Fog Events Research Articles

A Probability-Based Daytime Algorithm for Sea Fog Detection Using GOES-16 Imagery

Fog is a hazardous weather event that can endanger navigation, aviation, and transportation. While human has several limitations in detecting and forecasting offshore fog, satellite remote sensing offers cost-effective images. In this study, a probability-based daytime sea fog detection algorithm, applied to geostationary operational environmental satellite (GOES) 16 satellite data over the Grand Banks offshore Eastern Canada, is presented and compared with the National Oceanographic and Atmospheric Administration (NOAA)'s Low Instrument Flight Rules (LIFR) probability map. Initially, clear-sky and ice cloud classes were delineated in the GOES-16 image and then the remaining pixels were assigned a fog probability by conducting small droplet proxy, spatial homogeneity, and temperature difference tests. Moreover, a green band was linearly interpolated using the first three bands of GOES-16 images to generate pseudotrue color composites. The resulting maps were evaluated both during an extended sea fog event and using several statistical measures. The average detection probability for the observed advection fog events was 66% for the proposed method, while that for NOAA's LIFR map was 38%. Furthermore, by thresholding the generated maps at the probability of 60%, the false alarm rate, probability of detection, hit rate, and Hanssen–Kuiper skill score were 0.09, 0.77, 0.83, and 0.68, respectively. The proposed method is operationally being used in this region to detect and monitor sea fog, facilitating safe navigation and aviation. This is the first study that uses GOES-16 for daytime fog detection and discusses a satellite-based solution for fog modeling in Grand Banks, NL.

Sub‐km scale numerical weather prediction model simulations of radiation fog

AbstractThe numerical weather prediction (NWP) of fog remains a challenge, with accurate forecasts relying on the representation of many interacting physical processes. The recent Local And Non‐local Fog EXperiment (LANFEX) has generated a detailed observational dataset, creating a unique opportunity to assess the NWP of fog events. We evaluate the performance of operational and research configurations of the Met Office Unified Model (MetUM) with three horizontal grid lengths, 1.5 km and 333 and 100 m, in simulating four LANFEX case studies. In general, the subkilometre (sub‐km) scale versions of MetUM are in better agreement with the observations; however, there are a number of systematic model deficiencies. MetUM produces valleys that are too warm and hills that are too cold, leading to valleys that do not have enough fog and hills that have too much. A large sensitivity to soil temperature was identified from a set of parametrisation sensitivity experiments. In all the case studies, the model erroneously transfers heat too readily through the soil to the surface, preventing fog formation. Sensitivity tests show that the specification of the soil thermal conductivity parametrisation can lead to up to a 5‐hr change in fog onset time. Overall, the sub‐km models demonstrate promise, but they have a high sensitivity to surface properties.

Fog Forecast Using WRF Model Output for Solar Energy Applications

The occurrence of fog often causes errors in the prediction of the incident solar radiation and the power produced by photovoltaic cells. An accurate fog forecast would benefit solar energy producers and grid operators, who could take coordinated actions to reduce the impact of discontinuity, the main drawback of renewable energy sources. Considering that information on discontinuity is crucial to optimize power production estimation and plant management efficiency, in this work, a fog forecast method based on the output of the Weather Research and Forecasting (WRF) numerical model is presented. The areal extension and temporal duration of a fog event are not easy to predict. In fact, there are many physical processes and boundary conditions that cause fog development, such as the synoptic situation, air stability, wind speed, season, aerosol load, orographic influence, humidity and temperature. These make fog formation a complex and rather localized event. Thus, the results of a fog forecast method based on the output variables of the high spatial resolution WRF model strongly depend on the specific site under investigation. In this work, the thresholds are site-specifically designed so that the implemented method can be generalized to other sites after a preliminary meteorological and climatological study. The proposed method is able to predict fog in the 6–30 h interval after the model run start time; it has been evaluated against METeorological Aerodrome Report data relative to seven selected sites, obtaining an average accuracy of 0.96, probability of detection of 0.83, probability of false detection equal to 0.03 and probability of false alarm of 0.18. The output of the proposed fog forecast method can activate (or not) a specific fog postprocessing layer designed to correct the global horizontal irradiance forecasted by the WRF model in order to optimize the forecast of the irradiance reaching the photovoltaic panels surface.

