Aerosols overtake greenhouse gases causing a warmer climate and more weather extremes toward carbon neutrality

Domain: earth_science
Published: 2023-11-09
Editorial outcome: major_revision

Abstract
To mitigate climate warming, many countries have committed to achieve carbon neutrality in the mid-21st century. Here, we assess the global impacts of changing greenhouse gases (GHGs), aerosols, and tropospheric ozone (O3) following a carbon neutrality pathway on climate and extreme weather events individually using the Community Earth System Model version 1 (CESM1). The results suggest that the future aerosol reductions significantly contribute to climate warming and increase the frequency and intensity of extreme weathers toward carbon neutrality and aerosol impacts far outweigh those of GHGs and tropospheric O3. It reverses the knowledge that the changing GHGs dominate the future climate changes as predicted in the middle of the road pathway. Therefore, substantial reductions in GHGs and tropospheric O3 are necessary to reach the 1.5°C warming target and mitigate the harmful effects of concomitant aerosol reductions on climate and extreme weather events under carbon neutrality in the future.

Introduction
Due to human activities, atmospheric greenhouse gas (GHG) concentrations have increased dramatically since around 1750, causing the climate to warm in the last few hundred years. The rate of global warming has accelerated in recent decades, with the global mean surface air temperature rising by 1.1°C above the pre-industrial levels1. Global warming increases the thermal and latent energy that boosts extreme weather events2, such as heat waves, torrential rains, and flooding. For instance, the frequency, duration, and intensity of heat waves have been increasing worldwide in the past decades3, which adversely affected ecosystems, agricultural systems, and economies4. Carbon emission from fossil fuel-based energy consumption is a primary cause of the global greenhouse effect. To minimize the negative impacts and risks of climate change, more than 110 countries have committed to achieving carbon neutrality in the mid-21st century5–7. Carbon neutrality is believed to be critical and urgently needed to meet the Paris Agreement’s warming target of limiting global warming to within 2°C, but preferably to 1.5°C by 21008. Specifically, the United States rejoined the Paris Climate Agreement in 2021, pledging to achieve net-zero emissions of carbon dioxide (CO2) by 2050, through carbon reduction programs by the federal and local government. For example, California passed Assembly Bill No. 32 (AB32) in 2006, proposing to cut carbon emissions to the 1990 levels by 2020 and to 80% lower levels by 20509. The European Union’s 27 member countries have promised to cut at least 55% of carbon emissions from the 1990 levels by 2030 and achieve carbon neutrality by 205010. The Chinese government has established its ambitious goal of reaching a carbon peak by 2030 and carbon neutrality by 2060, endeavoring to gradually achieve net-zero carbon emissions11.

Climate change and air pollution are two sides of the same coin. Extraction and burning of fossil fuels emit GHGs and other pollutants, including particulate matter (PM) and ozone (O3) precursors, etc. Therefore, carbon neutrality would substantially reduce air pollution emissions, with co-benefits for air quality. The low-carbon policies driven by the carbon neutrality target of China are expected to reduce the emissions of sulfur dioxide (SO2), nitrogen oxides (NOx), primary PM2.5 (particulate matter with an aerodynamic diameter < 2.5 µm), and volatile organic compounds (VOCs) by 42%, 42%, 44%, and 28% in 2030 and by 93%, 93%, 90%, and 61% in 2060 respectively12. Consequently, the PM2.5 and O3-8h (the maximum 8-h moving average of O3 concentration) 90th percentile concentrations are estimated to be reduced by more than 80% in 2060 relative to the 2020 levels, and all municipal cities will reach the current national air quality standard12. Compared to other emission reduction pathways, Cheng et al.7 suggest that carbon neutrality pathways are necessary and effective if China is to meet international World Meteorological Organization (WMO) standards (i.e., annual mean less than 35 μg/m3) for PM2.5 concentrations. In the United States, the multiple feasible carbon neutrality pathways such as producing low-carbon fuels from biomass and electrification would effectively reduce the emissions of air pollutants13.

Besides reducing the co-emitted air pollutants, global GHG mitigations can also reduce air pollution by slowing climate change which alters the meteorology conducive to pollution production and/or accumulations14–18. In turn, changes in air pollutants and/or their precursors can also affect the climate. Specifically, tropospheric O3 in the atmosphere has a positive radiative forcing19, while different components of PM can have either warming or cooling effects on the climate20,21. For example, black carbon (BC), a particulate pollutant from combustion, contributes to the warming of the climate, while sulfate aerosol cools the earth22. Therefore, reducing air pollution emissions toward carbon neutrality may dampen or boost the effects of GHG mitigations. Although multiple attempts have been made to understand how mitigation options affect climate change, previous studies mainly focused on changes in the mean climate, but changes in extreme weather events have more direct, immediate, and visible impacts on human health and socioeconomics23. Yang et al.21 attributed the 2020 record-breaking rainfall in China partly to the abrupt emission reductions during the COVID-19 pandemic. It has also been argued that the increased surface air temperature and decreased relative humidity caused by the aerosol emission reductions during the pandemic explain one-third of the observed increase in wildfires during August–November over the western United States in 202024.

As part of the Coupled Model Intercomparison Project Phase 6 (CMIP6), the Detection and Attribution Model Intercomparison Project (DAMIP) has been conducted to estimate the individual contributions of various external forcings to the observed global and regional climate changes25,26. The experimental design includes historical and future simulations forced with GHG-only, aerosols-only, stratospheric-ozone-only, and natural-only forcing. However, the future experiments in DAMIP are conducted only under the Medium Shared Socioeconomic Pathway 2-4.5 (SSP2-4.5) scenario, representing an intermediate level of future changes in GHGs, aerosols, and land use. In this study, with a global-scale carbon neutrality pathway, i.e., the latest Shared Socioeconomic Pathway 1-1.9 (SSP1-1.9) scenario in CMIP6 which limits warming to 1.5°C set forth by the Paris Agreement27,28, we systematically investigate the impacts of the ambitious mitigation strategies on climate and extreme weather events, including extreme heat and precipitation. More specifically, we simulate the individual impacts attributed to changes in GHGs, aerosols, and tropospheric O3 under the carbon neutrality scenario.

Results
Future changes in GHGs, aerosols, and ozone levels under carbon neutrality scenario
The global mean concentrations of GHGs for 2020, 2050, and 2100 under the carbon neutrality scenario are listed in Table S1. Specifically, the global mean concentration of CO2 will increase from the current level of 414 ppm to 437 ppm by 2050 and then decrease to 400 ppm by 2100 following the SSP1-1.9 pathway. The global mean concentration of methane (CH4) will decrease from the current level of 1884 ppb to 1429 ppb by 2050, and further decrease to 1061 ppb by 2100, while nitrous oxide (N2O) will increase from the current level of 332 ppb to 344 ppb and 353 ppb by 2050 and 2100, respectively.

In general, the tropospheric O3 levels are projected to decrease across the globe by the mid-of-century, with apparent negative anomalies in tropospheric column O3 (TCO) in 2050 and 2100 compared to the 2020 levels (Fig. S1b and 1c). The decreases in TCO are higher, exceeding −6 DU in 2050 and −10 DU in 2100, over mid-to-high latitudes of the Northern Hemisphere where the current levels of TCO are relatively high (Fig. S1a). The changes in surface O3 concentrations agree with the TCO changes, with marked decreases above −10 ppb in 2050 and −20 ppb in 2100 over mid-to-high latitudes of the Northern Hemisphere, compared to 2020 levels (Fig. S1d–f).

In pace with the strict control of anthropogenic emissions under carbon neutrality, the emissions of aerosols and their precursors will decrease significantly in the future. Specifically, the changes in emissions of SO2 are mostly concentrated over East Asia, with the emission decreasing from 3 gm−2a−1 to lower than 1.4 gm−2a−1 in 2050 and lower than 1.0 gm−2a−1 in 2100 (Fig. S2a–c). And the emissions of BC over the polluted regions such as East Asia, South Asia, Europe, and North America will decline from the 2020 level of above 1 gm−2a−1 to lower than 0.3 gm−2a−1 in 2050 and below 0.1 gm−2a−1 in 2100 (Fig. S2d–f). Similarly, the emissions of OC (organic carbon) over the polluted regions will decrease from more than 0.2 gm−2 a−1 in 2020 to lower than 0.14 gm−2a−1 and 0.1 gm−2a−1 in 2100, respectively (Fig. S2g–i). Accordingly, the annual mean aerosol optical depth (AOD) at 550 nm will decrease by 0.08-0.2 over the polluted regions including East Asia, South Asia, Africa, and South America simulated by CESM1, with the maximum reduction above 0.2 in 2050 and above 0.3 in 2100 (Fig. S3).

The regional mean changes in TCO and the emissions of aerosols and the precursors in 2050 and 2100 relative to the 2020 levels are further depicted in Fig. S4. The TCO levels over most of the subregions will be reduced in the future, with TCO values decreasing by 10–15% in 2050 and 15–25% in 2100 relative to the 2020 levels. The emission reductions of aerosols and their precursors are relatively strong with SO2 emissions decreasing by more than 50% in 2050 and up to 90% in 2100 over most of the subregions relative to 2020, BC emissions decreasing by 30–70% in 2050 and 50–90% in 2100 and OC emissions decreasing by 10–40% in 2050 and 20–50% in 2100.

Changes in temperatures and precipitations attributed to GHGs, aerosols, and tropospheric ozone under carbon neutrality
With the fully coupled Community Earth System Model version 1 (CESM1, see “Methods” section), this study investigates the individual and combined climate impacts of the key anthropogenic climate drivers including GHGs, aerosols, and tropospheric O3 in the future of carbon neutrality. To assess the climate effects of anthropogenic emission changes on regional scale, the global land regions are divided into 21 subregions (Fig. S5). And CESM1 model shows good performance in capturing the spatial patterns and magnitudes of temperatures and precipitations for present-day climate on global and regional scales (Fig. S6). Figure 1 shows the spatial distributions of the simulated changes in annual mean surface air temperatures in GHG2050, AerGHG2050, ALL2050, and ALL2100 relative to the Baseline simulations (see “Methods” section), attributed to the strict control of anthropogenic emissions under carbon neutrality. Driven by the increased levels of GHGs, including CO2, N2O, and CFC-12 in 2050 relative to the 2020 values (see Table S1), surface air temperatures will change slightly over most of the globe, with maximum increases within 0.2°C over Greenland (Fig. 1a). By further reducing the emissions of aerosols and precursors, surface temperatures are significantly elevated in AerGHG2050, with maximum increases up to 2.0°C over mid-to-high latitudes of the Northern Hemisphere relative to Baseline (Fig. 1b). Adding the reductions in tropospheric O3, the warming will be slightly weakened in ALL2050 compared to AerGHG2050, relative to Baseline (Fig. 1c). The regional mean changes in surface air temperatures due to changes in GHGs, aerosol emissions and tropospheric O3 levels in 2050 indicate that aerosol reduction-caused warming dominates climate change overall subregions with surface air temperatures increasing by 0.5–1.4°C, noticeably higher than the GHG-caused surface temperature increases of below 0.2°C (Fig. 1e). In contrast, the changes in tropospheric O3 levels mainly induce cooling over most subregions, but the magnitudes of temperature changes are much weaker (<−0.2°C) compared to the changes attributed to aerosols. By further controlling anthropogenic emissions by the end of the century, the air temperature increases are slightly enhanced in the ALL2100 simulations, especially in the mid-to-high latitudes but weakened over the tropics, compared to those in ALL2050 (Fig. 1d). It indicates that even negative CO2 emissions after 2050 following the SSP1-1.929 would not be enough to compensate for the excessive warming caused by further reductions of aerosols after 2050.

