Articles | Volume 18, issue 11
https://doi.org/10.5194/acp-18-7827-2018
© Author(s) 2018. 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-18-7827-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Aerosol–fog interaction and the transition to well-mixed radiation fog
Met Office, Exeter, UK
Jeremy Price
Met Office, Exeter, UK
Innocent Kudzotsa
Atmospheric Research Centre of Eastern Finland, Finnish Meteorological Institute, Kuopio, Finland
Harri Kokkola
Atmospheric Research Centre of Eastern Finland, Finnish Meteorological Institute, Kuopio, Finland
Sami Romakkaniemi
Atmospheric Research Centre of Eastern Finland, Finnish Meteorological Institute, Kuopio, Finland
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Cited
76 citations as recorded by crossref.
- Sensitivity of Numerical Simulations of Near-Surface Atmospheric Conditions to Snow Depth and Surface Albedo during an Ice Fog Event over Heber Valley F. Zhang & Z. Pu 10.1175/JAMC-D-18-0064.1
- The ICON Single-Column Mode I. Bašták Ďurán et al. 10.3390/atmos12070906
- Unravelling the relative roles of physical processes in modelling the life cycle of a warm radiation fog G. Steeneveld & M. de Bode 10.1002/qj.3300
- An Observational Case Study of a Radiation Fog Event A. Gandhi et al. 10.1007/s00024-024-03498-w
- Long‐Term Fog Variation and Its Impact Factors Over Polluted Regions of East China S. Yan et al. 10.1029/2018JD029389
- Aerosol–stratocumulus interactions: towards a better process understanding using closures between observations and large eddy simulations S. Calderón et al. 10.5194/acp-22-12417-2022
- How important are aerosol–fog interactions for the successful modelling of nocturnal radiation fog? C. Poku et al. 10.1002/wea.3503
- Direct Numerical Simulation of Fog: The Sensitivity of a Dissipation Phase to Environmental Conditions M. Karimi 10.3390/atmos11010012
- Sofia Airport Visibility Estimation with Two Machine-Learning Techniques N. Penov & G. Guerova 10.3390/rs15194799
- Comparison of a spectral microphysics and a two-moment cloud scheme: Numerical simulation of a radiation fog event A. Bott 10.1016/j.atmosres.2021.105787
- Transition Periods in the Diurnally-Varying Atmospheric Boundary Layer Over Land W. Angevine et al. 10.1007/s10546-020-00515-y
- Identifying the key challenges for fog and low stratus forecasting in complex terrain S. Westerhuis et al. 10.1002/qj.3849
- A Lagrangian Cloud Model for the Study of Marine Fog D. Richter et al. 10.1007/s10546-020-00595-w
- Implementation of the urban parameterization scheme in the Delhi model with an improved urban morphology A. Theethai Jacob et al. 10.1002/qj.4382
- The evolution of cloud and aerosol microphysics at the summit of Mt. Tai, China J. Li et al. 10.5194/acp-20-13735-2020
- Changes in aerosol particle composition during sea fog formation events in the sea ice regions of the Arctic Ocean S. Zhao et al. 10.1016/j.atmosenv.2022.118943
- Importance of CCN activation for fog forecasting and its representation in the two‐moment microphysical scheme LIMA B. Vié et al. 10.1002/qj.4812
- LANFEX: A Field and Modeling Study to Improve Our Understanding and Forecasting of Radiation Fog J. Price et al. 10.1175/BAMS-D-16-0299.1
- Improved Aerosol Processes and Effective Radiative Forcing in HadGEM3 and UKESM1 J. Mulcahy et al. 10.1029/2018MS001464
- Stratus over rolling terrain: Large‐eddy simulation reference and sensitivity to grid spacing and numerics J. Weinkaemmerer et al. 10.1002/qj.4372
- Particle number size distribution of PM1 and PM10 in fogs and implications on fog droplet evolutions S. Wu et al. 10.1016/j.atmosenv.2022.119086
