How Sea Fog Influences Inland Visibility on the Southern China Coast

atmosphere

Article How Sea Fog Inﬂuences Inland Visibility on the Southern China Coast

Jianxiang Sun 1, Huijun Huang 2,*, Suping Zhang 1 and Weikang Mao 2

1 College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao 266100, China; [email protected] (J.S.); [email protected] (S.Z.) 2 Institute of Tropical and Marine Meteorology, China Meteorological Administration, Guangzhou 510080, China; [email protected] * Correspondence: [email protected]

Received: 1 August 2018; Accepted: 29 August 2018; Published: 3 September 2018

Abstract: Sea fog can lead to inland fog on the southern China coast, affecting visibility on land. To better understand how such fog influences inland visibility,we observed two sea-fog cases at three sites (over sea, at coast, and inland) and analyzed the results here. Our analysis suggests four factors may be key: (1) The synoptic pattern is the decisive factor determining whether fog forms inland. First, sea fog and low clouds form when the synoptic pattern involves warm, moist air moving from a warmer sea-surface temperature (SST) region to a colder SST region near the coast. Then, inland fog tends to occur under this low-cloud background with relatively large horizontal-vapor transport. A greater horizontal-vapor transport results in denser fog with higher liquid-water content. Conversely, a strong horizontal advection of temperature with less horizontal-vapor transport can hinder inland-fog formation. (2) Local cooling (including ground radiative cooling) helps promote inland fog formation. (3) Fog formation requires low wind speed and small turbulent kinetic energy (TKE). The small TKE helps the vapor accumulate close to the surface and maintain the local cooling effect. (4) Fog formation is promoted by having the energy flux downward at night with the land surface cooling the atmosphere as well as having lower soil temperature and higher soil humidity.

Keywords: sea fog; fog forms; inland visibility; southern China coast

1. Introduction Sea fog severely influences marine navigation as well as activities in harbors and coastal airports around the world [1–4]. This fog can drift inland. For example, Lamb (1943) [5] found that the sea fog (haar) of Scotland can move inland during the day if insolation is weak. He also noted that this inland fog tends to clear during the day and thicken at night. Leipper (1994) [6] found that coastal fog on the U.S. West Coast forms with an unusually strong inversion below 400 m, but stratus forms, instead, if the inversion is relatively weak and the inversion height is above 400 m. Thus, a strong inversion inland is needed for sea fog to persist inland. More recently, Koraˇcinet al. (2005) [7] found the cloud–fog transition to be determined by a combination of synoptic and boundary-layer processes, with the dissipation of sea fog being a consequence of a complex interplay between advection, synoptic evolution, and development of local circulations. Compared to sea-fog formation, inland-fog formation involves different physical processes. Petterssen (1939) [8], and later Jiusto (1981) [9], argued that the three most important formation processes are the cooling of air, the addition of water vapor, and the mixing of moist air parcels of different temperatures. Duynkerke (1991) [10] describes the importance of more specific processes; in particular, the cooling of moist air by radiation flux, the vertical mixing of heat and moisture, horizontal and vertical wind, heat and moisture transport in soil, advection, and topographic effects.

Atmosphere 2018, 9, 344; doi:10.3390/atmos9090344 www.mdpi.com/journal/atmosphere Atmosphere 2018, 9, 344 2 of 18

Bergot and Guedalia (1994) [11] argued that the local atmospheric cooling is critical for fog to form at night. Duynkerke (1999) [12] examined the effect of long-wave radiation on the structure of the clear, stable boundary layer as well as the relationship between radiative cooling near the surface and the top of the boundary layer together with its impact on the heat-flux profile. He thought it is necessary to further quantify the relative importance of radiative cooling and turbulence for the formation of fog. Zhou and Ferrier (2008) [13] pointed out that the small turbulence intensity inside a fog will help it persist. Steeneveld et al. (2010) [14] found the observed long-wave radiative heating to be minimal at the evening transition, and they argued that the total radiative-heating rate appears to be controlled by the upward long-wave flux divergence at night. Sun et al. (2017) [15] analyzed two sea-fog cases over the Yellow Sea to determine their influence on the coastal area. They argued that large-scale transport and boundary-layer structure are critical. However, their work lacks micrometeorological observations, and thus cannot determine the small-scale aspects of the mechanism. Overall, the mechanism of the sea-fog influence on inland visibility needs to be better understood. On the southern China coast, inland fog associated with sea fog is difficult to predict during the sea-fog season (from January to May [16]). In some cases, extensive fog exists inland during a sea-fog event, but not always. Moreover, sometimes the inland fog that occurs with sea fog is patchy, adding to the forecast difficulty [17,18]. To address coastal-weather issues such as this, the Institute of Tropical and Marine Meteorology (ITMM) established the Marine Meteorological Science Experiment Base (MMSEB) at Bohe, Maoming in 2007. Then, in 2008, the Integrated Observation Platform for Marine Meteorology (IOPMM) was set up over sea and began acquiring many observation datasets of sea fog [19]. Based on these data, ITMM investigated the formation mechanism, the microphysics structure, and the characteristics of the boundary layer during sea fog [20–22]. Here, we use observations of two sea-fog cases at three sites (over sea, at coast, and inland) to better understand how sea fog influences inland visibility on the southern China coast.

2. Observational Sites and Data

2.1. Observational Sites and Data We used observational data from three sites: site A on the coast, site B over sea, and site C inland. See Figure1 for their locations. These three sites are the same as those in our previous study [ 23]. Site A is the MMSEB and operated by the Institute of Tropical Marine and Meteorology (ITMM) (Figure1a). Site B is the IOPMM. Site C is the Dianbai National Climate Observatory (DNCO) (Figure1b). Figure1b shows the distances between the three sites and to the coastal line. The land–atmosphere and air-sea surface data come from instruments mounted at three sites. We collect data on two sea-fog cases in March 2017. The observation system over land and sea (i.e., sites C, B) both include an instrument tower equipped with gradient- and flux-observation systems (Figure1c,d), whereas we released a GPS sonde at coast (site A). Inland, the iron tower is 10 m high, with instruments to measure fluxes at the top. Other instruments include an automatic meteorological station, radiometers, and instruments to measure ground temperature and humidity, skin temperature, and soil heat flux (Figure1c,d; Table1). The sea site lies above ~15 m of water, and the regular triangle platform is about 11 m above sea level. The instruments, listed in Table1, and observational procedures are the same as before [ 23], except the present study does not have sea-temperature measurements. See Reference [23] for more details about the IOPMM. Atmosphere 2018, 9, 344 3 of 18 Atmosphere 2018, 9, x FOR PEER REVIEW 3 of 18

FigureFigure 1.1. ObservationalObservational sitesite locations locations and and close close views. views (.a ()a Observational) Observational site site A locationA location (gray (gray cross) cross) on theon the southern southern China China coast. coast. (b) The(b) The coastal coastal site Asite is A the is Marine the Marine Meteorological Meteorological Science Science Experiment Experiment Base (MMSEB)Base (MMSEB (21.45) ◦(21.45°N, 111.32 N, ◦ 111.32°E, 7.0 mE, MSL),7.0 m theMSL oversea), the oversea site B is thesite Integrated B is the Integrated Observation Observation Platform forPlatform Marine for Meteorology Marine Meteorology (IOPMM) (21.44(IOPMM◦ N,) 111.39 (21.44°◦ E, N, operated 111.39° byE, MMSEB),operated and by MMSEB),the inland andsite C the is theinland Dianbai site NationalC is the ClimateDianbai Observatory National Climate (DNCO) Observatory (21.55◦ N, 110.99(DNCO◦ E,) (21.55° 31.6 m MSL).N, 110.99° Distances E, 31.6 from m differentMSL). Distances locations from and fromdifferent coastal locations lines (from and Googlefrom coastal Earth). lines (c) Close (from view Google of oversea Earth). site (c) BClose (IOPMM); view theof over upper-rightsea site B corner (IOPMM of the); the image upper is- theright mounting corner of position the image of theis the Gill mounting Windmaster position Pro andof the Li-cor Gill 7500AWindmaster instruments Pro and at theLi-cor 23.4 7500A m level instruments (main photo at courtesy the 23.4 ofm Weikanglevel (main Mao photo on 27 courtesy June 2014). of Weikang (d) Close viewMao on of inland27 June site 2014). C (DNCO); (d) Close the view upper-right of inland corner site C of(DNCO the image); the is upper the mounting-right corner position of the of image the Gill is Windmasterthe mounting Pro position and Li-cor of the 7500A Gill instrumentsWindmaster at Pro the 10and m Li level-cor (main7500A photo instruments courtesy at of the Weikang 10 m level Mao on(main 20 Januaryphoto courtesy 2017). of Weikang Mao on 20 January 2017).