An Analysis of Fog in the Mainland Portuguese International Airports

An analysis of 17 years of half-hourly aeronautic observations (METAR) and special observations (SPECI) in the three international airports of mainland Portugal indicates strong variations in fog properties. Fog is a rare event at Faro, a winter phenomenon in Lisbon and mainly a summer process at Porto. At both Lisbon and Porto, fog is favoured by specific synoptic circulations, here classified into a set of weather types, compatible with the strict requirements of fog formation. At the same time, however, a detailed analysis of the distribution of fog, and the classification of its onset processes, reveal a crucial dependence on local wind. This suggests that the advection of moist air from nearby sources, from the Tagus estuary at Lisbon and from the ocean at Porto, is the dominant process at both locations, despite the large differences found in the timing of those fog processes. The observational data (METAR) prior to the fog formation is used to classify the fog generation mechanism for 96.9% of the fog events at Porto, and 98.9% at Lisbon. Among the five fog types identified using a classification algorithm, cloud base lowering is the most common one at both locations, gathering half of the classified fog events, followed by advection, precipitation, and radiation. No fog event of the evaporation type was detected at both airports. The analysis of the observed horizontal visibility during the fog events revealed that cloud base lowering and radiation fog are the most intense events. The median of the minimum horizontal visibility of these two types of fog varies between 150 and 250 m, as the average ranges between 217.8 and 312.9 m. The study results have revealed a promising prefog diagnosis tool to be explored in detail in further operational context studies.

A method for calibrating forward scatter meters indoors

In this study, we developed a method for calibrating forward scatter meters (FSMs) against transmissometers for measuring visibility under laboratory conditions, and we designed and constructed a novel fog chamber for calibrating FSMs indoors. The fog chamber was used to simulate a controlled visibility environment, and a transmissometer was installed on both ends of the fog chamber as the standard. The developed method involved a comparison of the FSMs and transmissometer in a group of fog events. FSMs were installed on both sides of the optical path between the transmitter and receiver of the transmissometer. The chamber door was closed, and, after creating fog to simulate low-visibility conditions, measurements were collected from the FSMs and transmissometer every minute while the fog dissipated very slowly. The measurement errors of the FSM could then be calculated. To evaluate this method, tests were conducted in the fog chamber, and the results show that the fog chamber could simulate visibility from 10 m to 10 000 m, while the FSMs could only be calibrated below a visibility of 1500 m due to the baseline of the transmissometer. The fog homogeneity was controlled within 1.2% or less, and the stability was limited to 5% per 30 min. These parameters are reasonably homogeneous and stable for FSM—transmissometer comparison. Three PWD22 FSMs were calibrated using this method, and the calibration uncertainties were estimated to be in the range of 7.8% to 9.2%.

The formation and evolution of parent and oxygenated polycyclic aromatic hydrocarbons during a severe winter haze-fog event over Xi'an, China.

In this study, 3- or 4-h high time-resolved PM2.5 was observed during a severe winter haze-fog event (1 to 6 January 2017) to investigate the formation and evolution of parent polycyclic aromatic hydrocarbons (pPAHs) and oxygenated polycyclic aromatic hydrocarbons (OPAHs) in Xi'an, a typical city in northwestern China. Three episodes (episode I, episode II, and rainy day (EI, EII, and RD)) have been identified during this haze-fog event. Nine water-soluble ions, 8 carbonaceous fractions, 18 pPAHs, and 3 OPAHs in PM2.5 were measured. pPAHs showed two peaks at around 12:00 local standard time (LST) and 24:00 LST and two troughs at around 2:00 LST and 18:00 LST during EI. However, the OPAHs presented highest at around 18:00 LST and lowest at around 2:00 LST. During EII, pPAHs and OPAHs displayed similar diurnal variations with the highest values at noon but lowest values at around 2:00-5:00 LST.In addition, no obvious diurnal variations of pPAHs and OPAHs were observed during RDwere absent during RD. Diurnal variations of pPAH ring distributions demonstrated coal combustion, and vehicle emissions contributed to pPAHs for three episodes, which is further confirmed by diagnostic ratio results. High oxygenation (Ro) rates were found during the sampling time, which favored OPAH formation. The study herein indicates that OPAH formation through complex atmospheric reactions provides us new insights into the severe haze-fog events.

