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  • View in gallery

    (a) The simulated domain. Three nested domains are used in this study with horizontal resolutions of 27, 9, and 3 km. The white line denotes the flight track of C130 research aircraft on 18 Oct 2008. Colors represent the height above sea level (m). (b) Satellite cloud imagery from GOES-10 visible channel (http://data.eol.ucar.edu/codiac/dss/id=89.080) at 1515 UTC (1215 LT at the place where the research aircraft took off and landed) 18 Oct 2008 in the finest domain in (a). The yellow line separates the finest domain into two regimes at 79°W.

  • View in gallery

    Comparison of profiles of (a),(b) potential temperature; (c),(d) water vapor mixing ratio; and (e),(f) LWC between observation data with simulation results. (right) Observed profiles are from 1054 to 1104 LT 18 Oct 2008 (73°–74°W), representing the eastern regime; (left) observed profiles are from 1529 to 1537 LT 18 Oct 2008 (81°–82°W), representing the western regime. The model results in the right column are for the snapshot at 1100 LT 18 Oct 2008, averaged over the region 73°–74°W; the model results in the left column are for the average of the two snapshots at 1500 and 1600 LT 19 Oct 2008, and averaged over the region 81°–82°W.

  • View in gallery

    The simulated (a) LWP (g m−2) at 1200 LT 18 Oct and (b) accumulated precipitation (mm) at the surface from 0900 LT 18 Oct to 0900 LT 19 Oct in the finest domain. The local time refers to the time at the place where the research aircraft took off and landed. Aerosol mixing ratio is 200 mg−1.

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    Time evolution of the simulated cloud properties in western and eastern regimes from 0900 LT 18 Oct to 0900 LT 19 Oct. (a) Cloud fraction; (b) LWP; (c) cloud-top and cloud-base heights; and (d) surface precipitation rate. Cloud fraction is the fraction of cloudy columns (LWP higher than 10 g m−2) in the finest domain. Cloud properties in (b)–(d) are averaged over cloudy columns. Cloud-top and cloud-base are the highest and lowest grids with LWC higher than 0.01 g kg−1 in the cloudy columns. The local time refers to the time at the place where the research aircraft took off and landed. Aerosol mixing ratio is 200 mg−1.

  • View in gallery

    Simulated vertical distributions of cloud properties in (left) western and (right) eastern regimes from 0900 LT 18 Oct to 0900 LT 19 Oct. (a),(b) Cloud fraction; (c),(d) LWC; (e),(f) rainwater mixing ratio; (g),(h) droplet number concentration Nd; and (i),(j) droplet effective radius re. The cloud fraction at each height is the fraction of cloudy grids in the domain at that height. LWC and rainwater mixing ratio are averaged over cloudy columns. The Nd and re values are averaged over cloudy grids at each height. The local time refers to the time at the place where the research aircraft took off and landed. Aerosol mixing ratio is 200 mg−1.

  • View in gallery

    Profiles of the simulated meteorological properties in western and eastern regimes from 0900 LT 18 Oct to 0900 LT 19 Oct with intervals of 6 h. (top) Potential temperature, (middle) water vapor mixing ratio, and (bottom) RH. All properties are averaged over the finest domain. The time shown in the figure is the local time at the place where the research aircraft took off and landed. Aerosol mixing ratio is 200 mg−1. Red lines indicate the inversion layer heights.

  • View in gallery

    Time evolution of the simulated cloud properties in western and eastern regimes from 0900 LT 18 Oct to 0900 LT 19 Oct. (a) Cloud fraction; (b) LWP; (c) cloud thickness; and (d) surface precipitation rate. All properties except cloud fraction are averaged over cloudy columns. The differences between red and black lines are changes caused by increasing aerosol number mixing ratio to 2000 mg−1. The local time refers to the time at the place where the research aircraft took off and landed.

  • View in gallery

    Simulated vertical distributions of cloud properties in (left) western and (right) eastern regimes from 0900 LT 18 Oct to 0900 LT 19 Oct. The differences of (a),(b) cloud fraction; (c),(d) LWC; (e),(f) rainwater mixing ratio between polluted and clean conditions; and absolute values of (g),(h) Nd and (i),(j) re. The local time refers to the time at the place where the research aircraft took off and landed. Aerosol mixing ratio is 2000 mg−1.

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Meteorological and Aerosol Effects on Marine Stratocumulus

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  • 1 Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing, China
  • | 2 Department of Atmospheric Sciences, National Taiwan University, Taipei, Taiwan
  • | 3 Atmospheric Sciences Research Center, University at Albany, State University of New York, Albany, New York
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Abstract

This study investigates the effects of meteorological conditions and aerosols on marine stratocumulus in the southeastern Pacific using the Weather Research and Forecasting (WRF) Model. Two regimes with different temperature and moisture conditions in the finest model domain are investigated. The western regime is around 87°–79°W, while the eastern regime is around 79°–71°W. In both regimes, cloud fraction, liquid water path (LWP), cloud thickness, and precipitation show significant diurnal cycles. Cloud fraction can be 0.83 during the night and down to 0.29 during the day in the western regime. The diurnal cycles in the eastern regime have smaller amplitudes but are still very strong. Stratocumulus properties also differ in the two regimes. Compared to the western regime, the eastern regime has lower temperature, higher relative humidity, and a more coupled boundary layer, leading to higher cloud fraction (by 0.11) and lower cloud-base height. The eastern regime also has lower inversion height that causes lower cloud-top height and thinner clouds and, hence, lower LWP and less precipitation.