Atmosphere 2018, 9, 344 4 of 18

Table 1. The observation sites, instruments, and data.

Instrument Type or Observation Sites and Nominal Height(s) Make and Model Measurement Variables MMSEB (A) IOPMM (B) DNCO (C) Ultrasonic Anemometer, U.K. Gill Windmaster Pro; USA —— 23.4 m MSL * 10 m AGL ** Infrared CO2/H2O Analyzers LI-COR LI-7500A GPS Sonde Finland Vaisala RS-92 7 m MSL —— —— Netherlands Kipp and Zonen Radiometer 1.5 m AGL 12 m MSL 1.5 m AGL CMP22/CGR4; CNR_4 Gradients of Wind, USA RM. Young 05106; Finland 13.4, 16.4, 20.0, —— 10 m AGL Temperature, and Humidity Vaisala HMP45d 27.3 m MSL Pressure USA Setra Setraceram CS100 —— 13 m MSL 1.5 m AGL Rain gauge USA Campbell TB4 —— 12 m MSL 1.5 m AGL Ground Temperature USA Campbell 109SS; Campbell −5, −10, −20, −5, −10, −20, —— and Humidity CS616 −40 cm AGL −40 cm AGL Skin Temperature USA Campbell IRR-P —— 8 m MSL 1.5 m AGL Soil Heat-Flux Plate USA Campbell HFP01SC —— —— −5 cm AGL Auto Meteorological Station China Guangdong Observation 1.5 m AGL —— 1.5 m AGL (six variables) Center, WP3103 Visibility USA Belfort Model 6000 1.5 m AGL —— —— Liquid-Water Content USA DMT Model FM-120 1.5 m AGL —— —— Datalogger USA Campbell Scientiﬁc CR3000 7 m MSL 13 m MSL 1.5 m AGL * MSL: mean sea level. ** AGL: above-ground level.

During each sea-fog period, we launched a GPS Vaisala RS-92 sonde about every 3 h from the coastal site. The first period, hereafter case 1, ran from 0900 LST Mar 10 to 0500 LST Mar 11, the second, case 2, from 1200 LST Mar 30 to 1100 LST Mar 31. In total, 12 GPS sondes were released during the two events. As in our previous study [23], processing of the GPS sonde data and calculation of the equivalent potential temperature (θe) follows that in Reference [24]. We used ultrasonic anemometers and infrared CO2/H2O analyzers at the inland and oversea sites. We calculated the turbulence flux and turbulent kinetic energy (TKE) with EddyPro 6.0 software over time intervals of 30 min. The software uses the Foken et al. method [25] to run quality-control tests of the fluxes as shown in Table2. See our previous study [23] for more details.

Table 2. Overall quality ﬂags of the EddyPro 6.2 software used in the turbulence analyses.

RNcov (%) * ITCσ (%) ** QA/QC Flag Data Quality This Study ≤30 ≤30 0 High q0 ≤100 ≤100 1 Moderate q1 >100 >100 2 Low q2 * RNcov is used to evaluate the steady state of turbulence. ** ITCσ is used to evaluate the integral turbulence characteristic. More information is available in Reference [25].

2.2. Satellite Data We used the Himawari-8 satellite data to determine fog and cloud extent near the southern China coast. Himawari-8 is the 8th Himawari geostationary weather satellite operated by the Japan Meteorological Agency, entering operational service on 7 July 2015. Himawari-8 provides 16-channel imagery, including visible- and infrared-band scanning of the Asia-Paciﬁc region [26]. We used hourly imagery with 0.05◦ horizontal resolution, which was freely obtained from Kochi University (http://weather.is.kochi-u.ac.jp/wiki/archive). Daytime-sea-fog retrieval mainly includes (1) cloud and clear detection based on the visible channel; (2) sea-fog and other cloud detection based on both the temperature difference between the Atmosphere 2018, 9, 344 5 of 18 cloud top and sea surface [27], as well as the standard deviation in the thermal infrared channel [28]; and (3) night-time sea-fog detection that mainly relies on the dual-channel difference test [28,29].

2.3. Other Data The sea-surface temperature data come from the real-time global (RTG) data from the National Center for Environmental Prediction (NCEP) [30] and the NCEP Global Analysis on 1◦ × 1◦ grid-spacing datasets from the National Center for Environmental Prediction/National Weather Service/NOAA/U.S. Department of Commerce (2000). Backward-airﬂow trajectories come from our use of the HYSPLIT trajectory model and reanalysis data from the Global Data Assimilation System (GDAS) [31]. See Huang et al. [22] for more details.

3. Synoptic Backgrounds and Inﬂuence on Inland Visibility of the Two Cases Both sea-fog cases were warm-advection fog. Warm-advection fog is the most common sea fog on the southern China coast. With this fog, the surface-air temperature (SAT) usually exceeds the sea-surface temperature (SST). Warm-advection fog forms by the lowering of an existing cloud base, and its growth is mainly driven by the advection of warm moist air [22]. We examine these cases to better understand how sea fog inﬂuences inland visibility. For the analysis periods of both sea fog cases at the three sites, see Table3.

Table 3. Measurement goals and analysis periods (LST) at the three observation sites for both cases of sea fog.

Observation Site Goal Case 1 Case 2 Boundary layer structure 0900, 1600, 2000, 2300 LST 10 March; 0200, 1200, 2000, 2300 LST 30 March; 0200, 0800, Coast (GPS sonde release times) 0500 LST 11 March 1100 LST 31 March Oversea Turbulence near the sea surface 0800 LST 10 March-1400 LST 11 March 0800 LST 30 March-1400 LST 31 March Inland Turbulence near the land surface 0800 LST 10 March-1400 LST 11 March 0800 LST 30 March-1400 LST 31 March

In case 1, at 1400 LST 10 March, which was before the fog formed over sea, mainly a southern wind prevailed, transporting warm, moist air to the observational site. However, a dry, strong northeast wind dominated at the Taiwan Strait, preventing fog formation there (Figure2a). By 0200 LST 11 March, sea fog had formed, the wind was southeastern and nearly along the isobars, but was still bringing warm, moist air to the observational site. Meanwhile, the dry northeast wind at the Taiwan Strait remained strong (Figure2c). At 1400 LST 11 March, this dry northeast wind extended over the north of the South China Sea, dissipating the fog (Figure2e). In case 2, the synoptic pattern differed because the sea fog encountered a cold front. First, at 1400 LST 30 March, a southeastern wind brought warm, moist air to the southern China coast, causing fog to form over the sea (Figure2b). Then, at 0200 LST 31 March, a cold front appeared at the south side of the Nanling Mountains (110–116◦ E, 24–26.5◦ N). At the same time, the warm, moist wind kept on blowing towards the observational site, further developing the sea fog (Figure2d). Later, at 1400 LST 31 March, the cold front moved across the coastline, resulting in the dissipation of the sea fog (Figure2f). Atmosphere 2018, 9, 344 6 of 18 Atmosphere 2018, 9, x FOR PEER REVIEW 6 of 18