Comparison of ambient air pollution levels of Amritsar during foggy conditions with that of five major north Indian cities: multivariate analysis and air mass back trajectories

In the present study, winter fog events (Nov. 2017–Feb. 2018) in Amritsar city were compared with other major cities of North India. Multivariate data analysis, along with air mass trajectory analysis, was used to explain the complex behaviour of ambient air quality during winter fog. Average particulate matter (PM) during fog events was PM2.5 (77 μg m−3), PM10 (162 μg m−3) above the 24 h average National Ambient Air Quality Standards (NAAQS) of PM2.5 (60 μg m−3) and PM10 (100 μg m−3), respectively prescribed by Government of India. Wind speed and visibility during fog events were studied along with prevailing wind direction for major PM episodes. Amritsar’s PM2.5 comparison with Ludhiana, Delhi, Kanpur, Lucknow, and Jaipur showed a clear link between Amritsar with Ludhiana (r = 0.807), a North Indian industrial hub. Lucknow and Kanpur had a strong correlation (r = 0.826) due to their proximity. Box-plot of PM2.5 to PM10 ratio revealed a lower contribution of PM2.5 in Amritsar as compared to other cities. Dimensionality reduction using factor analysis of ambient air quality and meteorological parameters grouped the data in order of their variance explained. The first principal component (PC-1) was PM2.5 and PM10, followed by an antagonist correlation of humidity with wind velocity and visibility in Amritsar city. Factor analysis of ambient air quality of six cities, grouped Delhi, Kanpur, and Lucknow into PC-1, followed by Ludhiana and Amritsar as PC-2 which could be due to their proximity signifying the similar ambient air quality of the sites. In order to determine the origin of air mass, 24 h backward trajectories were studied and corroborated with wind rose profile. The results revealed the transport of air masses from the west to the source location.

Evolution of Aerosol Under Moist and Fog Conditions in a Rural Forest Environment: Insights From High‐Resolution Aerosol Mass Spectrometry

AbstractThe effect of foggy/moist conditions on the characteristics of secondary organic aerosol (SOA) was studied. Analysis of the high‐resolution time‐of‐flight aerosol mass spectrometer measurements identified two fresh biogenic SOA factors (BSOA: BSOA‐1 and BSOA‐2), hypothesized to be formed through the nighttime reaction of biogenic volatile organic compounds with nitrate radical. During foggy periods, the more oxidized oxygenated OA (MO‐OOA) was scavenged most efficiently (86% removal), followed by the less oxidized OOA (LO‐OOA) (55%), SO4 (53%), and BSOA (25%). Aerosol mass increased during fog events, and the post‐fog aerosol mass was higher (11%) than during the prefog period, with a reduction for MO‐OOA and an enhancement for LO‐OOA and BSOA. The high positive correlation observed between aerosol liquid water (ALW) and BSOA suggests the importance of aqueous‐phase processing on the BSOA formation, and an increase in log10(ALW) of 1 corresponded to an average increase of about 0.9 μg m−3 in BSOA.

Why Does Fog Deepen? An Analytical Perspective

The overall depth of a fog layer is one of the important factors in determining the hazard that a fog event presents. With discrete observations and often coarse numerical grids, however, fog depth cannot always be accurately determined. To address this, we derive a simple analytical relation that describes the change in depth of a fog interface with time, which depends on the tendencies and vertical gradients of moisture. We also present a lengthscale estimate for the maximum depth over which mixing can occur in order for the fog layer to be sustained, assuming a uniform mixing of the vertical profiles of temperature and moisture. Even over several hours, and when coarse observational resolution is used, the analytical description is shown to accurately diagnose the depth of a fog layer when compared against observational data and the results of large-eddy simulations. Such an analytical description not only enables the estimation of sub-grid or inter-observation fog depth, but also provides a simple framework for interpreting the evolution of a fog layer in time.

