrations (kg kg -1 ) (bottom) for STANDARD (left) and PERTBC (right) simulations. 3

Low clouds (frac) Middle clouds (frac) High clouds (frac) Semi-direct RF Direct RF STANDARD NOBCabv500hPa PERTBC Supplementary Figure 4. Horizontal distributions of radiative forcing. Radiative forcing (W m -2 ) due to black carbon in the STANDARD (left), NOBCabv500hPa (middle) and PERTBC (right) simulations separated into direct (top) and semi-direct (bottom) forcing. Results are shown as differences to the NOBC simulation. STANDARD NOBCabv500hPa PERTBC Supplementary Figure 5. Cloud responses at different heights due to black carbon. Fractional change in high, middle and low cloud cover for cases STANDARD, NOBCabv500hPa and PERTBC. Results are shown as differences to the NOBC simulation. 4

STANDARD NOBCabv500hPa PERTBC Supplementary Figure 6. Effect of black carbon on zonal mean relative humidity. Absolute change in relative humidity (%) due to black carbon in the STANDARD (left), NOBCabv500hPa (middle) and PERTBC (right) simulations. Results are shown as differences to the NOBC simulation. STANDARD NOBCabv500hPa PERTBC Supplementary Figure 7. Precipitation changes due to black carbon. Change in precipitation (mm/yr) due to black carbon in the STANDARD (left), NOBCabv500hPa (middle) and PERTBC (right) simulations. Results are shown as differences to the NOBC simulation. Supplementary Figure 8. Influence of scaling factor on radiative forcing and precipitation. Results for the STANDARD simulation where the BC concentration field has been multiplied with a factor 10, and sensitivity tests with scaling factors of 2 and 50. The lines go through zero and the results for the STANDARD simulation. Results are shown as differences to the NOBC simulation. 5

Supplementary Tables Supplementary Table 1. List of experiments performed with the OsloCTM2 model. FFBF = fossil fuel and biofuel, BB = biomass burning. Emissions (Tg BC yr -1 ) Fraction of hydrophobic Factor increase in conversion rate Large-scale wet removal of BC for ice clouds Convective wet removal of BC Experiment FFBF BB Sum BC in emissions from hydrophobic to hydrophilic BC Hydrophilic Hydrophobic Hydrophilic Hydrophobic STANDARD 5.50 2.61 8.11 80% x 1 12% 0% 100% 0% PERTBC_A 12.1 a 5.40 17.5 b 25% a x 3 12% 0% 100% 0% PERTBC_B 12.1 a 5.40 17.5 b 25% a x 3 50% 50% 100% 0% PERTBC_C 12.1 a 5.40 17.5 b 50% a x 2 100% 100% 100% 100% PERTBC 12.1 a 5.40 17.5 b 25% a x 3 50% 50% 100% 100% a Emissions from aviation in the perturbation runs are implemented as in the STANDARD run (80% hydrophobic BC and no emission scaling) b Emissions have been scaled according to Supplementary Fig. 2d. Supplementary Table 2. Comparison of model and observations. Root-mean-square (RMS) error values (μg m -3 ) for the comparison between OsloCTM2 and observed (HIPPO and A-FORCE) BC vertical profiles. See Methods in the main manuscript for a description of the RMS error calculation. The number of data points is 83. Experiment RMS error (μg m -3 ) STANDARD 0.021 PERTBC_A 0.017 PERTBC_B 0.012 PERTBC_C 0.011 PERTBC 0.012 Supplementary Table 3. List of experiments performed with the NCAR CESM1 model. BC concentration fields from OsloCTM2 have been scaled by a factor 10 before implementation in the NCAR CESM1 model experiments. Experiment NOBC Description BC concentrations set to zero in whole atmosphere STANDARD a Prescribed BC field from STANDARD run of OsloCTM2 see Supplementary Table 1 NOBCabv200hPa a Same as STANDARD except BC concentrations set to zero above 200 hpa NOBCabv500hPa a Same as STANDARD except BC concentrations set to zero above 500 hpa PERTBC_A Prescribed BC field from PERTBC_A run of OsloCTM2 see Supplementary Table 1 PERTBC a Prescribed BC field from PERTBC run of OsloCTM2 see Supplementary Table 1 a Additional experiments have been carried out with BB BC and FFBF BC separated, to split the BB and FFBF contributions to the direct BC RF effect shown in Fig. 2 in the main manuscript. 6

