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    (top) The model domain and locations of eight observational stations along the coastline of the YS. The stations are Shengsi (SS), Shanghai (SH), Lusi (LS), Sheyang (SY), Qingdao (QD), Chengshantou (CT), and Dalian (DL), respectively, from south to north on the western side and Cheju (CJ) on the eastern side. The dashed rectangular region is selected for later analysis. (bottom) A magnification of the rectangular region in the top panel with topography height.

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    SAT − SST (shaded, °C), SH (solid line, g kg−1) at 2 m, and winds (vector, m s−1) at 0000 UTC 9 Mar 2005.

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    The albedo distribution of Geostationary Operational Environmental Satellite-9 (GOES-9) visible band (0.55–0.90 μm) at (a) 0200, (b) 0400, (c) 0600, and (d) 0800 UTC 9 Mar 2005.

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    The temporal evolution of atmospheric horizontal visibility (shaded) with (a) SH (contour, g kg−1) and (b) wind speed (contour, m s−1) and direction (barb) at seven stations along the western side of the YS. Shaded area denotes the atmospheric horizontal visibility below a 1-km area (fog). The x axis denotes the location distribution of seven stations (bottom axis) and the distance between these stations (top axis). The y axis denotes time.

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    Comparison of simulated (dashed) and observed (solid) temperature (°C) profiles at SY at (a) 0000 UTC 9 Mar and (b) 0000 UTC 10 Mar and at QD at (c) 0000 UTC 9 Mar and (d) 0000 UTC 10 Mar 2005.

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    Wind field and large wind speed area (shaded, >10 m s−1) at 360 m as well as LWP (contour, kg m−2) at (a) 0200, (b) 0400, (c) 0600, and (d) 0800 UTC 9 Mar 2005 in the control run. The line labeled AB in (c) is used for the later analysis.

  • View in gallery

    Vertical profiles of wind speed (m s−1) at CJ for (a) sounding, (b) FNL data, and (c) WRF control simulation results from 0000 UTC 8 Mar to 0000 UTC 11 Mar 2005. The shaded region denotes wind speed higher than 10 m s−1.

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    Horizontal distribution of the moisture divergence (shaded, 10−7 g kg−1 s−1) and CWMR (contour, g kg−1) at 10 m at (a) 0200, (b) 0400, (c) 0600, and (d) 0800 UTC 9 Mar 2005 in the control run.

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    Cross section of the TKE advection term (contour, 10−5 m2 s−3) along the line AB at 0500 UTC 9 Mar 2005 in the control run.

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    Cross section of TKE (contour, interval 5 × 10−2 m2 s−2) and CWMR (shaded, g kg−1) along the line AB at (a) 0500, (b) 0600, (c) 0700, and (d) 0800 UTC 9 Mar 2005 in the control run.

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    Cross section of TKE tendency (contour, 10−5 m2 s−3) along the line AB at (a) 0500, (b) 0600, (c) 0700, and (d) 0800 UTC 9 Mar 2005 in the control run.

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    Cross section of the TKE mechanical production term (contour, 10−3 m2 s−3) and wind speed (shaded with dash line, m s−1) along the line AB at (a) 0500, (b) 0600, (c) 0700, and (d) 0800 UTC 9 Mar 2005 in the control run.

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    Cross section of TKE buoyancy term (contour, 10−4 m2 s−3) and temperature (shaded with dash line, °C) along the line AB at (a) 0500, (b) 0600, (c) 0700, and (d) 0800 UTC 9 Mar 2005 in the control run.

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    Cross section of TKE mechanical production term (contour, 10−3 m2 s−3) and wind speed (shaded with dash line, m s−1) along the line AB in Fig. 4b at (a) 0500, (b) 0600, (c) 0700, and (d) 0800 UTC 9 Mar 2005 in the topography test.

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    SH (shaded, g kg−1) difference (topography test − control run) at 10 m at (a) 2200 UTC 8 Mar 2005 and at (b) 0000, (c) 0200, and (d) 0400 UTC 9 Mar 2005. The rectangular region denotes the removed topography area.