- Towards a Better Representation of Fog Microphysics in Large-Eddy Simulations Based on an Embedded Lagrangian Cloud Model J. Schwenkel & B. Maronga 10.3390/atmos11050466
- Formation of fog due to stratus lowering: An observational and modelling case study M. Fathalli et al. 10.1002/qj.4304
- Time-gated imaging through dense fog via physics-driven Swin transformer S. Jin et al. 10.1364/OE.519662
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- The First Characterization of Fog Microphysics in the United Arab Emirates, an Arid Region on the Arabian Peninsula M. Weston et al. 10.1029/2021EA002032
- A review on factors influencing fog formation, classification, forecasting, detection and impacts K. Lakra & K. Avishek 10.1007/s12210-022-01060-1
- Observations of Fog‐Aerosol Interactions Over Central Greenland H. Guy et al. 10.1029/2023JD038718
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- The first Met Office Unified Model–JULES Regional Atmosphere and Land configuration, RAL1 M. Bush et al. 10.5194/gmd-13-1999-2020
- Unusual bifurcation scenario in a stably stratified, valley-shaped enclosure heated from below P. Stofanak et al. 10.1103/PhysRevFluids.9.074401
- Impact of high‐resolution ocean–atmosphere coupling on fog formation over the North Sea J. Fallmann et al. 10.1002/qj.3488
- Numerical simulations of upslope fog observed at Beppu Bay in Oita Prefecture, Japan Y. Ohashi & M. Suido 10.1002/met.2003
- Sub‐km scale numerical weather prediction model simulations of radiation fog D. Smith et al. 10.1002/qj.3943
- C-FOG: Life of Coastal Fog H. Fernando et al. 10.1175/BAMS-D-19-0070.1
- Forecasts of fog events in northern India dramatically improve when weather prediction models include irrigation effects D. Smith et al. 10.1038/s43247-024-01314-w
- Decadal shift in sea fog frequency over the northern South China Sea in spring: Interdecadal variation and impact of the Pacific Decadal Oscillation L. Han et al. 10.1016/j.atmosres.2021.105905
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- NUMAC: Description of the Nested Unified Model With Aerosols and Chemistry, and Evaluation With KORUS‐AQ Data H. Gordon et al. 10.1029/2022MS003457
- Improving and Developing the Fog Stability Index for Predicting Fog at Borg El-Arab Airport, Egypt Using WRF Model T. Sayad et al. 10.1007/s00024-021-02785-0
- Stable boundary‐layer relative humidity profiles and the conditions for onset of radiation fog over land S. Derbyshire 10.1002/qj.3558
- Assessment of PM2.5 using satellite lidar observations: Effect of bio-mass burning emissions over India N. Lakshmi et al. 10.1016/j.scitotenv.2022.155215
- Scavenging of Black Carbon Aerosols by Radiation Fog in Urban Central China X. Zhang et al. 10.3390/atmos13020205
- Is a more physical representation of aerosol activation needed for simulations of fog? C. Poku et al. 10.5194/acp-21-7271-2021
- Modeled aerosol-cloud indirect effects and processes based on an observed partially glaciated marine deep convective cloud case I. Kudzotsa et al. 10.1016/j.atmosenv.2019.02.010
- On the Conditions for Onset and Development of Fog Over New Delhi: An Observational Study from the WiFEX N. Dhangar et al. 10.1007/s00024-021-02800-4
- Effect of the boundary layer low-level jet on fast fog spatial propagation S. Yan et al. 10.5194/acp-23-13987-2023
- Role of atmospheric aerosols in severe winter fog over the Indo-Gangetic Plain of India: a case study C. Bharali et al. 10.5194/acp-24-6635-2024
- Fog scavenging of particulate matters in air pollution events: Observation and simulation in the Yangtze River Delta, China J. Qian et al. 10.1016/j.scitotenv.2023.162728
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76 citations as recorded by crossref.
