Fog Simulation Research Articles

Improvement of Fog Simulation by the Nudging of Meteorological Tower Data in the WRF and PAFOG Coupled Model

Improvement of fog simulation accuracy was investigated for the fogs that occurred on the south coast of the Korean Peninsula using the WRF (3D) and PAFOG (1D) coupled model. In total, 22 fog cases were simulated and accuracy of the fog simulation was examined based on Critical Success Index, Hit Rate and False Alarm Rate. The performance of the coupled WRF-PAFOG model was better than that of the single WRF model as expected. However, much more significant improvement appeared only when the data from a 300 m meteorological tower was not only used for the initial conditions but also nudged during the simulation. Moreover, a proper prescription of soil moisture was found to be important for accurate fog simulation especially for the fog cases with prior precipitation since efficient moisture supply from the precipitation-soaked soil might have been critical for fog formation. It was also demonstrated that with such optimal coupled model setting, a coastal radiation fog event with prior precipitation could be very realistically simulated: the fog onset and dissipation times matched so well with observation. In detail, radiative cooling at the surface was critical to form a surface inversion layer as the night fell. Then the vapor flux from the precipitation-soaked surface was confined within the inversion layer to form fog. It is suggested that a proper prescription of soil moisture in the model based on observations, if readily available, could be a cost-effective method for improving operational fog forecasting, considering the fact that tall meteorological towers are a rarity in the world.

The Impact of Turbulent Diffusion Driven by Fog‐Top Cooling on Sea Fog Development

AbstractTurbulent mixing driven by cloud/fog‐top radiative and evaporative cooling (hereafter top‐driven diffusion), including top‐down mixing and top‐cooling entrainment, is critical for the development of cloud/fog. Previous work mainly focused on impacts of top‐driven diffusion on stratocumulus‐topped planetary boundary layer (PBL) and radiation fog over land. However, its exact role in sea fog process is yet unclear. Using the Weather Research and Forecasting (WRF) model with the updated Yonsei University (YSU) PBL scheme, in which the ysu_topdown_pblmix option is responsible for the parameterization of the top‐driven diffusion, the present study investigates respective effects of the top‐cooling entrainment and top‐down mixing on an advection fog event over the Yellow Sea that occurred on 20–21 May 2014. Evaluation of the modeling results confirms that the top‐driven diffusion significantly improves the sea fog simulation. The top‐cooling entrainment allows more relatively quiescent air above the fog top to mix into the sea fog layer, leading to a higher mixed layer with increased temperature and decreased humidity. With the enhancement of buoyant turbulence, the warming and dehumidifying moderately lift the sea fog bottom and reduce the false fog area. The top‐down mixing performs quite well in reproducing a stable structure near the fog top, which results from the added turbulent mixing determined by a revised K profile. Note that the effect of top‐driven diffusion shows high sensitivities to shortwave radiation and vertical resolution. Besides the fog‐top cooling, the fog‐droplet sedimentation is necessary to be included in the top‐cooling entrainment.

Direct Numerical Simulation of Fog: The Sensitivity of a Dissipation Phase to Environmental Conditions

The sensitivity of fog dissipation to the environmental changes in radiation, liquid-water lapse rate, free tropospheric temperature and relative humidity was studied through numerical experiments designed based on the 2007-Paris Fog observations. In particular, we examine how much of the stratocumulus-thinning mechanism can be extended to the near-surface clouds or fog. When the free troposphere is warmed relative to the reference case, fog-top descends and become denser. Reducing the longwave radiative cooling via a more emissive free troposphere favors thickening the physical depth of fog, unlike cloud-thinning in a stratocumulus cloud. Drying the free troposphere allows fog thinning and promotes fog dissipation while sustaining the entrainment rate. The numerical simulation results suggest that the contribution of entrainment drying is more effective than the contribution of entrainment warming yielding the reduction in liquid water path tendency and promoting the onset of fog depletion relative to the reference case studied here. These sensitivity experiments indicate that the fog lifting mechanism can enhance the effect of the inward mixing at the fog top. However, to promote fog dissipation, an inward mixing mechanism only cannot facilitate removing humidity in the fog layer unless a sufficient entrainment rate is simultaneously sustained.

