121 citations as recorded by crossref.

1. Regionally refined test bed in E3SM atmosphere model version 1 (EAMv1) and applications for high-resolution modeling Q. Tang et al. https://doi.org/10.5194/gmd-12-2679-2019
2. Assessing the sensitivity of aerosol mass budget and effective radiative forcing to horizontal grid spacing in E3SMv1 using a regional refinement approach J. Li et al. https://doi.org/10.5194/gmd-17-1327-2024
3. The fully coupled regionally refined model of E3SM version 2: overview of the atmosphere, land, and river results Q. Tang et al. https://doi.org/10.5194/gmd-16-3953-2023
4. Contrasting Aerosol Effects on Long‐Wave Cloud Forcing in South East Asia and Amazon Simulated With Community Atmosphere Model Version 5.3 M. Wang et al. https://doi.org/10.1029/2020JD032380
5. Development and Evaluation of an Explicit Treatment of Aerosol Processes at Cloud Scale Within a Multi‐Scale Modeling Framework (MMF) G. Lin et al. https://doi.org/10.1029/2018MS001287
6. Comparing the Radiative Forcings of the Anthropogenic Aerosol Emissions From Chile and Mexico T. Miinalainen et al. https://doi.org/10.1029/2020JD033364
7. Reduced effective radiative forcing from cloud–aerosol interactions (ERFaci) with improved treatment of early aerosol growth in an Earth system model S. Blichner et al. https://doi.org/10.5194/acp-21-17243-2021
8. Quantifying and attributing time step sensitivities in present-day climate simulations conducted with EAMv1 H. Wan et al. https://doi.org/10.5194/gmd-14-1921-2021
9. Assessing the Dynamic Versus Thermodynamic Origin of Climate Model Biases K. Wehrli et al. https://doi.org/10.1029/2018GL079220
10. The importance of considering sub-grid cloud variability when using satellite observations to evaluate the cloud and precipitation simulations in climate models H. Song et al. https://doi.org/10.5194/gmd-11-3147-2018
11. Precipitation characteristics of CAM5 physics at mesoscale resolution during MC3E and the impact of convective timescale choice W. Gustafson et al. https://doi.org/10.1002/2014MS000334
12. Distinct Contributions of Ice Nucleation, Large‐Scale Environment, and Shallow Cumulus Detrainment to Cloud Phase Partitioning With NCAR CAM5 Y. Wang et al. https://doi.org/10.1002/2017JD027213
13. Future vegetation–climate interactions in Eastern Siberia: an assessment of the competing effects of CO2 and secondary organic aerosols A. Arneth et al. https://doi.org/10.5194/acp-16-5243-2016
14. Global dust distribution from improved thin dust layer detection using A‐train satellite lidar observations T. Luo et al. https://doi.org/10.1002/2014GL062111
15. Cloud adjustments dominate the overall negative aerosol radiative effects of biomass burning aerosols in UKESM1 climate model simulations over the south-eastern Atlantic H. Che et al. https://doi.org/10.5194/acp-21-17-2021
16. Using the Atmospheric Radiation Measurement (ARM) Datasets to Evaluate Climate Models in Simulating Diurnal and Seasonal Variations of Tropical Clouds H. Wang et al. https://doi.org/10.1175/JCLI-D-17-0362.1
17. Implementation of the MEGAN (v2.1) biogenic emission model in the ECHAM6-HAMMOZ chemistry climate model A. Henrot et al. https://doi.org/10.5194/gmd-10-903-2017
18. Relative importance of high-latitude local and long-range-transported dust for Arctic ice-nucleating particles and impacts on Arctic mixed-phase clouds Y. Shi et al. https://doi.org/10.5194/acp-22-2909-2022
19. Droplet collection efficiencies inferred from satellite retrievals constrain effective radiative forcing of aerosol–cloud interactions C. Beall et al. https://doi.org/10.5194/acp-24-5287-2024
20. Toward Understanding the Simulated Phase Partitioning of Arctic Single‐Layer Mixed‐Phase Clouds in E3SM M. Zhang et al. https://doi.org/10.1029/2020EA001125
21. Southern Ocean cloud and shortwave radiation biases in a nudged climate model simulation: does the model ever get it right? S. Fiddes et al. https://doi.org/10.5194/acp-22-14603-2022
22. Evaluation of the CAM6 Climate Model Using Cloud Observations at McMurdo Station, Antarctica J. Yip et al. https://doi.org/10.1029/2021JD034653
