Articles | Volume 24, issue 12
https://doi.org/10.5194/acp-24-7227-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-24-7227-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
25 Jun 2024
Research article |
| 25 Jun 2024
| 25 Jun 2024
Impact of Asian aerosols on the summer monsoon strongly modulated by regional precipitation biases
Earth, Ocean and Atmospheric Sciences (EOAS) Thrust, Function Hub, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, China
School of GeoSciences, University of Edinburgh, Edinburgh, UK
Massimo A. Bollasina
School of GeoSciences, University of Edinburgh, Edinburgh, UK
Laura J. Wilcox
Department of Meteorology, National Centre for Atmospheric Science, University of Reading, Reading, UK
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Karen E. Helliesen, Bosi Sheng, and Massimo A. Bollasina
EGUsphere, https://doi.org/10.5194/egusphere-2026-3557, https://doi.org/10.5194/egusphere-2026-3557, 2026
This preprint is open for discussion and under review for Weather and Climate Dynamics (WCD).
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Midlatitude storms follow preferred pathways known as storm tracks, which shift poleward and change in strength as the climate warms, affecting precipitation across the Northern Hemisphere. Winter changes are less certain due to natural climate fluctuations, while summer changes are more consistent. These findings have implications for regional storm track and rainfall projections and climate adaptation planning.
Feifei Luo, Manoj Joshi, Bjørn H. Samset, Laura J. Wilcox, Camilla W. Stjern, Robert J. Allen, Yan-Ning Kuo, Wei Hua, and Shuanglin Li
EGUsphere, https://doi.org/10.5194/egusphere-2026-3301, https://doi.org/10.5194/egusphere-2026-3301, 2026
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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This study examines if this impact changes in a warmer world. Using a climate model, we compare identical Asian emissions under cooler and 1 K warmer climates. Aerosols reduce extreme rainfall in both, but more strongly over northern India in the warmer climate. A warmer, stabler atmosphere weakens circulation that partly offsets aerosol drying in cooler conditions. Continued warming may strengthen this drying over parts of Asia, while future pollution cuts could amplify heavy rainfall.
Tianhui Zhou, Massimo A. Bollasina, and David S. Stevenson
EGUsphere, https://doi.org/10.5194/egusphere-2026-3416, https://doi.org/10.5194/egusphere-2026-3416, 2026
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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Future drought risk will be shaped not only by greenhouse-gas-driven warming, but also by changes in air-pollution-related emissions. We examine how reducing non-methane short-lived climate forcers affects future droughts characteristics. The Sahel, Middle East, and Central Asia face substantially worsened drought conditions. Our findings show that air-pollution mitigation can substantially increase future drought risk and population exposure in vulnerable regions.
Bosi Sheng, Massimo A. Bollasina, Alexandre S. Gagnon, Laura J. Wilcox, Thomas P. S. Reynolds, Christopher T. S. Beckett, Haolin Wang, Qingxiang Li, Pierre Nabat, Robert J. Allen, Bjørn H. Samset, Joonas Merikanto, Geeta G. Persad, Toshihiko Takemura, Kostas Tsigaridis, Sharar Ahmadi, Maxwell T. Elling, Knut von Salzen, Daniel M. Westervelt, Naga Oshima, and Tsuyoshi Koshiro
EGUsphere, https://doi.org/10.5194/egusphere-2026-2198, https://doi.org/10.5194/egusphere-2026-2198, 2026
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Observational records indicate that austral summer rainfall over southern Africa experienced substantial wetting during the late 20th century, followed by pronounced drying over the past two decades. We show that East Asian sulphate aerosol emissions played a key role in shaping these rainfall trends. These findings have important implications for reducing uncertainties in regional rainfall projections and for understanding their links to ecosystem changes.
Stephanie Fiedler, Fiona M. O'Connor, Duncan Watson-Parris, Robert J. Allen, William J. Collins, Paul T. Griffiths, Matthew Kasoar, Jarmo Kikstra, Jasper F. Kok, Lee T. Murray, Fabien Paulot, Maria Sand, Steven T. Turnock, James Weber, Laura J. Wilcox, and Vaishali Naik
Geosci. Model Dev., 19, 3477–3508, https://doi.org/10.5194/gmd-19-3477-2026, https://doi.org/10.5194/gmd-19-3477-2026, 2026
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The Aerosol and Chemistry Model Intercomparison Project phase two (AerChemMIP2) allows the community to compare results from contemporary Earth system models. AerChemMIP2 is asking modelling centres to perform experiments following the same protocol. It includes experiments for enabling new science and for tracking progress. Model output will be used for addressing research and policy questions about anthropogenic and natural drivers of climate change, and the impacts on air quality.
Beth Dingley, James A. Anstey, Marta Abalos, Carsten Abraham, Tommi Bergman, Lisa Bock, Sonya Fiddes, Birgit Hassler, Ryan J. Kramer, Fei Luo, Fiona M. O'Connor, Petr Šácha, Isla R. Simpson, Laura J. Wilcox, and Mark D. Zelinka
Geosci. Model Dev., 19, 2945–2984, https://doi.org/10.5194/gmd-19-2945-2026, https://doi.org/10.5194/gmd-19-2945-2026, 2026
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This manuscript defines as a list of variables and scientific opportunities which are requested from the Coupled Model Intercomparison Project Phase 7 (CMIP7) Assessment Fast Track to address open atmospheric science questions. The list reflects the output of a large public community engagement effort, coordinated across autumn 2025 through to summer 2025.
Chang Su, Massimo Bollasina, James Weber, and David Stevenson
EGUsphere, https://doi.org/10.5194/egusphere-2026-836, https://doi.org/10.5194/egusphere-2026-836, 2026
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Hot weather can strongly increase surface ozone, a harmful air pollutant, but the reasons differ between urban and rural areas. We studied a large city and a nearby rural region in eastern China using air quality observations and simplified chemistry modelling. We found that heat-driven plant emissions dominate ozone increases in the city, while chemical nitrogen cycling is key in the rural area. Our results help identify heat-resilient air pollution control strategies under climate change.
Weihao Sun, Massimo A. Bollasina, Ioana Colfescu, Guoxiong Wu, and Yimin Liu
Atmos. Chem. Phys., 26, 2027–2039, https://doi.org/10.5194/acp-26-2027-2026, https://doi.org/10.5194/acp-26-2027-2026, 2026
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Observational records show that the Asian monsoon underwent substantial changes during the early 20th century, including a wetting trend over South Asia and a southward shift in rainfall over East Asia. We show that increasing European sulphate aerosol emissions played a crucial role in shaping the monsoon rainfall trends. This has important implications for reducing uncertainties in monsoon projections, particularly in light of the diverse future aerosol emission scenarios for the region.