On the performance of microlysimeters to measure non-rainfall water input in a hyper-arid environment with focus on fog contribution

The measurement of non-rainfall atmospheric water input (NRWI) in arid environments requires instruments that are capable to detect even smallest amounts of total daily water input of less than 0.1 mm. Microlysimeters yield robust and high precision data of such low NRWI. We provide a technical description of a self-constructed microlysimeter and demonstrate its excellent performance regarding the analysis of NRWI in the Central Namib Desert. Three stations of the FogNet measurement network have been equipped with microlysimeters in order to measure fog deposition. NRWI and evaporation for days/nights without fog shows a persistent diurnal course. Deviations from this baseline define the amount of fog deposition, intensity and duration of a fog events. A more detailed analysis of a five-day period reveals the complex nature and variation between individual fog events with respect to the different patterns of fog deposition and fog precipitation and the contribution of adsorption, dew and fog to NRWI. The relation between fog precipitation and fog deposition is not straightforward and a simple parameterization of the processes that quantifies the amount of the water sampled by fog collectors and its connection to NRWI is still lacking.

Study on a Large-Scale Persistent Strong Dense Fog Event in Central and Eastern China

A large-scale persistent strong dense fog (SDF) event that occurred from December 30, 2016, to January 5, 2017, in central and eastern China is analyzed by using a variety of data, including high-resolution satellite and surface observations, meteorological tower observations, fine-resolution sounding observations, and NCEP/NCAR reanalysis data. The results show the following: (1) The SDF event has the characteristics of long duration, wide influence range, large intensity, and serious air pollution. During the study period, there are 531 stations with SDF events, covering an area of over 360,000 km2. There were five stations in Hebei province where the fog lasted for more than 77 hours, and even some stations did not dissipate during the day. (2) Radiation fog and advection fog alternate in this SDF event, namely, radiation fog (20:00 BT on December 30 to 14:00 on January 1), advection radiation fog (20:00 on January 1 to 08:00 on January 2), radiation fog (night on January 2 to daytime on January 3), and advection radiation fog (night on January 3 to January 5). The characteristic of radiation fog is that the central and eastern part of China was controlled by “L” type high pressure. In the stage of advection radiation fog, the combined effect of weak cold advection and radiation cooling leads to the occurrence of SDF. (3) Regarding the duration of the fog event, the inversion structure is continuously maintained at night and in the morning near the stratum, and when the fog intensity is strong, the inversion intensity is correspondingly large, the fog top is lower than the inversion layer top, and the top of the SDF is between 80 and 400 meters.

Temporal and spatial variations of haze and fog and the characteristics of PM2.5 during heavy pollution episodes in China from 2013 to 2018

In recent years, the frequent occurrence of haze and fog events in East and Central China has caused a serious reduction in atmospheric visibility and had a huge impact on human health. Based on the relative humidity, visibility and PM2.5 concentration, the occurrence frequencies of haze as well as the spatial and temporal variations of fog, haze and mist in China from 2013 to 2018 were analyzed. The occurrence frequency of the three weather phenomena increased from 2013 until 2016, and then decreased. Regarding seasonal distribution, haze days are concentrated in winter, while mist often appears in spring and autumn. Clean fog mainly occurs in high-mountain stations and clean areas with high relative humidity, while polluted fog is more common in densely populated cities. In Beijing, the proportion of clean weather increases year by year, PM2.5 in haze weather in Beijing mainly consists of organic carbon, nitrate, sulfate and other secondary aerosols. Most fog events are accompanied by air pollution. The dominant haze is humid haze, which means that its occurrence and aggravation are usually related to aerosol hygroscopic growth.

Spatiotemporal variability and evolution of day and night winter fog over the Indo Gangetic Basin using INSAT-3D and comparison with surface visibility and aerosol optical depth

Every year during the peak winter months (December–January), dense and prolonged fog envelops the Indo-Gangetic Basin (IGB) over the Indian sub-continent leading to economic loss. Many efforts are being made to understand its characteristics to improve forecasting skills. In the present work Indian National SATellite (INSAT-3D), a geostationary satellite, retrieved fog data available at every 30 min interval throughout the day and night is used to study its evolution, spatial and temporal variability for the winter months of December 2016 and January 2017 in conjunction with surface measurements. Fog data when compared with ground-based horizontal visibility over different stations in IGB showed good relationship, also depicted similar temporal variability in tune with the favorable meteorological parameters of temperature, relative humidity, and wind speed. It is observed that INSAT-3D captured fog very well for visibility ranging from 0 to 500 m representing very dense, dense, and moderate fog, while, the shallow fog with visibility >600 m is captured occasionally. From the maps of spatial and temporal variability of fog, the regions most affected are identified based on fog duration. The intense fog events covering the entire IGB for long duration are observed mostly in the midnight (00:00–04:00) and early morning (04:00–08:00) hours (local time) of December as compared to January. While in January, moderate intense fog spans the entire IGB during day time also. Due to increase in pollution levels, including biomass burning as inferred from MODIS fire counts, and stable atmosphere, high aerosol optical depths (AOD) are observed across IGB. The high AOD regions (> 0.8) covering central and west IGB, are also the hotspot regions of fog/smog onset and slowly expand over a larger area and intensify.