Cloud microphysical properties are very sensitive to aerosols in both regimes. Increasing aerosols greatly increase cloud number concentration, decrease cloud effective radius, and suppress precipitation. Cloud macrophysical properties (cloud fraction, LWP) are not sensitive to aerosols in either regime, most notably in the eastern regime where precipitation amount is less. The changes in cloud fraction and LWP caused by changes in aerosol concentrations are smaller than the changes in the diurnal cycle and the spatial variability between the two regimes.

Publisher’s Note: This article was revised on 28 April 2016 to correct the affiliation of the first two authors.

Current affiliation: Numerical Weather Prediction Center, China Meteorological Administration, Beijing, China.

Corresponding author address: Huiwen Xue, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, North Physics Bldg., Rm. 518, 209 Chengfu Road, Beijing 100871, China. E-mail: hxue@pku.edu.cn

Abstract

This study investigates the effects of meteorological conditions and aerosols on marine stratocumulus in the southeastern Pacific using the Weather Research and Forecasting (WRF) Model. Two regimes with different temperature and moisture conditions in the finest model domain are investigated. The western regime is around 87°–79°W, while the eastern regime is around 79°–71°W. In both regimes, cloud fraction, liquid water path (LWP), cloud thickness, and precipitation show significant diurnal cycles. Cloud fraction can be 0.83 during the night and down to 0.29 during the day in the western regime. The diurnal cycles in the eastern regime have smaller amplitudes but are still very strong. Stratocumulus properties also differ in the two regimes. Compared to the western regime, the eastern regime has lower temperature, higher relative humidity, and a more coupled boundary layer, leading to higher cloud fraction (by 0.11) and lower cloud-base height. The eastern regime also has lower inversion height that causes lower cloud-top height and thinner clouds and, hence, lower LWP and less precipitation.

Cloud microphysical properties are very sensitive to aerosols in both regimes. Increasing aerosols greatly increase cloud number concentration, decrease cloud effective radius, and suppress precipitation. Cloud macrophysical properties (cloud fraction, LWP) are not sensitive to aerosols in either regime, most notably in the eastern regime where precipitation amount is less. The changes in cloud fraction and LWP caused by changes in aerosol concentrations are smaller than the changes in the diurnal cycle and the spatial variability between the two regimes.

Publisher’s Note: This article was revised on 28 April 2016 to correct the affiliation of the first two authors.

Current affiliation: Numerical Weather Prediction Center, China Meteorological Administration, Beijing, China.

Corresponding author address: Huiwen Xue, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, North Physics Bldg., Rm. 518, 209 Chengfu Road, Beijing 100871, China. E-mail: hxue@pku.edu.cn

1. Introduction

Stratocumulus is favored to occur in well-mixed shallow boundary layers with sufficient moisture supply from the surface. The regions in the downward branches of large-scale circulations tend to meet such requirements (Wood 2012). For example, the southeastern Pacific region is home to the largest subtropical stratocumulus deck on Earth (Wood et al. 2011; Wang et al. 2010; Klein and Hartmann 1993). The annually averaged coverage of stratocumulus is approximately 23% over the ocean and 12% over the land (Warren et al. 1986, 1988; Hahn and Warren 2007). Stratocumulus has small effect on Earth’s outgoing longwave radiation because its temperature is similar to the underlying surface. However, stratocumulus can strongly reflect the incoming solar radiation. Therefore, it shows a strong negative radiative effect on Earth’s radiation balance (e.g., Stephens and Greenwald 1991; Hartmann et al. 1992). The change of stratocumulus macrophysical properties such as cloud fraction, liquid water path (LWP), and microphysical properties such as droplet concentration Nd and effective radius re will strongly alter the radiative fluxes of Earth.

Previous studies using satellite and reanalysis data show that stratocumulus properties are strongly affected by meteorological conditions such as temperature and large-scale subsidence. The coverage of low clouds in southeastern Pacific is in proportion to the difference of potential temperatures at 700 hPa and the surface (Klein and Hartmann 1993; Sun et al. 2011). The albedo of stratocumulus is the highest around 500–1000 km offshore and becomes lower near the shore of Chile (Twohy et al. 2013). This is related to the thinner clouds induced by the increased subsidence and thinner boundary layer near the shore (George and Wood 2010; Wyant et al. 2010). Besides the macrophysical properties, stratocumulus microphysical properties are also found to be affected by the meteorological conditions. Satellite data analysis shows that high Nd episodes are likely associated with a weaker anticyclone and weaker surface and free-tropospheric winds at the location of climatological anticyclone (Painemal and Zuidema 2010); Nd is also related to sea level pressure (George and Wood 2010). However, how those meteorological parameters govern stratocumulus macrophysical properties is not well established and needs further investigation (e.g., Klein 1997; Lohmann and Lesins 2002; Zhang et al. 2009; Wood 2012).