Note that the multi-model analyses based on SSP245, SSP245-GHG, and SSP245-Aer experiments under the medium emission pathway from DAMIP in CMIP6 suggest that the increases in the global surface air temperature in the mid of the century is primarily attributed to changes in GHGs rather than aerosols (Fig. S7). Specifically, relative to the 2020 level, surface air temperatures increase more than 1.2°C over most of the land areas by the mid-of-century, with maximum above 1.4°C in the north of 60°N in SSP245 experiment (Fig. S7a), of which the changes in GHGs contribute the most with similar spatial pattern and magnitudes of temperature changes in SSP245-GHG (Fig. S7b). In contrast, changes in air temperatures driven by aerosols only are much weaker with magnitude <0.5°C over most of the land areas in SSP245-Aer (Fig. S7c). The results are consistent with a recent study that GHGs contribute the most to projected changes in land surface air temperature under SSP2-4.5 emission pathway30. Furthermore, future precipitation changes are also dominated by GHGs rather than anthropogenic aerosols as predicted under the SSP2-4.5 scenario26. Therefore, as opposed to the medium emission pathway, the unexpected amplified impacts of aerosols on climate changes should be taken seriously on the pathway to carbon neutrality.

Temperature changes are driven by perturbations of the earth’s radiative balance, associated with reduced anthropogenic emissions31. The changes in effective radiative forcing (ERF) at top of the atmosphere (TOA) and at the surface in GHG2050, AerGHG2050, ALL2050, and ALL2100 compared to Baseline are illustrated in Figs. S8 and S9. Compared to Baseline, the changes in ERF at TOA due to changes in GHG concentrations are weakly positive, with a maximum of 0.5-1.0 W/m2 over North America, South America, and West Africa (Fig. S8a). The TOA ERF changes between AerGHG2050 and Baseline are much larger, reaching 4.5 W/m2 over East Asia and 2.5 W/m2 over Northern Europe, North America, and East Africa (Fig. S8b). The positive TOA ERF anomalies associated with changes in GHGs and aerosols in 2050 indicate that more solar radiations will be captured by the earth system. However, negative TOA ERF anomalies up to −3.0 W/m2 are witnessed over Greenland, North Africa, the Middle East, and Central Asia in AerGHG2050 compared to Baseline, where the radiative impacts of absorbing aerosols (e.g., BC in this study) are enhanced by the bright surface with a high albedo32. The decreases in these absorbing aerosols lead to a negative ERF anomaly at TOA. The ERF changes in ALL2050 compared to Baseline are of similar spatial patterns and magnitudes to those in AerGHG2050, suggesting that the decreases in O3 have relatively weaker climate impacts than aerosols in 2050 (Fig. S8c). The regional mean ERF changes at TOA in 2050 due to changes in GHG concentrations, aerosol emissions, and tropospheric O3 suggest that aerosol-caused ERF changes (within ±2.0 W/m2) overtake the GHG and tropospheric O3 induced ERF changes (within ±0.5 W/m2; Fig. S8e). The ERF changes at TOA are further enhanced by the end of the century in ALL2100 (Fig. S8d), primarily driven by the continuing decreases in aerosol emissions (Figs. S1–S3). Note that the spatial distributions of ERF changes at the surface in GHG2050, AerGHG2050, ALL2050, and ALL2100 relative to Baseline are similar to the ERF changes at TOA (Fig. S9). The reduction in aerosol emissions contributes the most to the increases in ERF at the surface while changes in GHG concentrations and tropospheric O3 play a less significant role. The changes in ERF at TOA and surface support the temperature changes that the reductions in aerosols and their precursor emissions contribute dominantly to future warming under the carbon neutrality scenario.

The spatial distributions of annual mean precipitation changes caused by anthropogenic emission changes compared to Baseline are shown in Fig. 2. Precipitation anomalies caused by changes in GHGs are primarily identified over the tropical oceans, with significant positive anomalies over the Western Pacific and insignificant negative anomalies over the Eastern Pacific and Indian Ocean (Fig. 2a). The enhanced rainfall over the tropical Western Pacific agrees with previous findings33. By further reducing aerosol precursors, precipitation changes are amplified globally in AerGHG2050 compared to Baseline, with increased precipitation over the Northern Hemisphere, especially along the tropics, and decreased precipitation over many oceans of the Southern Hemisphere (Fig. 2b), suggesting a northward shift of the intertropical convergence zone due to aerosol reductions that largely occur over the Northern Hemisphere34. The spatial pattern of precipitation changes in ALL2050 is similar to that in AerGHG2050 (Fig. 2c), indicating that the reductions in tropospheric O3 levels have little impact on mean precipitations. The regional attributions of mean precipitation changes show that the decreases in aerosols generally increase precipitation over the global land regions, with maximum precipitation increases of up to 0.3 mm/day over Southeast Asia, East Asia, and South Asia. In contrast, changes in GHGs and tropospheric O3 levels generally have much weaker impacts on precipitations, with magnitudes within ±0.05 mm/day (Fig. 2e). In ALL2100, the spatial pattern of precipitation changes is similar to that of ALL2050, but with relatively larger amplitudes, consistent with the much lower aerosol levels by 2100 (Fig. 2d). The crucial impacts of aerosols on precipitations are consistent with previous works that higher aerosol concentrations reduce cloud-droplet size and prolong cloud lifetime, leading to reduced rainfall35,36.

The aerosol reduction-induced warming can also lead to more evaporation and ultimately result in more precipitation37. Thus, the changes in precipitation rates caused by anthropogenic emission changes under carbon neutrality are also closely related to the increase in water vapor with warming (Fig. S10). Compared to Baseline, except with weak increases in regions north to 60oN, the specific humidity changes little over other regions of the globe in GHG2050 simulations (Fig. S10a). But in AerGHG2050, specific humidity is much amplified, with large positive anomalies along tropical regions up to 1g/kg compared with Baseline (Fig. S10b), which may explain the increased precipitations there (Fig. 2b). The magnitude and spatial pattern of humidity changes in ALL2050 relative to Baseline are similar to those in AerGHG2050, suggesting that changes in tropospheric O3 levels contribute little to the changes in humidity and thus precipitations (Fig. S10c), in accordance with their small role in modulating temperature changes. With relatively enhanced warming in ALL2100 than ALL2050 relative to Baseline (Fig. 1), specific humidity changes are amplified in 2100 under the control policy of carbon neutrality. Overall, the decrease in aerosols and their precursors play a dominant role in modulating the changes in not only mean air temperatures but also precipitations.

It is worth noting that the spatial pattern of changes in surface air temperature (Fig. 1c) and precipitation (Fig. 2c) in ALL2050 simulated by CESM1 are similar to those projected by the multi-model ensemble mean of 13 global climate models in CMIP6 (Table S2) under SSP1-1.9 scenario (Fig. S11) with statistically significant spatial correlations above 0.8 for temperature change and 0.4 for precipitation change. Specifically, large increases in air temperature locate over mid-to-high latitudes of the Northern Hemisphere and increased rainfall anomalies mainly over the north of the equator, implying the crucial role of changing anthropogenic emissions in the future climate. It should be noted that the magnitudes of changes in air temperatures and precipitations in CESM1 are higher than those in multi-model results under SSP1-1.9. To be more specific, the global mean changes in air temperatures and precipitation in 2050 relative to 2020 simulated by CESM1 are 0.85°C and 0.07 mm/day, respectively, which are higher than the changes predicted by CMIP6 averages (0.60±0.50°C and 0.04±0.24 mm/day) related to the larger ERFs due to aerosol reductions and thus stronger climate sensitivities. Moreover, the global mean future changes in surface air temperatures and precipitations in 2100 relative to 2020 levels are 0.92oC and 0.10 mm/day in CESM1, also exceeding the CMIP6 averages (0.40±0.60oC and 0.04±0.24 mm/day).

Changes in extreme weather events attributed to GHGs, aerosols, and ozone under carbon neutrality
Extreme temperatures and precipitations are more influential to humans and societies. In this section, we focus on changes in extreme events including (dry) heat waves, humid heat waves, and extreme precipitation indices (see “Methods” section). In GHG2050 (Fig. 3a, e, i), the average frequency, length, and amplitude of extreme events are all quite moderate with average heat wave frequency (HWF, days/year), duration (HWD, days/event) and amplitude (HWA, °C day) lower than 5 days/year, 4 days/event, and 0.25°C/day, respectively, over most of the globe. When combined with aerosol emission abatement, heat wave frequency increases dramatically, along with increased mean duration and magnitude in AerGHG2050 (Figs. 3b, f, j), with HWF, HWD, and HWA increasing to more than 40 days/year, 20 days/event and 0.75°C/day globally. The spatial patterns and magnitudes of heat wave indices in ALL2050 are similar to those in AerGHG2050 (Fig. 3e, g, k), but tropospheric O3 abatement will have a small dampening effect on the occurrence of heat wave events (Fig. S12a). Further decreases in anthropogenic emissions by 2100 favor more, longer-duration, and stronger heatwaves such. Mean HWF and HWD will exceed 50 days/year and 28 days/event globally (Fig. 3d, h) and HWA increases to 1.5°C/day over mid-to-high latitudes (Fig. 3l), implying that the aerosol-dominated warming effect adds to excessive heat wave events by the end of the century (Fig. 3d). Therefore, substantial reductions in O3 precursors and GHGs emissions would have to be implemented to counteract the harmful climate consequences of future aerosol decline, which is also highlighted in SSP1-1.9 that CO2 emissions would decline to net zero around 2050, followed by net negative CO2 emissions29.

Reductions in aerosols have a similar amplification effect on humid heat waves as dry heat waves. Reductions in aerosol emissions favor increased humid heat waves with longer duration, and stronger amplitudes (Fig. S13). Specifically, the humid-HWF, humid-HWD, and humid-HWA (see “Methods” section) increase from less than 4 days/year, 4 days/event, and 0.25°C/day in GHG2050 (Fig. S13a, e, i) to more than 30 days/year, 24 days/event, and 0.5°C/day over most of the globe in AerGHG2050 (Fig. S13b, f, j), respectively. The enhancement of aerosol emission changes on the occurrences of humid heat waves outweighs the moderate effect of O3 and GHGs in 2050 (Fig. S12b). As aerosol emissions are further reduced by 2100, both dry and humid heat waves will threaten larger populations that increase the need to advance climate change adaptations.

