Radiation Fog Chemistry and Microphysics

1986 ◽  
pp. 213-226 ◽  
Author(s):  
Sandro Fuzzi
Keyword(s):  
Radiation Fog ◽  
Fog Chemistry

Measurements of Visual Range and Radiation-Fog (Haze) Microphysics

1980 ◽  
Vol 37 (3) ◽  
pp. 622-629 ◽  
Author(s):  
Michael B. Meyer ◽  
James E. Jiusto ◽  
G. Garland Lala
Keyword(s):  
Radiation Fog ◽  
Visual Range

A study of the contribution of pollution to visibility in a radiation fog

1973 ◽  
Vol 7 (11) ◽  
pp. 1079-1092 ◽  
Author(s):  
J.A. Garland ◽  
J.R. Branson ◽  
L.C. Cox
Keyword(s):  
Radiation Fog

scholarly journals Demistify: a large-eddy simulation (LES) and single-column model (SCM) intercomparison of radiation fog

2022 ◽  
Vol 22 (1) ◽  
pp. 319-333
Author(s):  
Ian Boutle ◽  
Wayne Angevine ◽  
Jian-Wen Bao ◽  
Thierry Bergot ◽  
Ritthik Bhattacharya ◽  
...  
Keyword(s):  
Large Eddy Simulation ◽  
Weather Prediction ◽  
Cloud Droplet ◽  
Droplet Size Distribution ◽  
Radiation Fog ◽  
Eddy Simulation ◽  
Cloud Droplet Size Distribution ◽  
Large Eddy ◽  
Single Column ◽  
Les Model

Abstract. An intercomparison between 10 single-column (SCM) and 5 large-eddy simulation (LES) models is presented for a radiation fog case study inspired by the Local and Non-local Fog Experiment (LANFEX) field campaign. Seven of the SCMs represent single-column equivalents of operational numerical weather prediction (NWP) models, whilst three are research-grade SCMs designed for fog simulation, and the LESs are designed to reproduce in the best manner currently possible the underlying physical processes governing fog formation. The LES model results are of variable quality and do not provide a consistent baseline against which to compare the NWP models, particularly under high aerosol or cloud droplet number concentration (CDNC) conditions. The main SCM bias appears to be toward the overdevelopment of fog, i.e. fog which is too thick, although the inter-model variability is large. In reality there is a subtle balance between water lost to the surface and water condensed into fog, and the ability of a model to accurately simulate this process strongly determines the quality of its forecast. Some NWP SCMs do not represent fundamental components of this process (e.g. cloud droplet sedimentation) and therefore are naturally hampered in their ability to deliver accurate simulations. Finally, we show that modelled fog development is as sensitive to the shape of the cloud droplet size distribution, a rarely studied or modified part of the microphysical parameterisation, as it is to the underlying aerosol or CDNC.

scholarly journals Demistify: an LES and SCM intercomparison of radiation fog

2021 ◽  
Author(s):  
Ian Boutle ◽  
Wayne Angevine ◽  
Jian-Wen Bao ◽  
Thierry Bergot ◽  
Ritthik Bhattacharya ◽  
...  
Keyword(s):  
Weather Prediction ◽  
Cloud Droplet ◽  
Droplet Size Distribution ◽  
Radiation Fog ◽  
Eddy Simulation ◽  
Cloud Droplet Size Distribution ◽  
Single Column ◽  
Research Grade ◽  
Model Variability ◽  
Les Model

Abstract. An intercomparison between 10 single-column (SCM) and 5 large-eddy simulation (LES) models is presented for a radiation fog case study inspired by the LANFEX field campaign. 7 of the SCMs represent single-column equivalents of operational numerical weather prediction (NWP) models, whilst 3 are research-grade SCMs designed for fog simulation, and the LES are designed to reproduce in the best manner currently possible the underlying physical processes governing fog formation. The LES model results are of variable quality, and do not provide a consistent baseline against which to compare the NWP models, particularly under high aerosol or cloud droplet number (CDNC) conditions. The main SCM bias appears to be toward over-development of fog, i.e. fog which is too thick, although the inter-model variability is large. In reality there is a subtle balance between water lost to the surface and water condensed into fog, and the ability of a model to accurately simulate this process strongly determines the quality of its forecast. Some NWP-SCMs do not represent fundamental components of this process (e.g. cloud droplet sedimentation) and therefore are naturally hampered in their ability to deliver accurate simulations. Finally, we show that modelled fog development is as sensitive to the shape of the cloud droplet size distribution, a rarely studied or modified part of the microphysical parametrization, as it is to the underlying aerosol or CDNC.

Microstructure of a Radiation Fog

1981 ◽  
Vol 38 (2) ◽  
pp. 454-458 ◽  
Author(s):  
H. E. Gerber
Keyword(s):  
Radiation Fog

Fog forecasting for Schiphol airport at sub-kilometre scale.  

2021 ◽  
Author(s):  
Gert-Jan Steeneveld ◽  
Roosmarijn Knol
Keyword(s):  
Spatial Resolution ◽  
Numerical Models ◽  
Wrf Model ◽  
Horizontal Resolution ◽  
Physical Processes ◽  
Radiation Fog ◽  
Fog Forecasting ◽  
Elevation Data ◽  
The Individual ◽  
The Impact

<p>Fog is a critical weather phenomenon for safety and operations in aviation. Unfortunately, the forecasting of radiation fog remains challenging due to the numerous physical processes that play a role and their complex interactions, in addition to the vertical and horizontal resolution of the numerical models. In this study we evaluate the performance of the Weather Research and Forecasting (WRF) model for a radiation fog event at Schiphol Amsterdam Airport (The Netherlands) and further develop the model towards a 100 m grid spacing. Hence we introduce high resolution land use and land elevation data. In addition we study the role of gravitational droplet settling, advection of TKE, top-down diffusion caused by strong radiative cooling at the fog top. Finally the impact of heat released by the terminal areas on the fog formation is studied. The model outcomes are evaluated against 1-min weather observations near multiple runways at the airport.</p><p>Overall we find the WRF model shows an reasonable timing of the fog onset and is well able to reproduce the visibility and meteorological conditions as observed during the case study. The model appears to be relatively insensitive to the activation of the individual physical processes. An increased spatial resolution to 100 m generally results in a better timing of the fog onset differences up to three hours, though not for all runways. The effect of the refined landuse dominates over the effect of refined elevation data. The modelled fog dissipation systematically occurs 3-4 h hours too early, regardless of physical processes or spatial resolution. Finally, the introduction of heat from terminal buildings delays the fog onset with a maximum of two hours, an overestimated visibility of 100-200 m and a decrease of the LWC with 0.10-0.15 g/kg compared to the reference.</p>

Fog Chemistry at an Urban Midwestern Site

1986 ◽  
Vol 36 (12) ◽  
pp. 1359-1361 ◽  
Author(s):  
Patricia S. Muir ◽  
Kimberly A. Wade ◽  
Bradley H. Carter ◽  
Thomas V. Armentano ◽  
Robert A. Pribush
Keyword(s):  
Fog Chemistry
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