23. Improving thermodynamic nudging in the E3SM Atmosphere Model version 2 (EAMv2): strategy and hindcast skills on weather systems S. Zhang et al. https://doi.org/10.5194/gmd-19-1937-2026
24. Bioindication and modelling of atmospheric deposition in forests enable exposure and effect monitoring at high spatial density across scales W. Schröder et al. https://doi.org/10.1007/s13595-017-0621-6
25. On the characteristics of aerosol indirect effect based on dynamic regimes in global climate models S. Zhang et al. https://doi.org/10.5194/acp-16-2765-2016
26. Exploring Impacts of Size‐Dependent Evaporation and Entrainment in a Global Model I. Karset et al. https://doi.org/10.1029/2019JD031817
27. The Common Representative Intermediates Mechanism Version 2 in the United Kingdom Chemistry and Aerosols Model S. Archer‐Nicholls et al. https://doi.org/10.1029/2020MS002420
28. Source attribution of cloud condensation nuclei and their impact on stratocumulus clouds and radiation in the south-eastern Atlantic H. Che et al. https://doi.org/10.5194/acp-22-10789-2022
29. Impacts of Aerosol Dry Deposition on Black Carbon Spatial Distributions and Radiative Effects in the Community Atmosphere Model CAM5 M. Wu et al. https://doi.org/10.1029/2017MS001219
30. How does increasing horizontal resolution in a global climate model improve the simulation of aerosol‐cloud interactions? P. Ma et al. https://doi.org/10.1002/2015GL064183
31. Global source attribution of sulfate concentration and direct and indirect radiative forcing Y. Yang et al. https://doi.org/10.5194/acp-17-8903-2017
32. Modeling the Sulfate Aerosol Evolution After Recent Moderate Volcanic Activity, 2008–2012 C. Brodowsky et al. https://doi.org/10.1029/2021JD035472
33. Impacts of spatial heterogeneity of anthropogenic aerosol emissions in a regionally refined global aerosol–climate model T. Hassan et al. https://doi.org/10.5194/gmd-17-3507-2024
34. Source attribution of black carbon and its direct radiative forcing in China Y. Yang et al. https://doi.org/10.5194/acp-17-4319-2017
35. The chemistry–climate model ECHAM6.3-HAM2.3-MOZ1.0 M. Schultz et al. https://doi.org/10.5194/gmd-11-1695-2018
36. Identifying Key Driving Processes of Major Recent Heat Waves K. Wehrli et al. https://doi.org/10.1029/2019JD030635
37. The decomposition of cloud–aerosol forcing in the UK Earth System Model (UKESM1) D. Grosvenor & K. Carslaw https://doi.org/10.5194/acp-20-15681-2020
38. Model representations of aerosol layers transported from North America over the Atlantic Ocean during the Two‐Column Aerosol Project J. Fast et al. https://doi.org/10.1002/2016JD025248
39. Features of mid- and high-latitude low-level clouds and their relation to strong aerosol effects in the Energy Exascale Earth System Model version 2 (E3SMv2) H. Wan et al. https://doi.org/10.5194/gmd-18-5655-2025
40. Further improvement and evaluation of nudging in the E3SM Atmosphere Model version 1 (EAMv1): simulations of the mean climate, weather events, and anthropogenic aerosol effects S. Zhang et al. https://doi.org/10.5194/gmd-15-6787-2022
41. Global and regional radiative forcing from 20 % reductions in BC, OC and SO4 – an HTAP2 multi-model study C. Stjern et al. https://doi.org/10.5194/acp-16-13579-2016
42. Does temperature nudging overwhelm aerosol radiative effects in regional integrated climate models? J. He et al. https://doi.org/10.1016/j.atmosenv.2017.01.040
43. Emission or atmospheric processes? An attempt to attribute the source of large bias of aerosols in eastern China simulated by global climate models T. Fan et al. https://doi.org/10.5194/acp-18-1395-2018
44. Intercomparison of initialization methods for seasonal-to-decadal climate predictions with the NorCPM L. Garcia-Oliva et al. https://doi.org/10.1007/s00382-024-07170-w
45. The Art and Science of Climate Model Tuning F. Hourdin et al. https://doi.org/10.1175/BAMS-D-15-00135.1
46. The linkage between stratospheric water vapor and surface temperature in an observation-constrained coupled general circulation model Y. Wang et al. https://doi.org/10.1007/s00382-016-3231-3
47. Improved subseasonal-to-seasonal precipitation prediction of climate models with nudging approach for better initialization of Tibetan Plateau-Rocky Mountain Circumglobal wave train and land surface conditions Y. Qin et al. https://doi.org/10.1007/s00382-023-07082-1