We further evaluate the impacts of anthropogenic emissions on extreme precipitation indices (see “Methods” section). Compared with Baseline, Pretotal, the annual total precipitations on wet days (rainfall rate (RR) ≥ 1 mm/day), are reduced over many land regions in GHG2050 with negative anomalies of more than −20 mm dominating the tropics, Northern Europe and North Asia (Fig. 4a), whereas further reductions in aerosols largely increase Pretotal with significant positive anomalies higher than 40 mm over most of the globe especially the mid-to-high latitudes of Northern Hemisphere in AerGHG2050 (Fig. 4b). Tropospheric O3 levels have relatively small impacts on Pretotal (Fig. 4c). The regional attributions of Pretotal indicate reductions in aerosols have positive contributions to Pretotal while changes in GHGs and tropospheric O3 have weak negative contributions in 2050 (Fig. S12c). The impacts of changes in GHGs, aerosols and precursor emissions, and tropospheric O3 levels on total wet days are similar to those of Pretotal (Fig. 4e–h). Continued strict controls of anthropogenic emissions by 2100 lead to more Pretotal and wet days, mainly contributed by the much lower aerosols by 2100 (Fig. 4d, h). Note that the enhancements of reductions in anthropogenic emissions on R10mm, total days of moderate precipitation with RR ≥ 10 mm/day are mainly located over tropical regions, of which the reduced aerosols contribute to increased R10mm while changes in GHGs and O3 have the opposite effects (Fig. 4i–l).

Methods
Model description
In this study, the climate effects of anthropogenic emission changes under carbon neutrality are investigated through model simulations with the fully coupled Community Earth System Model version 1 (CESM1)63. The atmosphere component uses the Community Atmosphere Model version 5 (CAM5) with a horizontal resolution of 1.9° x 2.5° and 30 vertical layers. Major aerosol species, including BC, primary organic matter (POM), secondary organic aerosol (SOA), sulfate (SUL), mineral dust, and sea salt, are predicted in four log-normal size distribution modes (i.e., Aitken, accumulation, coarse and primary carbon modes)58. Aerosols are internally mixed within each mode. The land component is the Community Land Model version 4 (CLM4) and the ocean component employs the Parallel Ocean Program version 2 (POP2). CESM1 incorporates both aerosol direct and indirect effects including the cloud albedo and cloud lifetime effects59. The CAM5 in CESM1 features improved aerosols representation and includes aerosol–cloud interactions, demonstrating improved performance relative to CAM460. Additionally, a few aerosol-related schemes in CAM5, such as aerosol convective transport and wet deposition, are modified to enhance the model performance61. Aerosols are well simulated in North America and Europe but somewhat underestimated in East Asia and remote regions20. The three-dimensional O3 concentrations are prescribed to estimate the radiative effect of O3.

CESM1 has been widely used to investigate the local and global climate effects of emission and concentration changes in GHGs and air pollutants21,62. The model realistically simulates the observed warming over the 20th-century63. In this study, the SSP1-1.9 scenario in CMIP6 is used to represent the carbon neutrality pathway, which is a sustainable development pathway yielding an approximate anthropogenic radiative forcing of 1.9 Wm−2 in 2100 relative to the preindustrial level. The SSP1-1.9 scenario is developed to meet the 1.5°C global warming target set by the Paris Agreement64–66 and has been widely used as the carbon neutrality scenario to examine the future air quality and climate in many studies67,68.

Experimental design
Five sets of climate simulations (Table S3) are performed to investigate the climate effects of changes in anthropogenic emissions under carbon neutrality, with perturbed GHGs concentrations, aerosols and precursor emissions, and tropospheric O3 levels following SSP1-1.9. Although for a long time, many numerical studies investigate the climate under the 1.5°C/2°C global warming as a transient phase, the 1.5°C/2°C global warming limits are set by the Paris agreement with quasi-stabilized scenarios47. Recent studies have revealed substantial differences in climate responses between transient and stabilized climates and suggested that it would be valuable to design experiments in meeting the needs of decision-makers given that the Paris Agreement is implicitly targeting stabilized global warming levels48,69. Our study aims to understand the future climate effects of different anthropogenic forcings under quasi-equilibrium conditions for the development of climate change adaptation policies.

We focus on climate changes over the mid (2050) and end (2100) of the 21st century, compared with the present-day climatology (2020). In the Baseline simulation, global mean GHG concentrations, aerosols, and their precursor emissions, and tropospheric O3 levels are prescribed from the CMIP6 data and all fixed at the 2020 levels under the SSP1-1.9 scenario. Specifically, the global mean concentrations of major GHGs, including CO2, CH4, N2O, and halocompounds (CFC-11 and CFC-12) for the 2020 level are fixed at 414 ppm, 1884 ppb, 331 ppb, 218 ppt, and 495 ppt in the Baseline simulations (Table S1). Emissions of aerosols and their precursors in the model simulations follow the emission pathway of SSP1-1.9. The O3 concentrations in 2020, 2050, and 2100 are the ensemble averages of six global climate models (GCMs) simulations of SSP1-1.9 from the Scenario Model Intercomparison Project (ScenarioMIP) in CMIP6 (Table S4). Although the O3 concentrations are prescribed throughout the atmosphere, the climate effects of O3 are dominated by the changes in tropospheric O31. The ScenarioMIP GCMs show good performance in simulating historical tropospheric O370,71.

In GHG2050, the GHG concentrations are held at the future 2050 levels under SSP1-1.9, along with aerosols and precursor emissions and tropospheric O3 fixed at 2020 levels. Comparing GHG2050 and Baseline isolates the quasi-equilibrium climate effect of GHG changes by 2050 under carbon neutrality. In AerGHG2050, both GHG concentrations and aerosol emissions are held at the future 2050 levels under SSP1-1.9, along with tropospheric O3 set at the current 2020 level. Thus, comparing AerGHG2050 and GHG2050 isolates the climate effects of aerosol changes by 2050 under carbon neutrality. In the ALL2050 simulations, GHG concentrations, aerosol emissions, and tropospheric O3 levels are all set at the 2050 levels under SSP1-1.9. Comparing ALL2050 and AerGHG2050 represents the climate effects of tropospheric O3 changes by 2050 under SSP1-1.9. We also perform the ALL2100 simulations in which GHGs concentrations, aerosol emissions and tropospheric O3 are all set to the 2100 levels under SSP1-1.9, which allows comparison with Baseline to estimate the combined climate impacts of carbon neutrality by the end of the 21st century. For each of the experiments, 3 ensemble members are performed with a small initial perturbation to atmospheric temperature. All model simulations are run for at least 200 years of which the last 100 years are used in the analysis of climate impacts.

DAMIP multi-model simulations
In this study, we also place a special focus on the future global surface air temperature changes under a medium emission pathway and the differences of anthropogenic effects between the medium emission pathway and those under the carbon neutrality. As mentioned above, in the DAMIP simulations of aerosols-only, stratospheric-ozone-only, GHG-only, solar-only, and volcanic-only forcing are carried out as part of the CMIP6 to facilitate an improved estimation of the global and regional climate response to individual forcing. And all the future experiments in DAMIP are conducted under the medium emission scenario SSP2-4.5.

Here, we conduct the multi-model analyses of all-forcing simulations under SSP2-4.5 scenario (SSP245), simulations of GHG-only (SSP245-GHG) and aerosol-only forcing (SSP245-Aer) from the DAMIP experiments to quantify the individual contributions of GHGs and aerosols to future surface air temperature changes in the mid-of-the-century under the medium emission pathway (Table S5) and compare those with the anthropogenic effects under carbon neutrality.

Climate extreme indices
To measure the impacts of anthropogenic changes on extreme weather events, five extreme indices derived from daily maximum temperatures (Tmax) and daily rainfall rate (RR) are analyzed in this work: heat waves, humid heat waves, heavy precipitation days (R10mm), maximum length of wet days (CWD), and total precipitation of wet days (Pretotal). Wet days here mean daily precipitation above 1 mm/day (RR ≥ 1 mm/day). Different from (dry) heat waves identified as extreme hot days72,73, humid-heat waves are compound hazards of consecutive hot and humid days, defined by daily maximum wet-bulb temperatures (TWs), an integral measure of humidity and air temperatures. Using the algorithm described in Davies-Jones74, the daily maximum TW is calculated from the daily maximum air temperature, daily mean relative humidity, and daily mean surface pressure. The co-occurrences of humid and hot days would amplify the negative impacts of excessive heat on human and mortality rates75–77. Detailed definitions of the five extreme indices are provided in Table S6. Among the five extreme indices, heat waves and humid heat waves consist of several days of extreme high temperatures/wet-bulb temperatures, which entail several aspects of interest including heat wave frequency (HWF, days/year), mean duration (HWD, days/event) and amplitude (HWA, °C/day). Frequency means the annual total number of days of (humid) heat waves, duration means the average number of consecutive days during (humid) heat waves, and amplitude means the average exceedance of daily Tmax/TW relative to the threshold of (humid) heat waves78. Note that heat waves and humid heat waves are identified based on the present-day thresholds derived from daily Tmax/TW in the Baseline simulations (see Table S6).

In this work, the present-day climatology of air temperatures and precipitation is evaluated against the ERA5 reanalysis at 0.25° × 0.25° resolution on 2020. ERA5 is the latest fifth-generation reanalysis global atmosphere dataset from the European Centre for Medium-Range Weather Forecasts (ECMWF)79 (see Fig. S6).