Catherine A. Toolan, Joe Adabouk Amooli, Laura J. Wilcox, Bjørn H. Samset, Andrew G. Turner, and Daniel M. Westervelt
Atmos. Chem. Phys., 25, 10523–10557, https://doi.org/10.5194/acp-25-10523-2025, https://doi.org/10.5194/acp-25-10523-2025, 2025
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Our research explores how well air pollution and rainfall patterns in Africa are represented in current climate models by comparing model data to observations from 1981 to 2023. While most models capture seasonal air quality changes well, they struggle to replicate the distribution of non-dust pollutants and certain rainfall patterns, especially over east Africa. Improving these models is crucial for better climate predictions and preparing for future risks.
Zixuan Jia, Massimo A. Bollasina, Wenjun Zhang, and Ying Xiang
Atmos. Chem. Phys., 25, 8805–8820, https://doi.org/10.5194/acp-25-8805-2025, https://doi.org/10.5194/acp-25-8805-2025, 2025
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Using multi-model mean data from regional aerosol perturbation experiments, we find that increased Asian sulfate aerosols strengthen the link between ENSO (El Niño–Southern Oscillation) and the East Asian winter monsoon. In coupled simulations, aerosol-induced broad cooling increases the ENSO amplitude by affecting the tropical Pacific mean state, contributing to the increase in monsoon interannual variability. These results provide important implications to reduce uncertainties in future projections of regional extreme variability.
Paul T. Griffiths, Laura J. Wilcox, Robert J. Allen, Vaishali Naik, Fiona M. O'Connor, Michael Prather, Alex Archibald, Florence Brown, Makoto Deushi, William Collins, Stephanie Fiedler, Naga Oshima, Lee T. Murray, Bjørn H. Samset, Chris Smith, Steven Turnock, Duncan Watson-Parris, and Paul J. Young
Atmos. Chem. Phys., 25, 8289–8328, https://doi.org/10.5194/acp-25-8289-2025, https://doi.org/10.5194/acp-25-8289-2025, 2025
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The Aerosol Chemistry Model Intercomparison Project (AerChemMIP) aimed to quantify the climate and air quality impacts of aerosols and chemically reactive gases. We review its contribution to AR6 (Sixth Assessment Report of the Intergovernmental Panel on Climate Change) and the wider understanding of the role of these species in climate and climate change. We identify challenges and provide recommendations to improve the utility and uptake of climate model data, detailed summary tables of CMIP6 models, experiments, and emergent diagnostics.
Feifei Luo, Bjørn H. Samset, Camilla W. Stjern, Manoj Joshi, Laura J. Wilcox, Robert J. Allen, Wei Hua, and Shuanglin Li
Atmos. Chem. Phys., 25, 7647–7667, https://doi.org/10.5194/acp-25-7647-2025, https://doi.org/10.5194/acp-25-7647-2025, 2025
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Black carbon (BC) aerosol is emitted from the incomplete combustion of biomass and fossil fuels. We found that Asian BC leads to strong local cooling and drying. Reductions in precipitation primarily depend on the thermodynamic effects due to solar radiation absorption by BC. The combined thermodynamic and dynamic effects shape the spatial pattern of precipitation responses to Asian BC. These results help us further understand the impact of emissions of anthropogenic aerosols on Asian climate.
Wah Kin Michael Lai, Jon Robson, Laura Wilcox, Nick Dunstone, and Rowan Sutton
EGUsphere, https://doi.org/10.5194/egusphere-2025-2598, https://doi.org/10.5194/egusphere-2025-2598, 2025
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In a climate model at two different resolutions, anthropogenic aerosols induce a fast cooling followed by a delayed warming in the subpolar North Atlantic. The delayed warming is stronger at higher resolution due to a stronger Atlantic Meridional Overturning Circulation (AMOC) response. This difference is due to the lower resolution model having more sea ice which insulates the ocean. This result show that the North Atlantic response to external forcing is sensitive to regional differences.
Duncan Watson-Parris, Laura J. Wilcox, Camilla W. Stjern, Robert J. Allen, Geeta Persad, Massimo A. Bollasina, Annica M. L. Ekman, Carley E. Iles, Manoj Joshi, Marianne T. Lund, Daniel McCoy, Daniel M. Westervelt, Andrew I. L. Williams, and Bjørn H. Samset
Atmos. Chem. Phys., 25, 4443–4454, https://doi.org/10.5194/acp-25-4443-2025, https://doi.org/10.5194/acp-25-4443-2025, 2025
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In 2020, regulations by the International Maritime Organization aimed to reduce aerosol emissions from ships. These aerosols previously had a cooling effect, which the regulations might reduce, revealing more greenhouse gas warming. Here we find that, while there is regional warming, the global 2020–2040 temperature rise is only +0.03 °C. This small change is difficult to distinguish from natural climate variability, indicating the regulations have had a limited effect on observed warming to date.
Alcide Zhao, Laura J. Wilcox, and Claire L. Ryder
Atmos. Chem. Phys., 24, 13385–13402, https://doi.org/10.5194/acp-24-13385-2024, https://doi.org/10.5194/acp-24-13385-2024, 2024
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Climate models include desert dust aerosols, which cause atmospheric heating and can change circulation patterns. We assess the effect of dust on the Indian and east Asian summer monsoons through multi-model experiments isolating the effect of dust in current climate models for the first time. Dust atmospheric heating results in a southward shift of western Pacific equatorial rainfall and an enhanced Indian summer monsoon. This shows the importance of accurate dust representation in models.
Stephanie Fiedler, Vaishali Naik, Fiona M. O'Connor, Christopher J. Smith, Paul Griffiths, Ryan J. Kramer, Toshihiko Takemura, Robert J. Allen, Ulas Im, Matthew Kasoar, Angshuman Modak, Steven Turnock, Apostolos Voulgarakis, Duncan Watson-Parris, Daniel M. Westervelt, Laura J. Wilcox, Alcide Zhao, William J. Collins, Michael Schulz, Gunnar Myhre, and Piers M. Forster
Geosci. Model Dev., 17, 2387–2417, https://doi.org/10.5194/gmd-17-2387-2024, https://doi.org/10.5194/gmd-17-2387-2024, 2024
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Climate scientists want to better understand modern climate change. Thus, climate model experiments are performed and compared. The results of climate model experiments differ, as assessed in the latest Intergovernmental Panel on Climate Change (IPCC) assessment report. This article gives insights into the challenges and outlines opportunities for further improving the understanding of climate change. It is based on views of a group of experts in atmospheric composition–climate interactions.
Joseph Smith, Cathryn Birch, John Marsham, Simon Peatman, Massimo Bollasina, and George Pankiewicz
Nat. Hazards Earth Syst. Sci., 24, 567–582, https://doi.org/10.5194/nhess-24-567-2024, https://doi.org/10.5194/nhess-24-567-2024, 2024
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Nowcasting uses observations to make predictions of the atmosphere on short timescales and is particularly applicable to the Maritime Continent, where storms rapidly develop and cause natural disasters. This paper evaluates probabilistic and deterministic satellite nowcasting algorithms over the Maritime Continent. We show that the probabilistic approach is most skilful at small scales (~ 60 km), whereas the deterministic approach is most skilful at larger scales (~ 200 km).