48. Carbon cycle and climate effects of forcing from fire-emitted aerosols J. Landry et al. https://doi.org/10.1088/1748-9326/aa51de
49. Biomass burning aerosol radiative effects in the Southeast Atlantic depend strongly on meteorological forcing method E. Giuffrida et al. https://doi.org/10.5194/acp-25-14879-2025
50. Evaluating EAMv2 Simulated High Latitude Clouds Using ARM Measurements in the Northern and Southern Hemispheres M. Zhang et al. https://doi.org/10.1029/2022JD038364
51. Observational constraint on cloud susceptibility weakened by aerosol retrieval limitations P. Ma et al. https://doi.org/10.1038/s41467-018-05028-4
52. Impact of a New Cloud Microphysics Parameterization on the Simulations of Mesoscale Convective Systems in E3SM J. Wang et al. https://doi.org/10.1029/2021MS002628
53. Towards an improved understanding of the impact of clouds and precipitation on the representation of aerosols over the Boreal Forest in GCMs S. Talvinen et al. https://doi.org/10.5194/acp-25-14449-2025
54. Surprising similarities in model and observational aerosol radiative forcing estimates E. Gryspeerdt et al. https://doi.org/10.5194/acp-20-613-2020
55. Large simulated radiative effects of smoke in the south-east Atlantic H. Gordon et al. https://doi.org/10.5194/acp-18-15261-2018
56. Assessing the Aerosols, Clouds and Their Relationship Over the Northern Bay of Bengal Using a Global Climate Model P. Sharma et al. https://doi.org/10.1029/2022EA002706
57. Impact of Nudging Strategy on the Climate Representativeness and Hindcast Skill of Constrained EAMv1 Simulations J. Sun et al. https://doi.org/10.1029/2019MS001831
58. Coupling aerosols to (cirrus) clouds in the global EMAC-MADE3 aerosol–climate model M. Righi et al. https://doi.org/10.5194/gmd-13-1635-2020
59. A multi-year short-range hindcast experiment with CESM1 for evaluating climate model moist processes from diurnal to interannual timescales H. Ma et al. https://doi.org/10.5194/gmd-14-73-2021
60. Biomass burning emission analysis based on MODIS aerosol optical depth and AeroCom multi-model simulations: implications for model constraints and emission inventories M. Petrenko et al. https://doi.org/10.5194/acp-25-1545-2025
61. Global Radiative Impacts of Mineral Dust Perturbations Through Stratiform Clouds Z. McGraw et al. https://doi.org/10.1029/2019JD031807
62. Global transformation and fate of SOA: Implications of low‐volatility SOA and gas‐phase fragmentation reactions M. Shrivastava et al. https://doi.org/10.1002/2014JD022563
63. Challenges in constraining anthropogenic aerosol effects on cloud radiative forcing using present-day spatiotemporal variability S. Ghan et al. https://doi.org/10.1073/pnas.1514036113
64. Prescribing the aerosol effective radiative forcing in the Simple Cloud-Resolving E3SM Atmosphere Model v1 N. Mahfouz et al. https://doi.org/10.5194/acp-25-15105-2025
65. Ice‐Nucleating Particles That Impact Clouds and Climate: Observational and Modeling Research Needs S. Burrows et al. https://doi.org/10.1029/2021RG000745
66. Effective radiative forcing of anthropogenic aerosols in E3SM version 1: historical changes, causality, decomposition, and parameterization sensitivities K. Zhang et al. https://doi.org/10.5194/acp-22-9129-2022
67. An Evaluation of Marine Boundary Layer Cloud Property Simulations in the Community Atmosphere Model Using Satellite Observations: Conventional Subgrid Parameterization versus CLUBB H. Song et al. https://doi.org/10.1175/JCLI-D-17-0277.1
68. Specified dynamics scheme impacts on wave-mean flow dynamics, convection, and tracer transport in CESM2 (WACCM6) N. Davis et al. https://doi.org/10.5194/acp-22-197-2022
69. A production-tagged aerosol module for Earth system models, OsloAero5.3 – extensions and updates for CAM5.3-Oslo A. Kirkevåg et al. https://doi.org/10.5194/gmd-11-3945-2018
70. The effect of atmospheric nudging on the stratospheric residual circulation in chemistry–climate models A. Chrysanthou et al. https://doi.org/10.5194/acp-19-11559-2019
71. Optimal Spectral Nudging for Global Dynamic Downscaling M. Schubert-Frisius et al. https://doi.org/10.1175/MWR-D-16-0036.1