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "The authors present the impacts of greenhouse gases, aerosols, and tropospheric O3 on climate and extreme weather events under a carbon neutrality pathway. With the Community Earth System Model version 1 (CESM1), the authors find that the climate effects of aerosol reducfions far outweigh those of GHGs and tropospheric O3 under carbon neutrality, which reverses the knowledge that the changing GHGs dominate the future climate changes as predicted in the medium forcing pathway. This study addresses very important quesfions that how the climate and extreme weather events evolve under a carbon neutrality scenario and which external forcing contributes the most to the climate change. The paper presents novel ideas and analysis and the scienfific methods and assumpfions are valid and clearly outlined. Before this paper can be considered for publicafion, I have a few minor comments need to be addressed.\n1. It is interesfing that the carbon neutrality scenario (SSP1-1.9) presents different contribufions of aerosols on climate as compared to SSP2-4.5. The author can compare aerosol reducfions under SSP1-1.9 with those under SSP2-4.5.\n2. According to the model simulafions, GHGs have very slight impacts on temperatures and precipitafions compared to aerosols toward carbon neutrality. It is the most significant finding and reverses the current climate projecfion in other scenarios. Does each of the 3 model ensemble members exhibit the same result?\n3. I wonder why you selected to run the simulafions using fixed forcing for 2020, 2050, and 2100 to get a quasi-equilibrium response. Some studies presented climate responses using the transient simulafions. It is not necessary that the author should perform new simulafion, but perhaps you should discuss the possible difference between transient and equilibrium responses.\n4. Recently, Wang et al. (2023, IJOC) have analyzed influences of anthropogenic and natural forcings on future changes in precipitafion projected by the CMIP6-DAMIP model. It would be befter to cite this paper to enhance the result obtained from this manuscript (Wang, Y., T. Zhao*, L. Hua, X. Guan, C. Xu, and X. Chen, 2023: Int. J. Climatol., doi: 10.1002/ioc.8064)\n5. About the climate Extreme Indices, the humid heat waves are defined based on daily maximum wet-bulb temperature (TW). The quesfion is how TW is calculated? Is it an output of the model?\n6. Orders of figures needed to be adjusted. For example, the supporfing figure starts from Figure S3.\n7. L115: 154: Table S3 to Table S2\n8. L170-178: Are there any published works to support the finding here?\n9. L318: SSP119 to SSP1-1.9\n10. Missing y-axis labels in Fig. S6d.\n11. Inconsistent fonts, e.g., Fig. S3.", "reviewer_2": "This study assesses individually the global impacts of changing GHGs, aerosols, and tropospheric O3 levels following a carbon neutrality pathway on climate and extreme weather events by using the Community Earth System Model version 1 (CESM1). The author found that the global changes in climate and extremes by 2050 and 2100 will be considerably stronger due to the emission reducfions in aerosols and precursors than those due to GHGs and tropospheric O3 changes. The study suggests that substanfial reducfions in GHGs and tropospheric O3 are necessary to reach the 1.5 warming target.\n℃\nThe finding is interesfing although expected as the CESM1 model has a strong (negafive) aerosol radiafive forcing at present-day. A reducfion in aerosol emissions in the future (e.g., 2050) implies a strong warming. As only one model (which may have too strong aerosol radiafive forcing) is used in this study, the authors may consider the inclusion of results from the other models. The uncertainty of aerosol radiafive forcing in the CESM1 model and implicafions to the results of this study should be discussed.\nThe authors menfioned 12 global climate models in CMIP6 under SSP1-1.9 scenario and used the mulfi-model ensemble mean (Figure S11 and Table S5). It would be interesfing to include these model results in the analyses.\nThis study used the approach for the equilibrium climate state (fime slides) rather than the transient climate change approach commonly used in the IPCC AR6. This may make the comparison with the DAMIP mulfi-model simulafions (SSP245) ambiguously.\nAlthough the impacts of aerosol on temperature and precipitafion are well studied, a discussion on the mechanisms of aerosol impacts on extreme weather events may be required to be included as this is the most interesfing part of this study.\nThe wrifing of this paper needs to be improved:\n1. The abstract is wordy and should be much condensed.\n2. The appearance of the first figure is Fig. S3 (line 123). This seems not in the right order of figures, e.g., the first figure appearing in the text should be Figure S1.\n3. When reading the results secfions, it is unclear that these results were obtained using the CESM1 model. CESM1 is menfioned in the abstract and then in the Method secfion. E.g., for the results in Lines 121-125, how and which model is used to derive them?\n4. Line 257, what are “HWF, HWD, and HWA”. They need to be defined.\n5. Line 281, it uses “Pretotal” while “Pretol” is used in Figure 4 capfion.", "reviewer_3": "Review of “Aerosols overtake greenhouse gases causing a warmer climate and more frequent extreme weather events toward carbon neutrality” by Pinya Wang, Yang Yang, Lili Ren, Daokai Xue, Jianping Tang, L. Ruby Leung, Hong Liao\nThe study invesfigates the relafive contribufion on future climate from the different climate forcers: well-mixed GHGs, aerosols and precursors, and ozone following a carbon-neutrality scenario using the model CESM. The main results are not ground-breaking or surprising, given the wealth of research showing the future changes in climate due to strong aerosol reducfions (many cited in the manuscript). In my opinion the main value of the study is that it demonstrates that under a carbon-neutrality scenario, aerosols largely dominate the future climate response, something that is sfill perhaps overlooked by the community and carries an important polifical message. The study has a well-defined scienfific quesfion, the methodology followed is clearly described and the manuscript is well wriften.\nGeneral comments:\n- It seems like the CESM simulafions show quite stronger responses in temperature and precipitafion than the mean of 12 CMIP6 models under scenario SSP1-1.9 by 2050 (Figs 1 and 2 vs. Fig S11). If scenario SSP1-1.9 by definifion limits warming to around 1.5 degrees based on a mulfi-model ensemble (See table SPM1 in IPCC, 2021: SPM), where does CESM stand in this ensemble? Is CESM more sensifive to aerosol reducfions than the mulfi-model mean? I think there should be enough literature comparing CESM with other models to try and befter understand where the model stands in terms of aerosol responses. Would the main conclusions be the same if the model was very insensifive to aerosol forcing? Or are these differences related to the semi-equilibrium response as opposed to the transient one?\n- The authors menfion many and very valid limitafions and uncertainfies, but miss the most important one, which is model uncertainty. The qualitafive comparison between Figs. 1-2 and Fig S11 seems insufficient to claim that CESM represents the real climate response to the studied forcings. This is not a parficular argument against the model, the same could be said about any model. I do think that the authors need to clearly state this in the discussion and wherever relevant in the manuscript. Furthermore, this relafive weakness could be turned into a powerful message: encourage the community to pursue in future mulfi-model detecfion and aftribufion assessments this type of best case, low carbon scenarios which may sfill carry important negafive consequences.\n- In addifion, despite of apparent negafive climate impacts of future aerosols emission reducfions, major health benefits could be expected in regions with air pollufion, something that in my opinion deserves to be highlighted in the manuscript. In fact, the warming due to aerosol reducfions is actually a commifted warming due to rising long-lived GHGs, the aerosols are simply masking that warming. Acknowledging the benefits of anthropogenic aerosols reducfions could help frame the message in a more balanced manner.\n- The fact that the climate response is stronger by 2100 than by 2050 means that at least according to CESM, not even negafive carbon dioxide emissions after 2050 following the SSP1-1.9 would be enough to compensate for the further reducfions of aerosols after 2050? If so, this can be an important message to convey.\nSpecific comments:\n-Lines 79-81: Is this sentence necessary? It seems a bit isolated from the context. Why Portugal?\n-Line 146: Missing y-axis label in Fig S6d.\n-Line 188: Seems like South America has a stronger signal than Northern Europe.\n-Line 189: The ERF of GHG2050 and AerGHG2050 seem quite different to me, AerGHG2050 seems much more like ALL2050.\n-Line 268-270: But this is indeed what the scenario SSP1-1.9 assumes, negafive emissions of carbon dioxide after 2050 (IPCC, 2021 SPM)."}, "author_response": "Reviewer #1:\nThe authors present the impacts of greenhouse gases, aerosols, and tropospheric O on\n3\nclimate and extreme weather events under a carbon neutrality pathway. With the\nCommunity Earth System Model version 1 (CESM1), the authors find that the climate\neffects of aerosol reductions far outweigh those of GHGs and tropospheric O under carbon\n3\nneutrality, which reverses the knowledge that the changing GHGs dominate the future\nclimate changes as predicted in the medium forcing pathway. This study addresses very\nimportant questions that how the climate and extreme weather events evolve under a carbon\nneutrality scenario and which external forcing contributes the most to the climate change.\nThe paper presents novel ideas and analysis and the scientific methods and assumptions\nare valid and clearly outlined. Before this paper can be considered for publication, I have\na few minor comments need to be addressed.\nReply: We thank the reviewer for the constructive comments and suggestions, which are\nvery helpful for improving the clarity and reliability of the manuscript. Please see our point-\nby-point responses to your comments below.\n1. It is interesting that the carbon neutrality scenario (SSP1-1.9) presents different\ncontributions of aerosols on climate as compared to SSP2-4.5. The author can compare\naerosol reductions under SSP1-1.9 with those under SSP2-4.5.\nReply: Thanks for your constructive and helpful suggestions. As we can see, the emission\nreductions of aerosols and their precursors are relatively weaker under SSP2-4.5 (Fig. R1,\nsee below) compared to those under SSP1-1.9 (Fig. S6). For example, in 2100, SO\n2\nemissions will be reduced by less than 40% under SSP2-4.5 (Fig. R1a), but by more than\n60% under SSP1-1.9 (Fig. S6b) in most subregions compared to 2020 levels. For BC and\nOC emissions, substantial differences in aerosol emissions between SSP2-4.5 (Fig. R1b&c)\nand SSP1-1.9 (Fig. S6c&d) are also seen.\nFigure R1 Regional mean reductions in emissions (%) of SO (a), BC (b) and OC (c) in\n2\n2050 and 2100, relative 2020, under SSP2-4.5 scenario.\n2. According to the model simulations, GHGs have very slight impacts on temperatures\nand precipitations compared to aerosols toward carbon neutrality. It is the most significant\nfinding and reverses the current climate projection in other scenarios. Does each of the 3\nmodel ensemble members exhibit the same result?\nReply: Yes, the three ensemble members show almost the same results. Figures R2-R7\ndemonstrate the surface air temperature and annual mean precipitation changes relative to\nthe 2020 levels in each of the three ensembles of GHG2050, AerGHG2050, ALL2050 and\nALL2100 simulations. The spatial patterns of air temperature and precipitations are similar\namong three ensemble members for each experiment, suggesting that the changes in\nsurface air temperature and precipitations driven by anthropogenic emissions are robust\namong the three ensemble members.