Stratocumulus cloud properties are also affected by the concentration of aerosol particles (i.e., natural sources, anthropogenic pollution). An investigation shows that when LWP is in the range of 50–200 g m−2, stratocumulus Nd is particularly sensitive to aerosol concentrations (Zuidema et al. 2005). Generally, increasing aerosols will produce more and smaller cloud droplets, leading to higher cloud albedo and suppressed precipitation (Wood 2012). Precipitation suppression might lead to increased cloud cover (Albrecht 1989). In addition, precipitation suppression can lead to higher LWP, especially at low-Nd conditions when precipitation is relatively strong (Ackerman et al. 2004, 2009). Similar results have been found by Caldwell and Bretherton (2009) that precipitation suppression causes a strong increase of LWP at night and early morning, when stratocumulus precipitates, but has little effect in the afternoon, when stratocumulus has little precipitation. The suppression of stratocumulus precipitation increases liquid water available for evaporative cooling and, therefore, has two effects on cloud thickness. On one hand, it can moisten and cool the boundary layer and lower the cloud base, leading to thicker clouds (Albrecht 1989; Wood 2007); on the other hand, it can increase the kinetic energy and cloud-top entrainment, leading to cloud thinning or thickening depending on the humidity of the free troposphere (Ackerman et al. 2004; Wood 2007; Stevens et al. 1998).

Previous investigations also show that aerosol effects on stratocumulus vary under different meteorological conditions. A model simulation shows that the open and closed cellular structures in stratocumulus can form only when aerosol sources and meteorological conditions are both appropriate (Wang et al. 2010). Based on field measurements, Yang et al. (2012) also point out that the aerosol impact on precipitation is different in the near-coast and remote ocean regimes, which implies that meteorological conditions may regulate aerosol effects on stratocumulus. Wood (2012) concludes that it is still not fully understood which factors control on Nd in the maritime boundary layer. It is also uncertain whether meteorological parameters or aerosol sources play a more significant role (Wang et al. 2010; Mechem et al. 2012).

Stratocumulus clouds over the southeastern Pacific region are investigated in this study. This area lies at the downward branches of the Hadley and Walker circulations (Schubert 1976; Randall 1980; Bretherton and Hartmann 2009), which contain strong lower-tropospheric stability and a ready supply of moisture from the surface. The Andes Mountains on the western coast of Chile and Peru block the zonal flow at midlatitudes with its great height and long extension, leading to strong parallel wind along the coasts (Wood et al. 2011). Such parallel wind, combined with easterlies at subtropical and tropical region, transports pollutants from the continent offshore, making the southeastern Pacific region highly affected by anthropogenic aerosols (e.g., Bretherton et al. 2004; Wood et al. 2011). The goal of this study is to investigate the effects of meteorological conditions and aerosols on stratocumulus using the Weather Research and Forecasting (WRF) Model. How cloud micro- and macrophysical properties respond to various meteorological parameters and aerosol mixing ratios has been investigated. The model and the experimental design are described in section 2, results and the discussion are shown in section 3, and summary and conclusion are presented in section 4.

2. Model description and experimental design

a. Model description

This study uses WRF, version 3.3.1, to simulate a marine stratocumulus case. The Yonsei University (YSU) boundary layer scheme (Hong et al. 2006) is used in this simulation to parameterize the boundary layer processes. Aerosols are transported and redistributed within the boundary layer. The mass and number mixing ratios are calculated in the scheme. The global version of rapid radiative transfer model (RRTMG_LW and RRTMG_SW) (Iacono et al. 2008) is adopted to parameterize radiative transfer. In this model, the radiation scheme is fully coupled with the cloud microphysical properties: the LWP is calculated from the predicted cloud water and the effective radii of liquid drops are calculated by the diagnostic formula from the microphysical scheme. The mixed-phase two-moment bulk water scheme CLR2 (Chen and Liu 2004; Cheng et al. 2007, 2010; Reisner et al. 1998) is used to simulate cloud microphysical processes.

The two-moment microphysical scheme CLR2 combines the warm cloud scheme from Chen and Liu (2004) and the cold cloud scheme from Reisner et al. (1998), as well as specific treatments on aerosol activation and recycling. The CLR2 scheme consists of a series of bulk formulas for mass and number concentrations of cloud droplets, raindrops, cloud ice, snow, and graupel. Detailed information is described in previous studies (Chen and Liu 2004; Cheng et al. 2007, 2010). In the treatment of aerosol activation into cloud droplets near cloud base, the CLR2 scheme applies a Lagrangian air parcel, which ascends/descends adiabatically with the vertical velocity at the grid, to better resolve the in-cloud supersaturation. In the Lagrangian parcel calculation, a smaller time step is needed to solve the supersaturation and droplet diffusional growth. The Köhler equation is used to get the critical radius of dry aerosols under a certain ambient supersaturation in each time step. If the critical radius is smaller than the minimum critical radius that ever occurred, the difference between the two critical radii determines the number of CCN to be activated in this time step. Aerosols can be released back to the air when cloud droplets evaporate. The formulas for droplet diffusional growth, autoconversions between cloud droplets and raindrops, collision–coalescence, and breakup are based on the statistical–numerical analyses of Chen and Liu (2004). In addition, the effective radius of cloud droplets, which is significantly important for precipitation process and radiative heating/cooling, is also provided by the diagnostic equations in the CLR2 scheme. Sedimentation is calculated in the Eulerian framework based on the mass and number concentration of cloud droplets.