Numerical Simulation of Sea Fog over the Yellow Sea: Comparison between UM + PAFOG and WRF + PAFOG Coupled Systems

Sea fogs over the Yellow Sea in the western coast of the Korean Peninsula were simulated by the coupled systems of 3D regional models (UM and WRF) and a 1D model (PAFOG) with fine vertical resolution. The coupling was conducted by generating meteorological fields with 3D regional model and providing them as the initial fields and boundary conditions (external forcings) of the 1D model. The accuracy of the cold sea fog (T – SST > 0) simulation improved through the proper treatment of turbulent cooling near the surface by the coupling. However, the accuracy of warm sea fog (T – SST < 0) was improved only slightly by the coupling, which is likely due to the inadequate estimation of the external forcing (advection) of heat and moisture below the upper inversion layer. It was found that the resolution of the 3D regional model did not significantly affect the initial fields of the 1D model but the performance of the 1D + 3D coupled systems were still affected by the resolution of the 3D regional model since it affected the external forcings on the 1D model in the coupled system. Surprisingly, the coupled system with coarse resolution 3D model produced generally better fog simulation than that with fine resolution 3D model, due to the high fluctuation of advection (external forcing) for fine resolution. Meanwhile, for the same resolution, the two 3D models (UM and WRF) produced significantly different initial fields and the overall performance seemed better for the UM coupled system than the WRF coupled system. In short, it was demonstrated that fog prediction could be improved by the coupling for cold sea fog cases over the Yellow Sea, but improvement from the coupling was small for warm sea fog cases, which indicates that more research is required to produce promising results for warm sea fogs.

Large-eddy simulation of radiation fog with comprehensive two-moment bulk microphysics: impact of different aerosol activation and condensation parameterizations

Abstract. In this paper we study the influence of the cloud microphysical parameterization, namely the effect of different methods for calculating the supersaturation and aerosol activation, on the structure and life cycle of radiation fog in large-eddy simulations. For this purpose we investigate a well-documented deep fog case as observed at Cabauw (the Netherlands) using high-resolution large-eddy simulations with a comprehensive bulk cloud microphysics scheme. By comparing saturation adjustment with a diagnostic and a prognostic method for calculating supersaturation (while neglecting the activation process), we find that, even though assumptions for saturation adjustment are violated, the expected overestimation of the liquid water mixing ratio is negligible. By additionally considering activation, however, our results indicate that saturation adjustment, due to approximating the underlying supersaturation, leads to a higher droplet concentration and hence significantly higher liquid water content in the fog layer, while diagnostic and prognostic methods yield comparable results. Furthermore, the effect of different droplet number concentrations is investigated, induced by using different common activation schemes. We find, in line with previous studies, a positive feedback between the droplet number concentration (as a consequence of the applied activation schemes) and strength of the fog layer (defined by its vertical extent and amount of liquid water). Furthermore, we perform an explicit analysis of the budgets of condensation, evaporation, sedimentation and advection in order to assess the height-dependent contribution of the individual processes on the development phases.

Curriculum Model Adaptation with Synthetic and Real Data for Semantic Foggy Scene Understanding

This work addresses the problem of semantic scene understanding under fog. Although marked progress has been made in semantic scene understanding, it is mainly concentrated on clear-weather scenes. Extending semantic segmentation methods to adverse weather conditions such as fog is crucial for outdoor applications. In this paper, we propose a novel method, named Curriculum Model Adaptation (CMAda), which gradually adapts a semantic segmentation model from light synthetic fog to dense real fog in multiple steps, using both labeled synthetic foggy data and unlabeled real foggy data. The method is based on the fact that the results of semantic segmentation in moderately adverse conditions (light fog) can be bootstrapped to solve the same problem in highly adverse conditions (dense fog). CMAda is extensible to other adverse conditions and provides a new paradigm for learning with synthetic data and unlabeled real data. In addition, we present three other main stand-alone contributions: 1) a novel method to add synthetic fog to real, clear-weather scenes using semantic input; 2) a new fog density estimator; 3) a novel fog densification method to densify the fog in real foggy scenes without using depth; and 4) the Foggy Zurich dataset comprising 3808 real foggy images, with pixel-level semantic annotations for 40 images under dense fog. Our experiments show that 1) our fog simulation and fog density estimator outperform their state-of-the-art counterparts with respect to the task of semantic foggy scene understanding (SFSU); 2) CMAda improves the performance of state-of-the-art models for SFSU significantly, benefiting both from our synthetic and real foggy data. The datasets and code are available at the project website.