On the Investigation of the Typology of Fog Events in an Arid Environment and the Link with Climate Patterns

AbstractThe central aim of this work is to investigate the characteristics of fog events over the United Arab Emirates (UAE) and identify the underlying physical processes responsible for fog initiation and dissipation. To achieve this, hourly meteorological measurements at eight airport stations, along with ERA5 reanalysis data (1995–2018), are utilized. The analysis indicates the dominance of radiation fog (RAD) as, on average, 70% of the observed events fall under this category. Fog in the UAE typically forms between 2000 and 0200 local time (LT) and dissipates between 0600 and 0900 LT. During a typical dense fog event recorded during 22–23 December 2017, cooling and moistening tendencies of up to 1.2 K h−1 and 0.7 g kg−1 h−1 are observed ~5–6 h before fog onset. In the vertical, a dry and warm layer above 750 hPa gradually descends from above 500 hPa to promote the development of fog. Similar conclusions are reached when analyzing composites of fog events. Further, the variability of fog occurrence associated with El Niño–Southern Oscillation (ENSO) patterns is explored. It is concluded that the El Niño (warm) and La Niña (cold) phases exhibit very different spatial characteristics with respect to surface meteorological variables. In particular, during El Niño events, the near-surface atmosphere is cooler and moister compared to La Niña events, favoring RAD fog formation over the UAE. Besides, fog events during El Niño years tend to last longer compared to La Niña years due to an earlier onset.

On the aerodynamic fog collection efficiency of fog water collectors via three-dimensional numerical simulations

Fog water collection gained interest in recent years as an emerging solution for water scarcity in arid and semi-arid areas. During a fog event, a porous mesh screen of plastic polymer retains the water through droplet impaction, where the droplets coalesce and trickle into a gutter for collection. This type of collecting system has existed since the 1960s; however, a substantial lack of understanding remains as to the aerodynamics that dominates the collection phenomena. The Aerodynamic Collection Efficiency (ηa) is the determining factor in the overall performance of such systems. This paper aims to further the fundamental knowledge on the aerodynamic behavior during fog collection. For this, a three-dimensional computational fluid dynamics model was developed, where the collector's mesh was modeled as a porous medium, which simulates a conventional two-dimensional double layer mesh. A parametric study was carried out varying the mesh's geometric characteristics (flat and concave), mesh-to-ground distance, and wind speed. The effect of wind speed on aerodynamic collection efficiency is mainly determined by the relative relationship between the viscous and inertial pressure drop in the porous medium. A greater curvature reduces the mesh's airflow impedance, leading to a significant improvement of the aerodynamic collection efficiency. Within the parameter range of our study, we found a maximum aerodynamic collection efficiency of 35% for the largest curvature (1.1 m), the highest mesh-to-ground distance (2 m), and the maximum wind speed (5 to 7 m s−1).

Geochemical insights into the relationship of rock varnish and adjacent mineral dust fractions