b. Experimental design

In this study, a case corresponding to the flight track 02 of the NSF/NCAR C130 research aircraft during the VAMOS Ocean–Cloud–Atmosphere–Land Study Regional Experiment (VOCALS-REx) campaign is simulated. The flight track is shown in Fig. 1a. The flight took off at 1004 local time (LT; 1304 UTC) 18 October 2008 and landed at 1827 LT (2127 UTC). This flight was aiming to sample the longitudinal gradients in clouds, maritime boundary layer, and aerosols. The flight data successfully demonstrated the stratocumulus development at about 20°S latitude, with essentially no precipitation and relatively high cloud droplet number concentration (300 cm−3 in general, up to 550 cm−3). Three nested domains, as shown in Fig. 1a, are used in this simulation with the horizontal resolutions of 27, 9, and 3 km. There are 41 levels in the vertical direction, with 19 levels below 1500 m. The finest domain basically covers the flight track 02 of C130 on 18 October. The simulated data from 0900 LT 18 October to 0900 LT 19 October are analyzed for a diurnal cycle. The local time throughout this study refers to the local time at the place where the research aircraft took off and landed. Notice that the simulation period started at 2100 LT 15 October 2008 and the first 2.5 days are used as spinup.

Fig. 1.
Fig. 1.

(a) The simulated domain. Three nested domains are used in this study with horizontal resolutions of 27, 9, and 3 km. The white line denotes the flight track of C130 research aircraft on 18 Oct 2008. Colors represent the height above sea level (m). (b) Satellite cloud imagery from GOES-10 visible channel (http://data.eol.ucar.edu/codiac/dss/id=89.080) at 1515 UTC (1215 LT at the place where the research aircraft took off and landed) 18 Oct 2008 in the finest domain in (a). The yellow line separates the finest domain into two regimes at 79°W.

Citation: Journal of the Atmospheric Sciences 73, 2; 10.1175/JAS-D-15-0101.1

Figure 1b is the satellite cloud imagery in the visible channel (1215 LT 18 October) from GOES-10. The domain is exactly the same as the finest domain in Fig. 1a. As shown in the satellite cloud imagery, the western region has more broken clouds, while the eastern region has more continuous clouds. To investigate how cloud properties are regulated by meteorological conditions and aerosols, the finest domain is divided into a western regime and an eastern regime with the longitude of 79°W. Note that the two regimes are separated roughly based on cloud amount in satellite cloud pictures. There is actually no sharp boundary between the two regimes. Using the longitudes of 81° and 77°W, which are 2° from 79°W, does not affect the results much. The basic difference between the western and eastern regimes remains the same.

The high-vertical-resolution temperature and vapor profiles from the daytime observations on 18 October 2008 (http://data.eol.ucar.edu/master_list/?project=VOCALS) show a well-mixed boundary layer below 1000 m and a thin inversion layer between 1000 and 1100 m, as shown in Fig. 2. However, the model input soundings generated from WRF Preprocessing System (WPS) using only the NCEP Final Analysis (FNL) data show an inversion layer at around 600–900 m, which is thicker and several hundred meters lower than the observations. The reason for this is that the FNL data have a coarse vertical resolution (seven layers below 1500 m). Although WPS can use them to generate input soundings with higher vertical resolution (19 layers below 1500 m, a vertical resolution of about 70 m at the height around 1000 m in this study), the input soundings still look very similar to the original FNL data and cannot represent the inversion layer very well. The WRF Model thus shows poor ability to represent the boundary layer height, as also described in previous studies (e.g., Andrejczuk et al. 2012; Wyant et al. 2010; Abel et al. 2010). Therefore, the model input soundings are modified based on observations in this study. The main purpose of doing this modification is to make the inversion layer thinner and at higher altitudes as in the observations. It is also noted that the observed temperature at 1000 m is close to the temperature at about 600 m in the unmodified input soundings, whereas the observed temperature at 1100 m is close to the temperature at about 1400 m in the unmodified input soundings. With this in mind, and also considering the fact that the simulation starts at night when the boundary layer becomes thicker (Wood 2012), we made the following modifications to the input soundings: first, the input data at levels 15 and 16 (about 1090 and 1160 m) were replaced by those at levels 7 and 18 (about 600 and 1400 m); second, the input data from levels 1–6 were interpolated to the layer from levels 1–14, while those from levels 18 and 19 were interpolated to the layer from the 16th to the 19th levels 16–19; above level 19, the input soundings were not modified. Using these modified input soundings, the modeled meteorological profiles are very similar to the observed profiles, as shown in Fig. 2. A similar method has been used by Sandu and Stevens (2011).

Fig. 2.
Fig. 2.

Comparison of profiles of (a),(b) potential temperature; (c),(d) water vapor mixing ratio; and (e),(f) LWC between observation data with simulation results. (right) Observed profiles are from 1054 to 1104 LT 18 Oct 2008 (73°–74°W), representing the eastern regime; (left) observed profiles are from 1529 to 1537 LT 18 Oct 2008 (81°–82°W), representing the western regime. The model results in the right column are for the snapshot at 1100 LT 18 Oct 2008, averaged over the region 73°–74°W; the model results in the left column are for the average of the two snapshots at 1500 and 1600 LT 19 Oct 2008, and averaged over the region 81°–82°W.