- Sensitivity of Numerical Simulations of Near-Surface Atmospheric Conditions to Snow Depth and Surface Albedo during an Ice Fog Event over Heber Valley F. Zhang & Z. Pu 10.1175/JAMC-D-18-0064.1
- The ICON Single-Column Mode I. Bašták Ďurán et al. 10.3390/atmos12070906
- Unravelling the relative roles of physical processes in modelling the life cycle of a warm radiation fog G. Steeneveld & M. de Bode 10.1002/qj.3300
- An Observational Case Study of a Radiation Fog Event A. Gandhi et al. 10.1007/s00024-024-03498-w
- Long‐Term Fog Variation and Its Impact Factors Over Polluted Regions of East China S. Yan et al. 10.1029/2018JD029389
- Aerosol–stratocumulus interactions: towards a better process understanding using closures between observations and large eddy simulations S. Calderón et al. 10.5194/acp-22-12417-2022
- How important are aerosol–fog interactions for the successful modelling of nocturnal radiation fog? C. Poku et al. 10.1002/wea.3503
- Direct Numerical Simulation of Fog: The Sensitivity of a Dissipation Phase to Environmental Conditions M. Karimi 10.3390/atmos11010012
- Sofia Airport Visibility Estimation with Two Machine-Learning Techniques N. Penov & G. Guerova 10.3390/rs15194799
- Comparison of a spectral microphysics and a two-moment cloud scheme: Numerical simulation of a radiation fog event A. Bott 10.1016/j.atmosres.2021.105787
- Transition Periods in the Diurnally-Varying Atmospheric Boundary Layer Over Land W. Angevine et al. 10.1007/s10546-020-00515-y
- Identifying the key challenges for fog and low stratus forecasting in complex terrain S. Westerhuis et al. 10.1002/qj.3849
- A Lagrangian Cloud Model for the Study of Marine Fog D. Richter et al. 10.1007/s10546-020-00595-w
- Implementation of the urban parameterization scheme in the Delhi model with an improved urban morphology A. Theethai Jacob et al. 10.1002/qj.4382
- The evolution of cloud and aerosol microphysics at the summit of Mt. Tai, China J. Li et al. 10.5194/acp-20-13735-2020
- Changes in aerosol particle composition during sea fog formation events in the sea ice regions of the Arctic Ocean S. Zhao et al. 10.1016/j.atmosenv.2022.118943
- Importance of CCN activation for fog forecasting and its representation in the two‐moment microphysical scheme LIMA B. Vié et al. 10.1002/qj.4812
- LANFEX: A Field and Modeling Study to Improve Our Understanding and Forecasting of Radiation Fog J. Price et al. 10.1175/BAMS-D-16-0299.1
- Improved Aerosol Processes and Effective Radiative Forcing in HadGEM3 and UKESM1 J. Mulcahy et al. 10.1029/2018MS001464
- Stratus over rolling terrain: Large‐eddy simulation reference and sensitivity to grid spacing and numerics J. Weinkaemmerer et al. 10.1002/qj.4372
- Particle number size distribution of PM1 and PM10 in fogs and implications on fog droplet evolutions S. Wu et al. 10.1016/j.atmosenv.2022.119086
- Towards a Better Representation of Fog Microphysics in Large-Eddy Simulations Based on an Embedded Lagrangian Cloud Model J. Schwenkel & B. Maronga 10.3390/atmos11050466
- Formation of fog due to stratus lowering: An observational and modelling case study M. Fathalli et al. 10.1002/qj.4304
- Time-gated imaging through dense fog via physics-driven Swin transformer S. Jin et al. 10.1364/OE.519662
- The Met Office Unified Model Global Atmosphere 7.0/7.1 and JULES Global Land 7.0 configurations D. Walters et al. 10.5194/gmd-12-1909-2019
- Visibility Data Assimilation and Prediction Using an Observation Network in South Korea M. Kim et al. 10.1007/s00024-019-02288-z
- Large-eddy simulation of radiation fog with comprehensive two-moment bulk microphysics: impact of different aerosol activation and condensation parameterizations J. Schwenkel & B. Maronga 10.5194/acp-19-7165-2019