72. Effects of black carbon mitigation on Arctic climate T. Kühn et al. https://doi.org/10.5194/acp-20-5527-2020
73. Upstream influence of midlatitude jet stream biases in boreal summer L. Boljka et al. https://doi.org/10.1002/asl.1272
74. Sulfate Aerosol in the Arctic: Source Attribution and Radiative Forcing Y. Yang et al. https://doi.org/10.1002/2017JD027298
75. Evolution of aerosol optical depth over China in 2010–2024: increasing importance of meteorological influences C. Fan et al. https://doi.org/10.5194/acp-25-11951-2025
76. The DOE E3SM Model Version 2: Overview of the Physical Model and Initial Model Evaluation J. Golaz et al. https://doi.org/10.1029/2022MS003156
77. BVOC–aerosol–climate feedbacks investigated using NorESM M. Sporre et al. https://doi.org/10.5194/acp-19-4763-2019
78. Reducing the aerosol forcing uncertainty using observational constraints on warm rain processes J. Mülmenstädt et al. https://doi.org/10.1126/sciadv.aaz6433
79. Contrasting the Role of Regional and Remote Circulation in Driving Asian Monsoon Biases in MetUM GA7.1 Z. Liu et al. https://doi.org/10.1029/2020JD034342
80. A spectral nudging method for the ACCESS1.3 atmospheric model P. Uhe & M. Thatcher https://doi.org/10.5194/gmd-8-1645-2015
81. Machine learning-based downscaling of aerosol size distributions from a global climate model A. Vartiainen et al. https://doi.org/10.5194/amt-18-5763-2025
82. Can nudging be used to quantify model sensitivities in precipitation and cloud forcing? G. Lin et al. https://doi.org/10.1002/2016MS000659
83. Using radar observations to evaluate 3-D radar echo structure simulated by the Energy Exascale Earth System Model (E3SM) version 1 J. Wang et al. https://doi.org/10.5194/gmd-14-719-2021
84. Absorbing aerosols over Asia – an inter-model and model-observation comparison study using CAM5.3-Oslo L. Frey et al. https://doi.org/10.1080/16000889.2021.1909815
85. Separating radiative forcing by aerosol–cloud interactions and rapid cloud adjustments in the ECHAM–HAMMOZ aerosol–climate model using the method of partial radiative perturbations J. Mülmenstädt et al. https://doi.org/10.5194/acp-19-15415-2019
86. Anthropogenic Aerosol Indirect Effects in Cirrus Clouds J. Penner et al. https://doi.org/10.1029/2018JD029204
87. Volcanic Radiative Forcing From 1979 to 2015 A. Schmidt et al. https://doi.org/10.1029/2018JD028776
88. How the extreme 2019–2020 Australian wildfires affected global circulation and adjustments F. Senf et al. https://doi.org/10.5194/acp-23-8939-2023
89. The E3SM version 1 single-column model P. Bogenschutz et al. https://doi.org/10.5194/gmd-13-4443-2020
90. Assessing the climate and air quality effects of future aerosol mitigation in India using a global climate model combined with statistical downscaling T. Miinalainen et al. https://doi.org/10.5194/acp-23-3471-2023
91. Investigation of short-term effective radiative forcing of fire aerosols over North America using nudged hindcast ensembles Y. Liu et al. https://doi.org/10.5194/acp-18-31-2018
92. Aerosols in the E3SM Version 1: New Developments and Their Impacts on Radiative Forcing H. Wang et al. https://doi.org/10.1029/2019MS001851
93. The July 2019 European Heat Wave in a Warmer Climate: Storyline Scenarios with a Coupled Model Using Spectral Nudging A. Sánchez-Benítez et al. https://doi.org/10.1175/JCLI-D-21-0573.1
94. Strong impacts on aerosol indirect effects from historical oxidant changes I. Karset et al. https://doi.org/10.5194/acp-18-7669-2018
95. Synoptic systems influence the effectiveness of spectral nudging in high-resolution simulations of extreme precipitation D. Kwon et al. https://doi.org/10.1038/s41612-025-01224-4
96. Evaluating the Lagrangian Evolution of Subtropical Low Clouds in GCMs Using Observations: Mean Evolution, Time Scales, and Responses to Predictors R. Eastman et al. https://doi.org/10.1175/JAS-D-20-0178.1
97. The Impact of Resolving Subkilometer Processes on Aerosol‐Cloud Interactions of Low‐Level Clouds in Global Model Simulations C. Terai et al. https://doi.org/10.1029/2020MS002274
98. Minimal Climate Impacts From Short‐Lived Climate Forcers Following Emission Reductions Related to the COVID‐19 Pandemic J. Weber et al. https://doi.org/10.1029/2020GL090326