Heterogeneous Fog Generated with the E ect of Light Scattering and Blur

The development of computer graphics forces new requirements on the developers, which will make the virtual world more similar to the real world. One of these elements is the simulation of fog. Common fog algorithms mix the color of the scene with the color of the fog over a certain distance. However, one feature of the naturally foggy scenery is ignored. With the distance and density of the fog, the observed scenery or individual objects become more blurred. In this paper we will present our implementation of the distance fog in the Unreal Engine 4, including the effect of blurring the foggy areas, simulating of light scattering and variations in fog density using noise.

Numerical simulations of an advection fog event over Shanghai Pudong International Airport with the WRF model

A series of numerical simulations is conducted to understand the formation, evolution, and dissipation of an advection fog event over Shanghai Pudong International Airport (ZSPD) with the Weather Research and Forecasting (WRF) model. Using the current operational settings at the Meteorological Center of East China Air Traffic Management Bureau, the WRF model successfully predicts the fog event at ZSPD. Additional numerical experiments are performed to examine the physical processes associated with the fog event. The results indicate that prediction of this particular fog event is sensitive to microphysical schemes for the time of fog dissipation but not for the time of fog onset. The simulated timing of the arrival and dissipation of the fog, as well as the cloud distribution, is substantially sensitive to the planetary boundary layer and radiation (both longwave and shortwave) processes. Moreover, varying forecast lead times also produces different simulation results for the fog event regarding its onset and duration, suggesting a trade-off between more accurate initial conditions and a proper forecast lead time that allows model physi-cal processes to spin up adequately during the fog simulation. The overall outcomes from this study imply that the complexity of physical processes and their interactions within the WRF model during fog evolution and dissipation is a key area of future research.

Combination of WENO and Explicit Runge–Kutta Methods for Wind Transport in the Meso-NH Model

AbstractThis paper investigates the use of the weighted essentially nonoscillatory (WENO) space discretization methods of third and fifth order for momentum transport in the Meso-NH meteorological model, and their association with explicit Runge–Kutta (ERK) methods, with the specific purpose of finding an optimal combination in terms of wall-clock time to solution. A linear stability analysis using von Neumann theory is first conducted that considers six different ERK time integration methods. A new graphical representation of linear stability is proposed, which allows a first discrimination between the ERK methods. The theoretical analysis is then completed by tests on numerical problems of increasing complexity (linear advection of high wind gradient, orographic waves, density current, large eddy simulation of fog, and windstorm simulation), using a fourth-order-centered scheme as a reference basis. The five-stage third-order and fourth-order ERK combinations appear as the time integration methods of choice for coupling with WENO schemes in terms of stability. An explicit time-splitting method added to the ERK temporal scheme for WENO improves the stability properties slightly more. When the spatial discretizations are compared, WENO schemes present the main advantage of maintaining stable, nonoscillatory transitions with sharp discontinuities, but WENO third order is excessively damping, while WENO fifth order provides better accuracy. Finally, WENO fifth order combined with the ERK method makes the whole physics of the model 3 times faster compared to the classical fourth-order centered scheme associated with the leapfrog temporal scheme.

A New Method for Fast Computation of Three-Dimensional Atmospheric Infrared Radiative Transfer in a Nonscattering Medium, with an Application to Dynamical Simulation of Radiation Fog in a Built Environment

Abstract The atmospheric radiation field has seen the development of more accurate and faster methods to take into account absorption. Modeling fog formation, where infrared radiation is involved, requires accurate methods to compute cooling rates. Radiative fog appears under clear-sky conditions owing to a significant cooling during the night where absorption and emission are the dominant processes. Thanks to high-performance computing, high-resolution multispectral approaches to solving the radiative transfer equation are often used. Nevertheless, the coupling of three-dimensional radiative transfer with fluid dynamics is very computationally expensive. Radiation increases the computation time by around 50% over the pure computational fluid dynamics simulation. To reduce the time spent in radiation calculations, a new method using analytical absorption functions fitted by Sasamori on Yamamoto’s radiation chart has been developed to compute an equivalent absorption coefficient (spectrally integrated). Only one solution of the radiative transfer equation is needed against Nband × Ngauss for an Nband model with Ngauss quadrature points on each band. A comparison with simulation data has been done and the new parameterization of radiative properties proposed in this article shows the ability to handle variations of gas concentrations and liquid water.