- On the Formation and Development of Radiation Fog: An Observational Study J. Price 10.1007/s10546-019-00444-5
- Radiative effects of clouds and fog on long-lasting heavy fog events in northern China L. Guo et al. 10.1016/j.atmosres.2020.105444
- The First Characterization of Fog Microphysics in the United Arab Emirates, an Arid Region on the Arabian Peninsula M. Weston et al. 10.1029/2021EA002032
- A review on factors influencing fog formation, classification, forecasting, detection and impacts K. Lakra & K. Avishek 10.1007/s12210-022-01060-1
- Observations of Fog‐Aerosol Interactions Over Central Greenland H. Guy et al. 10.1029/2023JD038718
- On the effect of nocturnal radiation fog on the development of the daytime convective boundary layer: A large‐eddy simulation study J. Schwenkel & B. Maronga 10.1002/qj.4352
- Investigating the Sensitivity of Marine Fog to Physical and Microphysical Processes Using Large-Eddy Simulation C. Wainwright & D. Richter 10.1007/s10546-020-00599-6
- In-situ measurements of fog microphysics: Visibility parameterization and estimation of fog droplet sedimentation velocity N. Nelli et al. 10.1016/j.atmosres.2024.107570
- Experimental study of the aerosol impact on fog microphysics M. Mazoyer et al. 10.5194/acp-19-4323-2019
- Numerical simulation of the microphysics and liquid chemical processes occur in fog using size resolving bin scheme J. Bodaballa et al. 10.1016/j.atmosres.2021.105972
- Numerical modelling of the evolution of the boundary layer during a radiation fog event D. Smith et al. 10.1002/wea.3305
- Aerosol Activation in Radiation Fog at the Atmospheric Radiation Program Southern Great Plains Site C. Wainwright et al. 10.1029/2021JD035358
- Climate change response in wintertime widespread fog conditions over the Indo-Gangetic Plains D. Hingmire et al. 10.1007/s00382-021-06030-1
- Surface deposition of marine fog and its treatment in the Weather Research and Forecasting (WRF) model P. Taylor et al. 10.5194/acp-21-14687-2021
- On the Predictability of Radiation Fog Formation in a Mesoscale Model: A Case Study in Heterogeneous Terrain T. Bergot & R. Lestringant 10.3390/atmos10040165
- The behaviour of charged particles (ions) during new particle formation events in urban Leipzig, Germany A. Rowell et al. 10.5194/acp-24-10349-2024
- Sensitivity analysis of an aerosol-aware microphysics scheme in Weather Research and Forecasting (WRF) during case studies of fog in Namibia M. Weston et al. 10.5194/acp-22-10221-2022
- Fog in heterogeneous environments: the relative importance of local and non‐local processes on radiative‐advective fog formation L. Ducongé et al. 10.1002/qj.3783
- Demistify: a large-eddy simulation (LES) and single-column model (SCM) intercomparison of radiation fog I. Boutle et al. 10.5194/acp-22-319-2022
- Impact of the Microphysics in HARMONIE-AROME on Fog S. Contreras Osorio et al. 10.3390/atmos13122127
- Modeling Extreme Warm‐Air Advection in the Arctic During Summer: The Effect of Mid‐Latitude Pollution Inflow on Cloud Properties E. Bossioli et al. 10.1029/2020JD033291
- Analysis of fog at Xianyang Airport based on multi-source ground-based detection data H. Ming et al. 10.1016/j.atmosres.2019.01.012
- Experimental study on the evolution of droplet size distribution during the fog life cycle M. Mazoyer et al. 10.5194/acp-22-11305-2022
- The propagation of fog and its related pollutants in the Central and Eastern China in winter Y. Zhu et al. 10.1016/j.atmosres.2021.105914
- A Single-Column Comparison of Model-Error Representations for Ensemble Prediction F. Bouttier et al. 10.1007/s10546-021-00682-6
- Simulations of sea fog case impacted by air–sea interaction over South China Sea L. Han et al. 10.3389/fmars.2022.1000051
- A new conceptual model for adiabatic fog F. Toledo et al. 10.5194/acp-21-13099-2021