Citation: Journal of the Atmospheric Sciences 73, 2; 10.1175/JAS-D-15-0101.1

To investigate the relative importance of aerosols and meteorological factors, a uniform aerosol field is used to focus on the meteorological effects in the two regimes. The initial aerosol field is vertically and horizontally uniform below 850 hPa. Above 850 hPa, the aerosol mixing ratio exponentially decreases with a scale height of 800 m. The aerosol mixing ratio is fixed at the lateral boundaries of the outermost domain. Thus, aerosols can flow in and out with winds of the inner-domain boundaries. Aerosols are all assumed as ammonium sulfate with a trimodal lognormal size distribution. The clean aerosol condition as observed by Jaenicke (1993) is used as one of the aerosol conditions in this study. The specific parameters of aerosol size distribution with a total number concentration around 200 mg−1 at the surface are shown in Table 1. The accumulation and coarse-mode aerosol number concentrations are about 30% of the total aerosol. For the aerosol perturbation run, the surface aerosol mixing ratio is set to be 10 times (around 2000 mg−1) of the clean condition to study aerosol effects. The corresponding CCN concentrations from the above aerosol size distributions are about 50 cm−3 in the clean case and 350 cm−3 in the perturbation case. Note that the aerosol size distribution in Table 1 is not from the VOCALS observation, but the CCN concentration in this study is very similar to the VOCALS measurements. Although horizontal variability are neglected in the initial CCN configuration, the two runs with different CCN concentrations correspond to the climatological MBL CCN concentrations at 82° (low CCN) and 70°W (high CCN), respectively, as mentioned by Allen et al. (2011).

Table 1.

Number, mean radius, and geometric width of nucleation, accumulation, and coarse modes of three aerosol size distribution types over a clean background.

Table 1.

3. Results and discussion

a. Comparison with field measurements

Measurements of meteorological conditions (potential temperature and water vapor mixing ratio) and cloud properties (LWC) from the flight-track 02 of the NSF/NCAR C130 are employed to evaluate the simulation of the case in this study. Two profiles are chosen for comparison. One is from 1054 to 1104 LT 18 October 2008 (73°–74°W) and the other is from 1529 to 1537 LT 18 October 2008 (81°–82°W). The two profiles correspond to locations close to the centers of the two regimes. The model results corresponding to the above time and space locations are compared to the measurements. Using the modified initial and boundary input soundings, the model can represent the depth of the boundary layer quite well. The maximum gradient of the simulated potential temperature and water vapor are around 1000 m, similar to the observations (Figs. 2a–d). The simulated LWC also matches well with observations in both the height and the magnitude, as shown in Figs. 2e and 2f.

b. Cloud properties under different meteorological conditions

Figure 3a shows the distribution of the simulated LWP in the finest domain with an aerosol mixing ratio of 200 mg−1 at a similar time (1200 LT 18 October) as the satellite cloud imagery in Fig. 1b. Although the simulated cloud distribution may not be the same as that in the satellite imagery, it can reflect the difference of cloud amount between the western and eastern regimes. The western regime has lower cloud fraction and more dispersed clouds, while the eastern regime has higher cloud fraction and more continuous clouds. The LWP on average is 160 g m−2, which is very typical for stratocumulus cloud (Wood 2012). Higher LWP occurs in the southwestern corner of the finest domain. The accumulated surface precipitation from 0900 LT 18 October to 0900 LT 19 October is shown in Fig. 3b. Precipitation occurs mainly at the southwestern corner with the accumulated precipitation up to 1.5 mm for the day.

Fig. 3.
Fig. 3.

The simulated (a) LWP (g m−2) at 1200 LT 18 Oct and (b) accumulated precipitation (mm) at the surface from 0900 LT 18 Oct to 0900 LT 19 Oct in the finest domain. The local time refers to the time at the place where the research aircraft took off and landed. Aerosol mixing ratio is 200 mg−1.

Citation: Journal of the Atmospheric Sciences 73, 2; 10.1175/JAS-D-15-0101.1

Figure 4 shows the time evolution of cloud properties in the western and eastern regimes. Diurnal cycles can be seen in all cloud properties. Stratocumulus develops and precipitates at night and early morning and dissipates in the afternoon. Table 2 summarizes the daily average, daily maximum, and daily minimum values of cloud fraction, LWP, cloud-top height, cloud-base height, and precipitation rate for both regimes. The differences in the daily maximum and daily minimum are also shown in the table to indicate the strength of the diurnal cycle. It is seen that the diurnal cycle is very strong. For example, in the western regime, the cloud fraction is as high as 0.83 at night and decreases to 0.29 in the afternoon. The diurnal cycle of cloud fraction is consistent with a previous satellite study of VOCALS (Burleyson and Yuter 2015), which pointed out that cloud fraction begins to increase at 1600 LT and reaches its maximum just before dawn. The averaged LWP in the western regime is up to 204 g m−2 at night and decreases to 75 g m−2 in the afternoon. Although results only in 24 h are analyzed in this simulation, the diurnal cycles of stratocumulus cloud fraction, LWP, cloud-top height, and cloud-base height are similar to ship observation in the VOCALS experiment (Burleyson et al. 2013). Precipitation rate can be as high as 0.35 mm day−1 and only occurs at night and early morning. The peak precipitation rate occurs early in the morning, which is consistent with ship observation (Boutle and Abel 2012; Burleyson et al. 2013). In addition, all cloud properties in the western regime has stronger diurnal cycles than in the eastern regime, which is consistent with previous studies showing that stronger diurnal cycles occur in the remote marine region (Rozendaal et al. 1995; Wang et al. 2011; Painemal et al. 2013, 2015; Burleyson and Yuter 2015).