\nFigure R2 Changes in annual mean surface temperature (℃) in first ensemble member of\nGHG2050 (a), AerGHG2050 (b), ALL2050 (c), and ALL2100 (d), relative to Baseline\n(2020) simulation.\nFigure R3 Same as in Figure R2, but for results in the second ensemble member of\nGHG2050 (a), AerGHG2050 (b), ALL2050 (c), and ALL2100 (d) simulations.\nFigure R4 Same as in Figure R2, but for results in the third ensemble member of GHG2050\n(a), AerGHG2050 (b), ALL2050 (c), and ALL2100 (d) simulations.\nFigure R5 Changes in annual mean precipitation (mm/day) in the first ensemble member\nof GHG2050 (a), AerGHG2050 (b), ALL2050 (c), and ALL2100 (d), relative to Baseline\n(2020) simulation.\nFigure R6 Same as in Figure R5, but for results in the second ensemble member of\nGHG2050 (a), AerGHG2050 (b), ALL2050 (c), and ALL2100 (d) simulations.\nFigure R7 Same as in Figure R5, but for results in the second ensemble member of\nGHG2050 (a), AerGHG2050 (b), ALL2050 (c), and ALL2100 (d) simulations.\n3. I wonder why you selected to run the simulations using fixed forcing for 2020, 2050,\nand 2100 to get a quasi-equilibrium response. Some studies presented climate responses\nusing the transient simulations. It is not necessary that the author should perform new\nsimulation, but perhaps you should discuss the possible difference between transient and\nequilibrium responses.\nReply: Thanks for pointing this out. As already stressed in the main context: “Although\nfor a long time, many numerical studies investigate the climate under the 1.5oC/2oC global\nwarming as a transient phase, the 1.5 oC/2 oC global warming limits are set by the Paris\nagreement with quasi-stabilized scenarios48. Recent studies have pointed out the substantial\ndifferences in climate response between transient and stabilized climates that the local\nclimate will eventually warm much more under transient global warming than equilibrium\nglobal warming at the same temperature threshold, causing differences in\nevapotranspiration, precipitation, and surface temperature49, 72. Our study aims to\nunderstand the future climate effects of different anthropogenic forcings under quasi-\nequilibrium conditions for the development of climate change adaptation policies.” We\nhave added more discussions on the potential differences between transient and quasi-\nequilibrium simulations in the revised manuscript: “The transient and equilibrium\nresponses of both surface air temperature and precipitation to CO increases are broadly\n2\nsimilar in spatial patterns over most of the globe among different forcing scenarios in\nCESM1 simulations47. If the transient simulations are performed, the patterns of\ntemperature/precipitation changes in response to GHGs changes would be similar to those\nobtained through the current equilibrium simulations following SSP1-1.9, but the\nresponses to GHGs changes would be even weaker in transient simulations as compared to\nequilibrium simulations48, which would not alter the finding in this study that the climate\neffects of aerosol reductions far outweigh those of GHGs under carbon neutrality.”\n4. Recently, Wang et al. (2023, IJOC) have analyzed influences of anthropogenic and\nnatural forcings on future changes in precipitation projected by the CMIP6-DAMIP model.\nIt would be better to cite this paper to enhance the result obtained from this manuscript\n(Wang, Y., T. Zhao*, L. Hua, X. Guan, C. Xu, and X. Chen, 2023: Int. J. Climatol., doi:\n10.1002/ioc.8064)\nReply: Thanks for your suggestion. We have cited this study in the revised manuscript as:\n“As part of the Coupled Model Intercomparison Project Phase 6 (CMIP6), the Detection\nand Attribution Model Intercomparison Project (DAMIP) has been conducted to estimate\nthe individual contributions of various external forcings to the observed global and regional\nclimate changes26, 27”.\n5. About the climate Extreme Indices, the humid heat waves are defined based on daily\nmaximum wet-bulb temperature (TW). The question is how TW is calculated? Is it an\noutput of the model?\nReply: Daily maximum wet-bulb temperature is obtained from surface pressure, air\ntemperature and specific humidity referring to the method. We have made it clear in the\nrevised manuscript: “Using the algorithm described in Davies-Jones 77, the daily maximum\nTW is calculated from the daily maximum air temperature, daily mean relative humidity,\nand daily mean surface pressure.”\n6. Orders of figures needed to be adjusted. For example, the supporting figure starts from\nFigure S3.\nReply: Thanks for pointing this out. The orders of all figures have been updated.\n7. L115: 154: Table S3 to Table S2\nReply: The orders of all tables are updated.\n8. L170-178: Are there any published works to support the finding here?\nReply: Thanks for pointing this out. Xu et al. (2022) have analyzed influences of\nanthropogenic and natural forcings on historical and future changes in global land-surface\nair temperature using model simulations from the CMIP6-DAMIP model. And their results\nsuggest that greenhouse gases contribute the most to projected changes in land-surface air\ntemperature, which support our finding here. Thus, we have we have cited this work in the\nrevised manuscript: “The results are consistent with a recent study that GHGs contribute\nthe most to projected changes in land surface air temperature under SSP2-4.5 emission\npathway 31.”\n9. L318: SSP119 to SSP1-1.9\nReply: Revised.\n10. Missing y-axis labels in Fig. S6d.\nReply: Added.\n11. Inconsistent fonts, e.g., Fig. S3.\nReply: Revised.\nReferences:\n26. Gillett, N.P. et al. The detection and attribution model intercomparison project (DAMIP v1. 0)\ncontribution to CMIP6. Geosci. Model Develop. 9(10), 3685-3697 (2016).\n27. Wang, Y., Zhao, T., Hua, L., Guan, X., Xu, C. & Chen, Q. Influence of anthropogenic and natural\nforcings on future changes in precipitation projected by the CMIP6–DAMIP models. Inter. J. Clim.\n(2023)\n31. Xu, C., Zhao, T., Zhang, J., et al. Impacts of natural and anthropogenic forcings on historical and\nfuture changes in the global land-surface air temperature simulated by CMIP6–DAMIP[J] (2022).\n47. Huang, D., Dai, A., & Zhu, J. (2020). Are the transient and equilibrium climate change patterns\nsimilar in response to increased CO ? J. Clim. 33(18), 8003-8023.\n2\n48. You, Q., Jiang, Z., Yue, X., Guo, W., Liu, Y., Cao, J., ... & Zhai, P. Recent frontiers of climate\nchanges in East Asia at global warming of 1.5° C and 2° C. Npj Clim. Atmospheric Sci., 5(1), 80.\n(2022).\n49. King, A. D., Lane, T. P, Henley, B. J. & Brown, J. R. Global and regional impacts differ between\ntransient and equilibrium warmer worlds. Nat. Clim. Change 10(1), 42-47 (2020).\n72. Julien, B., Naota, H., Jacob, S. & Hideo, S. Magnitude and robustness associated with the climate\nchange impacts on global hydrological variables for transient and stabilized climate states. Environ.\nRes. Lett. 13(6), 064017 (2018).\n77. Davies-Jones, R. An efficient and accurate method for computing the wet-bulb temperature along\npseudoadiabats. Mon. Weather Rev. 136(7), 2764-2785 (2008).\nReviewer #2:\nThis study assesses individually the global impacts of changing GHGs, aerosols, and\ntropospheric O levels following a carbon neutrality pathway on climate and extreme\n3\nweather events by using the Community Earth System Model version 1 (CESM1). The\nauthor found that the global changes in climate and extremes by 2050 and 2100 will be\nconsiderably stronger due to the emission reductions in aerosols and precursors than those\ndue to GHGs and tropospheric O changes. The study suggests that substantial reductions\n3\nin GHGs and tropospheric O are necessary to reach the 1.5 ℃ warming target.\nvery helpful for improving the clarity and reliability of the manuscript. Please see our point-\nby-point responses to your comments below.\n1. The finding is interesting although expected as the CESM1 model has a strong\n(negative) aerosol radiative forcing at present-day. A reduction in aerosol emissions in the\nfuture (e.g., 2050) implies a strong warming. As only one model (which may have too\nstrong aerosol radiative forcing) is used in this study, the authors may consider the inclusion\nof results from the other models. The uncertainty of aerosol radiative forcing in the CESM1\nmodel and implications to the results of this study should be discussed.\nReply: Thank you for the suggestions. We agree with the reviewer that CESM1 model\nestimates a relatively strong negative aerosol radiative forcing, due to the large negative\ncloud scattering components. Zelinka et al. (2014) reported that effective radiative forcing\n(ERF) at top of atmosphere (TOA) due to aerosol changes at present-day (2000) relative to\npreindustrial (1860) in CESM1 surpass most of the other global climate models, following\nCSIRO-Mk3-6-0 and GFDL-CM3 models. To minimize the uncertainty due to the model\ndependency, we have now added the comparison of the changes in ERF due to aerosol\nchanges in several global climate models by applying scaling factors characterizing the\nmodel differences in estimating ERF and discussed the potential impacts of model\nuncertainty in estimating aerosol ERF in CESM1.\nThe global mean changes in ERFs driven by aerosol reductions in 2050 relative to\n2020 in nine global climate models are given in Fig. S14. Though the multi-model average\nof aerosol-driven changes in ERF (1.93 W/m2) is lower than that in CESM1 (2.26 W/m2),\nit is still far beyond the global mean changes in ERF due to GHGs changes (0.01 W/m2).\nThus, the dominant role of aerosol reduction in affecting climate change following the\ncarbon neutrality pathway as stressed in this work would not be changed with multi-model\nsimulations.\nWe have accordingly added discussions on the model uncertainty of aerosol ERF in\nCESM1 in the revised manuscript (Line 345-355): “The interactions of anthropogenic\naerosols with radiation and clouds are the largest source of uncertainty in the estimation of\neffective radiative forcing52. According to Zelinka et al 51, among nine global climate\nmodels, ERF at TOA due to aerosol changes at present-day (2000) relative to preindustrial\n(1860) levels in CESM1 surpasses many other climate models and the aerosol ERF in\nCESM1 is 1.17 times as much as the multi-model average. Here, the global mean changes\nin ERFs driven by aerosol reductions in 2050 relative to 2020 in the nine global climate\nmodels used in Zelinka et al. 51 are estimated and given in Fig. S14. Though the multi-\nmodel average of aerosol-driven changes in ERF (1.93 W/m2) is lower than that in CESM1\n(2.26 W/m2), it is still far beyond the global mean changes in ERF due to GHGs changes\n(0.01 W/m2). Therefore, the main finding that aerosol reductions dominate climate changes\ntoward carbon neutrality target would not be changed with multi-model simulations.”\n2.5\n2\n1.5\nFigure S14 Estimated changes in global average effective radiative forcing (ERF, W/m2)\nat the top of the atmosphere due to aerosol changes in 2050 relative to 2020 levels. ERF\nchanges in other global climate models other than CESM1 are calculated by multiplying\nthe changes in ERF in CESM1 by the ratios of historical ERF (2000 Vs. 1860) between\nCESM1 and the other GCMs derived from ref. 51.\n2. The authors mentioned 12 global climate models in CMIP6 under SSP1-1.9 scenario\nand used the multi-model ensemble mean (Figure S11 and Table S5). It would be\ninteresting to include these model results in the analyses.\nReply: Thanks for the suggestion. The multi-model results are used to supported the\nprojected climate change in this study, but they lack the simulations for the contributions\nfrom individual forcings. We have now added more discussions on the model uncertainty\nof using CESM1 in the revised manuscript by referring to previous work (Line 337-344):\n“Moreover, large model uncertainties exist in projections of climate response to\nanthropogenic forcing, and CESM1 is relatively more sensitive to anthropogenic forcings.