Rock varnishes are μm-thin, dark, manganese(Mn)-rich crusts that accrete in the order of few μm/ka on weathering-resistant lithologies. Although these crusts can form in all climates, they are best known in arid to semi-arid settings. Aeolian dust is understood as a major contributor to the distinct trace metal and REE enrichments in rock varnish. However, the exact proportions of abiotic and biotic formation mechanisms that may explain the oxidation-reactions of Mn2+ to Mn4+, present as Mn oxyhydroxides in the varnish, are still a matter of ongoing debate.We present here the first systematic study of trace element enrichment processes between the uppermost layer of the varnish sequence and their adjacent <50 μm and >50 μm dust fractions across a selection of 41 major and trace elements. This approach is used to investigate samples from three fully arid deserts: the An Nafud in Saudi Arabia, the Negev in Israel, and the Mojave in the USA, which are compared to the significantly different environment of the semi-arid Knersvlakte in South Africa. A new in situ trace element analysis protocol was developed to perform femto- and nanosecond sector-field LA-ICP-MS microanalyses at high-spatial resolution, which allows us to measure the most recent varnish layers for their comparison with recent dust. In agreement with previous studies, all varnishes are enriched in Mn, Pb, Ce, Co, Ba, Zn, Ni, and the Rare-Earth Elements (REE). Here we demonstrate that fine (<50 μm) dust is characterized by similar trace element trends as the varnishes, at overall lower mass fractions. Dust >50 μm has low trace element mass fractions, and enrichment patterns plotting distinctly away from varnish and fine dust. Based on these geochemical patterns, our results indicate a general enrichment mechanism from fine dust to varnish. Previous studies suggested dust to play an integral role in providing the trace elements that are incorporated into the varnish by pH-Eh fluctuations in short-term rain and fog events. We amalgamate and refine previous growth models by providing direct evidence that leaching of about 10% of the Mn and other trace elements from clay minerals in rain or fog droplets at pH ~5 and subsequent scavenging on varnish surfaces at pH ~8 leads integrated over time to the distinct enrichment patterns of the varnish, while initial Mn oxyhydroxide formation is suggested to follow pathways of metal oxide mediated photo-catalysis.For the semi-arid occurrence in the Knersvlakte we present a distinct growth model as both environment, varnish, and dust composition differ significantly from the arid settings. Here, thick, metallic-looking varnish occurs mainly on the rim of quartz pebbles, lacks microlamination, and likely has upscaled growth processes. Among other aspects, we suggest a more complex interplay between photo-catalysis, nocturnal condensation events on quartz pebbles with subsequent water trapping at the rock-soil-atmosphere interface, due to a salic top-soil layer, to mainly account for these differences.

Effects of Weather on Highway Traffic Capacity in China: Characteristics and Causes of Roadblocks Due to Fog Events

Fog-induced highway roadblocks (access restrictions and traffic congestion) include not only the influence of fog conditions on traffic capacities but also human factors and traffic conditions that affect highway traffic. They directly reflect the combined effects of weather conditions, traffic conditions, and human factors on the flow of traffic. This work systematically studies the characteristics and causes of fog-blocked events in China and finds that the annual total mileage of highways in China that are blocked by fog events is roughly 178% of the entire national highway mileage. The distribution of fog-blocked events is very uneven in China, with 88.5% of annual totals occurring in East China, Central China, and North China. The high-occurrence period for fog roadblocks is around sunrise, whereas its low-occurrence period is from noon to nightfall. Roadblocks occur more frequently, with earlier peak time, in South China than in North China. Winter represents the high-occurrence period for fog-blocked events, followed by spring, autumn, and summer. Fog distribution characteristics, along with seasonal and diurnal variations, are generally consistent with those of fog-blocked events. All the above characteristics indicate that fog conditions are the main reason for fog-induced highway roadblocks. In addition, roadblocks are also affected by traffic flow, road network density, culverts and bridges, curved roads, slopes, and other conditions.

Characteristics of Low-level jets during 2015–2016 and the effect on fog in Tianjin

Characteristics of wind direction, wind speed, wind shear, and height of low-level jets (LLJs) are obtained and studied using the wind profile data collected by a wind-profile radar located at Xiqing station in Tianjin from 2015 to 2016. Results on the general characteristics of LLJs show that the dominate wind direction of LLJs ranges from 180° to 270° (47%), which is also the prevailing wind direction of strong LLJs (wind speed larger than 14 m s–1). The wind speeds of LLJs are mostly lower than 14 m s−1, and the occurrence proportion of strong LLJs is only 22.8%. The occurrence height distributions of LLJs are relatively uniform throughout the year except the peak at the lower heights (500–600 m). Moreover, the seasonal and diurnal variations of LLJs are investigated, respectively, and the results show that the occurrence frequency of LLJs during warm season is larger than that during cold season, which may be due to the increasing amplitude of inertial oscillations in the boundary layer. The diurnal variation of all categories of LLJs shows a pronounced a unimodal pattern, with the peak of occurrence number appearing at around midnight. In addition, the relationship between LLJs and fog events in Tianjin is investigated based on the data obtained from the surface automatic weather station (AWS) and a 255-m atmospheric boundary layer meteorological tower, since LLJs frequently occur in foggy days (almost 50%) in Tianjin. Eleven fog events accompanied by LLJs are analyzed and statistical results show LLJ plays a critical role in fog life cycle. The effect of northerly LLJs on fog is to enhance turbulent mixing in the fog layer, which is induced by wind shear associated with northerly LLJs and propagates downward to fog layer. There is a threshold relationship between the northerly LLJs and fog development, strong LLJs lead to inversion layer collapse and fog dissipation, while weak LLJs weaken the strength of inversion and atmospheric stability, which are favorable for fog development. Therefore, for fog events accompanied by northerly LLJs, there are negative correlations between fog durations and the strength of LLJs. However, the main contribution of northerly LJJs to fog is to result in fog dissipation in Tianjin, since the duration of fog with northerly LLJs is shorter than that without LLJs. The main contribution of the southwesterly LLJs are to transport water vapor to fog area and increase the humidity in fog layer. Therefore, the southwesterly LLJs are favorable for the fog formation, development and prolong the duration of fog.