Fig. 4.
Fig. 4.

Time evolution of the simulated cloud properties in western and eastern regimes from 0900 LT 18 Oct to 0900 LT 19 Oct. (a) Cloud fraction; (b) LWP; (c) cloud-top and cloud-base heights; and (d) surface precipitation rate. Cloud fraction is the fraction of cloudy columns (LWP higher than 10 g m−2) in the finest domain. Cloud properties in (b)–(d) are averaged over cloudy columns. Cloud-top and cloud-base are the highest and lowest grids with LWC higher than 0.01 g kg−1 in the cloudy columns. The local time refers to the time at the place where the research aircraft took off and landed. Aerosol mixing ratio is 200 mg−1.

Citation: Journal of the Atmospheric Sciences 73, 2; 10.1175/JAS-D-15-0101.1

Table 2.

Daily average, daily maximum, daily minimum, and daily maximum minus daily minimum values of cloud fraction, LWP, cloud-top height, cloud-base height, cloud thickness, rain rate, Nd, and cloud-top re for the clean condition in the western and eastern regimes. The difference of the daily average in the western and eastern regimes is also shown in the last column.

Table 2.

Figure 4 and Table 2 also show that cloud properties differ greatly in the two regimes. The last column of Table 2 shows the differences of the daily average cloud properties between the western and eastern regimes. For the eastern regime, the cloud fraction is generally 0.11 higher, and the LWP is 14 g m−2 lower than that in the western regime. Cloud-top height and cloud-base height are 152 and 123 m lower than in the western regime, respectively. The lower cloud layers in the eastern regime are consistent with ship observations (Brunke et al. 2010) and model simulation (Abel et al. 2010) of this area. Daily average precipitation rate in the eastern regime is much smaller than that in the western regime, which is consistent with previous studies that western regime has more climatological precipitation (e.g., Leon et al. 2008; Burleyson et al. 2013; Mechoso et al. 2014). The great variability in the diurnal cycles and the difference in cloud properties in the two regimes raise the question of how meteorological factors affect stratocumulus.

The vertical distribution of cloud properties are shown in Fig. 5. Diurnal cycles of cloud fraction, LWC, and rain mixing ratio are clear, as already seen in Fig. 4. For the eastern regime, the vertical maximum of cloud fraction, LWC, and rain mixing ratio appear at lower height than in the western regime. In addition, the maximum value of cloud fraction is higher than that in the western regime, while the maximum values of LWC and rain mixing ratio are lower than those in the western regime. In both regimes, Nd changes little with time and height (around 50 mg−1 throughout the simulation), while re increases vertically (up to 18 μm at cloud top). Note that Nd and re are averaged over cloudy grids at each height; thus, they might not show strong diurnal cycles. The Nd values are similar in both regimes because the initial aerosol distribution is spatially homogeneous in this study. The cloud-top re is also similar between the two regimes, with the re in the western regime a little higher. This is because droplets can grow bigger in thicker clouds in the western regime. The results indicate that cloud microphysical properties do not show diurnal cycles and do not show much difference between the western and eastern regimes. This implies that cloud microphysical properties are not very sensitive to the different meteorological conditions in the diurnal cycle and in the two regimes but may be dominated by the same aerosol condition in the simulation. The reasons for the strong diurnal cycles in cloud macrophysical properties such as cloud fraction, LWC, cloud-top height, cloud-base height, and precipitation, and the reasons for the significant difference in cloud macrophysical properties between the two regimes will be explained below. Note that in our study, aerosols are distributed homogeneously in space. The difference in cloud macrophysical properties between the eastern and western regimes would likely be larger if aerosol concentration decreases from the coast to the open ocean.

Fig. 5.
Fig. 5.

Simulated vertical distributions of cloud properties in (left) western and (right) eastern regimes from 0900 LT 18 Oct to 0900 LT 19 Oct. (a),(b) Cloud fraction; (c),(d) LWC; (e),(f) rainwater mixing ratio; (g),(h) droplet number concentration Nd; and (i),(j) droplet effective radius re. The cloud fraction at each height is the fraction of cloudy grids in the domain at that height. LWC and rainwater mixing ratio are averaged over cloudy columns. The Nd and re values are averaged over cloudy grids at each height. The local time refers to the time at the place where the research aircraft took off and landed. Aerosol mixing ratio is 200 mg−1.