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The Formation Mechanism of a Spring Sea Fog Event over the Yellow Sea Associated with a Low-Level Jet

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  • 1 Department of Marine Meteorology, Ocean University of China, Qingdao, China
  • | 2 Department of Marine Meteorology, and Laboratory of Physical Oceanography, and Key Laboratory of Ocean–Atmosphere Interaction and Climate, Ocean University of China, Qingdao, China
  • | 3 National Science Foundation, Arlington, Virginia
  • | 4 Department of Marine Meteorology, Ocean University of China, Qingdao, China
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Abstract

In this paper, a dense sea fog event that occurred over the Yellow Sea (YS) on 9 March 2005 is investigated using the Weather Research and Forecasting Model version 3.1.1 (WRF v3.1.1). It is shown that the WRF can reasonably reproduce the main features of this fog case with a newly implemented planetary boundary layer (PBL) scheme developed by Mellor–Yamada–Nakanishi–Niino (MYNN). The low-level jet (LLJ) associated with this fog episode played an important role in triggering the turbulence. During the fog formation, sea fog extended vertically with the aid of turbulence. The mechanical production term resulting from wind shear contributed to the generation of the turbulence. WRF simulation results showed that the fog layer was thicker in the northeastern part of the YS than that in the southwestern part due to the intensity of the inversion layer and the LLJ. The topography test in which the mountain region in Fujian Province was removed showed that the roles of topography were to prevent the moisture from extending to land, to intensify the inversion layer, and to enhance the intensity of LLJ, as well as to elevate its altitude.

Corresponding author address: Prof. Gang Fu, Dept. of Marine Meteorology, Ocean University of China, Qingdao 266100, China. E-mail: fugang@ouc.edu.cn

Abstract

In this paper, a dense sea fog event that occurred over the Yellow Sea (YS) on 9 March 2005 is investigated using the Weather Research and Forecasting Model version 3.1.1 (WRF v3.1.1). It is shown that the WRF can reasonably reproduce the main features of this fog case with a newly implemented planetary boundary layer (PBL) scheme developed by Mellor–Yamada–Nakanishi–Niino (MYNN). The low-level jet (LLJ) associated with this fog episode played an important role in triggering the turbulence. During the fog formation, sea fog extended vertically with the aid of turbulence. The mechanical production term resulting from wind shear contributed to the generation of the turbulence. WRF simulation results showed that the fog layer was thicker in the northeastern part of the YS than that in the southwestern part due to the intensity of the inversion layer and the LLJ. The topography test in which the mountain region in Fujian Province was removed showed that the roles of topography were to prevent the moisture from extending to land, to intensify the inversion layer, and to enhance the intensity of LLJ, as well as to elevate its altitude.

Corresponding author address: Prof. Gang Fu, Dept. of Marine Meteorology, Ocean University of China, Qingdao 266100, China. E-mail: fugang@ouc.edu.cn

1. Introduction

Fog is a boundary layer weather phenomenon wherein tiny water droplets (or ice crystals) are suspended in the vicinity of the earth’s surface, which leads to the atmospheric horizontal visibility being less than 1 km. Sea fog is classified based on the physiographic character of the underlying surface, typically referring to its source region being oceanic. Increased economic losses associated with the impacts of sea fog on coastal, aviation, and marine transportation have been incurred as more and more human activities have been located in marine areas in recent decades. These facts stress the importance of fog studies and bring renewed interests in this kind of weather phenomenon. In fact, sea fog has received considerable attentions in the literature recently (Leipper 1994; Filonczuk et al. 1995; Cho et al. 2000; Koračin et al. 2001; Lewis et al. 2003; Zhou et al. 2004; Fu et al. 2004; Koračin et al. 2005; Gultepe et al. 2006; Fu et al. 2006; Wang et al. 2006; Gao et al. 2007; S. Zhang et al. 2009; Fu et al. 2010; Heo and Ha 2010; Kim and Yum 2010; Lee et al. 2010; Li et al. 2011).

Taylor (1915, 1917) laid a fundamental framework for considering turbulent transfer and its relationship with fog formation over land and sea. Taylor (1915) suggested that the vertical transport of air properties was through the action of wind shear. The stratus-lowering process was first reported as another fog formation mechanism along the California coast by Anderson (1931) and has been investigated by many researchers (Oliver et al. 1978; Pilié et al. 1979; Telford and Chai 1984). Building upon previous studies, Duynkerke (1991) and Pagowski et al. (2004) suggested that the physical mechanism of fog formation can be generalized into two primary processes: radiative cooling and mixing of air parcels with different temperatures and humidities. Corresponding to this understanding, fog can primarily be classified to be a radiation or advection type on the basis of the dominating formation mechanism of a fog event.