Figure 2. Wind vectors (m s−1), water-vapor mixing ratio (shaded, g kg−1), and air pressure at sea-surfaceFigure 2. Wind level (hPa).vectors (a )(m 1400 s− LST1), water March-vapor 10. (b mixing) 1400 LST ratio Mar (shaded, 30. (c) 0200 g kg LST−1), Marand 11. air ( d pressure) 0200 LST at 31sea March-surface (with level cold-front (hPa). (a)location). 1400 LST (Marche) 1400 10 LST. (b) March 1400 LST 11. (Marf) 1400 30. LST(c) 0200 31 March LST Mar (From 11. ( thed) 0200 FNL LST on 131◦ × Mar1◦ chgrid (with spacing cold- datasets.).front location) “A”. is (e the) 1400 coastal LST site.March 11. (f) 1400 LST 31 March (From the FNL on 1° × 1° grid spacing datasets.). “A” is the coastal site. In both cases, coastal visibility was hazardous near coastal site A (Figure3a,b). The retrieved In both cases, coastal visibility was hazardous near coastal site A (Figure 3a,b). The retrieved satellite data indicate more extensive sea fog near site A in case 1 than in case 2 (Figure3c–f). Case 1 also satellite data indicate more extensive sea fog near site A in case 1 than in case 2 (Figure 3c–f). Case 1 appeared to have more inland fog than case 2. At the inland site C (DNCO), fog occured in case 1 with also appeared to have more inland fog than case 2. At the inland site C (DNCO), fog occured in case visibility of 0.1 km, but not in case 2 (Figure4a,b). The aim was to determine the cause of this difference. 1 with visibility of 0.1 km, but not in case 2 (Figure 4a,b). The aim was to determine the cause of this difference. Atmosphere 2018, 9, 344 7 of 18 AtmosphereAtmosphere 2018 2018, ,9 9, ,x x FOR FOR PEER PEER REVIEW REVIEW 77 ofof 1818

FigFigureFigureure 3. 3. VisibleVisibleVisible cloud cloud cloud image image image from from from Hima Hima Himawari-8wariwari--88 and and and retrieval retrieval retrieval of of of the the fog‐ fog‐fog-cloudcloudcloud based based on on the the HimawariHimawari-8Himawari--88 datadata ofof casecase 11 (left(left (left column)column) column) andand and casecase case 22 2 (right(right (right column).column). column). ((aa) () a 16001600) 1600 LSTLST LST 1010. 10.. ((bb)) ( 1600b1600) 1600 LSTLST LST 3030 March30March March... ((cc)) (02000200c) 0200 LSTLST LST 1111 11MarchMarch March... ((dd) () d 02000200) 0200 LSTLST LST 3131 31 MarchMarch March... ((ee ())e 0900)0900 0900 LSTLST LST 1111 11 MarMar March.chch.. ((f (f)f) ) 09000900 0900 LSTLST LST 31 31 MarchMarch ((A(AA is is the thethe coastal coastal site site.).site..))..

Figure 4. Fog and light-fog visibilities (km) at various inland and coastal stations during the two FigureFigure 4.4. FogFog andand light-fog light-fog visibilities visibilities (km) (km) atvarious at various inland inland and coastaland coastal stations stations during during the two the sea-fog two sea-fog periods. (a) Case 1. (b) Case 2. The “+” is inland site C (DNCO). Red denotes fog; black is periods.sea-fog periods. (a) Case 1.(a ()b Case) Case 1. 2. (b The) Case “+” 2. is inlandThe “+ site” is Cinland (DNCO). site Red C (DNCO denotes). fog;Red black denotes is light fog fog.; black is lightlight fog.fog. Consider the relative humidities (RH). In case 1, fog was reported inland when the visibility ConsiderConsider thethe relativerelative humiditieshumidities (RH)(RH).. InIn casecase 1,1, fogfog waswas reportedreported inlandinland whenwhen thethe visibilityvisibility was about 1.0 km and RH = 96.5%. So, we used RH = 96.5% as the RH criterion for inland fog. waswas aboutabout 1.0 1.0 kmkm andand RHRH == 96.5%.96.5%. So So,, wewe used used RH RH = = 96.5% 96.5% as as thethe RH RH criterioncriterion for for inland inland fog.fog. However, the sensors at the oversea site experienced greater aging effects (due to greater sea-salt However,However, thethe sensorssensors atat thethe overseaoversea sitesite experienceexperiencedd greatergreater agingaging effectseffects (due(due toto greatergreater seasea--saltsalt erosionerosion andand longerlonger ttimeime beforebefore maintenancemaintenance oror replacement)replacement),, andand,, byby thethe samesame procedure,procedure, wewe ffououndnd Atmosphere 2018, 9, 344 8 of 18

Atmosphere 2018, 9, x FOR PEER REVIEW 8 of 18 erosion and longer time before maintenance or replacement), and, by the same procedure, we found thatthat RH RH = = 95% 95% g gaveave the the same same criterion criterion for for fog fog over over the the sea sea.. By By this this measure, measure, the the fog fog over over the the sea sea occuroccurredred from from 1600 1600 LST LST 10 10 Mar Marchch to to 0900 0900 LST LST 11 11 Mar March,ch, and and from from 2300 2300 LST LST 10 10Mar Marchch to 0800 to 0800 LST LST 11 Mar11 Marchch at inland at inland in case in case 1 (Figure 1 (Figure 5a).5 a).Before Before the thefog fogoccur occurred,red, the theinland inland region region was wasovercast overcast.. An observerAn observer at site at siteC noted C noted dense dense fog fog at 0200 at 0200 and and 0500 0500 LST LST 11 11 Mar Marchch at at inland inland (Table (Table 4).4). Applying Applying the samesame criteria toto casecase 2,2, we we determined determined that that fog fog occurred occurred from from 0430 0430 LST LST 30 March 30 Mar toch 1130 to LST1130 31 LST March 31 Maroverch sea, over while sea, while no fog no occurred fog occur inlandred inland (Figure (Fig5b).ure The 5b) RH. The brieﬂy RH briefly exceeded exceed 96.5%ed 96.5% after after 0800 0800 LST LST31 March, 31 Mar butch, it but was it due was to due a small to a rain.small We rain. will We later will discuss later thisdiscuss event. this The event weather. The during weather case during 2 was casealso 2 cloudy was also inland, cloudy with inland, a light with fog ata night.light fog However, at night. no However, fog formed no and fog theform lowested and visibility the lowest was visibility3.2 km at wa 0500s 3.2 LST km 31 at March 0500 LST (Table 31 4Mar). ch (Table 4).

FigFigureure 5. 5. RelativeRelative humidity humidity over over sea sea and and inland, inland, and and visibility visibility inland. inland. ( (aa)) Case Case 1. 1. ( (bb)) Case Case 2. 2. RH RH is is relativerelative humidity, humidity, VIS VIS is is visibility. visibility. The The green green line line indicates indicates the the sea sea-fog-fog period period defined deﬁned as as RH RH > > 95% 95% overover sea, sea, the the grey grey shading shading indicates indicates inland inland fog fog defined deﬁned as as RH RH > > 96.5%. 96.5%.

TableTable 4. 4. WeatherWeather observations observations inland inland (site (site C) C) during during the the sea sea-fog-fog e events.vents.