\nThe equilibrium climate sensitivity in CESM1-CAM5 is 4.1oC 50, exceeding the upper tail\nof the very likely range of 2.5 oC to 4 oC obtained by multi-model simulations in CMIP6\n39. CESM1 generally has a higher ERF due to aerosol-cloud interactions than other climate\n2-\n)\nm\nW(\ngnicroF\nevitaidaR\nevitceffE\nmodels related to its aerosol-ice cloud interaction51, partly explaining the relatively\nstronger responses in temperature and precipitation to the anthropogenic forcings in\nALL2050 than the ensemble means of multi-models in CMIP6 by 2050 (Fig. S11).”And\n(Line 345-353): “The interactions of anthropogenic aerosols with radiation and clouds are\nthe largest source of uncertainty in the estimation of ERF52. According to Zelinka et al. 51,\namong nine global climate models, ERF at TOA due to aerosol changes at present-day\n(2000) relative to preindustrial (1860) levels in CESM1 surpasses many other climate\nmodels and the aerosol ERF in CESM1 is 1.17 times as much as the multi-model average.\nHere, the global mean changes in ERFs driven by aerosol reductions in 2050 relative to\n2020 in the nine global climate models used in ref. 51 are estimated and given in Fig. S14.\nThough the multi-model average of aerosol-driven changes in ERF (1.93 W/m2) is lower\nthan that in CESM1 (2.26 W/m2), it is still far beyond the global mean changes in ERF due\nto GHGs changes (0.01 W/m2).” And we have stressed in the revised manuscript that it\nwould be interesting to involve more models (Line 355-357): “Still, it is of great\nsignificance for the community to conduct multi-model intercomparison of future climate\nchange in response to individual anthropogenic forcings under carbon neutrality scenario.”\n3. This study used the approach for the equilibrium climate state (time slides) rather than\nthe transient climate change approach commonly used in the IPCC AR6. This may make\nthe comparison with the DAMIP multi-model simulations (SSP245) ambiguously.\nReply: Thank you for pointing this out. Recent studies have pointed out the substantial\ndifferences in climate response between transient and stabilized climates that the local\nclimate will eventually warm much more under transient global warming than equilibrium\nglobal warming at the same temperature threshold 49, 72. The transient and equilibrium\nresponses of both surface air temperature and precipitation to CO increases are broadly\n2\nsimilar in spatial patterns over most of the globe among different forcing scenarios in\nCESM1 simulations 47. If the quasi-equilibrium simulations are performed, the patterns of\ntemperature/precipitation changes in response to GHGs changes would be similar to those\nobtained the DAMIP multi-model simulations (transient simulations), but the responses\nwould be even stronger in quasi-equilibrium simulations as compared to transient\nsimulations48, which would not alter the finding in this study that the climate effects of\naerosol reductions far outweigh those of GHGs under carbon neutrality. And it reverses the\nknowledge that the changing GHGs dominate the future climate changes as predicted in\nthe middle of the road pathway. We have now added these discussions in the revised\nmanuscript.\n4. Although the impacts of aerosol on temperature and precipitation are well studied, a\ndiscussion on the mechanisms of aerosol impacts on extreme weather events may be\nrequired to be included as this is the most interesting part of this study.\nReply: As suggested, we have now accordingly added discussions on the mechanisms of\naerosol impacts on extreme weather events in the revised manuscript (Line 310-322): “The\nanthropogenic forcers including GHGs and aerosols are the main drivers of the past and\nfuture changes in the climate as well as the extremes, as extremes are parts of the climate\nsystem. In particular, in the future of carbon neutrality, reduced aerosols enhance the\nwarming effect caused by GHGs. Changes in extremes at the global and regional scales are\na direct consequence of the enhanced radiative forcing, and the associated global warming\nand/or its resultant increase in the water-holding capacity of the atmosphere based on the\nClausius-Clapeyron relationship through thermodynamical processes30. At global scale, the\nnumber of heatwave days and the length of heatwave seasons in various regions scale well\nwith global mean temperatures39, 40, and changes in annual maximum one-day precipitation\nare proportional to global mean temperature changes41, 42. At the local and regional scales,\naerosol concentrations changes are also a key factor in controlling and modulating\ntemperature and extremes43, through the combined effects of the atmospheric energy\nbalance, dynamical adjustment, and vertical structure of forcing 44, 45.”\nThe writing of this paper needs to be improved:\n1. The abstract is wordy and should be much condensed.\nReply: Abstract has been rewritten to be concise.\n2. The appearance of the first figure is Fig. S3 (line 123). This seems not in the right\norder of figures, e.g., the first figure appearing in the text should be Figure S1.\nReply: Corrected.\n3. When reading the results sections, it is unclear that these results were obtained using\nthe CESM1 model. CESM1 is mentioned in the abstract and then in the Method section.\nE.g., for the results in Lines 121-125, how and which model is used to derive them?\nReply: Thanks for pointing this out. This structure of manuscript has been updated for a\nclearer description.\n4. Line 257, what are “HWF, HWD, and HWA”. They need to be defined.\nReply: Thanks for pointing this out. All the variables have been defined.\n5. Line 281, it uses “Pretotal” while “Pretol” is used in Figure 4 caption.\nReply: Corrected.\nReferences:\n30. IPCC, 2021: Climate Change 2021: The Physical Science Basis. Contribution of Working\nGroup I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change\n[Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen,\nL. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock,\nT. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge,\nUnited Kingdom and New York, NY, USA, 2391 pp. doi:10.1017/9781009157896.\n49. Wartenburger, R., Hirschi, M., Donat, M. G., Greve, P., Pitman, A. J., and Seneviratne, S. I..\nChanges in regional climate extremes as a function of global mean temperature: an interactive\nplotting framework. Geosci. Model Dev. Discuss., 1–30. doi:10.5194/gmd-2017-33 (2017).\n40. Sun, Y., Hu, T., & Zhang, X. Substantial increase in heat wave risks in China in a future\nwarmer world. Earth's Future, 6(11), 1528-1538 (2018).\n41. Kharin, V. V., Zwiers, F. W., Zhang, X., and Wehner, M.. Changes in temperature and\nprecipitation extremes in the CMIP5 ensemble. Clim. Change 119, 345–357.\ndoi:10.1007/s00382-013-0705-8 (2013).\n42. Westra, S., Alexander, L. V., and Zwiers, F. W. Global increasing trends in annual maximum\ndaily precipitation. J. Clim. 26, 3904–3918. doi:10.1175/JCLI-D-12-00502.1 (2013).\n43. Dong, B., Sutton, R. T., and Shaffrey, L. Understanding the rapid summer warming and\nchanges in temperature extremes since the mid-1990s over Western Europe. Clim. Dyn. 48,\n1537–1554. doi:10.1007/s00382-016-3158-8 (2017).\n44. Lin, L., Wang, Z., Xu, Y., and Fu, Q. Sensitivity of precipitation extremes to radiative forcing\nof greenhouse gases and aerosols. Geophys. Res. Lett. 43, 9860–9868.\ndoi:10.1002/2016GL070869 (2016).\n45. Lin, L., Wang, Z., Xu, Y., Fu, Q., and Dong, W.. Larger Sensitivity of Precipitation Extremes\nto Aerosol Than Greenhouse Gas Forcing in CMIP5 Models. J. Geophys. Res. Atmos.\ndoi:10.1029/2018JD028821 (2018).\n47. Huang, D., Dai, A., & Zhu, J. Are the transient and equilibrium climate change patterns similar\nin response to increased CO2? J. Clim. 33(18), 8003-8023 (2020).\n48. You, Q., Jiang, Z., Yue, X., Guo, W., Liu, Y., Cao, J., ... & Zhai, P. Recent frontiers of\nclimate changes in East Asia at global warming of 1.5° C and 2° C. Npj Clim. Atmospheric\nSci., 5(1), 80. (2022)\n49. King, A. D., Lane, T. P, Henley, B. J. & Brown, J. R. Global and regional impacts differ between\ntransient and equilibrium warmer worlds. Nat. Clim. Change 10(1), 42-47 (2020).\n50. Meehl, G. A., Washington, W. M., Arblaster, J. M., Hu, A., Teng, H., Kay, J. E., ... & Strand,\nW. G. Climate change projections in CESM1 (CAM5) compared to CCSM4. Journal of\nClimate, 26(17), 6287-6308 (2013).\n51. Zelinka, M. D., Andrews, T., Forster, P. M., & Taylor, K. E. Quantifying components of aerosol‐\ncloud‐radiation interactions in climate models. Journal of Geophysical Research: Atmospheres,\n119(12), 7599-7615 (2014).\n52. Boucher, O. et al. Clouds and Aerosols. In: Climate Change: The Physical Science Basis.\nContribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel\non Climate Change [Stocker, T.F., D. Qin, G.-K. Plattner, M. Tignor, S.K. Allen, J. Boschung, A.\nNauels, Y. Xia, V. Bex, and P.M. Midgley (eds.)]. Cambridge University Press, Cambridge,\nUnited Kingdom and New York, NY, USA, pp. 571–657, doi:10.1017/cbo9781107415324.016\n(2013).\n72. Julien, B., Naota, H., Jacob, S. & Hideo, S. Magnitude and robustness associated with the climate\nchange impacts on global hydrological variables for transient and stabilized climate states. Environ.\nRes. Lett. 13(6), 064017 (2018).\nReviewer #3:\nThe study investigates the relative contribution on future climate from the different climate\nforcers: well-mixed GHGs, aerosols and precursors, and ozone following a carbon-\nneutrality scenario using the model CESM. The main results are not ground-breaking or\nsurprising, given the wealth of research showing the future changes in climate due to strong\naerosol reductions (many cited in the manuscript). In my opinion the main value of the\nstudy is that it demonstrates that under a carbon-neutrality scenario, aerosols largely\ndominate the future climate response, something that is still perhaps overlooked by the\ncommunity and carries an important political message. The study has a well-defined\nscientific question, the methodology followed is clearly described and the manuscript is\nwell written.\nReply: We thank the reviewer for the constructive comments and suggestions, which are\nvery helpful for improving the clarity and reliability of the manuscript. Please see our point-\nby-point responses to your comments below.\nGeneral comments:\n1. It seems like the CESM simulations show quite stronger responses in temperature and\nprecipitation than the mean of 12 CMIP6 models under scenario SSP1-1.9 by 2050 (Figs 1\nand 2 vs. Fig S11). If scenario SSP1-1.9 by definition limits warming to around 1.5 degrees\nbased on a multi-model ensemble (See table SPM1 in IPCC, 2021: SPM), where does\nCESM stand in this ensemble? Is CESM more sensitive to aerosol reductions than the\nmulti-model mean? I think there should be enough literature comparing CESM with other\nmodels to try and better understand where the model stands in terms of aerosol responses.\nWould the main conclusions be the same if the model was very insensitive to aerosol\nforcing? Or are these differences related to the semi-equilibrium response as opposed to\nthe transient one?\nReply: Thank you for the very useful comments and suggestions. Yes, the CESM1 results\nshould stand around the upper tail of the multi-model ensemble related to its strong aerosol\nERF, despite the CMIP6 does not include CESM1 simulation. However, the strong\nsensitivity and equilibrium response should not influence the main results in this study.\nPlease see the responses below.\n1) For the strong sensitivity of CESM1 to anthropogenic aerosols, we have added\nthe following clarifications in the updated manuscript (Line 337-344): “Moreover,\nlarge model uncertainties exist in projections of climate response to anthropogenic forcing,\nand CESM1 is relatively more sensitive to anthropogenic forcings. The equilibrium climate\nsensitivity in CESM1-CAM5 is 4.1oC50, exceeding the upper tail of the very likely range\nof 2.5 oC to 4 oC obtained by multi-model simulations in CMIP630. CESM1 generally has\na higher ERF due to aerosol-cloud interactions than other climate models related to its\naerosol-ice cloud interaction51, partly explaining the relatively stronger responses in\ntemperature and precipitation to the anthropogenic forcings in ALL2050 than the ensemble\nmeans of multi-models in CMIP6 by 2050 (Fig. S11).”and Line (345-355): “The\ninteractions of anthropogenic aerosols with radiation and clouds are the largest source of\nuncertainty in the estimation of effective radiative forcing52. According to Zelinka et al. 51,\namong nine global climate models, ERF at TOA due to aerosol changes at present-day\n(2000) relative to preindustrial (1860) levels in CESM1 surpasses many other climate\nmodels and the aerosol ERF in CESM1 is 1.17 times as much as the multi-model average.