Laura J. Wilcox, Robert J. Allen, Bjørn H. Samset, Massimo A. Bollasina, Paul T. Griffiths, James Keeble, Marianne T. Lund, Risto Makkonen, Joonas Merikanto, Declan O'Donnell, David J. Paynter, Geeta G. Persad, Steven T. Rumbold, Toshihiko Takemura, Kostas Tsigaridis, Sabine Undorf, and Daniel M. Westervelt
Geosci. Model Dev., 16, 4451–4479, https://doi.org/10.5194/gmd-16-4451-2023, https://doi.org/10.5194/gmd-16-4451-2023, 2023
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Changes in anthropogenic aerosol emissions have strongly contributed to global and regional climate change. However, the size of these regional impacts and the way they arise are still uncertain. With large changes in aerosol emissions a possibility over the next few decades, it is important to better quantify the potential role of aerosol in future regional climate change. The Regional Aerosol Model Intercomparison Project will deliver experiments designed to facilitate this.
Andrew P. Schurer, Gabriele C. Hegerl, Hugues Goosse, Massimo A. Bollasina, Matthew H. England, Michael J. Mineter, Doug M. Smith, and Simon F. B. Tett
Clim. Past, 19, 943–957, https://doi.org/10.5194/cp-19-943-2023, https://doi.org/10.5194/cp-19-943-2023, 2023
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We adopt an existing data assimilation technique to constrain a model simulation to follow three important modes of variability, the North Atlantic Oscillation, El Niño–Southern Oscillation and the Southern Annular Mode. How it compares to the observed climate is evaluated, with improvements over simulations without data assimilation found over many regions, particularly the tropics, the North Atlantic and Europe, and discrepancies with global cooling following volcanic eruptions are reconciled.
Nora L. S. Fahrenbach and Massimo A. Bollasina
Atmos. Chem. Phys., 23, 877–894, https://doi.org/10.5194/acp-23-877-2023, https://doi.org/10.5194/acp-23-877-2023, 2023
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We studied the monthly-scale climate response to COVID-19 aerosol emission reductions during January–May 2020 using climate models. Our results show global temperature and rainfall anomalies driven by circulation changes. The climate patterns reverse polarity from JF to MAM due to a shift in the main SO2 reduction region from China to India. This real-life example of rapid climate adjustments to abrupt, regional aerosol emission reduction has large implications for future climate projections.
Alcide Zhao, Claire L. Ryder, and Laura J. Wilcox
Atmos. Chem. Phys., 22, 2095–2119, https://doi.org/10.5194/acp-22-2095-2022, https://doi.org/10.5194/acp-22-2095-2022, 2022
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The CMIP6 models' simulated dust processes are getting more uncertain as models become more sophisticated. Of particular challenge are the links between dust cycles and optical properties, and we recommend more detailed output relating to dust cycles in future intercomparison projects to constrain such links. Also, models struggle to capture certain key regional dust processes such as dust accumulation along the slope of the Himalayas and dust seasonal cycles in North China and North America.
Jie Zhang, Kalli Furtado, Steven T. Turnock, Jane P. Mulcahy, Laura J. Wilcox, Ben B. Booth, David Sexton, Tongwen Wu, Fang Zhang, and Qianxia Liu
Atmos. Chem. Phys., 21, 18609–18627, https://doi.org/10.5194/acp-21-18609-2021, https://doi.org/10.5194/acp-21-18609-2021, 2021
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The CMIP6 ESMs systematically underestimate TAS anomalies in the NH midlatitudes, especially from 1960 to 1990. The anomalous cooling is concurrent in time and space with anthropogenic SO2 emissions. The spurious drop in TAS is attributed to the overestimated aerosol concentrations. The aerosol forcing sensitivity cannot well explain the inter-model spread of PHC biases. And the cloud-amount term accounts for most of the inter-model spread in aerosol forcing sensitivity.
Liang Guo, Laura J. Wilcox, Massimo Bollasina, Steven T. Turnock, Marianne T. Lund, and Lixia Zhang
Atmos. Chem. Phys., 21, 15299–15308, https://doi.org/10.5194/acp-21-15299-2021, https://doi.org/10.5194/acp-21-15299-2021, 2021
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Severe haze remains serious over Beijing despite emissions decreasing since 2008. Future haze changes in four scenarios are studied. The pattern conducive to haze weather increases with the atmospheric warming caused by the accumulation of greenhouse gases. However, the actual haze intensity, measured by either PM2.5 or optical depth, decreases with aerosol emissions. We show that only using the weather pattern index to predict the future change of Beijing haze is insufficient.
Cited articles
Adler, R. F., Huffman, G. J., Chang, A., Ferraro, R., Xie, P. P., Janowiak, J., Rudolf, B., Schneider, U., Curtis, S., Bolvin, D., Gruber, A., Susskind, J., Arkin, P., and Nelkin, E.: The version-2 global precipitation climatology project (GPCP) monthly precipitation analysis (1979–present), J. Hydrometeorol., 4, 1147–1167, https://doi.org/10.1175/1525-7541(2003)004<1147:TVGPCP>2.0.CO;2, 2003 (data available at: https://psl.noaa.gov/data/gridded/data.gpcp.html, last access: 19 June 2024).
Albrecht, B. A.: Aerosols, cloud microphysics, and fractional cloudiness, Science, 245, 1227–1230, https://doi.org/10.1126/science.245.4923.1227, 1989.
An, Z., Colman, S. M., Zhou, W., Li, X., Brown, E. T., Jull, A. J. T., Cai, Y., Huang, Y., Lu, X., Chang, H., Song, Y., Sun, Y., Xu, H., Liu, W., Jin, Z., Liu, X., Cheng, P., Liu, Y., Ai, L., Li, X., Liu, X., Yan, L., Shi, Z., Wang, X., Wu, F., Qiang, X., Dong, J., Lu, F., and Xu, X.: Interplay between the Westerlies and Asian monsoon recorded in Lake Qinghai sediments since 32 ka, Sci. Rep., 2, 619, https://doi.org/10.1038/srep00619, 2012.
Andrews, T. and Forster, P. M.: Energy budget constraints on historical radiative forcing, Nat. Clim. Change, 10, 313–316, https://doi.org/10.1038/s41558-020-0696-1, 2020.
Andrews, T., Boucher, O., Fläschner, D., Kasoar, M., Kharin, V., Kirkevåg, A., Lamarque, J.-F., Myhre, G., Mülmenstädt, J., Oliviè, D. J. L., Samset, B., Sandstad, M., Shawki, D., Shindell, D., Stier, P., Takemura, T., Voulgarakis, A., and Watson-Parris, D.: Precipitation Driver Response Model Intercomparison Project data sets 2013–2021, World Data Center for Climate (WDCC) at DKRZ [data set], https://doi.org/10.26050/WDCC/PDRMIP_2012-2021, 2021.