After Sea Before theBefore Sea the Fog Sea FogSea Sea-Fog-Fog Period After Sea Fog 1400 LST 1700 LST 2000 LST 2300 LST 0200 LST 0500 LST 0800 LST 1100 LSTFog Day and time (LST) March 10 March 10 2000March 10 March 10 March0200 11 March0500 11 March 11 March 11 Case 1Day and timeCloud *1400 LST 300, 7/71700 LST 1000, 10/8LST 1000, 8/82300 -, LST 9/- -,LST 9/- -,LST 9/- 1000,0800 8/8 LST 1000,1100 8/8 LST (LST)Visibility (km)March 10 9.0March 10 9.0 March 6.0 March 1.1 10 Mar 0.1ch Mar 0.1ch Mar 1.6ch 11 Mar 8.0 ch 11 Weather phenomena Cloudy Overcast10 Light fog Light fog Fog11 Fog11 Light fog Overcast Case 1700 LST 2000 LST 2300 LST 0200 LST 0500 LST 0800 LST 1100 LST 1400 LST CloudDay and * time (LST)300, 7/7 1000, 10/8 1000, 8/8 -, 9/- -, 9/- -, 9/- 1000, 8/8 1000, 8/8 1 March 30 March 30 March 30 March 31 March 31 March 31 March 31 March 31 Visibility Case 2 Cloud9.0 300, 7/79.0 300, 6/66.0 -, 9/-1.1 -,9/- -,0.1 9/- 1000,0.1 8/8 300, 7/71.6 300, 7/78.0 (km)Visibility (km) 20.0 12.0 7.0 11.0 3.2 3.5 30.0 30.0 Weather Light Weather phenomenaCloudy CloudyOvercast Cloudy Light fogLight Overcast fog LightFog fog LightFog fog CloudyLight fog CloudyOvercast * Thephenomena upper number is cloud-base height (m), thefog lower fraction is total cloud cover/low-cloud amount (10/10; using a scale of 1 to 10; 10− means larger than 9.5, but2300 less than 10; 0 means less0500 than 0.5); “-”0800 indicates no observation. AllDay symbols and time follow 1700 the specificationsLST 2000 forLST surface LST meteorological 0200 LST observations LST of China.LST 1100 LST 1400 LST (LST) March 30 March 30 March March 31 March March March 31 March 31 30 31 31 Case4. Advection and Boundary-Layer Characteristics Cloud 300, 7/7 300, 6/6 -, 9/- -, 9/- -, 9/- 1000, 8/8 300, 7/7 300, 7/7 2 ◦ In fogVisibility season, warm, moist air that advects from the warmer SST area south of the 23 C isotherm 20.0 12.0 7.0 11.0 3.2 3.5 30.0 30.0 and mixes(km) with air in the colder SST region near the coast always results in fog and low clouds. Weather Light Light Light To examine these processes,Cloudy weCloudy calculated the 48 h backwardOvercast trajectories of airflowCloudy to the inlandCloudy site phenomena fog fog fog for both cases at 20 m, 100 m, and 300 m heights. The surface air in both cases came from the warmer * The upper number is cloud-base height (m), the lower fraction is total cloud cover/low-cloud SST areas, but different locations. For case 1, Figure6a shows the air origin to be the northern area of amount (10/10; using a scale of 1 to 10; 10− means larger than 9.5, but less than 10; 0 means less than the South0.5); “- China” indicates Sea, and,no observation. for case 2, All Figure symbols6b shows follow the the origin specifications to be the for Bashi surface Channel meteorological (Luzon Strait). Theobservations figure also showsof China. that the colder SST region around the southern China coast in case 1 is larger than that in case 2, which helps to create more extensive fog in case 1. 4. Advection and Boundary-Layer Characteristics In fog season, warm, moist air that advects from the warmer SST area south of the 23 °C isotherm and mixes with air in the colder SST region near the coast always results in fog and low clouds. To examine these processes, we calculated the 48 h backward trajectories of airflow to the inland site for both cases at 20 m, 100 m, and 300 m heights. The surface air in both cases came from the warmer SST areas, but different locations. For case 1, Figure 6a shows the air origin to be the northern area of the South China Sea, and, for case 2, Figure 6b shows the origin to be the Bashi Atmosphere 2018, 9, x FOR PEER REVIEW 9 of 18

AtmosphereChannel2018 (Luzon, 9, 344 Strait). The figure also shows that the colder SST region around the southern China9 of 18 coast in case 1 is larger than that in case 2, which helps to create more extensive fog in case 1.

FigureFigure 6.6. AirflowAirﬂow trajectories to to inland inland site site C C with with background background of of daily daily average average sea sea-surface-surface temperaturestemperatures ( ◦(°CC).). ((aa)) Sea-surfaceSea-surface temperaturetemperature (SST)(SST) on March 10. Dotted Dotted lines lines denote denote 48 48 h h backward backward trajectoriestrajectories ofof airﬂowairflow atat 2020 m,m, 100100 m,m, and 300 m heights from 0200 0200 LST LST 11 11 March March.. (b (b) )Same Same as as (a ()a,), exceptexcept SST SST onon 3030 MarchMarch andand trajectoriestrajectories from 0200 LST 31 March March.. SSTs SSTs are are from from real real-time-time global global data data onon 0.083 0.083°◦ × × 0.083°0.083◦ gridgrid-spacing-spacing datasets. datasets.

We calculated the horizontal advection of temperature to show the warm advection We calculated the horizontal advection of temperature to show the warm advection characteristics characteristics using the NCEP Global Analysis on 1° × 1° grid-spacing datasets. Results in Figure 7 using the NCEP Global Analysis on 1◦ × 1◦ grid-spacing datasets. Results in Figure7 show that for show that for case 1, the warm advection moved mostly towards the Beibu Gulf and the west case 1, the warm advection moved mostly towards the Beibu Gulf and the west Guangdong area, Guangdong area, whereas for case 2, it spread over nearly the whole southern China coast. whereas for case 2, it spread over nearly the whole southern China coast. Surprisingly, given the Surprisingly, given the observed visibilities, the warm advection moved into the inland area more in observed visibilities, the warm advection moved into the inland area more in case 2 than in case 1. case 2 than in case 1. To help understand this finding, we examined the average values of three 6 h To help understand this ﬁnding, we examined the average values of three 6 h time periods: for case 1, time periods: for case 1, starting at 2000 LST 10 March, 0200 LST 11 March, and 0800 LST 11 March; starting at 2000 LST 10 March, 0200 LST 11 March, and 0800 LST 11 March; for case 2, from 2000 LST for case 2, from 2000 LST 30 March, 0200 LST 31 March, and 0800 LST◦ 31◦ March. ◦The region◦ is 20°– 3021° March, N, 111° 0200–112° LST E. 31 For March, case 1, and the 0800 values LST are 31 March.0.31 × 10 The−4 K region s−1 at 1000 is 20 hPa–21 andN, 1110.23 –112× 10−4 E.K Fors−1 at case 975 1, × −4 −1 × −4 −1 thehPa values. For case are 0.312, the values10 K are s 0.21at 1000× 10−4 hPa K s− and1 at 1000 0.23 hPa10 andK 0.32 s ×at 10 975−4 K hPa. s−1 at For 975 case hPa 2,(Fig theure values 7a– −4 −1 −4 −1 ared). 0.21To calculate× 10 Kthe s horizontalat 1000 hPa advection and 0.32 of ×vapor10 , weKs useatd the 975 same hPa (Figure datasets7a–d).. The Toresulting calculate vapor the horizontaladvection advectionin Figure of8 ha vapor,s a similar we used pattern the same as the datasets. temperature The resulting advection. vapor However, advection the in average Figure8 hasvalues a similar over the pattern same as time the and temperature region give advection., for case However,1, the values the 0.35 average × 10−4 valuesg kg−1 s over−1 at 1000 the same hPa and time −4 −1 −1 −4 −1 −1 and0.22 region × 10−4 g give, kg−1 fors−1 caseat 975 1, hPa, the valueswhich 0.35are much× 10 largerg kg thans theat case 1000 2 hPavalues and of 0.22 0.15× × 10−4 gg kg kg−1 s−1 sat −4 −1 −1 at1000 975 hPa hPa, and which 0.07 are × 10 much−4 g kg larger−1 s−1 at than 975 thehPa. case Thus 2 values, there is of more 0.15 ×vapor10 advectiog kg ns to atsite 1000 C in hPa case and 1 −4 −1 −1 0.07than× in10 caseg 2. kg s at 975 hPa. Thus, there is more vapor advection to site C in case 1 than in case 2. Atmosphere 2018, 9, 344 10 of 18 Atmosphere 2018, 9, x FOR PEER REVIEW 10 of 18