The Yellow Sea (hereafter YS; see Fig. 1) is the most susceptible and notable fog-prone region among the China Seas, in which fog frequency could reach 12% or more during the foggy season (typically from April to July) (Song 2009). The characteristics of fog over the YS are different from those of the other China Seas in terms of their appearance and duration, as well as the dominating mechanism (Wang 1985; Cho et al. 2000; Lee et al. 2010). The fog events present in the YS are mainly advection fog (Wang 1985; Zhou and Liu 1986; Fu et al. 2006; Kim and Yum 2010). The vertical mixing process is typically deemed to be the dominating formation mechanism of a sea fog event over the YS. Previous studies have provided a comprehensive view of fogs over the YS with respect to the characteristics of satellite imagery and evolution (Fu et al. 2004; Gao et al. 2009), modeling (Fu et al. 2006; Gao et al. 2007), climatology (S. Zhang et al. 2009), and large-scale environmental factors (Li et al. 2011). However, the detailed formation mechanism of fogs over the YS has not been discussed sufficiently, especially for situations in which low-level jets (LLJs) come into play. Fogs over the YS typically form under a stably stratified atmosphere. The vertical mixing process triggered mainly by the turbulence in the stably stratified atmosphere may be the dominant process in the formation of advection fogs over the YS. Gao et al. (2007) suggested that the turbulence mixing by wind shear is the primary mechanism for the cooling and moistening of the marine layer. Duynkerke (1991) and Pagowski et al. (2004) indicated that the turbulence is essential to the generation and development of fogs. However, there has been little work on the quantitative assessment of the contributions of the turbulence generation factors, such as buoyancy and wind shear, to the turbulence kinetic energy (TKE). In the present study, a sea fog event that occurred in a stably stratified boundary layer and was accompanied with an LLJ at around 360 m above the sea level was investigated using the Advanced Research core of the Weather Research and Forecasting Model (WRF ARW; Skamarock et al. 2008). We analyzed the relationship between the formation mechanism of this fog episode and the low-level jet, and examined the role of each term in the TKE budget equation, such as shear and buoyancy production, to quantify the contributions of these terms to TKE. Previous studies on LLJs suggested that topography played a role in enhancing the intensity of LLJs and elevated their altitudes (e.g., Wexler 1961; Holton 1967; Pan et al. 2004; Zhang et al. 2006). In this fog case, the LLJ occurred over the Yellow and East China Seas, which are channeled by the China mainland and the Korean Peninsula (Fig. 1). Following on to previous studies on LLJs in the U.S. Great Plains in terms of the role of topography (Wexler 1961; Pan et al. 2004), we conducted a topography test, in which the mountainous area (Fig. 1) in Fujian Province was removed. The topography test results suggested that the topography area has three major impacts, including the moisture distribution, the intensity of the inversion layer, and the LLJ over the Yellow Sea.

Fig. 1.
Fig. 1.

(top) The model domain and locations of eight observational stations along the coastline of the YS. The stations are Shengsi (SS), Shanghai (SH), Lusi (LS), Sheyang (SY), Qingdao (QD), Chengshantou (CT), and Dalian (DL), respectively, from south to north on the western side and Cheju (CJ) on the eastern side. The dashed rectangular region is selected for later analysis. (bottom) A magnification of the rectangular region in the top panel with topography height.

Citation: Weather and Forecasting 27, 6; 10.1175/WAF-D-11-00152.1

The rest of the paper is organized as follows. Section 2 gives a brief synoptic description of the selected fog event. Section 3 describes the model configuration. Section 4 analyzes the control-run and topography test results. Finally, section 5 presents conclusions and discussions.

2. Observations of the fog event

A dense fog event occurred from 8 to 10 March 2005, which was reported and observed at three coastal stations in China: Chengshantou (CT), Qingdao (QD), and Sheyang (SY) (see Fig. 1 for their locations). Eight observatory stations in Fig. 1 typically provide sounding data twice a day at 0000 and 1200 UTC. The weather information observed at these stations, including current and past weather, air pressure, atmospheric horizontal visibility, wind speed and direction, air temperature and dewpoint temperature, is recorded every 3 h. Detailed description of the datasets used in the present study can be found on the National Center for Atmospheric Research’s (NCAR) web site (http://dss.ucar.edu/datasets/ds464.0/ and http://dss.ucar.edu/datasets/ds353.4); this dataset is managed by NCAR’s data support section and available for free access.

The northwestern Pacific high pressure system (NPH) centering around (30°N, 135°E) dominated over the YS during the onset stage of this fog episode (Fig. 2). The southerlies associated with the NPH prevailed over the YS during this period. The maximum air–sea temperature difference (surface air temperature minus sea surface temperature, SAT − SST) is about 4°C at 0000 UTC 9 March 2005. This fog was classified as an advection cooling fog (Gao et al. 2007; Li et al. 2011), which can also be considered to be a cold sea fog (SAT − SST > 0) according to Kim and Yum (2010). Cho et al. (2000) also mentioned that SAT is larger than SST in spring and summer at Chukdo station in the YS. Lee et al. (2010) found that the YS has lower SST than SAT from April to July. The specific humidity (SH) ranging from 3 to 8 g kg−1 in the fog region is larger in the southern seas than that in the northern seas. The situation that southerlies bring warm and moist air from the southern China Seas to the YS is favorable for the formation of advection cooling fog. The detailed observational characteristics of this case have been investigated by Li (2011).

