Search for: All records

Abstract The Regional Aerosol Model Intercomparison Project (RAMIP) is designed to quantify the forcing and climate impacts of mid-21st century anthropogenic aerosol and precursor gas (AA) emissions reductions (both industrial and biomass burning), by comparing a weak (SSP3-7.0) versus strong (SSP1-2.6) level of air quality control aerosol emissions pathway. AA emissions reductions experiments include global (GLO), East Asia (EAS), South Asia, Africa and the Middle East (AFR), and North America and Europe (NAE). Here, we use RAMIP time-slice simulations with fixed sea surface temperatures and sea-ice distributions from nine models to quantify the aerosol effective radiative forcing (ERF), including aerosol radiation (ERF_ari) and aerosol cloud interactions (ERF_aci). The multi-model global mean net ERF_ari+aciis $0.77\pm 0.25$W m⁻²for GLO, and three of the four regional perturbations yield a significant positive net ERF_ari+aci(up to $0.15\pm 0.07$W m⁻²for EAS). In all cases, net ERF_ari+aciis dominated by aerosol-cloud interactions, which are largely due to reduced cloud scattering. Of the four regions, NAE yields the largest forcing efficiency whereas AFR yields the weakest. Although the areas outside our four target regions contribute 25% to the GLO aerosol optical depth reduction, they disproportionately contribute 44% to the GLO net ERF_ari+aci. The multimodel regional mean net ERF_ari+acifor three regional perturbations is much larger (up to $1.64\pm 1.36$W m⁻²for EAS) than the corresponding global mean value. However, these regional values are even larger (up to $2.69\pm 1.72$W m⁻²for EAS) under global aerosol reductions, implying remote emission reductions represent a sizable contribution (up to $1.05\pm 0.56$W m⁻²for EAS). These large regional ERFs will in turn drive relatively large regional climate impacts, which continue to be underappreciated in most policy discussions. 

Abstract Global surface warming has accelerated since around 2010, relative to the preceding half century^1–3. This has coincided with East Asian efforts to reduce air pollution through restricted atmospheric aerosol and precursor emissions^4,5. A direct link between the two has, however, not yet been established. Here we show, using a large set of simulations from eight Earth System Models, how a time-evolving 75% reduction in East Asian sulfate emissions partially unmasks greenhouse gas-driven warming and influences the spatial pattern of surface temperature change. We find a rapidly evolving global, annual mean warming of 0.07 ± 0.05 °C, sufficient to be a main driver of the uptick in global warming rate since 2010. We also find North-Pacific warming and a top-of-atmosphere radiative imbalance that are qualitatively consistent with recent observations. East Asian aerosol cleanup is thus likely a key contributor to recent global warming acceleration and to Pacific warming trends. 

Abstract. Changes in anthropogenic aerosol emissions have strongly contributed to global and regional trends in temperature, precipitation, and other climate characteristics and have been one of the dominant drivers of decadal trends in Asian and African precipitation. These and other influences on regional climate from changes in aerosol emissions are expected to continue and potentially strengthen in the coming decades. However, a combination of large uncertainties in emission pathways, radiative forcing, and the dynamical response to forcing makes anthropogenic aerosol a key factor in the spread of near-term climate projections, particularly on regional scales, and therefore an important one to constrain. For example, in terms of future emission pathways, the uncertainty in future global aerosol and precursor gas emissions by 2050 is as large as the total increase in emissions since 1850. In terms of aerosol effective radiative forcing, which remains the largest source of uncertainty in future climate change projections, CMIP6 models span a factor of 5, from −0.3 to −1.5 W m−2. Both of these sources of uncertainty are exacerbated on regional scales. The Regional Aerosol Model Intercomparison Project (RAMIP) will deliver experiments designed to quantify the role of regional aerosol emissions changes in near-term projections. This is unlike any prior MIP, where the focus has been on changes in global emissions and/or very idealised aerosol experiments. Perturbing regional emissions makes RAMIP novel from a scientific standpoint and links the intended analyses more directly to mitigation and adaptation policy issues. From a science perspective, there is limited information on how realistic regional aerosol emissions impact local as well as remote climate conditions. Here, RAMIP will enable an evaluation of the full range of potential influences of realistic and regionally varied aerosol emission changes on near-future climate. From the policy perspective, RAMIP addresses the burning question of how local and remote decisions affecting emissions of aerosols influence climate change in any given region. Here, RAMIP will provide the information needed to make direct links between regional climate policies and regional climate change. RAMIP experiments are designed to explore sensitivities to aerosol type and location and provide improved constraints on uncertainties driven by aerosol radiative forcing and the dynamical response to aerosol changes. The core experiments will assess the effects of differences in future global and regional (Africa and the Middle East, East Asia, North America and Europe, and South Asia) aerosol emission trajectories through 2051, while optional experiments will test the nonlinear effects of varying emission locations and aerosol types along this future trajectory. All experiments are based on the shared socioeconomic pathways and are intended to be performed with 6th Climate Model Intercomparison Project (CMIP6) generation models, initialised from the CMIP6 historical experiments, to facilitate comparisons with existing projections. Requested outputs will enable the analysis of the role of aerosol in near-future changes in, for example, temperature and precipitation means and extremes, storms, and air quality.