Bartlett, R. E., Bollasina, M. A., Booth, B. B. B., Dunstone, N. J., Marenco, F., Messori, G., and Bernie, D. J.: Do differences in future sulfate emission pathways matter for near-term climate? A case study for the Asian monsoon, Clim. Dynam., 50, 1863–1880, https://doi.org/10.1007/s00382-017-3726-6, 2018.
Bastin, S., Drobinski, P., Chiriaco, M., Bock, O., Roehrig, R., Gallardo, C., Conte, D., Domínguez Alonso, M., Li, L., Lionello, P., and Parracho, A. C.: Impact of humidity biases on light precipitation occurrence: observations versus simulations, Atmos. Chem. Phys., 19, 1471–1490, https://doi.org/10.5194/acp-19-1471-2019, 2019.
Bellouin, N., Mann, G. W., Woodhouse, M. T., Johnson, C., Carslaw, K. S., and Dalvi, M.: Impact of the modal aerosol scheme GLOMAP-mode on aerosol forcing in the Hadley Centre Global Environmental Model, Atmos. Chem. Phys., 13, 3027–3044, https://doi.org/10.5194/acp-13-3027-2013, 2013.
Bollasina, M. and Nigam, S.: Indian Ocean SST, evaporation, and precipitation during the South Asian summer monsoon in IPCC-AR4 coupled simulations, Clim. Dynam., 33, 1017–1032, https://doi.org/10.1007/s00382-008-0477-4, 2009.
Bollasina, M. A., Ming, Y., and Ramaswamy, V.: Anthropogenic aerosols and the weakening of the south asian summer monsoon, Science, 334, 502–505, https://doi.org/10.1126/science.1204994, 2011.
Bollasina, M. A., Ming, Y., and Ramaswamy, V.: Earlier onset of the Indian monsoon in the late twentieth century: The role of anthropogenic aerosols, Geophys. Res. Lett., 40, 3715–3720, https://doi.org/10.1002/grl.50719, 2013.
Bollasina, M. A., Ming, Y., Ramaswamy, V., Schwarzkopf, M. D., and Naik, V.: Contribution of local and remote anthropogenic aerosols to the twentieth century weakening of the South Asian Monsoon, Geophys. Res. Lett., 41, 680–687, https://doi.org/10.1002/2013GL058183, 2014.
Boucher, O., Randall, D., Artaxo, P., Bretherton, C., Feingold, G., Forster, P., Kerminen, V.-M., Kondo, Y., Liao, H., Lohmann, U., Rasch, P., Satheesh, S. K., Sherwood, S., Stevens, B., and Zhang, X. Y.: IPCC: Clouds and Aerosols, in: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, UK, https://doi.org/10.1017/CBO9781107415324.016, 2013.
Boutle, I. A., Eyre, J. E. J., and Lock, A. P.: Seamless Stratocumulus Simulation across the Turbulent Gray Zone, Mon. Weather Rev., 142, 1655–1668, https://doi.org/10.1175/MWR-D-13-00229.1, 2014a.
Boutle, I. A., Abel, S. J., Hill, P. G., and Morcrette, C. J.: Spatial variability of liquid cloud and rain: observations and microphysical effects, Q. J. Roy. Meteor. Soc., 140, 583–594, https://doi.org/10.1002/qj.2140, 2014b.
Cao, J., Wang, B., Wang, B., Zhao, H., Wang, C., and Han, Y.: Sources of the Intermodel Spread in Projected Global Monsoon Hydrological Sensitivity, Geophys. Res. Lett., 47, e2020GL089560, https://doi.org/10.1029/2020GL089560, 2020.
Chadwick, R.: Which aspects of CO2 forcing and SST warming cause most uncertainty in projections of tropical rainfall change over land and ocean?, J. Climate, 29, 2493–2509, https://doi.org/10.1175/JCLI-D-15-0777.1, 2016.
Chen, X., Wu, P., Roberts, M. J., and Zhou, T.: Potential underestimation of future Mei-Yu Rainfall with coarse-resolution climate models, J. Climate, 31, 6711–6727, https://doi.org/10.1175/JCLI-D-17-0741.1, 2018.
Christidis, N., Stott, P. A., Scaife, A. A., Arribas, A., Jones, G. S., Copsey, D., Knight, J. R., and Tennant, W. J.: A new HADGEM3-a-based system for attribution of weather- and climate-related extreme events, J. Climate, 26, 2756–2783, https://doi.org/10.1175/JCLI-D-12-00169.1, 2013.
Chung, C. E. and Ramanathan, V.: Weakening of north Indian SST gradients and the monsoon rainfall in India and the Sahel, J. Climate, 19, 2036–2045, https://doi.org/10.1175/JCLI3820.1, 2006.
Cowan, T. and Cai, W.: The impact of Asian and non-Asian anthropogenic aerosols on 20th century Asian summer monsoon, Geophys. Res. Lett., 38, L11703, https://doi.org/10.1029/2011GL047268, 2011.
Dai, L., Cheng, T. F., and Lu, M.: Anthropogenic warming disrupts intraseasonal monsoon stages and brings dry-get-wetter climate in future East Asia, npj Clim. Atmos. Sci., 5, 11, https://doi.org/10.1038/s41612-022-00235-9, 2022.
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., Mcnally, A. P., Monge-Sanz, B. M., Morcrette, J. J., Park, B. K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J. N., and Vitart, F.: The ERA-Interim reanalysis: Configuration and performance of the data assimilation system, Q. J. Roy. Meteor. Soc., 137, 553–597, https://doi.org/10.1002/qj.828, 2011 (data aavailable at: https://www.ecmwf.int/en/forecasts/dataset/ecmwf-reanalysis-interim, last access: 19 June 2024).
Deser, C., Phillips, A., Bourdette, V., and Teng, H.: Uncertainty in climate change projections: The role of internal variability, Clim. Dynam., 38, 527–546, https://doi.org/10.1007/s00382-010-0977-x, 2012.
Dong, B., Sutton, R. T., Highwood, E. J., and Wilcox, L. J.: Preferred response of the East Asian summer monsoon to local and non-local anthropogenic sulphur dioxide emissions, Clim. Dynam., 46, 1733–1751, https://doi.org/10.1007/s00382-015-2671-5, 2016.
Dong, B., Wilcox, L. J., Highwood, E. J., and Sutton, R. T.: Impacts of recent decadal changes in Asian aerosols on the East Asian summer monsoon: roles of aerosol–radiation and aerosol–cloud interactions, Clim. Dynam., 53, 3235–3256, https://doi.org/10.1007/s00382-019-04698-0, 2019.