Fig. 2.
Fig. 2.

SAT − SST (shaded, °C), SH (solid line, g kg−1) at 2 m, and winds (vector, m s−1) at 0000 UTC 9 Mar 2005.

Citation: Weather and Forecasting 27, 6; 10.1175/WAF-D-11-00152.1

Figure 3 shows the appearance of this fog episode in the visible satellite image on 9 March 2005. It is seen that stratus clouds extended into the coastal areas on both sides of the YS, which was confirmed as a fog patch by the coastal observational reports. The features of the fog patch in the visible satellite image were as follow: 1) the brightness of the fog patch was weaker than that of high clouds in the south, which are probably cumulus; 2) the fog patch matched the coastline well; 3) the appearance of the fog patch shows little difference during the next 6 h of evolution; and 4) the movement of the fog patch was not remarkable. These features are basically consistent with sea fog characteristics described by Fu et al. (2006). This suggests that these features can probably be used as the criteria for verifying sea fog versus stratus over the YS in satellite images. However, this approach still needs further surface observations to distinguish sea fog from stratus clouds.

Fig. 3.
Fig. 3.

The albedo distribution of Geostationary Operational Environmental Satellite-9 (GOES-9) visible band (0.55–0.90 μm) at (a) 0200, (b) 0400, (c) 0600, and (d) 0800 UTC 9 Mar 2005.

Citation: Weather and Forecasting 27, 6; 10.1175/WAF-D-11-00152.1

Figure 4a shows the temporal evolution of atmospheric horizontal visibility and specific humidity during the fog episode. It can be seen that fog (shaded) first appeared around SY (Fig. 1) shortly after 1200 UTC 8 March 2005. After 0000 UTC 9 March, it disappeared in the SY area. Six hours later, the fog patch appeared around QD. A few hours after that, CT station reported fog with atmospheric horizontal visibility about 100 m. Combining with the evidence from the satellite images (Fig. 3), one may conclude that the fog patch was advected northward by the southerlies. From the temporal evolution of specific humidity (Fig. 4a), one can see that the area of specific humidity ranging from 2 to 8 g kg−1 is larger in the south than that in the north. This indicates that the moisture in the fog formation is probably from the southern seas of China. In the fog area (shaded), the specific humidity is about 4–6 g kg−1, and the corresponding relative humidity (figure not shown) is from 70% to 100%. In Fig. 4b, the wind speed is on the order of 2–8 m s−1 in the fog area and the wind direction shifts from southerlies during the onset period (in early hours of 9 March) to northerlies in the dissipation stage (in early hours of 10 March) in the fog area.

Fig. 4.
Fig. 4.

The temporal evolution of atmospheric horizontal visibility (shaded) with (a) SH (contour, g kg−1) and (b) wind speed (contour, m s−1) and direction (barb) at seven stations along the western side of the YS. Shaded area denotes the atmospheric horizontal visibility below a 1-km area (fog). The x axis denotes the location distribution of seven stations (bottom axis) and the distance between these stations (top axis). The y axis denotes time.

Citation: Weather and Forecasting 27, 6; 10.1175/WAF-D-11-00152.1

3. Model setup

The WRF is a fully compressible Eulerian nonhydrostatic model with a terrain-following hydrostatic-pressure vertical coordinate. It is designed to be a flexible state-of-the-art atmospheric simulation system and is suitable for use in a broad range of applications across scales ranging from meters in large eddy simulation model (Catalano and Cenedese 2010; Catalano and Moeng 2010; Moeng et al. 2007) to thousands of kilometers for climate studies (Sertel et al. 2009; Y. Zhang et al. 2009). In the present study, version 3.1.1 of the WRF’s Advanced Research core (Skamarock et al. 2008), released in July 2009, was employed. We conducted a 72-h simulation initialized at 0000 UTC 8 March 2005. The domain (Fig. 1) is centered at 36°N, 124°E with horizontal grid spacing of 30 km × 30 km and with mesh sizes of 100 × 100 points. Forty σ levels were applied in the simulation with high resolution below 850 hPa (20 levels). The top of the model is at 50 hPa. The planetary boundary layer scheme is critical in simulating fogs realistically. A Mellor–Yamada Nakanishi–Niino (MYNN) level-3 scheme was employed in the simulation; this approach was originally proposed by Mellor and Yamada (1982). The MYNN scheme was modified by Nakanishi and Niino (2004) and was verified by Nakanishi and Niino (2006) for an advection fog simulation. It is noteworthy that the MYNN scheme predicts TKE and other second-moment terms. The corresponding MYNN surface layer scheme was also involved in the simulation. A Morrison double-moment scheme (Morrison et al. 2009) with double-moment ice, snow, rain, and graupel for cloud-resolving simulations was used. Other schemes of physical parameterizations include the Betts–Miller–Janjić cumulus parameterization scheme (Betts and Miller 1986; Janjić 1994, 2000), the Rapid Radiative Transfer Model (RRTM; Mlawer et al. 1997) scheme, and the Dudhia scheme (Dudhia 1989) for longwave and shortwave radiation. The lateral and initial conditions were obtained from a 6-hourly global reanalysis (FNL)1 issued by the National Centers for Environmental Prediction (NCEP) with horizontal resolution of 1° × 1°.