To what extents do urbanization and air pollution affect fog?

Abstract. The remarkable development of China has resulted in rapid urbanization (urban heat island and dry island) and severe air pollution (aerosol pollution). Previous studies demonstrate that these two factors have either suppressing or promoting effects on fog, but what are the extents of their individual and combined effects? In this study, a dense radiation fog event in eastern China in January 2017 was reproduced by the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem), and the individual and combined effects of urbanization and aerosols on fog (indicated by liquid water content – LWC) are quantitatively revealed. Results show that urbanization inhibits low-level fog, delays its formation and advances its dissipation due to higher temperatures and lower saturations. In contrast, upper-level fog could be enhanced because of the updraught-induced vapour convergence. Aerosols promote fog by increasing LWC, increasing droplet concentration and decreasing droplet effective radius. Further experiments show that the current pollution level in China could still be below the critical aerosol concentration that suppresses fog. Urbanization influences fog to a larger extent than aerosols do. When urbanization and aerosol pollution are combined, the much weaker aerosol-promoting effect is counteracted by the stronger urbanization-suppressing effect on fog. Budget analysis of LWC reveals that urban development (urbanization and aerosols) alters the LWC profile and fog structure mainly by modulating condensation–evaporation process. Our results infer that urban fog will be further reduced if urbanization keeps developing and air quality keeps deteriorating in the future.

Towards a Better Representation of Fog Microphysics in Large-Eddy Simulations Based on an Embedded Lagrangian Cloud Model

The development of radiation fog is influenced by multiple physical processes such as radiative cooling and heating, turbulent mixing, and microphysics, which interact on different spatial and temporal scales with one another. Once a fog layer has formed, the number of fog droplets and their size distribution have a particularly large impact on the development of the fog layer due to their feedback on gravitational settling and radiative cooling at the fog top, which are key processes for fog. However, most models do not represent microphysical processes explicitly, or parameterize them rather crudely. In this study we simulate a deep radiation fog case with a coupled large-eddy simulation (LES)–Lagrangian cloud model (LCM) approach for the first time. By simulating several hundred million fog droplets as Lagrangian particles explicitly (using the so-called superdroplet approach), we include a size-resolved diffusional growth including Köhler theory and gravitational sedimentation representation. The results are compared against simulations using a state of the art bulk microphysics model (BCM). We simulate two different aerosol backgrounds (pristine and polluted) with each microphysics scheme. The simulations show that both schemes generally capture the key features of the deep fog event, but also that there are significant differences: the drop size distribution produced by the LCM is broader during the formation and dissipation phase than in the BCM. The LCM simulations suggest that its spectral shape, which is fixed in BCMs, exhibits distinct changes during the fog life cycle, which cannot be taken into account in BCMs. The picture of the overall fog droplet number concentration is twofold: For both aerosol environments, the LCM shows lower concentrations of larger fog droplets, while we observe a higher number of small droplets and swollen aerosols reducing the visibility earlier than in the BCM. As a result of the different model formulation we observe higher sedimentation rates and lower liquid water paths for the LCM. The present work demonstrates that it is possible to simulate fog with the computational demanding approach of LCMs to assess the advantages of high-resolution cloud models and further to estimate errors of traditional parameterizations.