Efron, B. and Tibshirani, R. J.: An introduction to the bootstrap, Monographs on Statistics and Applied Probability, Vol. 57, Chapman and Hall, London, p. 436, https://doi.org/10.1111/1467-9639.00050, 1993.
Fang, C., Haywood, J. M., Liang, J., Johnson, B. T., Chen, Y., and Zhu, B.: Impacts of reducing scattering and absorbing aerosols on the temporal extent and intensity of South Asian summer monsoon and East Asian summer monsoon, Atmos. Chem. Phys., 23, 8341–8368, https://doi.org/10.5194/acp-23-8341-2023, 2023.
Fläschner, D., Mauritsen, T., and Stevens, B.: Understanding the intermodel spread in global-mean hydrological sensitivity, J. Climate, 29, 801–817, https://doi.org/10.1175/JCLI-D-15-0351.1, 2016.
Ganguly, D., Rasch, P. J., Wang, H., and Yoon, J. H.: Fast and slow responses of the South Asian monsoon system to anthropogenic aerosols, Geophys. Res. Lett., 39, L18804, https://doi.org/10.1029/2012GL053043, 2012.
Gong, D.-Y. and Ho, C.-H.: Shift in the summer rainfall over the Yangtze River valley in the late 1970s, Geophys. Res. Lett., 29, 78-1–78-4, https://doi.org/10.1029/2001gl014523, 2002.
Gregory, D. and Rowntree, P. R.: A Mass Flux Convection Scheme with Representation of Cloud Ensemble Characteristics and Stability-Dependent Closure, Mon. Weather Rev., 118, 1483–1506, https://doi.org/10.1175/1520-0493(1990)118<1483:AMFCSW>2.0.CO;2, 1990.
Gu, Y., Liou, K. N., Xue, Y., Mechoso, C. R., Li, W., and Luo, Y.: Climatic effects of different aerosol types in China simulated by the UCLA general circulation model, J. Geophys. Res.-Atmos., 111, D15201, https://doi.org/10.1029/2005JD006312, 2006.
Guilbert, M., Terray, P., and Mignot, J.: Intermodel spread of historical Indian monsoon rainfall change in CMIP6: The role of the tropical Pacific mean-state, J. Climate, 1, 1–42, https://doi.org/10.1175/JCLI-D-22-0585.1, 2023.
Guo, L., Highwood, E. J., Shaffrey, L. C., and Turner, A. G.: The effect of regional changes in anthropogenic aerosols on rainfall of the East Asian Summer Monsoon, Atmos. Chem. Phys., 13, 1521–1534, https://doi.org/10.5194/acp-13-1521-2013, 2013.
Guo, L., Turner, A. G., and Highwood, E. J.: Impacts of 20th century aerosol emissions on the South Asian monsoon in the CMIP5 models, Atmos. Chem. Phys., 15, 6367–6378, https://doi.org/10.5194/acp-15-6367-2015, 2015.
Han, Y., Zhang, M. Z., Xu, Z., and Guo, W.: Assessing the performance of 33 CMIP6 models in simulating the large-scale environmental fields of tropical cyclones, Clim. Dynam., 58, 1683–1698, https://doi.org/10.1007/s00382-021-05986-4, 2022.
He, J. and Soden, B. J.: The impact of SST biases on projections of anthropogenic climate change: A greater role for atmosphere-only models?, Geophys. Res. Lett., 43, 7745–7750, https://doi.org/10.1002/2016GL069803, 2016.
He, L., Zhou, T., and Chen, X.: South Asian summer rainfall from CMIP3 to CMIP6 models: biases and improvements, Clim. Dynam., 61, 1049–1061, https://doi.org/10.1007/s00382-022-06542-4, 2022.
Herbert, R., Wilcox, L. J., Joshi, M., Highwood, E., and Frame, D.: Nonlinear response of Asian summer monsoon precipitation to emission reductions in South and East Asia, Environ. Res. Lett., 17, 014005, https://doi.org/10.1088/1748-9326/ac3b19, 2022.
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J. N.: The ERA5 global reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020 (data available at: https://www.ecmwf.int/en/forecasts/dataset/ecmwf-reanalysis-v5, last access: 18 June 2024).
Hoesly, R. M., Smith, S. J., Feng, L., Klimont, Z., Janssens-Maenhout, G., Pitkanen, T., Seibert, J. J., Vu, L., Andres, R. J., Bolt, R. M., Bond, T. C., Dawidowski, L., Kholod, N., Kurokawa, J.-I., Li, M., Liu, L., Lu, Z., Moura, M. C. P., O'Rourke, P. R., and Zhang, Q.: Historical (1750–2014) anthropogenic emissions of reactive gases and aerosols from the Community Emissions Data System (CEDS), Geosci. Model Dev., 11, 369–408, https://doi.org/10.5194/gmd-11-369-2018, 2018.
Huang, X., Zhou, T., Dai, A., Li, H., Li, C., Chen, X., Lu, J., von Storch, J. S., and Wu, B.: South Asian summer monsoon projections constrained by the interdecadal Pacific oscillation, Science Advances, 6, eaay6546, https://doi.org/10.1126/sciadv.aay6546, 2020a.
Huang, X., Zhou, T., Turner, A., Dai, A., Chen, X., Clark, R., Jiang, J., Man, W., Murphy, J., Rostron, J., Wu, B., Zhang, L., Zhang, W., and Zou, L.: The recent decline and recovery of Indian summer monsoon rainfall: Relative roles of external forcing and internal variability, J. Climate, 33, 5035–5060, https://doi.org/10.1175/JCLI-D-19-0833.1, 2020b.
Jiang, D., Hu, D., Tian, Z., and Lang, X.: Differences between CMIP6 and CMIP5 Models in Simulating Climate over China and the East Asian Monsoon, Adv. Atmos. Sci., 37, 1102–1118, https://doi.org/10.1007/s00376-020-2034-y, 2020.
Jiang, Y., Liu, X., Yang, X. Q., and Wang, M.: A numerical study of the effect of different aerosol types on East Asian summer clouds and precipitation, Atmos. Environ., 70, 51–63, https://doi.org/10.1016/j.atmosenv.2012.12.039, 2013.
Jin, Q. and Wang, C.: A revival of Indian summer monsoon rainfall since 2002, Nat. Clim. Change, 7, 587–594, https://doi.org/10.1038/NCLIMATE3348, 2017.
John, V. O. and Soden, B. J.: Temperature and humidity biases in global climate models and their impact on climate feedbacks, Geophys. Res. Lett., 34, L18704, https://doi.org/10.1029/2007GL030429, 2007.
Kooperman, G. J., Pritchard, M. S., Ghan, S. J., Wang, M., Somerville, R. C. J., and Russell, L. M.: Constraining the influence of natural variability to improve estimates of global aerosol indirect effects in a nudged version of the Community Atmosphere Model 5, J. Geophys. Res.-Atmos., 117, D23204, https://doi.org/10.1029/2012JD018588, 2012.