Supplementary Discussion As described in Methods (in the main manuscript), the BC concentration fields were scaled by a factor of 10 in all NCAR CESM simulations. The large natural variability associated with clouds makes it challenging to quantify the semi-direct aerosol effect in climate models. A scaling factor of 10 for BC has been used before 2 and was chosen here to increase the signal-to-noise ratio. Such scaling may, however, lead to inaccuracies due to non-linearities in the climate system. For this reason we have carried out two sensitivity simulations with BC scaled by factors of 2 and 50. Supplementary Figure 8 shows results from the sensitivity tests together with the STANDARD simulation, and these results show that the response in direct and semi-direct aerosol radiative forcing for BC is relatively linear with the scaling factor for BC. Supplementary Methods Treatment of black carbon in the models In the offline chemical transport model OsloCTM2, advection of gases and aerosols is calculated using the second-order moment method 3. Vertical mixing by convection is based on the Tiedtke mass flux scheme 4, while the Holtslag K-profile scheme 5 is used for turbulent mixing in the boundary layer. Treatment of carbonaceous aerosols is based on a simple bulk parameterization scheme 6, where black carbon (BC) is represented as four different species; fractions of hydrophobic and hydrophilic BC for each of fossil fuel and biomass burning BC. In the STANDARD simulation, emissions of BC are assumed to be 80% hydrophobic and 20% hydrophilic (Supplementary Table 1). To represent the process of oxidation or coating by a hydrophilic compound, the hydrophobic fraction of BC is gradually converted to hydrophilic BC after a given aging time. In contrast to Cooke et al. 6, where a single exponential lifetime was used, we use aging times that are dependent on latitude and season as introduced in ref. 7 (see their Table 1 and associated description) and based on simulations in ref. 8. Black carbon is removed from the atmosphere by wet and dry deposition. In the STANDARD simulation, only hydrophilic BC is removed by wet deposition while both hydrophobic and hydrophilic BC is removed by dry deposition 7-9. Wet deposition is the main removal mechanism for BC and in this version of OsloCTM2, all (100%) hydrophilic BC is removed for convective precipitation and for largescale water clouds, while 12% is removed for large-scale ice clouds 7. The default monthly year 2000 aerosol climatology in NCAR CESM1.0.4 was, for black carbon, replaced by results from OsloCTM2. Hence, the emissions, transport and removal of BC were treated in OsloCTM2, while impacts of BC on radiative forcing and climate were treated in the NCAR CESM1.0.4 climate model. As in OsloCTM2, BC in the climate model is represented by hydrophobic and hydrophilic components. Shortwave radiation is calculated once every model hour for 19 spectral bands using the δ-eddington approximation 10. The optics for black carbon are from the Optical Properties of Aerosols and Clouds (OPAC) data set 11 and further details can be found in ref. 12. 7