− − − FigureFigure 7. TimeTime-average-average horizontal horizontal advection advection of of temperature temperature (10 (10−4 K4 Ks−1 s) and1) and wind wind vectors vectors (m s (m−1). sLeft1). Leftcolumn column (a,c) (isa ,casec) is case1, from 1, from2000 2000LST Mar LST 10 Mar to 100800 to LST 0800 March LST March 11. Right 11. Rightcolumn column (b,d) is (b case,d) is 2, case from 2, from2000 LST 2000 Mar LST 30 Mar to 300800 to LST 0800 March LST March 31. Top 31. row Top ( rowa,b) (isa, atb) 10 is00 at 1000hPa. hPa.Bottom Bottom row ( rowc,d) (isc, d975) is hPa. 975 hPa.The Thered line red lineis the is zero thezero line linefor the for sign the signof advection. of advection. (A is (A the is coastal the coastal site) site)..

−4 −1 FigureFigure 8. SameSame asas Figure Figure7, 7 except, except for for time-average time-average horizontal horizontal vapor vapor transport transport (shaded, (shaded, 10 −4 g10 kg−4− g1 kgs−1−1) −1 −1 ands−1) and wind wind vectors vectors (m s −(m1). s−1). Atmosphere 2018, 9, x FOR PEER REVIEW 11 of 18 AtmosphereAtmosphere 20182018,, 99,, 344x FOR PEER REVIEW 1111 of of 1818 The GPS sondes at the coast site (MMSEB) depicted the boundary-layer structures during both fog cases.The GPS The sonde datas areat the plotted coast site in Fig (MMSEBure 9. )T depicthe winded the vectors boundary of both-layer cases structures mostly during show edboth a consistent,fog cases.The GPS butThe sondes relatively data atare the weak plotted coast, southern site in Fig (MMSEB)ure or eastern9. T depictedhe wind wind the at vectors the boundary-layer lower of bothlevel, casesand structures a mostlystrong during ershow west bothedern a windfogconsistent, cases. at the The but upper data relatively are level. plotted weakBoth in, casessouthern Figure show9. Theored eastern wind a warm vectors wind layer at of the bothbelow lower cases about level, mostly 4 00and showedm a. strongConsidering a consistent,er west theern humidity,butwind relatively at the we upper weak,used RH level.southern = 98%Both or to cases eastern define show windtheed cloud ata thewarm edge lower layer (appropriate level, below and about a for stronger GPS 400 sonde westernm. Considering data wind [21] at). the theAs such,upperhumidity, the level. figure we Both use shows casesd RH that showed = 98% both to afog warmdefine cases layer theform belowclouded by edge aboutthe lowering (appropriate 400 m. Consideringof the for cloud GPS base. the sonde humidity, The data RH [21]in we case used). As 2 alsoRHsuch, =shows 98%the figure to the deﬁne fog shows trans the that cloudition bothing edge fogback (appropriate cases into form stratused for byagain. GPSthe loweringCase sonde 1 dataha ofd the [t21he]). cloudobserved As such,base. highest theThe ﬁgure RH fog in shows topcase of 2 aboutthatalso bothshows 1310 fog mthe casesat fog 0500 trans formed LSTition 11 by ingMar the backch lowering, whereas into stratus of case the again. cloud2 reache Case base.d the 1 The ha slightlyd RH the inobserved lower case 2top also highest of shows910 fogm theat top 0200 fog of LSTtransitioningabout 31 1310 March m back.at 0500 into LST stratus 11 Mar again.ch, whereas Case 1 hadcase the2 reache observedd the highest slightly fog lower top top of aboutof 910 1310m at m0200 at 0500LST 31 LST March 11 March,. whereas case 2 reached the slightly lower top of 910 m at 0200 LST 31 March.

Figure 9. Soundings at the coastal site during the two sea-fog cases. The red line is air temperature, theFigureFig ureshading 9.9. SoundingsSoundings is relative at humidity, the coastal and site the during vector the is twohorizontal sea-fogsea-fog wind. cases. ( aThe ) Case red 1. line (b ) is Case air temperature, 2. Scales for RHthethe shading(%)shading and iswindis relative relative (m s humidity,− 1humidity,) are at right. and and the the vector vector is horizontalis horizontal wind. wind. (a) ( Casea) Case 1. ( b1.) Case(b) Case 2. Scales 2. Scales for RHfor (%)RH and(%) and wind wind (m s −(m1) s are−1) are at right. at right. Consider now the fog structures at the time of highest fog top. From the potential equivalent Consider now the fog structures at the time of highest fog top. From the potential equivalent Consider now the fog structures at the time of highest fog top. From the potential equivalente temperatures (Figure 10), we found that the thermal-turbulence interface (where = 0 ) ∂θe e temperaturestemperatures (Figure (Figure 10 10),), we we found fou thatnd that the thermal-turbulence the thermal-turbulence interface interface (where (∂wherez = 0) occurredz = 0 ) occurat a heightred at a of height about of 290about m 290 in casem in 1case and 1 and about about 170 170 m m in in case case 2. 2. In In both both cases, cases, the the profiles proﬁlesz of potentialofoccur potentialred at equivalent a equivalent height of temperature about temperature 290 m abovein abovecase the1 theand thermal thermal-turbulenceabout -170turbulence m in case interface interface2. In both are arecases, nearly nearly the profiles constant, of meanmeaningpotentialing that equivalent the layers temperature we werere well well-mixed.-mixed above. This This the result result thermal agrees agrees-turbulence with with that that interface reported reported arein in ReferencesReferences nearly constant, [21 [21,,22]22].. OverOverall,meanall,ing the that boundary boundary-layer the layers-layer were structure well-mixed in case . This 1 result shows agrees strong stronger wither warm that andreported moist in advection, References which [21,22] is . moreOver all, suitable the boundary for the development-layer structure of sea in case fog, and1 shows also result resultedstrongeder inwarm a higher and fogmoist top advection, than that inwhich case is2 (Figure(Figmoreure suitable 1010a,b).a,b). for the development of sea fog, and also resulted in a higher fog top than that in case 2 (Figure 10a,b).