4. Results

a. Control simulation

The control simulation of this sea fog event began at 0000 UTC 8 March 2005 with 72 h of integration time. The simulated fields of wind and temperature at 700, 850, and 1000 hPa at 0000, 0600, 1200, and 1800 UTC 9 March are validated against the corresponding FNL data (figure not shown). The simulated temperature profiles at the QD and SY stations are validated against the observed temperature profiles at 0000 UTC 9 March and 0000 UTC 10 March (Fig. 5). The interpolation process for the QD and SY stations may cause some errors. Based on the verifications, it is suggested that the control simulation reproduced the atmospheric circulation and the vertical profiles reasonably well. A good reproduction of a sea fog event by a model is mainly judged by fog appearance. Cloud water mixing ratio (CWMR), which is a model prognostic variable from the Morrison scheme (Morrison et al. 2009), is used for verification purposes. CWMR can be used to represent fog/stratus (Pagowski et al. 2004; Fu et al. 2006; Zhang et al. 2011) and higher-level clouds (Jiang and Cotton 2000). Jiang and Cotton (2000) used cloud liquid water path (LWP) to denote the depth of the cloud layer. LWP is defined as follows:
eq1
where z1 is about 10 m, zt is the fog-top height (about 500 m), ρ is standard air density at sea level (1.225 kg m−3), rc is CWMR, and dz denotes the height difference between two model layers. From the definition of LWP, it can be inferred that LWP can be used both to represent fog patches and to denote the depth of the fog layer. LWP is integrated vertically by using CWMR. It is more reasonable when verifying fog areas to compare visible satellite imagery with LWP results (Figs. 6 and 3) than with CWMR at any single level. It can be seen that the main feature of a fog patch, such as the shape of sea fog, and the movement and depth of the fog layer, is reproduced reasonably well. Note that the fog patch moved northeastward by the southerlies. Based on the above analyses, the control simulation is a reasonable reproduction of the sea fog event and can be used for later analysis.
Fig. 5.
Fig. 5.

Comparison of simulated (dashed) and observed (solid) temperature (°C) profiles at SY at (a) 0000 UTC 9 Mar and (b) 0000 UTC 10 Mar and at QD at (c) 0000 UTC 9 Mar and (d) 0000 UTC 10 Mar 2005.

Citation: Weather and Forecasting 27, 6; 10.1175/WAF-D-11-00152.1

Fig. 6.
Fig. 6.

Wind field and large wind speed area (shaded, >10 m s−1) at 360 m as well as LWP (contour, kg m−2) at (a) 0200, (b) 0400, (c) 0600, and (d) 0800 UTC 9 Mar 2005 in the control run. The line labeled AB in (c) is used for the later analysis.

Citation: Weather and Forecasting 27, 6; 10.1175/WAF-D-11-00152.1

It was defined in Stull (1988) that the LLJ is a thin stream of fast-moving air, with maximum wind speeds of 10–20 m s−1, usually located 100–300 m above the ground. Altitudes of the peak were occasionally as high as 900 m above ground. We have adopted this definition of the LLJ in the present study. In the control simulation (Fig. 6), an LLJ with its peak speed core of about 20 m s−1 was found over the YS around 360 m above sea level. This LLJ has a width of 300–400 km (to its half-peak value) and a length larger than 1000 km. It has a vertical extension to about 900 m with a maximum speed of about 16 m s−1. This LLJ was verified by both sounding data at Cheju Island (Fig. 1) and the FNL dataset. Based on comparisons between the modeling results and the sounding and FNL data (Figs. 7a–c), it is suggested that the simulated LLJ overestimated the speed by about 2–4 m s−1 and underestimated the height by about 50–100 m. However, the core of the LLJ was reproduced reasonably well. It is also suggested that the modeling result has a better degree of agreement with the FNL data than the sounding data. This is reasonable because FNL data were used as the first guess in the simulation. To investigate the roles of the LLJ in the formation of this fog event, the horizontal distribution of the moisture divergence and the terms of the TKE budget equation are analyzed based on the modeling results. The moisture divergence (Qυ) is defined as
e1
where u, υ (m s−1) are the horizontal velocity components and q (g kg−1) is the specific humidity. The horizontal distribution of the moisture divergence is shown in Figs. 8a–d. As defined in Eq. (1), the negative shaded area denotes the convergence zone, whereas the positive area denotes the divergence zone. As shown in Fig. 8a, the convergence occurred near the northern front of the sea fog patch and also in the coastal area. The convergence zone in the coastal area was probably caused by the interactions between the land and sea winds. It can be seen in Fig. 6 that larger LWP locates in the front of LLJ. Hence, the convergence zone near the northern front of the sea fog patch is due to LLJ, according to the definition of the moisture divergence (Qυ). In addition, larger LWP suggests that the fog layer is thicker in the northern front of the fog patch. It will be further confirmed later that sea fog had a higher extension in this convergence area than that in the other part of the sea fog patch.
Fig. 7.
Fig. 7.