Citation: Journal of the Atmospheric Sciences 73, 2; 10.1175/JAS-D-15-0101.1

The domain-averaged profiles of potential temperature, water vapor mixing ratio, and relative humidity (RH) are shown in Fig. 6. It is well known that the capping inversion layer above the boundary layer limits cloud vertical development and, therefore, limits the cloud-top height. The inversion height is defined as the height with the biggest gradient of potential temperature in this study, as shown by the small red lines in Fig. 6. This is also the height where water vapor mixing ratio has the biggest gradient, as also pointed out in Bretherton et al. (2010). Compared to the western regime, the eastern regime has a lower inversion height that is caused by stronger downward branches of both Hadley and Walker circulation and cooler SST (e.g., Wood and Bretherton 2004; Leon et al. 2008; Zuidema et al. 2009). Therefore, the cloud-top height is lower in the eastern regime. The temperature within the boundary layer in the eastern regime can be 1 K lower than that in the western regime, especially at night. This is induced by the cooler SST in the eastern regime. At the same time, water vapor mixing ratio within the boundary layer is similar in the two regimes. The result is that the eastern regime has higher RH within the boundary layer, leading to lower cloud-base height and higher cloud fraction, compared to the western regime (Fig. 5). Meanwhile, the eastern regime has a more coupled boundary layer (Jones et al. 2011), which might also contribute to the lower cloud-base height and higher cloud fraction. However, clouds in the eastern regime are thinner and, thus, have lower LWP and precipitate less, as already shown in Fig. 3. It should be pointed out that the differences in LWC and cloud fraction in the two regimes may lead to differences in the entrainment rates and boundary layer developments, which in turn can lead to differences in cloud-top height in the two regimes. However, this kind of feedback is not the focus of this study and therefore is not discussed here.

Fig. 6.
Fig. 6.

Profiles of the simulated meteorological properties in western and eastern regimes from 0900 LT 18 Oct to 0900 LT 19 Oct with intervals of 6 h. (top) Potential temperature, (middle) water vapor mixing ratio, and (bottom) RH. All properties are averaged over the finest domain. The time shown in the figure is the local time at the place where the research aircraft took off and landed. Aerosol mixing ratio is 200 mg−1. Red lines indicate the inversion layer heights.

Citation: Journal of the Atmospheric Sciences 73, 2; 10.1175/JAS-D-15-0101.1

The diurnal cycles are also shown in the vertical profiles. In both regimes, the inversion height increases at night and early morning and decreases in the afternoon. For example, in the western regime, at 0900 LT 18 October, the inversion height is about 1160 m, which can be seen in the profiles of potential temperature, water vapor mixing ratio, and RH. From 0900 to 2100 LT October 18, the inversion height decreases from 1160 to 950 m. From 2100 LT 18 October to 0900 LT 19 October, the inversion height increases back to a higher height. The significant diurnal cycle of the inversion height in the western regime can explain the diurnal cycle of the cloud-top height in Fig. 4c. In the eastern regime, the inversion height is 950 m at night and early morning and 890 m in the afternoon. This weaker diurnal cycle of the inversion height in the eastern regime leads to weaker diurnal cycle of cloud-top height, as seen in Fig. 4c. The potential temperature, water vapor mixing ratio, and RH in the boundary layer also have diurnal cycles. The potential temperature and water vapor mixing ratio decrease at night and early morning and increase in the afternoon. RH increases at night and early morning and decreases in the afternoon because temperature dominates RH in this case. This explains the diurnal cycles of the cloud-base height, cloud fraction, and LWP in Fig. 4. In addition, the boundary layer becomes less coupled during the daytime and more coupled at night, which may be another reason for the diurnal cycle of cloud fraction, as suggested by Medeiros et al. (2012).

c. Aerosol effect

In this part, aerosol mixing ratio is increased to 2000 mg−1 for investigating aerosol effects in the two regimes. As shown in Table 3 and Fig. 7, aerosol effects are stronger in the western regime than in the eastern regime. In the western regime, cloud fraction increases for about 0.09 and LWP increases for about 26 g m−2 with increased aerosols. Precipitation rate decreases from 0.11 to 0.036 mm day−1 because of aerosols. The fact that cloud fraction increases with aerosols is consistent with the second aerosol indirect effect proposed in previous study (e.g., Albrecht 1989). Precipitation suppression by aerosols means that less cloud water is removed from clouds and, therefore, leads to increases of LWP and cloud fraction. However, the aerosol effect on cloud thickness is not obvious in both regimes. For the eastern regime, precipitation rate decreases from 0.039 to 0.007 mm day−1. It is seen in Fig. 7 that aerosol effects on cloud fraction and LWP are weaker in the eastern regime, possibly because precipitation is weak in this regime.

Table 3.

Daily average cloud fraction, LWP, cloud-top height, cloud-base height, cloud thickness, rain rate, Nd, and cloud-top re for the polluted condition in the western and eastern regimes. The difference of the daily average between the polluted and clean conditions is also shown.

Table 3.
Fig. 7.
Fig. 7.

Time evolution of the simulated cloud properties in western and eastern regimes from 0900 LT 18 Oct to 0900 LT 19 Oct. (a) Cloud fraction; (b) LWP; (c) cloud thickness; and (d) surface precipitation rate. All properties except cloud fraction are averaged over cloudy columns. The differences between red and black lines are changes caused by increasing aerosol number mixing ratio to 2000 mg−1. The local time refers to the time at the place where the research aircraft took off and landed.