Krinner, G. and Flanner, M. G.: Striking stationarity of large-scale climate model bias patterns under strong climate change, P. Natl. Acad. Sci. USA, 115, 9462–9466, https://doi.org/10.1073/pnas.1807912115, 2018.
Lau, K. M. and Kim, K. M.: Observational relationships between aerosol and Asian monsoon rainfall, and circulation, Geophys. Res. Lett., 33, L21810, https://doi.org/10.1029/2006GL027546, 2006.
Lau, W. K. M. and Kim, K. M.: Fingerprinting the impacts of aerosols on long-term trends of the Indian summer monsoon regional rainfall, Geophys. Res. Lett., 37, L16705, https://doi.org/10.1029/2010GL043255, 2010.
Li, X., Ting, M., and Lee, D. E.: Fast Adjustments of the Asian Summer Monsoon to Anthropogenic Aerosols, Geophys. Res. Lett., 45, 1001–1010, https://doi.org/10.1002/2017GL076667, 2018.
Li, X., Ting, M., You, Y., Lee, D. E., Westervelt, D. M., and Ming, Y.: South Asian Summer Monsoon Response to Aerosol-Forced Sea Surface Temperatures, Geophys. Res. Lett., 47, e2019GL085329, https://doi.org/10.1029/2019GL085329, 2020.
Lin, J., Tong, D., Davis, S., Ni, R., Tan, X., Pan, D., Zhao, H., Lu, Z., Streets, D., Feng, T., Zhang, Q., Yan, Y., Hu, Y., Li, J., Liu, Z., Jiang, X., Geng, G., He, K., Huang, Y., and Guan, D.: Global climate forcing of aerosols embodied in international trade, Nat. Geosci., 9, 790–794, https://doi.org/10.1038/ngeo2798, 2016.
Lin, R., Zhu, J., and Zheng, F.: Decadal shifts of East Asian summer monsoon in a climate model free of explicit GHGs and aerosols, Sci. Rep., 6, 38546, https://doi.org/10.1038/srep38546, 2016.
Liu, C., Yang, Y., Wang, H., Ren, L., Wei, J., Wang, P., and Liao, H.: Influence of Spatial Dipole Pattern in Asian Aerosol Changes on East Asian Summer Monsoon, J. Climate, 36, 1575–1585, https://doi.org/10.1175/JCLI-D-22-0335.1, 2023.
Liu, L., Shawki, D., Voulgarakis, A., Kasoar, M., Samset, B. H., Myhre, G., Forster, P. M., Hodnebrog, Sillmann, J., Aalbergsjø, S. G., Boucher, O., Faluvegi, G., Iversen, T., Kirkevåg, A., Lamarque, J. F., Olivié, D., Richardson, T., Shindell, D., and Takemura, T.: A PDRMIP Multimodel study on the impacts of regional aerosol forcings on global and regional precipitation, J. Climate, 31, 4429–4447, https://doi.org/10.1175/JCLI-D-17-0439.1, 2018.
Liu, Z., Bollasina, M. A., Wilcox, L. J., Rodríguez, J. M., and Regayre, L. A.: Contrasting the Role of Regional and Remote Circulation in Driving Asian Monsoon Biases in MetUM GA7.1, J. Geophys. Res.-Atmos., 126, 126, e2020JD034342, https://doi.org/10.1029/2020JD034342, 2021.
Liu, Z., Lee, S.-S., Nellikkattil, A. B., Lee, J.-Y., Dai, L., Ha, K.-J., and Franzke, C. L. E.: The East Asian Summer Monsoon Response to Global Warming in a High Resolution Coupled Model: Mean and Extremes, Asia-Pac. J. Atmos. Sci. 2022, 1–17, https://doi.org/10.1007/S13143-022-00285-2, 2022.
Lock, A. P., Brown, A. R., Bush, M. R., Martin, G. M., and Smith, R. N. B.: A New Boundary Layer Mixing Scheme. Part I: Scheme Description and Single-Column Model Tests, Mon. Weather Rev., 128, 3187–3199, https://doi.org/10.1175/1520-0493(2000)128<3187:ANBLMS>2.0.CO;2, 2000.
Lund, M. T., Myhre, G., and Samset, B. H.: Anthropogenic aerosol forcing under the Shared Socioeconomic Pathways, Atmos. Chem. Phys., 19, 13827–13839, https://doi.org/10.5194/acp-19-13827-2019, 2019.
Mann, G. W., Carslaw, K. S., Spracklen, D. V., Ridley, D. A., Manktelow, P. T., Chipperfield, M. P., Pickering, S. J., and Johnson, C. E.: Description and evaluation of GLOMAP-mode: a modal global aerosol microphysics model for the UKCA composition-climate model, Geosci. Model Dev., 3, 519–551, https://doi.org/10.5194/gmd-3-519-2010, 2010.
Matsueda, M. and Palmer, T. N.: Accuracy of climate change predictions using high resolution simulations as surrogates of truth, Geophys. Res. Lett., 38, L05803, https://doi.org/10.1029/2010GL046618, 2011.
Menon, S., Hansen, J., Nazarenko, L., and Luo, Y.: Climate effects of black carbon aerosols in China and India, Science, 297, 2250–2253, https://doi.org/10.1126/science.1075159, 2002a.
Menon, S., Del Genio, A. D., Koch, D., and Tselioudis, G.: GCM simulations of the aerosol indirect effect: Sensitivity to cloud parameterization and aerosol Burden, J. Atmos. Sci., 59, 692–713, https://doi.org/10.1175/1520-0469(2002)059<0692:gsotai>2.0.co;2, 2002b.
Monerie, P. A., Wilcox, L. J., and Turner, A. G.: Effects of Anthropogenic Aerosol and Greenhouse Gas Emissions on Northern Hemisphere Monsoon Precipitation: Mechanisms and Uncertainty, J. Climate, 35, 2305–2326, https://doi.org/10.1175/JCLI-D-21-0412.1, 2022.
Myhre, G., Forster, P. M., Samset, B. H., Hodnebrog, Sillmann, J., Aalbergsjø, S. G., Andrews, T., Boucher, O., Faluvegi, G., Fläschner, D., Iversen, T., Kasoar, M., Kharin, V., Kirkevag, A., Lamarque, J. F., Olivié, D., Richardson, T. B., Shindell, D., Shine, K. P., Stjern, C. W., Takemura, T., Voulgarakis, A., and Zwiers, F.: PDRMIP: A precipitation driver and response model intercomparison project-protocol and preliminary results, B. Am. Meteorol. Soc., 98, 1185–1198, https://doi.org/10.1175/BAMS-D-16-0019.1, 2017.
Park, M. and Lee, S.: Is the Stationary Wave Bias in CMIP5 Simulations Driven by Latent Heating Biases?, Geophys. Res. Lett., 48, e2020GL091678, https://doi.org/10.1029/2020GL091678, 2021.