Vertical profiles of wind speed (m s−1) at CJ for (a) sounding, (b) FNL data, and (c) WRF control simulation results from 0000 UTC 8 Mar to 0000 UTC 11 Mar 2005. The shaded region denotes wind speed higher than 10 m s−1.

Citation: Weather and Forecasting 27, 6; 10.1175/WAF-D-11-00152.1

Fig. 8.
Fig. 8.

Horizontal distribution of the moisture divergence (shaded, 10−7 g kg−1 s−1) and CWMR (contour, g kg−1) at 10 m at (a) 0200, (b) 0400, (c) 0600, and (d) 0800 UTC 9 Mar 2005 in the control run.

Citation: Weather and Forecasting 27, 6; 10.1175/WAF-D-11-00152.1

The TKE budget equation has the following form:
e2
where the overbars denote time averages, Km (m2 s−1) is the eddy viscosity, Kh (m2 s−1) is the eddy diffusivity, and θυ is the virtual potential temperature.2 Term I represents the local tendency of TKE, and term II describes the advection of TKE. Term III is a mechanical or shear production term. Term IV represents the buoyant production or consumption. Term V is the turbulent transport of TKE. Term VI represents the viscous dissipation of TKE. Mellor and Yamada (1974) and Stull (1988) suggested that among these terms the mechanical term, the buoyant term, and the viscous dissipation are typically dominant based on the scaling analysis. In the present study, the aforementioned terms in Eq. (2) were computed using the estimates provided by the MYNN PBL scheme for the second moments, except for the viscous dissipation term, which is hard to measure using the model output. On the other hand, the purpose of the present analysis is to investigate the role of the LLJ and the source of TKE. Hence, it is acceptable to neglect the dissipation term due to its nonsource term on the generation of TKE. Bear in mind that the dissipation rate of the viscous term is typically largest near the surface. The results show that the mechanical term and the buoyant term are on the order of 10−3 and 10−4 m2 s−3, respectively, whereas the other terms (such as the advection term) are on the order of 10−5 m2 s−3 or less (Fig. 9). Hence, we will mainly focus on the two dominant terms in the following analyses.
Fig. 9.
Fig. 9.

Cross section of the TKE advection term (contour, 10−5 m2 s−3) along the line AB at 0500 UTC 9 Mar 2005 in the control run.

Citation: Weather and Forecasting 27, 6; 10.1175/WAF-D-11-00152.1

Figures 10a–d show the vertical profiles of CWMR and TKE along the line AB (Fig. 6c) at 0500, 0600, 0700, and 0800 UTC 9 March, respectively. It can be seen that significant values of CWMR are observed at higher levels of the atmosphere in the east, which is consistent with the height of turbulent activities. This suggests that the intensity of the inversion layer is crucial for extending the fog patch vertically and the vertical mixing processes activated by turbulence favors the vertical extension of fog in the east. It is noteworthy that in Fig. 10a, TKE was larger in the west than that in the east ranging from 5 to 40 × 10−2 m2 s−2. However, the fog layer was lower in the west than that in the east. Later analyses showed that the inversion layer was stronger in the west than that in the east, which suppressed the vertical extension of the fog in the west and favored the extension in the east. The strong turbulence in the west is originally generated by the land heating during daytime and transported downstream by advection (Fig. 9). The criterion on how strong the inversion layer should be to suppress the vertical extension of sea fog for a given strength of turbulent activity cannot be determined in the present study. Note that the fog patch did not dissipate as it evolved.

Fig. 10.
Fig. 10.

Cross section of TKE (contour, interval 5 × 10−2 m2 s−2) and CWMR (shaded, g kg−1) along the line AB at (a) 0500, (b) 0600, (c) 0700, and (d) 0800 UTC 9 Mar 2005 in the control run.