- Radiation fog properties in two consecutive events under polluted and clean conditions in the Yangtze River Delta, China: a simulation study N. Shao et al. 10.5194/acp-23-9873-2023
- The first Met Office Unified Model–JULES Regional Atmosphere and Land configuration, RAL1 M. Bush et al. 10.5194/gmd-13-1999-2020
- Unusual bifurcation scenario in a stably stratified, valley-shaped enclosure heated from below P. Stofanak et al. 10.1103/PhysRevFluids.9.074401
- Impact of high‐resolution ocean–atmosphere coupling on fog formation over the North Sea J. Fallmann et al. 10.1002/qj.3488
- Numerical simulations of upslope fog observed at Beppu Bay in Oita Prefecture, Japan Y. Ohashi & M. Suido 10.1002/met.2003
- Sub‐km scale numerical weather prediction model simulations of radiation fog D. Smith et al. 10.1002/qj.3943
- C-FOG: Life of Coastal Fog H. Fernando et al. 10.1175/BAMS-D-19-0070.1
- Forecasts of fog events in northern India dramatically improve when weather prediction models include irrigation effects D. Smith et al. 10.1038/s43247-024-01314-w
- Decadal shift in sea fog frequency over the northern South China Sea in spring: Interdecadal variation and impact of the Pacific Decadal Oscillation L. Han et al. 10.1016/j.atmosres.2021.105905
- Precipitation enhancement in stratocumulus clouds through airborne seeding: sensitivity analysis by UCLALES-SALSA J. Tonttila et al. 10.5194/acp-21-1035-2021
- NUMAC: Description of the Nested Unified Model With Aerosols and Chemistry, and Evaluation With KORUS‐AQ Data H. Gordon et al. 10.1029/2022MS003457
- Improving and Developing the Fog Stability Index for Predicting Fog at Borg El-Arab Airport, Egypt Using WRF Model T. Sayad et al. 10.1007/s00024-021-02785-0
- Stable boundary‐layer relative humidity profiles and the conditions for onset of radiation fog over land S. Derbyshire 10.1002/qj.3558
- Assessment of PM2.5 using satellite lidar observations: Effect of bio-mass burning emissions over India N. Lakshmi et al. 10.1016/j.scitotenv.2022.155215
- Scavenging of Black Carbon Aerosols by Radiation Fog in Urban Central China X. Zhang et al. 10.3390/atmos13020205
- Is a more physical representation of aerosol activation needed for simulations of fog? C. Poku et al. 10.5194/acp-21-7271-2021
- Modeled aerosol-cloud indirect effects and processes based on an observed partially glaciated marine deep convective cloud case I. Kudzotsa et al. 10.1016/j.atmosenv.2019.02.010
- On the Conditions for Onset and Development of Fog Over New Delhi: An Observational Study from the WiFEX N. Dhangar et al. 10.1007/s00024-021-02800-4
- Effect of the boundary layer low-level jet on fast fog spatial propagation S. Yan et al. 10.5194/acp-23-13987-2023
- Role of atmospheric aerosols in severe winter fog over the Indo-Gangetic Plain of India: a case study C. Bharali et al. 10.5194/acp-24-6635-2024
- Fog scavenging of particulate matters in air pollution events: Observation and simulation in the Yangtze River Delta, China J. Qian et al. 10.1016/j.scitotenv.2023.162728
- The UKC3 regional coupled environmental prediction system H. Lewis et al. 10.5194/gmd-12-2357-2019
Latest update: 08 Nov 2024
Short summary
Aerosol processes are a key mechanism in the development of fog. Poor representation of aerosol–fog interaction can result in large biases in fog forecasts, such as surface temperatures which are too high and fog which is too deep and long lived. A relatively simple representation of aerosol–fog interaction can actually lead to significant improvements in forecasting. Aerosol–fog interaction can have a large effect on the climate system but is poorly represented in climate models.
Aerosol processes are a key mechanism in the development of fog. Poor representation of...
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