Forecasting radiation fog at climatologically contrasting sites: evaluation of statistical methods and WRF

A six‐year climatology of radiation fog has been compiled at two sites: the Research Centre for the Lower Atmosphere (CIBA, Spain) and the Cabauw Experimental Site for Atmospheric Research (CESAR, The Netherlands). These sites are contrasted in terms of geographical situation, climate zone, altitude, humidity and soil water availability. Therefore, several climatological differences in fog abundance, onset, dissipation and duration have been quantified between the two sites. The more humid site (CESAR) is characterised by relatively short radiation fog events distributed throughout the year. However, radiation fog at the drier site (CIBA) is more persistent and appears during late autumn/winter months. In general, its formation requires more time after sunset (∼2 h more), since further cooling is required to reach saturation. The forecast of these fog events has been evaluated through two different approaches. First, we extend the statistical method presented by Menut et al. (2014) (M14). This method uses statistics to define threshold values on key variables for fog formation (pre‐fog) and verifies its predictability using observations and numerical model output. We present some of the most appropriate threshold values for the forecasting of pre‐fog periods at both sites, which differ from those presented in M14 and depend on the optimisation of the hit rate or the false‐alarm rate. Additionally, we also extend M14 by suggesting other variables as potential predictors for fog formation (friction velocity and visibility tendency). Finally, we focus on fog simulation by the Weather Research and Forecasting (WRF) model in terms of liquid water content. The WRF model was able to simulate radiation fog when configured with sophisticated physical options and high resolution. However it failed in simulating the onset, dissipation and the vertical extent of fog (which was overestimated). The model results were extremely sensitive to the spin‐up time.

Fog and Hazy Simulation for outside Lighting Study

With the high humidity caused by the urban microclimate, the visibility is greatly reduced due to the fog weather as well as the hazy weather formed by the accumulation of pollutant and vapor. In order to evaluate how the fog and haze weather affects outside lighting, a hazy simulation environment is introduced in this paper. An ultrasonic humidifier is used to produce droplets for fog simulation. Haze is simulated by using air blower to blow plant ashes. Transmittance of several different light sources under the simulated fog and haze conditions is shown. The results can be used to study outside lighting.

Predictability of an Advection Fog Event over North China. Part I: Sensitivity to Initial Condition Differences

Abstract The predictability of a dense advection fog event on 21 February 2007 over north China (NC) is investigated with ensemble simulations using the Weather Research and Forecasting Model (WRF). Members with the best and worst simulation are selected from the ensemble, and their initial condition (IC) differences are explored. To test the sensitivity of fog simulation to those differences, the model is initialized with ICs that change linearly from the worst member to the best member, and the changes in simulated results are examined. The improvement in simulations due to the linear improvement of ICs is found to be monotonic. The IC differences at lower levels are of more influence to the simulation than IC differences at higher levels. By removing the IC differences of each meteorological variable individually, it is found that improvements in potential temperature and horizontal wind are more important than that of water vapor mixing ratio in this case. Additionally, the linear improvement in each meteorological variable also contributes monotonically to the simulated results. The budget analyses of the tendency of potential temperature and water vapor mixing ratio show that turbulence mixing and advection are the major factors contributing to the formation of fog. The correct initial temperature field ensures the formation and maintenance of an inversion, and the correct initial wind field ensures the correct transport of temperature and moisture in this case. Further discussion examines the reasons for the monotonic behavior in the simulation improvement.

Effects of Aerosols on Fogs Observed in the North China Plain

Fog simulation and prediction are becoming increasingly important in China because of the great impact of fog on traffic and other human activities. More studies are needed to have a better underst...