\nHere, the global mean changes in ERFs driven by aerosol reductions in 2050 relative to\n2020 in the nine global climate models used in Zelinka et al. 51 are estimated and given in\nFig. S14. Though the multi-model average of aerosol-driven changes in ERF (1.93 W/m2) is\nlower than that in CESM1 (2.26 W/m2), it is still far beyond the global mean changes in\nERF due to GHGs changes (0.01 W/m2). Therefore, the main finding that aerosol\nreductions dominate climate changes toward carbon neutrality target would not be changed\nwith multi-model simulations.”\n2.5\n2\n1.5\nFigure S14 Estimated changes in global average effective radiative forcing (ERF, W/m2)\nat the top of the atmosphere due to aerosol changes in 2050 relative to 2020 levels. ERF\nchanges in other global climate models other than CESM1 are calculated by multiplying\nthe changes in ERF in CESM1 by the ratios of historical ERF (2000 Vs. 1860) between\nCESM1 and the other GCMs derived from ref. 51.\n2) For the potential differences between equilibrium climate simulation and\ntransient climate simulations, we have now added the following discussions in the\nrevised manuscript: “Recent studies have pointed out the substantial differences in\nclimate response between transient and stabilized climates that the local climate will\neventually warm much more under transient global warming than equilibrium global\nwarming at the same temperature threshold” (Line 411-414), and “The transient and\nequilibrium responses of both surface air temperature and precipitation to CO increases\n2\nare broadly similar in spatial patterns over most of the globe among different forcing\nscenarios in CESM1 simulations47. If the transient simulations are performed, the patterns\nof temperature/precipitation changes in response to GHGs changes would be similar to\nthose obtained through the current equilibrium simulations following SSP1-1.9, but the\n2-\n)\nm\nW(\ngnicroF\nevitaidaR\nevitceffE\nresponses to GHGs changes would be even weaker in transient simulations as compared to\nequilibrium simulations48, which would not alter the finding in this study that the climate\neffects of aerosol reductions far outweigh those of GHGs under carbon neutrality. (Line\n326-333)”\n2. The authors mention many and very valid limitations and uncertainties, but miss the\nmost important one, which is model uncertainty. The qualitative comparison between Figs.\n1-2 and Fig S11 seems insufficient to claim that CESM represents the real climate response\nto the studied forcings. This is not a particular argument against the model, the same could\nbe said about any model. I do think that the authors need to clearly state this in the\ndiscussion and wherever relevant in the manuscript. Furthermore, this relative weakness\ncould be turned into a powerful message: encourage the community to pursue in future\nmulti-model detection and attribution assessments this type of best case, low carbon\nscenarios which may still carry important negative consequences.\nReply: Thank you for pointing this out. We agree with the reviewer that model uncertainty\nis important and we have now made it clearer in the manuscript and added discussions in\nthe revised manuscript associated the model uncertainty:\n1) We have added discussions on the significance of model uncertainty (Line 337-\n344): “Moreover, large model uncertainties exist in projections of climate response to\nanthropogenic forcing, and CESM1 is relatively more sensitive to anthropogenic\nforcings. The equilibrium climate sensitivity in CESM1-CAM5 is 4.1 oC50, exceeding\nthe upper tail of the very likely range of 2.5 oC to 4 oC obtained by multi-model\nsimulations in CMIP630. CESM1 generally has a higher ERF due to aerosol-cloud\ninteractions than other climate models related to its aerosol-ice cloud interaction51,\npartly explaining the relatively stronger responses in temperature and precipitation to\nthe anthropogenic forcings in ALL2050 than the ensemble means of multi-models in\nCMIP6 by 2050 (Fig. S11).”\n2) We have compared the effective radiative forcing (ERF) due to aerosol changes in\nCESM1 with several other global climate models and discussed the impacts of\nmodel uncertainty on the current results (Line 345-355): “The interactions of\nanthropogenic aerosols with radiation and clouds are the largest source of uncertainty\nin the estimation of effective radiative forcing52. According to ref. 51, among nine\nglobal climate models, ERF at TOA due to aerosol changes at present-day (2000)\nrelative to preindustrial (1860) levels in CESM1 surpasses many other climate models\nand the aerosol ERF in CESM1 is 1.17 times as much as the multi-model average.\nHere, the global mean changes in ERFs driven by aerosol reductions in 2050 relative to\n2020 in the nine global climate models used in ref. 51 are estimated and given in Fig. S14.\nThough the multi-model average of aerosol-driven changes in ERF (1.93 W/m2) is\nlower than that in CESM1 (2.26 W/m2), it is still far beyond the global mean changes\nin ERF due to GHGs changes (0.01 W/m2). Therefore, the main finding that aerosol\nreductions dominate climate changes toward carbon neutrality target would not be\nchanged with multi-model simulations.”\n3) We have now emphasized the significance to conduct multi-model detection and\nattribution assessments toward carbon neutrality (Line 355-357): “Still, it is of\ngreat significance for the community to conduct multi-model intercomparison of\nfuture climate change in response to individual anthropogenic forcings under carbon\nneutrality scenario.”\n3. In addition, despite of apparent negative climate impacts of future aerosols emission\nreductions, major health benefits could be expected in regions with air pollution, something\nthat in my opinion deserves to be highlighted in the manuscript. In fact, the warming due\nto aerosol reductions is actually a committed warming due to rising long-lived GHGs, the\naerosols are simply masking that warming. Acknowledging the benefits of anthropogenic\naerosols reductions could help frame the message in a more balanced manner.\nReply: Thank you for this helpful and constructive suggestion. We have now added the\nbenefits of anthropogenic aerosols reductions and stated the committed warming of aerosol\nreductions due to rising long-lived GHGs in the revised manuscript (Line 373-377): “It\nshould be noted that the warming due to aerosol reductions toward carbon neutrality are\nactually a committed warming due to rising long-lived GHGs, and the aerosol reductions\nsimply unmask that GHGs-induced warming. In addition, despite of negative climate\nimpacts of future aerosols emission reductions, the benefits of carbon neutrality on air\nquality and global health burden are worthy of attention57, 58”\n4. The fact that the climate response is stronger by 2100 than by 2050 means that at least\naccording to CESM, not even negative carbon dioxide emissions after 2050 following the\nSSP1-1.9 would be enough to compensate for the further reductions of aerosols after 2050?\nIf so, this can be an important message to convey.\nReply: Thanks for pointing this out. We have added message in the revised manuscript\n(Line 160-166): “By further controlling anthropogenic emissions by the end of the century,\nthe air temperature increases are further enhanced in the ALL2100 simulations especially\nin the mid-to-high latitudes, compared to those in ALL2050 (Fig. 1d), which is primarily\ncontributed by the warming effects associated with more significant reductions in aerosols.\nIt indicates that even negative CO emissions after 2050 following the SSP1-1.930 would\n2\nnot be enough to compensate for the excessive warming caused by further reductions of\naerosols after 2050.”\nSpecific comments:\n-Lines 79-81: Is this sentence necessary? It seems a bit isolated from the context. Why\nPortugal?\nReply: The sentence has been removed.\n-Line 146: Missing y-axis label in Fig S6d.\nReply: Added.\n-Line 188: Seems like South America has a stronger signal than Northern Europe.\nReply: Thanks for pointing this out. This sentence has been corrected: “Compared to\nBaseline, the changes in ERF at TOA due to changes in GHG concentrations are weakly\npositive, with a maximum of 0.5-1.0 W/m2 over North America, South America, and West\nAfrica (Fig. S8a).”\n-Line 189: The ERF of GHG2050 and AerGHG2050 seem quite different to me,\nAerGHG2050 seems much more like ALL2050.\nReply: This sentence has been corrected in the revised manuscript: “The TOA ERF\nchanges between AerGHG2050 and Baseline are much larger, reaching 4.5 W/m2 over East\nAsia and 2.5 W/m2 over Northern Europe, North America, and East Africa (Fig. S8b).”\n-Line 268-270: But this is indeed what the scenario SSP1-1.9 assumes, negative emissions\nof carbon dioxide after 2050 (IPCC, 2021 SPM).\nReply: Thanks for pointing this out. We have updated this statement and cited IPCC (2021):\n“Therefore, substantial reductions in O precursors and GHGs emissions would have to be\n3\nimplemented to counteract the harmful climate consequences of future aerosol decline,\nwhich is also highlighted in SSP1-1.9 that CO emissions would decline to net zero around\n2\n2050, followed by net negative CO emissions 30”.\n30. IPCC, 2021: Climate Change 2021: The Physical Science Basis. Contribution of Working Group\nI to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-\nDelmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb,\nM.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O.\nYelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and\nNew York, NY, USA, 2391 pp. doi:10.1017/9781009157896.\n47. Huang, D., Dai, A., & Zhu, J. Are the transient and equilibrium climate change patterns similar in\nresponse to increased CO2? J. Clim. 33(18), 8003-8023 (2020).\n48. You, Q., Jiang, Z., Yue, X., Guo, W., Liu, Y., Cao, J., ... & Zhai, P. Recent frontiers of climate\nchanges in East Asia at global warming of 1.5° C and 2° C. Npj Clim. Atmospheric Sci., 5(1), 80.\n(2022)\n50. Meehl, G. A., Washington, W. M., Arblaster, J. M., Hu, A., Teng, H., Kay, J. E., ... & Strand, W.\nG. Climate change projections in CESM1 (CAM5) compared to CCSM4. Journal of Climate,\n26(17), 6287-6308 (2013).\n51. Zelinka, M. D., Andrews, T., Forster, P. M., & Taylor, K. E. Quantifying components of aerosol‐\ncloud‐radiation interactions in climate models. Journal of Geophysical Research: Atmospheres,\n119(12), 7599-7615 (2014).\n52. Boucher, O. et al. Clouds and Aerosols. In: Climate Change: The Physical Science Basis.\nContribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel\non Climate Change [Stocker, T.F., D. Qin, G.-K. Plattner, M. Tignor, S.K. Allen, J. Boschung, A.\nNauels, Y. Xia, V. Bex, and P.M. Midgley (eds.)]. Cambridge University Press, Cambridge, United\nKingdom and New York, NY, USA, pp. 571–657, doi:10.1017/cbo9781107415324.016 (2013).\n57. Li, H., Yang, Y., Wang, H., Wang, P., Yue, X., & Liao, H. Projected Aerosol Changes Driven by\nEmissions and Climate Change Using a Machine Learning Method. Environmental Science &\nTechnology, 56(7), 3884-3893 (2022).\n58. Yang, H., Huang, X., Westervelt, D. M., Horowitz, L., & Peng, W. Socio-demographic factors\nshaping the future global health burden from air pollution. Nature Sustainability, 6(1), 58-68.\n(2023)."}, {"round": 2, "reviewer_comments": {"reviewer_1": "As I am safisfied with the revised version of manuscript, I recommend for acceptance of this manuscript.", "reviewer_2": "The authors have addressed many of my comments. I appreciate their efforts. However, there are sfill a few comments not fully addressed or there are some place where are not very clearly elucidated, parficularly regarding the aerosol ERF.