Model experiments and emission scaling In this section, additional description of the OsloCTM2 and NCAR CESM model experiments is presented. Supplementary Table 1 gives an overview of the OsloCTM2 model experiments. The table includes the total global black carbon (BC) emissions in each experiment, and how the values for different properties affecting the BC lifetime, such as the aging time and wet removal of BC, have been modified in each of these experiments. The motivation for changing these properties is related to the strong indication from observations of an overestimated BC lifetime in most AeroCom models, including the OsloCTM2 (see Fig. 1 in main manuscript and associated discussion). In order to decrease the BC lifetime in OsloCTM2, there are only a limited number of parameters that can be changed. The governing parameters affecting the BC lifetime are related to the wet removal, more specifically the fraction of hydrophobic BC in emissions, the aging time from hydrophobic to hydrophilic BC, and the various fractions of BC removal in precipitating clouds. In the OsloCTM2 experiments listed in Supplementary Table 1, we tune these parameters in order for the BC concentration profiles to be better, albeit not perfectly, constrained by the aircraft observations. The BC emission data used in the STANDARD and perturbation simulations are shown in Supplementary Fig. 2, along with the regional scaling factors (Supplementary Fig. 2d) which were applied to the emissions in STANDARD to obtain the emission data used in the perturbation simulations. The scaling factors derived here are based roughly on the differences between observed and modelled BC absorption aerosol optical depth (AAOD) presented in Bond et al. 13 see their Figure 23 and associated discussion for a description of how the modelled BC direct climate forcing was adjusted to be consistent with the BC AAOD retrieved from AERONET stations. It should be noted that the scale factors applied here and in Bond et al. 13 are associated with large uncertainties, and the factors here are applied at a coarse resolution. In this study, the emission scaling factors have been applied equally throughout the year and for all BC emission sources. The NCAR CESM model experiments have used different prescribed BC concentration fields, and an overview of these experiments is given in Supplementary Table 3. 8

Supplementary References 1 Schwarz, J. P. et al. Global-scale seasonally resolved black carbon vertical profiles over the Pacific. Geophys. Res. Lett. 40, 2013GL057775, doi:10.1002/2013gl057775 (2013). 2 Kvalevåg, M. M., Samset, B. H. & Myhre, G. Hydrological sensitivity to greenhouse gases and aerosols in a global climate model. Geophys. Res. Lett. 40, 1432-1438, doi:10.1002/grl.50318 (2013). 3 Prather, M. J. Numerical advection by conservation of 2nd-order moments. J. Geophys. Res.- Atmos. 91, 6671-6681 (1986). 4 Tiedtke, M. A comprehensive mass flux scheme for cumulus parameterization in large-scale models. Mon. Weather Rev. 117, 1779-1800 (1989). 5 Holtslag, A. A. M., Debruijn, E. I. F. & Pan, H. L. A High Resolution Air Mass Transformation Model for Short-Range Weather Forecasting. Mon. Weather Rev. 118, 1561-1575, doi:10.1175/1520-0493(1990)118<1561:ahramt>2.0.co;2 (1990). 6 Cooke, W. F., Liousse, C., Cachier, H. & Feichter, J. Construction of a 1 degrees x 1 degrees fossil fuel emission data set for carbonaceous aerosol and implementation and radiative impact in the ECHAM4 model. J. Geophys. Res.-Atmos. 104, 22137-22162, doi:10.1029/1999jd900187 (1999). 7 Skeie, R. B. et al. Black carbon in the atmosphere and snow, from pre-industrial times until present. Atmos. Chem. Phys. 11, 6809-6836, doi:10.5194/acp-11-6809-2011 (2011). 8 Lund, M. T. & Berntsen, T. Parameterization of black carbon aging in the OsloCTM2 and implications for regional transport to the Arctic. Atmos. Chem. Phys. 12, 6999-7014, doi:10.5194/acp-12-6999-2012 (2012). 9 Berntsen, T., Fuglestvedt, J., Myhre, G., Stordal, F. & Berglen, T. F. Abatement of greenhouse gases: Does location matter? Climatic Change 74, 377-411, doi:10.1007/s10584-006-0433-4 (2006). 10 Briegleb, B. P. Delta-Eddington approximation for solar-radiation in the NCAR community climate model. J. Geophys. Res.-Atmos. 97, 7603-7612 (1992). 11 Hess, M., Koepke, P. & Schult, I. Optical properties of aerosols and clouds: The software package OPAC. Bull. Amer. Meteorol. Soc. 79, 831-844, doi:10.1175/1520-0477(1998)079<0831:opoaac>2.0.co;2 (1998). 12 Neale, R. B. et al. Description of the NCAR Community Atmosphere Model (CAM4), NCAR Technical Report, NCAR/TN-485+STR, National Center for Atmospheric Research (NCAR), Boulder, Colorado. (2011). 13 Bond, T. C. et al. Bounding the role of black carbon in the climate system: A scientific assessment. Journal of Geophysical Research: Atmospheres, doi:10.1002/jgrd.50171 (2013). 9