Citation: Journal of the Atmospheric Sciences 73, 2; 10.1175/JAS-D-15-0101.1

It is also noticeable that the aerosol effects on cloud macrophysical properties and precipitation are weaker than the change in diurnal cycles in both regimes, which is clearly shown in Tables 2 and 3. This is consistent with the finding by Andrejczuk et al. (2014). Aerosol effects are also weaker than the spatial variability between the two regimes with different meteorological conditions. This raises the question to what extent aerosol can affect clouds, especially stratocumulus, which has strong diurnal cycles and great spatial extent.

The vertical distribution of cloud properties for an aerosol mixing ratio of 2000 mg−1 are shown in Fig. 8. Note that Figs. 8a–f show the differences of cloud fraction, LWC, and rain mixing ratio between the 200 and 2000 mg−1 aerosol scenarios, while Figs. 8g–j show the cloud-grid-averaged Nd and re for the 2000 mg−1 aerosol condition. Cloud fraction and LWP are increased by aerosols, but not significantly, although precipitation is significantly suppressed (Fig. 8e). As shown in Figs. 8g and 8i and Tables 2 and 3, Nd increases from 49 to 320 mg−1 and the cloud-top re decreases from 17 to 9.1 μm by aerosols. In the eastern regime, aerosols have an even weaker effect on cloud fraction and LWC compared to the western regime but have strong effect on Nd and re as well. Therefore, in both regimes, precipitation and cloud microphysical properties such as Nd and re are very sensitive to aerosols; cloud macrophysical properties such as cloud fraction and LWP are affected by aerosols to some degree, but aerosol effects are not as big as the difference in the two regimes and the variations in the diurnal cycles.

Fig. 8.
Fig. 8.

Simulated vertical distributions of cloud properties in (left) western and (right) eastern regimes from 0900 LT 18 Oct to 0900 LT 19 Oct. The differences of (a),(b) cloud fraction; (c),(d) LWC; (e),(f) rainwater mixing ratio between polluted and clean conditions; and absolute values of (g),(h) Nd and (i),(j) re. The local time refers to the time at the place where the research aircraft took off and landed. Aerosol mixing ratio is 2000 mg−1.

Citation: Journal of the Atmospheric Sciences 73, 2; 10.1175/JAS-D-15-0101.1

4. Summary and conclusions

This study investigates the relative effects of meteorological factors and aerosols on marine stratocumulus properties, including cloud fraction, LWP, LWC, cloud-top height, cloud-base height, Nd, and re. The mesoscale model WRF with a numerical statistical cloud microphysics scheme is used. The study divides the finest model domain into two regimes that have different meteorological conditions. The western regime has a deeper boundary layer and the eastern regime has a shallower boundary layer. Cloud properties in the two regimes are analyzed separately.

It is shown that, in both regimes, especially in the western regime, stratocumulus properties have significant diurnal cycles. In the western regime, the daily maximum (at night and early morning) of cloud fraction is 0.83 and daily minimum (in the afternoon) is about 0.29; LWP in the western regime is up to 204 g m−2 at night and decreases to 75 g m−2 in the afternoon; and precipitation can be as high as 0.35 mm day−1 and only occurs at night and early morning.

Stratocumulus properties also show a much difference between the two regimes under the same aerosol condition. Compared to the western regime, the eastern regime has higher cloud fraction (by 0.11), lower LWP (by 14 g m−2), and lower cloud-top and lower cloud-base heights. Precipitation in the eastern regime is also less than one-third of that in the western regime. The maxima of cloud fraction, LWC, and rain mixing ratio in the eastern regime exist at lower heights than in the western regime. The different cloud properties in the two regimes are strongly determined by the different meteorological conditions. The eastern regime has lower inversion height as a result of both the stronger downward branches of both Hadley and Walker circulations and cooler SSTs and, therefore, has lower cloud-top height. The eastern regime has higher RH owing to the cooler surface and similar water vapor mixing ratio and more coupled boundary as well when compared to the western regime. Therefore, the eastern regime has higher cloud fraction and lower cloud-base height. However, the thinner clouds in the eastern regime have lower LWP and, therefore, less precipitation.

This study also investigates aerosol effects on stratocumulus in the two regimes. On one hand, aerosol effects on cloud microphysical properties are very strong in both regimes. Increasing aerosol mixing ratio from 200 to 2000 mg−1 can greatly increase Nd, decrease re, and suppress precipitation. On the other hand, aerosol effects on cloud macrophysical properties (cloud amount, LWP) are small in both regimes. Aerosol effects are even weaker in the eastern regime compared to the western regime. This is possibly because the eastern regime has less precipitation, and adding aerosols can have a weaker regulation on stratocumulus amount and LWP through precipitation suppression. It is quite obvious that the change in cloud amount and LWP induced by aerosols is smaller than the changes in diurnal cycles and the spatial variation in the two regimes.

Acknowledgments

This project is supported by Chinese 973 program under Grant 2013CB955803 and Chinese NSF Grant 41275144. The research is also supported by a grant from the Office of Science (BER), U.S. DOE. Zhe Li acknowledges Chinese Scholarship Council for a visiting student scholarship at the University at Albany, State University of New York. The authors acknowledge NCAR/EOL under sponsorship of the National Science Foundation (http://data.eol.ucar.edu/) for providing data of C130 during the VOCALS campaign. We also thank the three anonymous reviewers for very helpful suggestions and comments that greatly improved the manuscript.

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