\n1. The authors used the nine global climate models in Zelinka et al., (Line 345-355) “…ERF at TOA due to aerosol changes at present-day (2000) relafive to preindustrial (1860) levels in CESM1 surpasses many other climate models and the aerosol ERF in CESM1 is 1.17 fimes as much as the mulfi-model average”. How do you get this 1.17 number? Please use the absolute value of the difference.\nAerosol ERF from preindustrial to present-day in CESM1 is about -1.8 W m-2. This is substanfially higher than the other climate models assessed in IPCC AR5 and AR6. Is there a reason why the authors used the models in Zelinka et al.? Ideally the authors should refer to the models in IPCC ARs, not the models in Zelinka et al.\n2. “Though the mulfimodel average of aerosol-driven changes in ERF (1.93 W/m2) is lower than that in CESM1 (2.26 W/m2), it is sfill far beyond the global mean changes in ERF due to GHGs changes (0.01 W/m2).” This 0.01 W/m2 of ERF due to GHGs changes in 2050 relafive to 2020 is very small. Where do you derive this number?\n3. The capfion of Figure S14. Should it be “by mulfiplying the changes in ERF in CESM1 by the rafios of historical ERF (2000 Vs. 1860) between the other GCMs derived from ref. 51 and CESM1”?\n4. The authors replied to my major comment #2, that the mulfi-model results lack the simulafions for the contribufions form individual forcings. Then can the authors compare the mulfi-model results with the ALL2050 and ALL2100 simulafions from CESM1?\n5. In line 337-344: “CESM1 generally has a higher ERF due to aerosol-cloud interacfions than other climate models related to its aerosol-ice cloud interacfion”. I don’t agree. The higher ERF due to aerosol-cloud interacfions in CESM1 should be due to the aerosol-warm cloud interacfions.\n6. There is a confusion when comparing the transient and equilibrium responses: “that the local climate will eventually warm much more under transient global warming than equilibrium global warming at the same temperature threshold 49, 72.” And “but the responses would be even stronger in quasi-equilibrium simulafions as compared to transient simulafions48”. Please explain more clearly.", "reviewer_3": "The authors have addressed all my comments and changed the manuscript accordingly. I have no further comments."}, "author_response": "Reviewer #2:\nThe authors have addressed many of my comments. I appreciate their efforts. However,\nthere are still a few comments not fully addressed or there are some place where are not\nvery clearly elucidated, particularly regarding the aerosol ERF.\nReply: We thank the reviewer for the constructive comments and suggestions, which are\nvery helpful for improving the clarity and reliability of the manuscript. Please see our point-\nby-point responses to your comments below.\n1. The authors used the nine global climate models in Zelinka et al., (Line 345-355)\n“…ERF at TOA due to aerosol changes at present-day (2000) relative to preindustrial\n(1860) levels in CESM1 surpasses many other climate models and the aerosol ERF in\nCESM1 is 1.17 times as much as the multi-model average”. How do you get this 1.17\nnumber? Please use the absolute value of the difference.\nAerosol ERF from preindustrial to present-day in CESM1 is about -1.8 W m-2. This is\nsubstantially higher than the other climate models assessed in IPCC AR5 and AR6. Is there\na reason why the authors used the models in Zelinka et al.? Ideally the authors should refer\nto the models in IPCC ARs, not the models in Zelinka et al.\nReply: Thank you for pointing out the inappropriate descriptions. According to Zelinka et\nal (2014), aerosol ERF at TOA in present-day (2000) relative to the preindustrial (1860)\nlevel is -1.37 W/m2 in CESM1 and -1.17 W/m2 averaged over nine global climate models.\nThe number 1.17 is the ratio between -1.37 W/m2 and -1.17 W/m2. All the modeling results\nof Zelinka et al (2014) have been adopted in both IPCC AR5 and AR6 (Figure 8.23 in\nIPCC AR5 and Table 7.6 in IPCC AR6 as shown below).\nIn the revised manuscript, we have modified the descriptions as: “Aerosol ERF at\nTOA in present-day (2000) relative to the preindustrial (1860) level simulated by CESM1\nis –1.37 W/m2 51 and –1.44 W/m2 with an additional 5% applied to account for land-surface\ncooling 53, relative higher than the multi-model averages of –1.23 ± 0.48 W/m2 in the\nCoupled Model Intercomparison Project Phase 5 (CMIP5) over 1860–2000 and –1.11 ±\n0.38 W/m2 in the CMIP6 over 1850–2014 30.”\nTable 7.6 | Present-day effective radiative forcing (ERF) due to changes in aerosol–radiation interactions (ERFari) and\nchanges in aerosol–cloud interactions (ERFaci), and total aerosol ERF (ERFari+aci) from GCM CMIP6 (2014 relative to\n1850; Smith et al., 2020b and later model results) and CMIP5 (year 2000 relative to 1860; Zelinka et al., 2014). CMIP6 results\nare simulated as part of RFMIP (Pincus et al., 2016). An additional 5% is applied to the CMIP5 and CMIP6 model results to\naccount for land-surface cooling (Figure 7.4; Smith et al., 2020a).\n2. “Though the multimodel average of aerosol-driven changes in ERF is lower than that in\nCESM1, it is still far beyond the global mean changes in ERF due to GHGs changes (0.01\nW/m2).” This 0.01 W/m2 of ERF due to GHGs changes in 2050 relative to 2020 is very\nsmall. Where do you derive this number?\nReply:\nThe 0.01 W/m2 is obtained by averaging the global ERF due to GHGs changes in 2050\nrelative to 2020 (Figure S8a). As shown in Table S1, the global mean concentrations of\nCO would increase from 414.04 ppm to 437.48 ppm during 2020 to 2050, but the CH\n2 4\nwould decrease from 1884.13 ppb to 1429.12 ppb, partly compensating the CO increases.\nAccordingly, we have made it more clearly in the updated manuscript: “it is still far beyond\nthe global averaged ERF due to GHGs changes (0.01 W/m2), as shown in Figure S8a”.\nFigure S8 Changes in effective radiative forcing (ERF) at top of atmosphere ((cid:1849)/(cid:1865)2) in GHG2050 (a),\nAerGHG2050(b), ALL2050 (c), and ALL2100 (d), relative to Baseline (2020). Regional mean changes\nin ERF at top of atmosphere in 2050 attributed to GHGs, aerosols and tropospheric O changes over 21\n3\nsubregions (e). The stippled areas indicate statistical significance with 95% confidence from a two-\ntailed Student’s t-test.\n3. The caption of Figure S14. Should it be “by multiplying the changes in ERF in CESM1\nby the ratios of historical ERF (2000 Vs. 1860) between the other GCMs derived from ref.\n51 and CESM1”?\nReply: Thanks. We have modified the caption of Figure S14 accordingly.\n4. The authors replied to my major comment #2, that the multi-model results lack the\nsimulations for the contributions from individual forcings. Then can the authors compare\nthe multi-model results with the ALL2050 and ALL2100 simulations from CESM1?\nReply:\nThanks for this suggestion. The climate changes in 2050 relative to 2020 simulated in\nthis study are compared with thoses from 13 global climate models in CMIP6 under SSP1-\n1.9 scenario, as the follows: “It is worth noting that the spatial pattern of changes in surface\nair temperature (Figure 1c) and precipitation (Figure 2c) in ALL2050 simulated by CESM1\nare similar to those projected by the multi-model ensemble mean of 13 global climate\nmodels in CMIP6 under SSP1-1.9 scenario (Figure S11) with statistical significant spatial\ncorrelations above 0.8 for temperature change and 0.4 for precipitation change. Specifically,\nlarge increases in air temperature locate over mid-to-high latitudes of the Northern\nHemisphere and increased rainfall anomalies mainly over the north of the equator,\nimplying the crucial role of changing anthropogenic emissions in the future climate.\nIt should be noted that the magnitudes of changes in air temperatures and precipitations in\nCESM1 are higher than those in multi-model results under SSP1-1.9. To be more specific,\nthe global mean changes in air temperatures and precipitation in 2050 relative to 2020\nsimulated by CESM1 are 0.85 oC and 0.07 mm/day, respectively, which are higher than\nthe changes predicted by CMIP6 averages (0.60 ± 0.50 oC and 0.04 ± 0.24 mm/day) related\nto the larger ERFs due to aerosol reductions simulated in CESM1. Moreover, the global\nmean future changes in surface air temperatures and precipitations in 2100 relative to 2020\nlevels are 0.92 oC and 0.10 mm/day in CESM1, also exceeding the CMIP6 averages (0.40\n± 0.60 oC and 0.04 ± 0.24 mm/day).”\nFigure S11 (a, b) Changes in annual mean surface air temperature (℃) and precipitation (mm/day,\nb) of the CMIP6 multi-model ensemble mean in 2050 under SSP1-1.9, relative to the 2020 levels.\nStippling indicates more than half of the simulations show consistent changes. (c, d) Standard\ndeviation of changes in surface air temperature and precipitation for the 13 CMIP6 models.\n5. In line 337-344: “CESM1 generally has a higher ERF due to aerosol-cloud interactions\nthan other climate models related to its aerosol-ice cloud interaction”. I don’t agree. The\nhigher ERF due to aerosol-cloud interactions in CESM1 should be due to the aerosol-warm\ncloud interactions.\nReply: Thank you for the correction. We have deleted this statement and revised the\ndescription as: “CESM1generally has a higher ERF due to aerosol-cloud interactions than\nother climate models 51, partly explaining the relatively stronger responses in temperature\nand precipitation to the anthropogenic forcings in ALL2050 than the ensemble means of\nmulti-models in CMIP6 by 2050.”\n6. There is a confusion when comparing the transient and equilibrium responses: “that the\nlocal climate will eventually warm much more under transient global warming than\nequilibrium global warming at the same temperature threshold 49, 72.” And “but the\nresponses would be even stronger in quasi-equilibrium simulations as compared to\ntransient simulations 48”. Please explain more clearly.\nReply: Thanks for pointing this out.\n In the Experimental design section, we have revised the statement as “Recent studies\nhave revealed substantial differences in climate responses between transient and\nstabilized climates and suggested that it would be valuable to design experiments in\nmeeting the needs of decision-makers given that the Paris Agreement is implicitly\ntargeting stabilized global warming levels49, 73.”\n For the statement in the discussion section “but the responses would be even\nstronger in quasi-equilibrium simulations as compared to transient simulations 48” is\nindicated by previous works that in response to a given changes in CO concentrations,\n2\nsuch as a quadrupling of the preindustrial CO2 (4× CO ) or a doubling of the\n2\npreindustrial CO (2×CO ), the global mean surface air temperature get warmer in the\n2 2\nquasi-equilibrium experiment than the transient one (Huang et al., 2020; You et al.,\n2022).\nReferences:\nHuang, D., Dai, A., & Zhu, J. Are the transient and equilibrium climate change patterns similar in\nresponse to increased CO2? J. Clim. 33(18), 8003-8023 (2020).\nYou, Q., Jiang, Z., Yue, X., Guo, W., Liu, Y., Cao, J., ... & Zhai, P. Recent frontiers of climate changes\nin East Asia at global warming of 1.5° C and 2° C. Npj Clim. Atmospheric Sci., 5(1), 80. (2022)"}, {"round": 3, "reviewer_comments": {"reviewer_2": "The authors have sufficiently addressed my comments in the last round. I found one typo and one minor error in their revised manuscript.\n1. in revised text: \"relafive higher than the mulfi-model averages of –1.23 ± 0.48 W/m2 in the Coupled Model Intercomparison Project Phase 5 (CMIP5)\". Here \"relafive\" should be \"relafively\".\n2. Figure S1capfion. There is an error in the order of (a)-(d).\n(a) and (b) are the mean and standard deviafion of temperature. (c) and (d) are for precipitafion."}, "author_response": "Reviewer #2:\nThe authors have sufficiently addressed my comments in the last round. I found one typo\nand one minor error in their revised manuscript.\n1. in revised text: \"relative higher than the multi-model averages of –1.23 ± 0.48 W/m2 in\nthe Coupled Model Intercomparison Project Phase 5 (CMIP5)\". Here \"relative\" should be\n\"relatively\".\nReply: Changed.\n2. Figure S11 caption. There is an error in the order of (a)-(d).\n(a) and (b) are the mean and standard deviation of temperature. (c) and (d) are for\nprecipitation.\nReply: Changed."}]

Decision letter