FigFigureure 10.10. Boundary-layerBoundary-layer structure structure at theat the time time of the of highestthe highest fog top fog of top each of fog each case. fog (a )case. 0500 LST(a) 0500 11 March LST 112017Fig Marure of ch case10. 2017 Boundary 1. (b of) 0200 case-layer LST 1. ( 31b structure) March0200 LST 2017 at the31 of caseMartimech 2. of Horizontal2017 the highest of case lines: fog2. 1Horizontaltop = height of each of lines: thefog thermal-turbulencecase. 1 = height(a) 0500 of LSTthe 11 March 2017 of case 1.∂θ (e b) 0200 LST 31 March 2017 of case 2. Horizontal lines: 1 = height of the interface (determined as ∂z = 0); 2 = top of the fog (determined as RH = 98%, the same as 3 and 4), thermal-turbulence interface (determined as ); 2 = top of the fog (determined as RH = 98%, 3 = cloud base, 4 = cloud top. Symbols: T = temperature (K), θe = potential equivalent temperature (K), thermal-turbulence interface (determined as ); 2 = top of the fog (determined as RH = 98%, q = mixing ratio (kg kg−1), Wd = wind direction (◦), Ws = wind speed (m s−1), RH = relative humidity (%), the same as 3 and 4), 3 = cloud base, 4 = cloud top. Symbols: T = temperature (K), θe = potential and height = AGL (m). equivalentthe same as temperature 3 and 4), 3 (K), = cloud q = mixing base, ratio4 = cloud (kg kg top.−1), WdSymbols: = wind T direction= temperature (), Ws (K), = wind θe = speedpotential (m sequivalent−1), RH = relative temperature humidity (K), (%), q = mixingand height ratio = ( AGLkg kg (m).−1), Wd = wind direction (), Ws = wind speed (m s−1), RH = relative humidity (%), and height = AGL (m). Atmosphere 2018, 9, 344 12 of 18

5. Differences of Meteorological Variables We now focus on the main meteorological variables and turbulent kinetic energies, considering differences between those at sea and inland. In case 1, the average temperature at the inland site was hotter than that at the oversea site (by 2.5 ◦C from 0800 to 2000 LST 10 March), with a maximum difference around 1400 on 10 March 2017 (Figure 11a). Later, from about 1500 that day, the inland site cooled by about 3.3 ◦C until the inland fog formed at 2300 LST 10 March. This cooling was due to cold advection to the inland site. For case 2, the average inland temperature was also hotter than that over sea (by 3.3 ◦C from 0800 to 2000 LST 30 March), with a maximum difference during daytime at about 1600 LST 30 March. However, the cooling effect was not as strong in this case, with temperature dropping slowly by only 2.4 ◦C by the next morning at 0800 LST 31 March (Figure 11b). As with case 1, the cooling effect was consistent with the horizontal advection of temperature shown in Figure7. But in this case, warm advection prevailed all the time at the inland site, hindering the radiative-cooling effect. In general, this case also has much less temperature variation over sea than that in case 1. Consider now the wind prior and during the sea fog in case 1. Figure 11c shows that before the fog formed, the wind direction changed from northeast to southeast at about 1500 LST 10 March over sea, with fog forming one hour later. After the fog formed, the wind direction returned to northeast, but was steadier in direction. Meanwhile, the wind speed was low before the fog forms, but gradually increased after the fog forms. Compared to the sea-fog event, the inland fog in case 1 showed a different wind pattern. The wind speed became very low when the fog first formed, making the wind direction erratic (though mainly southeast). Later, the wind speed increases by about 2 m s−1, and the wind direction changed from northeast to east (Figure 11c). For case 2, the wind direction was relatively steady over sea and at inland, being east over sea and southeast at inland. The wind speeds at both sites decrease gradually, but do not become as low as that for case 1 (Figure 11d). TKE is an important quantity to qualify the turbulence intensity [32]. In case 1, the TKE remained small over the sea before, after, and during the fog. Inland, the TKE was also small before the inland fog formed (Figure 11e). The small TKE agrees with Zhou and Ferrier’s finding [13] that a weak turbulence intensity helps to maintain fog. This case also had a little drizzle inland and over sea (Figure 11g), suggesting times of dense fog [33]. Thus, three factors may contribute the formation of the inland fog in this case: quick temperature decrease, low wind speed, and small TKE. For case 2, the TKE was relative high inland, indicating that the boundary-layer condition is not suitable for fog there (Figure 11f). Nevertheless, the inland site had both drizzle and significant precipitation from 0540 to 1050 LST 31 March (Figure 11h). This precipitation indicates that the case was influenced by a cloud and frontal system, and the precipitation also resulted in a short period of high RH values inland (Figure5b). Over sea also showed two brief periods of drizzle (Figure 11h). Atmosphere 2018, 9, 344 13 of 18 Atmosphere 2018, 9, x FOR PEER REVIEW 13 of 18

FigFigureure 11. MeteorologicalMeteorological parameters and turbulence characteristics of case 1 (left column) and case 2 (right column) column) over over sea sea and and inland. inland. (a,b ) ( T10ma,b) T10m = air temperature = air temperature at 10 m AGL, at 10 T13.4m m AGL, = air T13.4m temperature = air temperatureat 13.4 m MSL. at (13.4c,d) m WD, MSL. WS; (c (,de,)f )WD TKE;, WS; (g, h(e), rainfallf) TKE; =(g the,h) rainfall in= the an rainfall hour. The in greenan hour. line T indicateshe green linethe sea-fogindicates period, the sea the-fog grey period, shading the indicatesgrey shading the inland-fogindicates the period. inland-fog period.

66.. Differences of Land Land–Atmosphere–Atmosphere and Air Air–Sea–Sea Exchange between the Two CasesCases HereHere,, wewe assumeassume energy energy conservation conservation to analyzeto analyze the energythe energy fluxes fluxes at the at surface. the surface Specifically,. Specifically, we use we use RN = H + LE + HG (1) RNG= H + LE + H (1) where RN is the net radiation, H and LE are the sensible- and latent-heat fluxes to or from the air, wandhereH GRisN theis the ground net radiation, heat flux toH or and from LE the are submedium. the sensible We- and use latent the sign-heat convention fluxes to or that from all the radiative fluxes directed toward the surface are positive, while other (nonradiative) energy fluxes air, and HG is the ground heat flux to or from the submedium. We use the sign convention that all directed away from the surface are positive, and vice versa [34]. the radiative fluxes directed toward the surface are positive, while other (nonradiative) energy Now consider the sensible- and latent-heat fluxes. The sensible-heat flux is negative on average fluxes directed away from the surface are positive, and vice versa [34]. during the sea-fog period (case 1 average = −5.1 W m−2, case 2 = −2.9 W m−2), meaning that the Now consider the sensible- and latent-heat fluxes. The sensible-heat flux is negative on average atmosphere transfers sensible heat to the sea (Figure 12a,b). However, the latent-heat fluxes during the during the sea-fog period (case 1 average = −5.1 W m−2, case 2 = −2.9 W m−2), meaning that the sea-fog period differed between the two cases (Figure 12c,d), being positive in case 1 (average value atmosphere transfers sensible heat to the sea (Figure 12a,b). However, the latent-heat fluxes during 0.63 W m−2), but negative in case 2 (average value −3.86 W m−2). the sea-fog period differed between the two cases (Figure 12c,d), being positive in case 1 (average value 0.63 W m−2), but negative in case 2 (average value −3.86 W m−2). Atmosphere 2018, 9, 344 14 of 18 AtmosphereAtmosphere 2018 2018, 9, ,x 9 FOR, x FOR PEER PEER REVIEW REVIEW 14 14of 18of 18

FigFigureFigureure 12. 12. 12.SensibleSensible- Sensible- and- and and latent latent-heat latent-heat-heat fluxes fluxes fluxes over over over sea sea sea (23.4 (23.4 (23.4 m m MSLm MSL). MSL). ().a () a ()Casea Case) Case 1, 1, sensible.1, sensible. sensible. (b ( )b( bCase)) Case Case 2, 2, 2, sensible.sensible.sensible. (c) (Casec)) Case Case 1, latent.1, 1, latent. latent. (d) ( Cased) ( dCase) 2, Case latent.2, latent. 2, latent.Dots Dots are Dotsare the the flux are flux thevalues, values, flux a values,verag averaged averagededover over 30 30min. over min. Missing 30 Missing min. dataMissingdata are are either data either out are out eitherof rangeof range out or of doubtful.or range doubtful. or Colors doubtful. Colors mark mark Colors the the quality mark quality flags the flags quality of theof the fluxes, flags fluxes, of with the with fluxes,q0 q0= green = withgreen (seeq0(see =labels green labels at (see top)at labelstop) the the athighest top)highest the quality, highestquality, q2 quality, q2= red = red the q2 the =lowest red lowest the (see lowest (see Table Table (see 2 Tablefor 2 for details).2 fordetails). details). The T hegreen The green greenline line indicateslineindicates indicates the the sea the sea-fog sea-fog-fog period, period, period, the the grey the grey shading grey shading shading indicates indicates indicates the the inland the inland inland-fog-fog-fog period. period. period.

