SUPPLEMENTARY INFORMATION

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1 In the format provided by the authors and unedited. SUPPLEMENTARY INFORMATION DOI: /NGEO2988 Hemispheric climate shifts driven by anthropogenic aerosol-cloud interactions Eui-Seok Chung and Brian J. Soden Rosenstiel School of Marine and Atmospheric Science University of Miami, Miami, Florida, USA 1. Evaluation of the kernel-derived aerosol forcing The instantaneous aerosol forcing and the aerosol-mediated cloud response derived using radiative kernel method are compared with that estimated using approximate partial radiative perturbation (APRP) method 46. The APRP-derived aerosol forcing is adopted from ref. 41 which used fixed- SST simulations of CMIP5. Supplementary Figures 2a and 2b indicate that the multi-model ensemble mean aerosol-mediated cloud response exhibits a consistent spatial distribution between these two methods and nearly identical global-means (-0.86 W m -2 for APRP method and W m -2 for radiative kernel method). Furthermore, as shown in Supplementary Fig. 2c, the interhemispheric difference shows good agreement between the two methods (r: 0.98, RMSD: 0.09 W m -2 ). Given that the CMIP5 RCPs (representative concentration pathways) scenarios are forced with nearly identical anthropogenic aerosols emissions but differing concentrations of anthropogenic greenhouse gases, the robustness of the kernel-estimated aerosol-mediated cloud response is further assessed by comparing the interhemispheric difference in the kernel-estimated aerosolmediated cloud response for the RCP4.5 scenario with that for the RCP2.6 and RCP8.5 scenarios NATURE GEOSCIENCE Macmillan Publishers Limited, part of Springer Nature. All rights reserved.

2 (Supplementary Fig. 8). The consistency between all three sets of scenarios lends further supports to our methodology and demonstrates that the kernel estimates of aerosol-mediated cloud response are insensitive to differences in cloud radiative feedback between emission scenarios. To further demonstrate the robustness of our conclusions, we compare the instantaneous aerosol forcing and aerosol-mediated cloud response computed using the APRP method with fixed-sst simulations (i.e., sstclimaerosol with the accompanying control experiment, sstclim) versus the corresponding hemispheric changes in temperature and precipitation (symbols in red in Fig. 2 d- i). Although the number of models available is smaller, these results support the conclusion derived using the radiative kernel method that the aerosol-mediated cloud response is a primary driver of the model projected shifts in rainfall and temperature. Note that the range of aerosol-mediated cloud response in coupled models is roughly twice that in the fixed-sst simulations. This is due to the fact that prescribing SSTs inhibits changes in the large-scale atmospheric circulation and suggests that the dynamical response of clouds to aerosol forcing provides an important feedback that amplifies the inter-hemispheric climate shifts by roughly a factor of two. Thus both in-situ microphysical changes in clouds and remote dynamical cloud changes provide roughly the same contribution to the hemispheric contrast in aerosol-mediated cloud response. 2. Aerosol-induced circulation shifts To further document the contribution of the aerosol-induced circulation shifts to the aerosolmediated cloud response, the response of mid-tropospheric vertical velocity to increased anthropogenic aerosols is compared between coupled (i.e., historicalaa) and fixed-sst (i.e., sstclimaerosol) simulations for models for which both simulations are available. Supplementary 2

3 Figure 3 shows that while pressure velocity at 500 hpa does not exhibit any systematic meridional shifts over the tropics in the fixed-sst simulations (Supplementary Fig. 3c), the coupled simulations (Supplementary Fig. 3b) clearly show a weakening of ascending motion in the NH together with anomalous ascending motion in the SH relative to the control climate (Supplementary Fig. 3a). This difference between the coupled and fixed-sst simulations highlights the change in the Hadley circulation in response to increased anthropogenic aerosols. The aerosol-induced circulation shifts are expected to induce cloud changes. For instance, Supplementary Figure 9 shows the aerosol-induced cloud amount changes at three pressure levels relative to the pre-industrial climate for the historicalaa simulations. The southward shift of the Inter-Tropical Convergence Zone (ITCZ) results in increased cloud amount just south of the equator, which is likely to cause more cooling by reducing incoming solar radiation at the surface. However, the boundary layer clouds slightly decrease or do not change significantly over much of the SH oceanic regions in stark contrast to the NH oceans, which is consistent with Fig. 2b. 3. Relation of the control climate tropical precipitation asymmetry with the global precipitation asymmetry change The position of the ITCZ results in tropical precipitation asymmetry between the hemispheres 12. Global warming/cooling arising from radiative forcings is, therefore, likely to exert a greater influence on the NH where the ITCZ is located. To examine whether the tropical precipitation asymmetry in the control climate exerts a substantial influence on the extent of the global precipitation asymmetry in response to increased anthropogenic aerosols, we compared the change in the global precipitation asymmetry with the control climate tropical precipitation asymmetry 3

4 (20ºS-Eq minus Eq-20ºN). Supplementary Figure 10 reveals a substantial inter-model spread in the control climate tropical precipitation asymmetry, with some models simulating greater precipitation in the SH. However, the change in the global precipitation asymmetry does not exhibit a coherent relation with the tropical precipitation asymmetry in the control climate for either the historical (i.e., all forcing) or historicalaa (i.e., anthropogenic aerosol-only) simulations. 4. Precipitation shifts in unforced control simulations We use unforced control simulations (i.e., picontrol) to examine whether the precipitation shifts simulated in the historical and RCP4.5 scenarios can be attributed to internal variability of the climate system. Supplementary Figure 1 displays the multi-model mean changes in precipitation, surface air temperature and cloud radiative effect (CRE) between the first 20-yr period and a later 20-year period of the control simulations. The multi-model precipitation change is substantially weaker and less organized compared to that for both the historical and RCP4.5 scenarios, and exhibits a spatial distribution irrelevant to the corresponding change in either surface air temperature over the oceans (with the mean over the tropical ocean removed) or CRE. Thus, the hemispheric precipitation shifts in the historical and RCP4.5 scenarios cannot be explained by internal variability. 4