Multidecadal simulation of coastal fog with a regional climate model

In order to model stratocumulus clouds and coastal fog, we have coupled the University of Washington boundary layer model to the regional climate model, RegCM (RegCM-UW). By comparing fog occurrences observed at various coastal airports in the western United States, we show that RegCM-UW has success at modeling the spatial and temporal (diurnal, seasonal, and interannual) climatology of northern California coastal fog. The quality of the modeled fog estimate depends on whether coast-adjacent ocean or land grid cells are used; for the model runs shown here, the oceanic grid cells seem to be most appropriate. The interannual variability of oceanic northern California summertime fog, from a multi-decadal simulation, has a high and statistically significant correlation with the observed interannual variability (r = 0.72), which indicates that RegCM-UW is capable of investigating the response of fog to long-term climatological forcing. While RegCM-UW has a number of aspects that would benefit from further investigation and development, RegCM-UW is a new tool for investigating the climatology of coastal fog and the physical processes that govern it. We expect that with appropriate physical parameterizations and moderate horizontal resolution, other climate models should be capable of simulating coastal fog. The source code for RegCM-UW is publicly available, under the GNU license, through the International Centre for Theoretical Physics.

Numerical simulation of fog using non-hydrostatic NWP model with third-order turbulence closure

Numerical simulation of a fog episode is conducted using the Hong Kong Observatory’s Non-Hydrostatic Model (NHM) to study various physical processes in the formation of a shallow saturated layer. It is found that a third-order turbulence closure model and partial condensation scheme implemented in NHM can improve the parametrization of turbulent mixing and condensation processes. Physically, the formation of fog or low-level clouds over the coastal waters is primarily due to advection of warm and humid maritime air mass over a cooler sea surface. The numerical experiments show that the radiative cooling above the low-level cloud top further enhances the mixing process during nighttime and results in condensation of cloud liquid water near the surface. Differences in the forecast low-level clouds, wind and moisture fields within the boundary layer using the original first-order turbulence closure scheme will also be illustrated.

Real-time simulation of fog on GPU

Fog simulation is an important research topic in the field of three-dimensional simulation.It puts forward high requirements on real-time performance as well as realistic rendering results for complex three-dimensional simulation system.By analyzing the traditional simulation methods of fog,the authors proposed a Graphic Processing Unit(GPU)-based method to simulate the fog effect in real-time.The basic idea was to employ an exponential function to simulate the fade of fog with height.Then a GPU implementation of this formula was presented.And finally the fog color was blended with the fragment color according to the fog factor.The experimental results show that the proposed method can generate strongly realistic fog in real-time.

Static Estimation of the Meteorological Visibility Distance in Night Fog with Imagery

In this paper, we propose a new way to estimate fog extinction at night using a classification of fog depending on the forward scattering. We show that a characterization of fog based on the atmospheric extinction parameter only is not sufficient. This method works in dense fogs (meteorological visibility distances < 400m) with a single image and three known light sources. The method is validated on synthetic images generated with a semi Monte-Carlo ray tracing software dedicated to fog simulation. We drove this study in simulated environment in order to help us designing a test site located outdoor.

Fog simulation using a mesoscale model in and around the Yodo River Basin, Japan

In this study, fog simulations were conducted using the Fifth-Generation NCAR/Penn State Mesoscale Model (MM5) in and around the Yodo River Basin, Japan. The purpose is to investigate the MM5 performance of fog simulation for long-term periods. The simulations were performed for January, February, March, and July, 2005 with a coarse 3-km and a nested fine 1-km grid domains. Results of the simulations were compared with data from ten meteorological observatories, fog sampling site in Mt. Rokko, and visibility measurement sites along the Second Meishin Expressway. At the meteorological observatories, the MM5 predictions agreed well with the observed temperature and specific humidity. In the Mt. Rokko region, MM5 generally reproduced the occurrence of relatively thick fog events but tended to overestimate liquid water content (LWC) of fog (by factors of 2.2-3.3 in terms of monthly mean LWC). In the Second Meishin Expressway region, while MM5 identified the specific sites at which fog either frequently or seldom occurs, the model underestimated the monthly fog frequencies by factors of more than 1.5. Overall, MM5 reproduced the general trend of fog events, and the model performance may be improved by using more adequate land surface data and suitable physics options for our study.

Simulation of fog with the ECMWF prognostic cloud scheme

Simulation of fog with the ECMWF prognostic cloud scheme