TheTheThe latent latent-heat latent-heat-heat fl fluxux fl uxis is positiveis positive positive on on on average average average during during during the the the warm warm warm sea sea sea fog fog fog of of ofcase case case 1, 1, which1 which, which does does does not not not agreeagreeagree with with with our our our previous previous previous study study study [22] [ 22[22].]. Of. Of Ofthe the the two two two cases, cases, cases, case case case 1 1 also1 also also ha had dha thed the the more more more variable variable variable latent latent-heat latent-heat-heat fluxfluxflux and and and a a higher highera higher liquid liquid-water liquid-water-water contentcontent content (LWC)(LWC (LWC) (Figure (Fig) (Figure ure13 13)). 13) In. In general,. Ingeneral, general, a largea largea large liquid-water liquid liquid-water-water content content content will willcontaminatewill contaminate contaminate the the window the window window of theof ofthe instrument the instrument instrument of model of ofmodel model LI-7500A, LI -LI7500A,-7500A, resulting result resulting ining unreliable in inunreliable unreliable data data and data and thus and thusanthus unreliable an an unreliable unreliable latent-heat latent latent- flux.heat-heat The flux flux larger. The. The sea-foglarger larger sea LWC sea-fog- isfog also LWC LWC consistent is is also also consistent with consistent the vapor with with advection the the vapor vapor in advectioncaseadvection 1 being in incase larger case 1 beingthan1 being that larger larger incase than than 2 that (Figure that in incase8). case This 2 (Fig2 discrepancy (Figureure 8). 8This). withThis discrepancy discrepancy our previous with with study our our mayprevious previous have studyarisenstudy may from may have thehave arisen large arisenLWC from from inthe thethe large foglarge LWC of LWC case in 1. inthe the fog fog of ofcase case 1. 1.

(b)(b) (a)(a) 0.30 0.300.30 0.30 0.25

0.250.25 0.25

)

- 3

3 0.20

- 0.20 0.20- 0.20 0.150.15 0.150.15 0.10 0.100.10

0.10 (g m LWC

LWC (g m LWC

LWC (g m LWC LWC (g m LWC 0.050.05 0.050.05 0.000.00 0.000.00 10/1810/18 11/0011/00 11/0611/06 11/1211/12 30/1830/18 31/0031/00 31/0631/06 31/1231/12 TimeTime (LST) (LST) TimeTime (LST) (LST)

FigFigureFigureure 13. 13. 13.ObservedObserved Observed liquid liquid-water liquid-water-water content content content (LWC) (LWC) (LWC) at at coastat coast coast site site site A A (MMSEB)A (MMSEB) (MMSEB) of of theof the the two two two sea sea-fog sea-fog-fog cases cases cases (Plotted(Plotted(Plotted are are are 1 1min 1 min min averages averages averages of of 1of 1s 1 sdata) data).s data). (a (.)a ()Casea Case) Case 1. 1. (1.b (b) ( Case)b Case) Case 2. 2. 2.

BothBothBoth the the t he sensible sensiblesensible- and- and and latent latent-heat latent-heat-heat flux fluxes fluxes esinland inland inland differ differ differ between between between the the the two two two cases cases. cases. For. For For betterbetter better comparison,comparison,comparison, we we we focus focused focused ed on on thethe the fluxflux flux data data data mainly mainly mainly during during during the the nighttime the night nighttime (fromtime (from (from 2000 2000 to 2000 0630 to to0630 LST). 0630 LST At LST). night, At). At night,thenight, sensible-heat the t hesensible sensible flux-heat-heat is flux negative, flux is negativeis negative meaning, meaning, meaning the atmosphere the the atmosphere atmosphere transfers transfers heattransfers to theheat heat ground, to tothe the ground, but ground, thevalue but but theforthe value case value for 2 atfor case− case4.4 2 at W2 −at4.4 m −−4.4 W2 (average) Wm− m2 (average)−2 (average) greatly greatly greatly exceeds exceeds exceeds that that of that caseof caseof 1case at1 at −1 −at0.70.7 −0.7 WW W m− m22 (Fig−(Figure2 (Figureure 14a 14 14a,a,b).b),. b). Meanwhile,Meanwhile,Meanwhile, the the the latent latent-heat latent-heat-heat flux flux flux for for for case case case 1 1 is is1 negative is negative at −at1.41.4 −1.4 W W Wm m −−m2 2(average),−2(average), (average), sha sharply sharplyrply contrasting contrasting contrasting withwithwith case case case 2 2at 2 at aat apositive a positive positive 5.5 5.55.5 W W Wm −mm2 (Fig−−22 (Fig(Figureureure 14 c14 ,14dc).,c,d).d Thus). Thus Thus,, the, the total the total totalheat heat heatflux flux wa flux was negative wass negative negative in incase incase 1 case, but1, but1, positivebutpositive positive in incase incase case2. A2. 2.negativeA Anegative negative total total totalheat heat heatflux flux fluxmeans means means that that that the the theground ground kep keptkept coolingt coolingcooling the thethe atmosphere atmosphere.atmosphere. . Thus,Thus,Thus, the the the negative negative negative flux flux flux help helped helped edto to sustain sustain inlandinland inland fogfog fog inin caseincase case 1,1, but but1, but thethe the positivepositive positive flux flux flux hindered hinder hindered the edthe fogthe fog fog in incase incase case 2. 2. 2. Atmosphere 2018, 9, 344 15 of 18 Atmosphere 2018, 9, x FOR PEER REVIEW 15 of 18

FigureFigure 14. 14.Sensible- Sensible and- and latent-heat latent-heat ﬂuxes fluxes inland inlan (10d m ( AGL).10 m AGL(a) Case). (a 1,) sensible.Case 1, sensible. (b) Case 2,(b sensible.) Case 2, (csensible.) Case 1, ( latent.c) Case (d 1,) Caselatent. 2, ( latent.d) Case Averaging 2, latent. Averaging interval for interval the ﬂuxes for is the 30 fluxes min. Missing is 30 min. data Missing are either data outare of either range out or of doubtful. range or Markings doubtful. are Markings the same are as the those same in Figureas those 12 in. Figure 12.