Citation: Weather and Forecasting 27, 6; 10.1175/WAF-D-11-00152.1

Judging from the tendency of TKE (Fig. 11), TKE gradually increased in the east around (35°–37°N, 123°–125.5°E) under 200 m ranging from 0.1 to 1 × 10−5 m2 s−3 except at 0500 UTC and decreased in the west around 31–33°N, 122–123°E in the range of −0.3 to −5 × 10−5 m2 s−3 except at 0800 UTC. This tendency is consistent with the evolution of TKE in Fig. 10, which shows a decrease in TKE in the west and an increase in the east. Figure 12 shows the contribution of shear production to the TKE budget and the profile of the LLJ. The wind shear production shows the maximum value about 1.7 × 10−3 m2 s−3 occurring at the surface and extends to about 100 m with the value of 0.1 × 10−3 m2 s−3. The LLJ has a maximum speed of 18 m s−1 around 300 m at 0600 UTC 9 March (Fig. 12b). Note that the wind speed increased, as shown in Figs. 12a–d. However, the wind shear production showed little change. In Fig. 13, the buoyancy term near the ground around 122°–123°E showed the largest negative value corresponding to the largest consumption rate of turbulence, with the value of −2.1 × 10−4 m2 s−3. The contribution of the buoyancy term to the consumption of the turbulence gradually increased as the inversion layer was strengthened. This also explained the situation of the vertical extension of the fog in Fig. 10, where the fog patch extended higher in the east than in the west. The shear production term is about an order of magnitude larger than the buoyancy term in the east during this period. TKE tends to increase during this period (Fig. 11) in the east. It can be inferred that the shear production due to the existence of the LLJ contributes to the generation of TKE. In the western area, TKE tends to decrease during the first 3 h (Figs. 11a–c). The buoyancy term suppressed the generation of TKE as the inversion layer was strengthened gradually.

Fig. 11.
Fig. 11.

Cross section of TKE tendency (contour, 10−5 m2 s−3) along the line AB at (a) 0500, (b) 0600, (c) 0700, and (d) 0800 UTC 9 Mar 2005 in the control run.

Citation: Weather and Forecasting 27, 6; 10.1175/WAF-D-11-00152.1

Fig. 12.
Fig. 12.

Cross section of the TKE mechanical production term (contour, 10−3 m2 s−3) and wind speed (shaded with dash line, m s−1) along the line AB at (a) 0500, (b) 0600, (c) 0700, and (d) 0800 UTC 9 Mar 2005 in the control run.

Citation: Weather and Forecasting 27, 6; 10.1175/WAF-D-11-00152.1

Fig. 13.
Fig. 13.

Cross section of TKE buoyancy term (contour, 10−4 m2 s−3) and temperature (shaded with dash line, °C) along the line AB at (a) 0500, (b) 0600, (c) 0700, and (d) 0800 UTC 9 Mar 2005 in the control run.

Citation: Weather and Forecasting 27, 6; 10.1175/WAF-D-11-00152.1

b. Topography test

In the following, a topography test has been conducted using the same physical parameterizations as the control simulation. In the test, all modeling setups, such as the integration time and domain size, are kept the same as the control run, except that the mountainous area (Fig. 1) in Fujian Province was removed. The results showed that both the LLJ and the shear production were weakened (cf. Figs. 14 and 12). The maximum speed was reduced from 18 m s−1 in the control run to 14 m s−1 in the absence of topography. The largest shear production was reduced from 1.7 to 1.3 × 10−3 m2 s−3. It also can be seen that the altitude of the LLJ core is about 150 m lower than that in the control run (cf. Figs. 14d and 12d). Compared with TKE and CWMR in the control run (Fig. 10), the topography test results showed decreasing trends in TKE and CWMR, as well as the height of the fog top (figures not shown) during the same time period. It can be inferred based on the previous analyses that the LLJ has an important impact on the TKE. Due to the decrease in TKE, the fog cannot extend as high as it does in the control run. The decrease in the CWMR suggested that the moisture supply may be influenced by the removal of topography in this test. Figure 15 shows the moisture (specific humidity, SH) difference (topography test − control run) before and during the fog formation. The positive value indicates that the moisture is larger in the topography test than that in the control run. One can see that the largest moisture difference is located at the removed mountainous region ranging from 1 to 4 g kg−1. This suggests that more moisture was brought into the coastal region in the topography test than was the case in the control experiment. This is probably due to the removal of the mountainous area, which prevents the moisture brought by the southerlies from entering into the coastal mountainous area. In addition, the inversion layer was weaker in the topography test case. A possible reason for the weakening of the inversion layer is that the adiabatic heating process was weakened or vanished after the removal of the mountainous area.

