RAMIP simulations and recent emissions changes in East Asia
We first document the emissions perturbation applied in the RAMIP baseline and East Asia simulations21 (see “Methods”), and compare them to the actual emissions reductions from the same region since around 2010. Briefly, RAMIP isolates the climate effects of aerosol emissions in one region by comparing two sets of transient emission simulations; one following a global, high emissions pathway (SSP3-7.0, which assumes weak air quality policies), and one where aerosol emissions in one region (East Asia, consisting mainly of mainland China emissions) have been replaced by those from a strong air quality policy trajectory (SSP1-2.6). See “Methods,” or21, for a full description. In the present analysis, we use simulations from 8 global models, each with 10 ensemble members, for a total of 80 ensemble members. This simulation set effectively samples both model uncertainty and internal climate variability.
Figure 1a shows changes in aerosol optical depth (AOD) retrieved by MODIS Terra and Aqua between the two previous decades. Consistent with previous literature, we find a dipole pattern consisting of an increase over India and a strong decrease over China following their air quality improvement initiatives. For comparison, Fig. 1b shows the pattern of AOD change between the RAMIP East Asia and baseline simulations, for the simulated period 2035–2049. Here, and elsewhere, this time period is chosen for RAMIP to sample the climate response after most of the emission reductions have occurred, while maximizing the number of years (RAMIP simulations end in 2050, so 2049 is the last year we can use while also letting the last DJF season run into the following year.) Fig. 1c, d shows the corresponding SO 2 emissions and AOD change, for observations and simulations, within the box labeled East Asia in Fig. 1a (a geographical box that covers the main emission regions).
Fig. 1: Observed changes in aerosol optical depth since 2010, and the corresponding changes in emissions and in the RAMIP model simulations. a AOD observations, difference between 2014–2023 and 2005–2014. Mean of MODIS Aqua and Terra. The Inset box shows the East Asia domain used throughout this paper. b Spatial distribution of AOD change in RAMIP. Multi-model (80 ensemble member) mean, difference between the East Asia and Baseline simulations. Hatching indicates statistical significance (see “Methods”). c Annual SO 2 emissions difference, relative to 2010, in CEDSv2024 (red), and between the two scenarios used by RAMIP (black). Mean over the East Asia domain. d AOD change, mean over the East Asia domain, from MODIS (red) and in RAMIP (black). The range is ±1 standard deviation of the RAMIP multi-model response. Full size image
For observations, relative to the 2005–2010 period, we find an AOD change of −0.13 units for the period 2014–2023, resulting primarily from emissions reductions of around 20 Tg SO 2 /year (Supplementary Fig. 1b). The emissions data are from the December 2024 release of the Community Emissions Data System (CEDS)22, which includes updated estimates of recent East Asian SO 2 emission changes. Concurrent changes in black carbon aerosol emissions are shown in Supplementary Fig. 1; they are smaller, in absolute terms and in particle number, and are not expected to contribute strongly to the AOD change, though they may influence climate features through their strong atmospheric shortwave absorption23.
RAMIP transient simulations start in 2015 but use CMIP6 emissions based on a CEDS version that projected a delayed reduction in East Asia emissions compared to the actual, realized changes. The RAMIP East Asia and baseline simulations, however, still have an emissions difference trajectory that broadly corresponds to recent observations (20 Tg SO 2 /year), for the last 15 years of the RAMIP simulations (2035–2049). In the following, we use this period to quantify RAMIP climate responses (see “Methods”). We also find a multi-model mean AOD change trajectory and magnitude that broadly tracks MODIS observations (∆AOD of −0.11 ± 0.05 units for the RAMIP period 2035–2049). We do note, however, that even though all models used the same emissions, the RAMIP 2035–2049 mean East Asia AOD change ranges from −0.08 to −0.28, and the local magnitudes do differ from MODIS observations (see Fig. S1). This is due to a combination of factors including the optical properties of the simulated aerosols, the cloud fields, wind and precipitation climatologies, and aerosol removal rates. See further discussion on model diversity below.
Physically, AOD decreases are associated with less scattering of incoming solar radiation and hence increases in downwelling surface solar radiation. Supplementary Fig. 1 shows the corresponding changes in downwelling shortwave radiation at the surface, in response to aerosol emissions reductions. Here, we find a multi-model mean change of 7.7 ± 2.5 Wm−2, over the East Asia domain, with inter-model variation and spatial pattern that broadly follow that of AOD.
Based on Fig. 1 and Supplementary Fig. 1, we conclude that the RAMIP East Asia results for the 2035–2049 period can be used as a proxy for the response to the emission rate change that has occurred in the real world over the 2010–2023 period (i.e., a 20 Tg/year sustained reduction in SO 2 emissions). We note that neither the overall conclusions nor the absolute numbers cited below are sensitive to changing the endpoints of these time periods by up to 2 years.
Modeled temperature and precipitation changes
In the RAMIP simulations, we find robust changes in both temperature and precipitation in response to East Asian aerosol emission reductions, with a mean change that extends beyond the interannual variability in the multi-model, multi-ensemble-member mean. In Fig. 2, we show the global, annual mean temperature responses to a 20 Tg/year reduction in SO 2 emissions from East Asia. For 2035–2049, we find a multi-model mean global warming of 0.07 ± 0.05 °C, where the uncertainty is the standard deviation of the eight individual model results. The signal evolves in overall correspondence with the emission reductions, indicating a rapid climate response to SO 2 emissions reductions, in line with previous studies24. The overall rate of change for the full 2015–2049 period is 0.02 °C/decade. Note also the strong inter-model variability (Fig. 2b), with one model (NorESM2-LM) showing an ensemble mean warming of 0.15 °C, while another outlier (GISS-E2-1-G) even shows a slight cooling (−0.02 °C). We link these model differences, in particular the outlier models, primarily to aerosol–cloud interactions in the North Pacific, and to Arctic amplification that is known to be strong both for Asian aerosol emissions, and for our warmest model (NorESM2-LM)25. See also Supplementary Fig. 2, and further discussion on the radiative responses of the models below.
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