Pillai, P. A., Rao, S. A., Srivastava, A., Ramu, D. A., Pradhan, M., and Das, R. S.: Impact of the tropical Pacific SST biases on the simulation and prediction of Indian summer monsoon rainfall in CFSv2, ECMWF-System4, and NMME models, Clim. Dynam., 56, 1699–1715, https://doi.org/10.1007/s00382-020-05555-1, 2021.
Rajendran, K., Surendran, S., Varghese, S. J., and Sathyanath, A.: Simulation of Indian summer monsoon rainfall, interannual variability and teleconnections: evaluation of CMIP6 models, Clim. Dynam., 58, 2693–2723, https://doi.org/10.1007/s00382-021-06027-w, 2022.
Seager, R., Naik, N., and Vecchi, G. A.: Thermodynamic and dynamic mechanisms for large-scale changes in the hydrological cycle in response to global warming, J. Climate, 23, 4651–4668, https://doi.org/10.1175/2010JCLI3655.1, 2010.
Samset, B. H., Myhre, G., Forster, P. M., Hodnebrog, Andrews, T., Faluvegi, G., Fläschner, D., Kasoar, M., Kharin, V., Kirkevåg, A., Lamarque, J. F., Olivié, D., Richardson, T., Shindell, D., Shine, K. P., Takemura, T., and Voulgarakis, A.: Fast and slow precipitation responses to individual climate forcers: A PDRMIP multimodel study, Geophys. Res. Lett., 43, 2782–2791, https://doi.org/10.1002/2016GL068064, 2016.
Samset, B. H., Lund, M. T., Bollasina, M., Myhre, G., and Wilcox, L.: Emerging Asian aerosol patterns, Nat. Geosci., 12, 582–584, https://doi.org/10.1038/s41561-019-0424-5, 2019.
Sato, Y., Goto, D., Michibata, T., Suzuki, K., Takemura, T., Tomita, H., and Nakajima, T.: Aerosol effects on cloud water amounts were successfully simulated by a global cloud-system resolving model, Nat. Commun., 9, 985, https://doi.org/10.1038/s41467-018-03379-6, 2018.
Sherman, P., Gao, M., Song, S., Archibald, A. T., Abraham, N. L., Lamarque, J.-F., Shindell, D., Faluvegi, G., and McElroy, M. B.: Sensitivity of modeled Indian monsoon to Chinese and Indian aerosol emissions, Atmos. Chem. Phys., 21, 3593–3605, https://doi.org/10.5194/acp-21-3593-2021, 2021.
Singh, D., Bollasina, M., Ting, M., and Diffenbaugh, N. S.: Disentangling the influence of local and remote anthropogenic aerosols on South Asian monsoon daily rainfall characteristics, Clim. Dynam., 52, 6301–6320, https://doi.org/10.1007/s00382-018-4512-9, 2019.
Soden, B. and Chung, E.-S.: The Large-Scale Dynamical Response of Clouds to Aerosol Forcing, J. Climate, 30, 8783–8794, https://doi.org/10.1175/JCLI-D-17-0050.1, 2017.
Song, F. and Zhou, T.: The climatology and interannual variability of east Asian summer monsoon in CMIP5 coupled models: Does air-sea coupling improve the simulations?, J. Climate, 27, 8761–8777, https://doi.org/10.1175/JCLI-D-14-00396.1, 2014.
Song, F., Zhou, T., and Qian, Y.: Responses of East Asian summer monsoon to natural and anthropogenic forcings in the 17 latest CMIP5 models, Geophys. Res. Lett., 41, 596–603, https://doi.org/10.1002/2013GL058705, 2014.
Sperber, K. R., Annamalai, H., Kang, I. S., Kitoh, A., Moise, A., Turner, A., Wang, B., and Zhou, T.: The Asian summer monsoon: An intercomparison of CMIP5 vs. CMIP3 simulations of the late 20th century, Clim. Dynam., 41, 2711–2744, https://doi.org/10.1007/s00382-012-1607-6, 2013.
Tian, F., Dong, B., Robson, J., and Sutton, R.: Forced decadal changes in the East Asian summer monsoon: the roles of greenhouse gases and anthropogenic aerosols, Clim. Dynam., 51, 3699–3715, https://doi.org/10.1007/s00382-018-4105-7, 2018.
Tong, M., Zheng, Z., and Fu, Q.: Evaluation of East Asian Meiyu from CMIP6/AMIP simulations, Clim. Dynam., 59, 2429–2444, https://doi.org/10.1007/s00382-022-06218-z, 2022.
Twomey, S.: Pollution and the planetary albedo, Atmos. Environ., 8, 1251–1256, https://doi.org/10.1016/0004-6981(74)90004-3, 1974.
Vidya, P. J., Ravichandran, M., Subeesh, M. P., Chatterjee, S., and Nuncio, M.: Global warming hiatus contributed weakening of the Mascarene High in the Southern Indian Ocean, Sci. Rep., 10, 3255, https://doi.org/10.1038/s41598-020-59964-7, 2020.
Walters, D., Baran, A. J., Boutle, I., Brooks, M., Earnshaw, P., Edwards, J., Furtado, K., Hill, P., Lock, A., Manners, J., Morcrette, C., Mulcahy, J., Sanchez, C., Smith, C., Stratton, R., Tennant, W., Tomassini, L., Van Weverberg, K., Vosper, S., Willett, M., Browse, J., Bushell, A., Carslaw, K., Dalvi, M., Essery, R., Gedney, N., Hardiman, S., Johnson, B., Johnson, C., Jones, A., Jones, C., Mann, G., Milton, S., Rumbold, H., Sellar, A., Ujiie, M., Whitall, M., Williams, K., and Zerroukat, M.: The Met Office Unified Model Global Atmosphere 7.0/7.1 and JULES Global Land 7.0 configurations, Geosci. Model Dev., 12, 1909–1963, https://doi.org/10.5194/gmd-12-1909-2019, 2019.
Wang, B., Yim, S. Y., Lee, J. Y., Liu, J., and Ha, K. J.: Future change of Asian-Australian monsoon under RCP 4.5 anthropogenic warming scenario, Clim. Dynam., 42, 83–100, https://doi.org/10.1007/s00382-013-1769-x, 2014.
Wang, B., Jin, C., and Liu, J.: Understanding Future Change of Global Monsoons Projected by CMIP6 Models, J. Climate, 33, 6471–6489, https://doi.org/10.1175/JCLI-D-19-0993.1, 2020.