5 Supplementary Table 1. A list of the CMIP5 climate models and experiments analyzed in this study. Model Experiment Historical Historical AA Historical GHG RCP4.5 1pctCO2 ACCESS1.0 O O O BCC-CSM1.1 O O O O BNU-ESM O O O O CNRM-CM5 O O O O sstclim Aerosol CanESM2 O O O O O O CSIRO-Mk3.6.0 O O O O O O GFDL-CM3 O O O O O O GFDL-ESM2M O O O O O GISS-E2-R O O O O O HadGEM2-ES O O O O O INMCM4 O O O IPSL-CM5A-LR O O O O O O IPSL-CM5A-MR O O O MIROC-ESM O O O O MIROC5 O O O O MPI-ESM-LR O O O MRI-CGCM3 O O O O O NorESM1-M O O O O O O NorESM1-ME O O O 5

6 Supplementary Figure 1: Climate changes in unforced control simulations. a-c, Spatial distribution of the multi-model ensemble mean change: precipitation (a), surface air temperature over the ocean (b), and cloud radiative effect (c). In b, the mean value over the tropical ocean (30ºS-30ºN) is removed from the surface air temperature change. 6

7 Supplementary Figure 2: Assessment of radiative kernel-derived aerosol-mediated cloud response. a,b, Spatial distribution of the multi-model ensemble mean aerosol-mediated cloud response derived using APRP method (a) and radiative kernel method (b) for the sstclimaerosol relative to sstclim simulations. c, Scatter plot of interhemispheric difference (SH NH) in the aerosol-mediated cloud response derived using radiative kernel method with that from APRP method. In c, each symbol denotes an individual model and the one-to-one line is shown for reference. The APRP-estimated aerosol-mediated cloud response is adopted from ref

8 Supplementary Figure 3: Response of the large-scale atmospheric circulation to increased anthropogenic aerosols in coupled and fixed-sst simulations. a, Spatial distribution of the multi-model ensemble mean 500-hPa pressure velocity (unit: hpa day -1 ) in the control climate. b,c, Changes in 500-hPa pressure velocity arising from increased anthropogenic aerosols in coupled (historicalaa) and fixed-sst (sstclimaerosol) simulations for models for which both simulations are available: coupled (b) and fixed-sst (c) simulations. Note that negative values denote ascending motion, and vice versa. 8

9 Supplementary Figure 4: Interhemispheric asymmetry in precipitation and temperature changes. Scatter plot of interhemispheric difference (SH NH) in precipitation change (dpr) against the corresponding interhemispheric difference in surface air temperature change (dtas) for the historical, historicalghg, and RCP4.5 experiments. The changes are computed over the period relative to the pre-industrial climate for the historical and historicalghg experiments, and over the period relative to the period of the historical experiment for the RCP4.5 experiment. Each symbol denotes an individual model. 9

10 Supplementary Figure 5: Dependence of interhemispheric precipitation asymmetry on model physics. Scatter plot of interhemispheric difference (SH NH) in precipitation change (dpr) between the historical and RCP4.5 experiments. The precipitation change is computed over the period relative to the pre-industrial climate for the historical experiment, and over the period relative to the period of the historical experiment for the RCP4.5 experiment. Each symbol denotes an individual model. 10

11 Supplementary Figure 6: Shifts of tropical rain belt in observations and model simulations. a, Temporal variations of the zonal-mean precipitation anomaly relative to the climatology for a gridded data set of surface observations over land (GHCN; ref. 37). Anomalies are smoothed with an 11-year running average to suppress sub-decadal fluctuations. b, Same as in a, but for the multi-model mean of CMIP5 historical simulations including oceanic regions. c,d, Same as in b, but for a subset of models that show the largest (top 25%) and lowest (bottom 25%) cloud response to aerosol forcing: top 25% (c) and bottom 25% (d). 11

12 Supplementary Figure 7: Interhemispheric asymmetry in temperature change. Time series of the interhemispheric difference in surface air temperature anomaly relative to the climatology for a gridded data set of surface observations (GISTEMP; ref. 42). 12

13 Supplementary Figure 8: Assessment of radiative kernel-derived aerosol-mediated cloud response. a,b, Comparison of the interhemispheric difference (SH NH) in kernel-estimated aerosol-mediated cloud response for the RCP4.5 scenario with that for the RCP2.6 (a) and RCP8.5 (b) scenarios. Each symbol denotes an individual model. The one-to-one line is shown for reference. 13

14 Supplementary Figure 9: Changes in the cloud amount in the boundary layer in anthropogenic aerosol-only simulations. a-c, Spatial distribution of the multi-model ensemble mean cloud amount change (unit: %) over the ocean for the period relative to the preindustrial climate at three pressure levels: 850 hpa (a), 900 hpa (b) and 950 hpa (c). 14

15 Supplementary Figure 10: Relation of the control climate tropical precipitation asymmetry with the aerosol-induced global precipitation asymmetry change. Scatter plot of the change in global precipitation asymmetry (90ºS-Eq minus Eq-90ºN) in the historical (i.e., all forcing) and historicalaa (i.e., anthropogenic aerosol-only) simulations against the tropical precipitation asymmetry (20ºS-Eq minus Eq-20ºN) in the pre-industrial climate. Each symbol denotes an individual model. 15