99. Representations of Precipitation Diurnal Cycle in the Amazon as Simulated by Observationally Constrained Cloud‐System Resolving and Global Climate Models S. Tai et al. https://doi.org/10.1029/2021MS002586
100. Direct comparisons of ice cloud macro- and microphysical properties simulated by the Community Atmosphere Model version 5 with HIPPO aircraft observations C. Wu et al. https://doi.org/10.5194/acp-17-4731-2017
101. Evaluation of observed and modelled aerosol lifetimes using radioactive tracers of opportunity and an ensemble of 19 global models N. Kristiansen et al. https://doi.org/10.5194/acp-16-3525-2016
102. Earth System Model Aerosol–Cloud Diagnostics (ESMAC Diags) package, version 1: assessing E3SM aerosol predictions using aircraft, ship, and surface measurements S. Tang et al. https://doi.org/10.5194/gmd-15-4055-2022
103. Incorporation of aerosol into the COSPv2 satellite lidar simulator for climate model evaluation M. Bonazzola et al. https://doi.org/10.5194/gmd-16-1359-2023
104. Storylines of the 2018 Northern Hemisphere heatwave at pre-industrial and higher global warming levels K. Wehrli et al. https://doi.org/10.5194/esd-11-855-2020
105. Constraints on global aerosol number concentration, SO2 and condensation sink in UKESM1 using ATom measurements A. Ranjithkumar et al. https://doi.org/10.5194/acp-21-4979-2021
106. Development and basic evaluation of a prognostic aerosol scheme (v1) in the CNRM Climate Model CNRM-CM6 M. Michou et al. https://doi.org/10.5194/gmd-8-501-2015
107. Anthropogenic aerosol forcing – insights from multiple estimates from aerosol-climate models with reduced complexity S. Fiedler et al. https://doi.org/10.5194/acp-19-6821-2019
108. Are Changes in Atmospheric Circulation Important for Black Carbon Aerosol Impacts on Clouds, Precipitation, and Radiation? B. Johnson et al. https://doi.org/10.1029/2019JD030568
109. Role of Troposphere‐Convection‐Land Coupling in the Southwestern Amazon Precipitation Bias of the Community Earth System Model Version 1 (CESM1) K. Sakaguchi et al. https://doi.org/10.1029/2018JD028999
110. A global model–measurement evaluation of particle light scattering coefficients at elevated relative humidity M. Burgos et al. https://doi.org/10.5194/acp-20-10231-2020
111. Fungal spores as a source of sodium salt particles in the Amazon basin S. China et al. https://doi.org/10.1038/s41467-018-07066-4
112. Molecular markers for fungal spores and biogenic SOA over the Antarctic Peninsula: Field measurements and modeling results J. Deng et al. https://doi.org/10.1016/j.scitotenv.2020.143089
113. An improved hindcast approach for evaluation and diagnosis of physical processes in global climate models H. Ma et al. https://doi.org/10.1002/2015MS000490
114. Impacts of meteorological nudging on the global dust cycle simulated by NICAM coupled with an aerosol model T. Dai et al. https://doi.org/10.1016/j.atmosenv.2018.07.016
115. Cloud Phase and Relative Humidity Distributions over the Southern Ocean in Austral Summer Based on In Situ Observations and CAM5 Simulations J. D’Alessandro et al. https://doi.org/10.1175/JCLI-D-18-0232.1
116. Composite Aerosol Optical Depth Mapping over Northeast Asia from GEO-LEO Satellite Observations S. Ahn et al. https://doi.org/10.3390/rs13061096
117. Assessing modifications to the Abdul-Razzak and Ghan aerosol activation parameterization (version ARG2000) to improve simulated aerosol–cloud radiative effects in the UK Met Office Unified Model (UM version 13.0) P. Ghosh et al. https://doi.org/10.5194/gmd-18-4899-2025
118. Quantifying the impact of sub-grid surface wind variability on sea salt and dust emissions in CAM5 K. Zhang et al. https://doi.org/10.5194/gmd-9-607-2016
119. Unexpected Changes of Aerosol Burdens With Decreased Convection in the Context of Scale‐Aware Convection Schemes W. Xia et al. https://doi.org/10.1029/2022GL099008
120. Radiative forcing of anthropogenic aerosols on cirrus clouds using a hybrid ice nucleation scheme J. Zhu & J. Penner https://doi.org/10.5194/acp-20-7801-2020
121. Global organic and inorganic aerosol hygroscopicity and its effect on radiative forcing M. Pöhlker et al. https://doi.org/10.1038/s41467-023-41695-8