Wang, N., Zhang, K., Shen, X., Wang, Y., Li, J., Li, C., Mao, J., Malinka, A., Zhao, C., Russell, L. M., Guo, J., Gross, S., Liu, C., Yang, J., Chen, F., Sijie Chen1, L. W., Ke, J., Xiao, D., Zhou, Y., Fang, J., and Liu, D.: Dual-field-of-view high-spectral-resolution lidar: Simultaneous profiling of aerosol and water cloud to study aerosol–cloud interaction, P. Natl. Acad. Sci. USA, 119, e2110756119, https://doi.org/10.1073/pnas.2110756119, 2022.
West, R. E. L., Stier, P., Jones, A., Johnson, C. E., Mann, G. W., Bellouin, N., Partridge, D. G., and Kipling, Z.: The importance of vertical velocity variability for estimates of the indirect aerosol effects, Atmos. Chem. Phys., 14, 6369–6393, https://doi.org/10.5194/acp-14-6369-2014, 2014.
Westervelt, D. M., Conley, A. J., Fiore, A. M., Lamarque, J.-F., Shindell, D. T., Previdi, M., Mascioli, N. R., Faluvegi, G., Correa, G., and Horowitz, L. W.: Connecting regional aerosol emissions reductions to local and remote precipitation responses, Atmos. Chem. Phys., 18, 12461–12475, https://doi.org/10.5194/acp-18-12461-2018, 2018.
Wilcox, L. J., Dong, B., Sutton, R. T., and Highwood, E. J.: The 2014 hot, dry summer in northeast Asia, B. Am. Meteorol. Soc., 96, S105–S110, https://doi.org/10.1175/BAMS-D-15-00123.1, 2015.
Wilcox, L. J., Dunstone, N., Lewinschal, A., Bollasina, M., Ekman, A. M. L., and Highwood, E. J.: Mechanisms for a remote response to Asian anthropogenic aerosol in boreal winter, Atmos. Chem. Phys., 19, 9081–9095, https://doi.org/10.5194/acp-19-9081-2019, 2019.
Wilcox, L. J., Liu, Z., Samset, B. H., Hawkins, E., Lund, M. T., Nordling, K., Undorf, S., Bollasina, M., Ekman, A. M. L., Krishnan, S., Merikanto, J., and Turner, A. G.: Accelerated increases in global and Asian summer monsoon precipitation from future aerosol reductions, Atmos. Chem. Phys., 20, 11955–11977, https://doi.org/10.5194/acp-20-11955-2020, 2020.
Wilson, D. R. and Ballard, S. P.: A microphysically based precipitation scheme for the UK meteorological office unified model, Q. J. Roy. Meteor. Soc., 125, 1607–1636, https://doi.org/10.1002/qj.49712555707, 1999.
Xie, P. and Arkin, P. A.: Global Precipitation: A 17-Year Monthly Analysis Based on Gauge Observations, Satellite Estimates, and Numerical Model Outputs, B. Am. Meteorol. Soc., 78, 2539–2558, https://doi.org/10.1175/1520-0477(1997)078<2539:GPAYMA>2.0.CO;2, 1997 (data available at: https://psl.noaa.gov/data/gridded/data.cmap.html, last access: 19 June 2024).
Xie, X., Myhre, G., Liu, X., Li, X., Shi, Z., Wang, H., Kirkevåg, A., Lamarque, J.-F., Shindell, D., Takemura, T., and Liu, Y.: Distinct responses of Asian summer monsoon to black carbon aerosols and greenhouse gases, Atmos. Chem. Phys., 20, 11823–11839, https://doi.org/10.5194/acp-20-11823-2020, 2020.
Yang, B., Zhang, Y., Qian, Y., Song, F., Leung, L. R., Wu, P., Guo, Z., Lu, Y., and Huang, A.: Better monsoon precipitation in coupled climate models due to bias compensation, npj Clim. Atmos. Sci., 2, 43, https://doi.org/10.1038/s41612-019-0100-x, 2019.
Yu, S., Li, P., Wang, L., Wang, P., Wang, S., Chang, S., Liu, W., and Alapaty, K.: Anthropogenic aerosols are a potential cause for migration of the summer monsoon rain belt in China, P. Natl. Acad. Sci. USA, 113, E2209–E2210, https://doi.org/10.1073/pnas.1601104113, 2016.
Zanis, P., Akritidis, D., Georgoulias, A. K., Allen, R. J., Bauer, S. E., Boucher, O., Cole, J., Johnson, B., Deushi, M., Michou, M., Mulcahy, J., Nabat, P., Olivié, D., Oshima, N., Sima, A., Schulz, M., Takemura, T., and Tsigaridis, K.: Fast responses on pre-industrial climate from present-day aerosols in a CMIP6 multi-model study, Atmos. Chem. Phys., 20, 8381–8404, https://doi.org/10.5194/acp-20-8381-2020, 2020.
Zha, J., Shen, C., Zhao, D., Feng, J., Xu, Z., Wu, J., Fan, W., Luo, M., and Zhang, L.: Contributions of External Forcing and Internal Climate Variability to Changes in the Summer Surface Air Temperature over East Asia, J. Climate, 35, 5013–5032, https://doi.org/10.1175/JCLI-D-21-0577.1, 2022.
Zhang, P., Yang, S., and Kousky, V. E.: South Asian high and Asian–Pacific–American climate teleconnection, Adv. Atmos. Sci., 22, 915–923, https://doi.org/10.1007/bf02918690, 2005.
Zhang, S., Stier, P., and Watson-Parris, D.: On the contribution of fast and slow responses to precipitation changes caused by aerosol perturbations, Atmos. Chem. Phys., 21, 10179–10197, https://doi.org/10.5194/acp-21-10179-2021, 2021.
Zheng, B., Tong, D., Li, M., Liu, F., Hong, C., Geng, G., Li, H., Li, X., Peng, L., Qi, J., Yan, L., Zhang, Y., Zhao, H., Zheng, Y., He, K., and Zhang, Q.: Trends in China's anthropogenic emissions since 2010 as the consequence of clean air actions, Atmos. Chem. Phys., 18, 14095–14111, https://doi.org/10.5194/acp-18-14095-2018, 2018.
Zhou, S., Huang, P., Huang, G., and Hu, K.: Leading source and constraint on the systematic spread of the changes in East Asian and western North Pacific summer monsoon, Environ. Res. Lett., 14, 124059, https://doi.org/10.1088/1748-9326/ab547c, 2019.
Zhou, Z. Q. and Xie, S. P.: Effects of climatological model biases on the projection of tropical climate change, J. Climate, 28, 9909–9917, https://doi.org/10.1175/JCLI-D-15-0243.1, 2015.
Short summary
The aerosol impact on monsoon precipitation and circulation is strongly influenced by a model-simulated spatio-temporal variability in the climatological monsoon precipitation across Asia, which critically modulates the efficacy of aerosol–cloud–precipitation interactions, the predominant driver of the total aerosol response. There is a strong interplay between South Asia and East Asia monsoon precipitation biases and their relative predominance in driving the overall monsoon response.
The aerosol impact on monsoon precipitation and circulation is strongly influenced by a...
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