Investigating the Sensitivity of Marine Fog to Physical and Microphysical Processes Using Large-Eddy Simulation

Wainwright, Charlotte E.; Richter, David H.

doi:10.1007/s10546-020-00599-6

Cited by 12 publications

(9 citation statements)

References 58 publications

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“…3a, 6, 10 and most of Fig. 11 from Wainwright and Richter, 2021) appear to show Q c maxima at the surface, although Fig. 7 in Schwenkel and Maronga (2019) suggests a rapid drop in Q c near the surface.…”

Section: Model Studiesmentioning

confidence: 92%

“…These and other papers confirm the strong size dependence of deposition velocity, and acknowledge wind speed dependence, but are often concerned with long-term estimates of the deposition of chemical species to the ocean or lake rather than short-term events. One way in which wind speed plays a role is via wave breaking and broken water surfaces, a concept used in a model proposed by Williams (1982). This proposes that dry deposition of aerosol particles is considerably different between smooth and broken patches of the water surface, with a much higher resistance over the smooth areas.…”

Section: Past Field and Laboratory Measurementsmentioning

confidence: 99%

“…Recent papers by Wainwright and Richter (2021) and focus on marine fog, using a LES model, following on from the work of Maronga and Bosveld (2017) and Maronga (2019, 2020) on LES studies of radiation fog. The marine fog models use Morrison et al's (2005) microphysics.…”

Section: Model Studiesmentioning

confidence: 99%

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Surface deposition of marine fog and its treatment in the Weather Research and Forecasting (WRF) model

Taylor

Chen

et al. 2021

Atmos. Chem. Phys.

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Abstract. There have been many studies of marine fog, some using Weather Research and Forecasting (WRF) and other models. Several model studies report overpredictions of near-surface liquid water content (Qc), leading to visibility estimates that are too low. This study has found the same. One possible cause of this overestimation could be the treatment of a surface deposition rate of fog droplets at the underlying water surface. Most models, including the Advanced Research Weather Research and Forecasting (WRF-ARW) Model, available from the National Center for Atmospheric Research (NCAR), take account of gravitational settling of cloud droplets throughout the domain and at the surface. However, there should be an additional deposition as turbulence causes fog droplets to collide and coalesce with the water surface. A water surface, or any wet surface, can then be an effective sink for fog water droplets. This process can be parameterized as an additional deposition velocity with a model that could be based on a roughness length for water droplets, z0c, that may be significantly larger than the roughness length for water vapour, z0q. This can be implemented in WRF either as a variant of the Katata scheme for deposition to vegetation or via direct modifications in boundary-layer modules.

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Section: Model Studiesmentioning

confidence: 92%

Section: Past Field and Laboratory Measurementsmentioning

confidence: 99%

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Surface deposition of marine fog and its treatment in the Weather Research and Forecasting (WRF) model

Taylor

Chen

et al. 2021

Atmos. Chem. Phys.

View full text Add to dashboard Cite

show abstract

“…Recent papers by Wainwright and Richter (2021) and Richter et al (2021) focus on marine fog using a large eddy simulation model, following on from the work of Maronga and Bosveld (2017) and Maronga (2019, 2020) on LES studies of radiation fog. The marine fog models use Morrison et al (2005) show number densities that are maximum at the fog top, around 30 m after 10 h, while Qc and mean droplet radius are maximum near the ground.…”

Section: Model Studiesmentioning

confidence: 99%

Surface deposition of marine fog and its treatment in the WRF model

Taylor

Chen

et al. 2021

Preprint

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Abstract. There have been many studies of marine fog, some using WRF and other models. Several model studies report over-predictions of near surface liquid water content (Qc) leading to visibility estimates that are too low. This study has found the same. One possible cause of this overestimation could be the treatment of a surface deposition rate of fog droplets at the underlying water surface. Most models, including the Advanced Research Weather Research and Forecasting (WRF-ARW) Model, available from the National Center for Atmospheric Research (NCAR), take account of gravitational settling of cloud droplets throughout the domain and at the surface. However, there should be an additional deposition as turbulence causes fog droplets to collide and coalesce with the water surface. A water surface, or any wet surface, can then be an effective sink for fog water droplets. This process can be parameterized as an additional deposition velocity with a model that could be based on a roughness length for water droplets, z0c, that may be significantly larger than the roughness length for water vapour, z0q. This can be implemented in WRF either as a variant of the Katata scheme for deposition to vegetation, or via direct modifications in boundary-layer modules.

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“…Previous studies have shown that fog growth can be altered by surface boundary conditions, terrain, and SST (e.g. Bari et al, 2015; Gultepe, 2015; Tang, 2012; Wainwright & Richer, 2021). Hence, it is considered that potential surface conditions are important for fog occurrence and development in this study area.…”

Section: Introductionmentioning

confidence: 99%

Numerical simulations of upslope fog observed at Beppu Bay in Oita Prefecture, Japan

Ohashi

Suido

2021

Meteorological Applications

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The present study focussed on the formation of upslope fog. This fog causes chronic expressway closures near Beppu Bay (BB) in Oita Prefecture, Japan. A dense fog event, occurring on 3 and 4 May 2020, resulting from the passage of an extratropical cyclone through the southern Japanese islands, was simulated using the Weather Research and Forecasting (WRF) numerical model. The simulation results indicated that warm and humid air with a lifting condensation level less than 20 m flowed into a plain from BB. Simulated fog and poor visibility were more severe on mountain slope adjacent to BB than on the surroundings. Here, the westward horizontal flux of water vapour by the wind flow was prolonged at lower heights. Analyses of the simulated elements verified that the upslope fog was induced by moist adiabatic cooling of the air lifted by the upslope winds. At the mature stage of upslope fog, a simulated local vertical circulation generated in conjunction with the upper synoptic flow extended the dense fog into the upper atmosphere over BB. During the decaying stage of upslope fog on mountain, a fog covered on the entire BB. This was associated with weakening winds at lower heights. Sensitivity experiments for model boundary conditions supported the importance of mountain steepness and the rectangular shape of BB for the generation of upslope fog. Finally, an application possibility of dense fog forecasts was discussed by using a simulated difference in the equivalent potential temperature between the base of the mountain and Beppuwan expressway interchange located midslope.

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Investigating the Sensitivity of Marine Fog to Physical and Microphysical Processes Using Large-Eddy Simulation

Cited by 12 publications

References 58 publications

Surface deposition of marine fog and its treatment in the Weather Research and Forecasting (WRF) model

Surface deposition of marine fog and its treatment in the Weather Research and Forecasting (WRF) model

Surface deposition of marine fog and its treatment in the WRF model

Numerical simulations of upslope fog observed at Beppu Bay in Oita Prefecture, Japan

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