Fig. 14.
Fig. 14.

Cross section of TKE mechanical production term (contour, 10−3 m2 s−3) and wind speed (shaded with dash line, m s−1) along the line AB in Fig. 4b at (a) 0500, (b) 0600, (c) 0700, and (d) 0800 UTC 9 Mar 2005 in the topography test.

Citation: Weather and Forecasting 27, 6; 10.1175/WAF-D-11-00152.1

Fig. 15.
Fig. 15.

SH (shaded, g kg−1) difference (topography test − control run) at 10 m at (a) 2200 UTC 8 Mar 2005 and at (b) 0000, (c) 0200, and (d) 0400 UTC 9 Mar 2005. The rectangular region denotes the removed topography area.

Citation: Weather and Forecasting 27, 6; 10.1175/WAF-D-11-00152.1

5. Conclusions and discussions

In this paper, we have presented a modeling and diagnostic study of a spring sea fog event that occurred over the YS on 9 March 2005. The fog event, which was classified as an advection cooling fog, was associated with a low-level jet. The southerlies associated with the NPH prevailed over the YS during the fog onset period and brought warm and moist air from the southern China Seas to the YS. The situation is favorable for advection cooling fog formation. A control simulation of this fog event using the WRF was reasonably accurate. A topography test in which a mountainous region in Fujian Province was removed was conducted to examine the impact of the topography on the LLJ and the fog event.

In the control run, the simulated LLJ overestimated the speed by about 2–4 m s−1 and underestimated the height by about 50–100 m. The fog formation mechanism was analyzed based on the simulation results. It was found that the wind shear production associated with the LLJ contributed to the generation of TKE. The inversion layer played an important role in suppressing the vertical extension of this fog event. The fog layer reached the bottom of the inversion layer and extended higher vertically in the northeastern region than in the southwestern region with the aid of TKE. The vertical distribution of the fog patch was mainly due to the intensity of the inversion layer; that is, the stronger the inversion, the lower the height of the fog top. The criterion for estimating how strong the inversion layer should be to suppress the vertical extension of sea fog for a given strength of turbulent activity cannot be determined in the present study. However, it can be inferred based on the analysis of the cross section of TKE (Fig. 10) and temperature (Fig. 13) that fog cannot extend vertically with the aid of TKE in the range of 5–40 × 10−2 m2 s−2 under the inversion layer [3°C (100 m)−1].

The topography test showed that the intensity of the LLJ over the YS was reduced from a maximum of 18 m s−1 in the control run to 14 m s−1 in the absence of coastal topography. The altitude of the marine LLJ was lower by about 150 m in the topography test than that in the control run. The test also suggested that the mountainous topography blocked the moisture brought by the southerlies. The moisture cannot be diverted inland due to the existence of the mountainous area. The inversion layer was weakened during the topography test. The adiabatic process may be responsible for the weakening of the inversion layer.

There are some limitations in the present approach when studying turbulence. PBL models aim at reproducing the bulk effects of subgrid-scale turbulence on the larger scales, which represent Reynolds averaged fields. The present study was analyzed based on the 30-km-resolution simulation. Hence, the grid values are not representative of turbulent fields. The characteristic turbulent structures of a fog boundary layer cannot be explicitly resolved at 30-km resolution. The results of the study only showed the bulk properties of the atmosphere. Furthermore, surface inhomogeneities could be very important in the column models, which neglect horizontal advection terms. Those undertaking future work on turbulence should be aware of these issues.

Acknowledgments

The authors would like to express their great thanks to two anonymous reviewers for their constructive and helpful comments for the improvement of this manuscript. Special thanks are due to one of the reviewers for pointing out the limitation of the approach. P. Li would like to express his sincere thanks to the China Scholarship Council for financial support, which made his study in NOAA possible. P. Li was supported by China Postdoctoral Funding under Grant 2012M511545. C. Lu’s efforts toward this study were supported by NOAA. G. Fu was partly supported by the National Natural Science Foundation of China under Grant 406750060 and the Chinese Ministry of Science and Technology under 973 Project Grant 2009CB421504. This work was also partly supported by the Chinese Meteorological Administration under Grant GYHY200706031 and the Chinese Government Program of Introducing Talents of Discipline to Universities (B07036).

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1

FNL data can be downloaded online (http://dss.ucar.edu/datasets/ds083.2/).

2

There exists an empirical relationship between Km and Kh; Kh = 1.35 Km in the neutral layer. Values of Km reported in the literature vary from 0.1 to 2000 m2 s−1; here, Km = 0.1 m2 s−1, Kh = 0.135 m2 s−1. In this case θυ is for saturated (cloud) air.

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