SoilSoil temperatures temperatures also also differ differ between between the the two two cases. cases. For For case case 1, 1, the the soil soil temperature temperature was was always always lowerlower than than the the 10 10 m m atmosphericatmospheric temperature.temperature. Within the s soil,oil, at at night night the the temperature temperature at at a adepth depth of of5 5 cm cm wa wass always always higher higher than than that that at at the 10 cmcm depthdepth (Figure(Figure 1515a)a).. Thus,Thus, the the soil soil heat heatflux flux was was downwarddownward in in case case 1 (Figure1 (Figure 15 c),15 whichc), which corresponds correspond tos the to heatthe heat flux beingflux being downward. downward. That is,That the is, land the surfaceland surface was cooling was cool theing atmosphere the atmosphere during during the night. the night. ForFor case case 2, 2, the the relation relation between between 10 10 m m atmospheric atmospheric temperature temperature and and soil soil temperature temperature is is more more complicated.complicated. In In the the afternoon, afternoon, the the temperature temperatureat at the the 5 5 cm cm soil soil depth depth was was higher higher than than that that at at 10 10 m m AGL.AGL. But, But during, during the the night, night the, the soil soil temperature temperature at 5at cm 5 cm depth depth was wa justs just slightly slightly less less than than that atthat 10 at cm 10 depthcm depth (Figure (Fig 15ureb), meaning15b), meaning that the that soil the heat soil flux heat was flux slightly was upwardslightly (Figureupward 15 (Figd). Theure 15 soild). heat The flux soil beingheat flux upward being agrees upward well agree withs the well total with heat the flux total being heat upward.flux being upward.

NetNet radiation radiationR NR,N the, the net net shortwave shortwave plus plus long-wave long-wave ﬂux, flux, had had a a maximum maximum negative negative value value at at thethe evening evening transition transition (Figure (Figure 15 15c,d)c,d), in, in agreement agreement with with the the study study of of Steeneveld Steeneveld [14 [14]]. Case. Case 1 1 had had a a smallersmaller peak peak negative negative value value than than case case 2 2 due due to to case case 1 1 having having a a greater greater low-cloud low-cloud amount amount at at these these timestimes (Table (Table4). 4) Thus,. Thus, case case 2 had 2 ha greaterd greater ground ground radiation radiation cooling cooling at night, at night, causing causing the temperaturethe temperature at 5at cm 5 cm depth depth to goto belowgo below that that at 10at cm.10 cm In. I casen case 2, 2, because because the the land land temperature temperature was wa highers higher than than the the airair temperature temperature in in the the afternoon, afternoon, the the larger larger negative negative value value of of net net radiation radiation also also drove drove rapid rapid decrease decrease inin temperature temperature at at the the 55 cmcm depthdepth (Figure(Figure 1515b)b).. Moreover, Moreover, the the s soiloil volumetric volumetric water water content content (VWC) (VWC) at at5 5cm cm depth depth in in case case 1 1 wa wass larger than that inin casecase 2.2. AA soil-humiditysoil-humidity conditioncondition withwith larger larger VWC VWC indicatesindicates a a greater greater rate rate of of evaporation evaporation from from the the surface, surface, which which is is more more favorable favorable to to fog fog formation formation becausebecause it it increases increases the the moisture moisture in thein the air asair well as well as further as further cooling cooling the air the via air the via absorption the absorption of latent of heatlatent by heat the ground.by the ground. Thus, This Thus, condition This condition then helped then promotehelped promote fog in case fog 1in more case than1 more that than in casethat 2in (Figurecase 2 15(Fige,f).ure 15e,f). Atmosphere 2018, 9, 344 16 of 18 Atmosphere 2018, 9, x FOR PEER REVIEW 16 of 18

FigureFigure 15. Land–atmosphere15. Land–atmosphere exchange exchange characteristics characteristics at at the the inlandinland sitesite C.C. (a,b) Air (10 (10 m m AGL) AGL) and and soilsoil temperatures temperatures (5 and (5 and 10 cm10 cm depths) depths for) for cases cases 1 (left)1 (left) and and 2 2 (right). (right).( (cc,d,d)) SoilSoil heatheat ﬂuxflux ( (HHG, ,positive positive downward) and net radiation (R , positive downward) for both cases. (e,f) Soil volumetric water downward) and net radiation N( RN , positive downward) for both cases. (e,f) Soil volumetric water content (VWC) at 5 cm depth for both cases. The green line indicates the sea-fog period, the grey content (VWC) at 5 cm depth for both cases. The green line indicates the sea-fog period, the grey shading indicates the inland-fog period. shading indicates the inland-fog period.

7. Discussion7. Discussion and and Conclusions Conclusions WeWe compared compare twod two sea-fog sea-fog cases cases on theon the southern southern China China coast, coast, one one also also occurring occurring with with inland inland fog, the otherfog, the without. other without The data. The came data from came an from oversea an oversea site, a site coastal, a coast site,al andsite, anand inland an inland site. site. For For these these two cases,two we cases found, we the found following: the following: (1) (1)In In both both cases, cases, the the synoptic synoptic conditions conditions involved involved warm, warm, moist air air from from a a warmer warmer SST SST region region advectingadvecting to to a coldera colder SST SST area area at at the the coast, coast, forming forming seasea fog.fog. But,But, the inland fog fog case case had had larger larger horizontalhorizontal advection advection of of water water vapor vapor over over thethe landland and about 80% 80% low low-cloud-cloud coverage. coverage.

(2) (2)TheThe surrounding surrounding boundary boundary layer layer was was important. important. BothBoth sea-fogsea-fog cases had low low wind wind speed speedss and and a a small TKE. The small TKE allowed the vapor to accumulate close to the surface and maintain the small TKE. The small TKE allowed the vapor to accumulate close to the surface and maintain the local cooling effect, eventually producing fog. local cooling effect, eventually producing fog. (3) Both cases had radiative cooling of the ground, but the inland fog case had a downward energy (3) Both cases had radiative cooling of the ground, but the inland fog case had a downward energy flux at night, with the land surface cooling the atmosphere. The non-fog case had the opposite fluxflux at. night,The fog with case the also land had surfacelower soil cooling temperature the atmosphere. and higher The soil non-foghumidity. case had the opposite flux. The fog case also had lower soil temperature and higher soil humidity. Although both sea fogs transported vapor inland over an extensive span of coast, inland fog formedAlthough only both in some sea fogsareas transported. This nonuniformity vapor inland of the overfog might an extensive due to nonuniformities span of coast, in inland surface fog formedconditions only in such some as areas.local cooling This nonuniformity and boundary-layer of the conditions. fog might due to nonuniformities in surface conditionsThis such study as local analyze coolingd how and sea boundary-layer fog can influence conditions. inland-fog formation with the aim of determiningThis study analyzedthe relationship how sea between fog can the influence two fog inland-fogs. In addition formation to the large with-scale the aiminfluence of determining from sea thefog, relationship local conditions between are the critical two fogs. to inland In addition-fog formation. to the large-scale This finding influence suggests from that sea forecaster fog, locals conditionsshould pay are more critical attention to inland-fog to the local formation. meteorological This finding conditions suggests and the that soil forecastersconditions under should such pay morea synoptic attention background. to the local meteorologicalThese results are conditions based on and just the two soil cases, conditions and thus under should such be evaluateda synoptic background.against more These cases, results but the are results based may on justbe help twoful cases, for coastal and thus forecasters. should be evaluated against more cases, but the results may be helpful for coastal forecasters. Atmosphere 2018, 9, 344 17 of 18

Author Contributions: Conceptualization, H.H., S.Z.; Methodology, H.H., S.Z.; Software, J.S.; Formal Analysis, J.S., H.H.; Data Curation, W.M.; Writing-Original Draft Preparation, J.S., H.H.; Writing-review & Editing, J.S., H.H.; Funding Acquisition, H.H. Acknowledgments: Special thanks to the crew of the Marine Meteorological Science Experiment Base at Bohe for their help in conducting the field program and providing the data. This study was supported jointly by the National Natural Science Foundation of China (Grants 41675021, 41576108, and 41675019), subproject of the science and technology pilot project of the Chinese Academy of Sciences (Grant XDA11010403), the Meteorological Sciences Research Project (Grant GRMC2017M04), and the innovation team of forecasting technology for typhoon and marine meteorology of the Guangdong Provincial Meteorological Bureau. Conflicts of Interest: The authors declare no conflict of interest.

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