1. Introduction
Marine stratocumulus (Sc) significantly alters Earth’s radiative budgets at both the surface and the top of the atmosphere (Hartmann et al. 1992; Hahn and Warren 2007; Wood 2012). The Sc strongly interacts with the sea surface via exchanges of heat, moisture, and momentum, forming a coupled Sc–surface system commonly known as the stratocumulus-topped planetary boundary layer (STBL). The earliest credible description of the STBL physics is Lilly’s (1968) mixed-layer model. The model treats the column of air from the surface to the top of Sc as a well-mixed bulk layer and parameterizes basic cloud physics and fluxes (i.e., energy, moisture, and mass). The model succeeds in explaining a series of important behaviors of STBL over the subtropical oceans such as the STBL response to large-scale environment (Schubert et al. 1979a,b; Wakefield and Schubert 1981; Stevens 2006), the STBL decoupling during the cloud regime transition (Bretherton and Wyant 1997; Zheng et al. 2020), diurnal cycle (Caldwell et al. 2005; Zhang et al. 2005), dominant time scales (Jones et al. 2014), slow manifold behavior (Bretherton et al. 2010), and aerosol influences on Sc (Wood 2007; Caldwell and Bretherton 2009; Uchida et al. 2010).
The mixed-layer model becomes invalid if the STBL stably stratifies, a phenomenon widely known as STBL decoupling (Nicholls 1984). The decoupling physics can be understood from the perspective of boundary layer energetics. In a well-mixed STBL over cold water, air parcels entrained from the overlying inversion are cooled by thermal radiation at the cloud top, sinking through the boundary layer. This well-mixed state is sustained by a rough balance between entrainment warming and radiative cooling in the upper part of the STBL. When the warming outweighs the cooling, the entrained warm air parcels are too light to sink, leading to the stable stratification of the boundary layer. Examples include the decoupling during the subtropical stratocumulus-to-cumulus transition due to enhanced entrainment warming (Bretherton and Wyant 1997), decoupling by precipitation that warms the cloud layer (Nicholls 1984; Stevens et al. 1998), and daytime decoupling by solar insolation that weakens cloud-top radiative cooling (Nicholls and Leighton 1986; Zheng et al. 2018).
The above decoupling mechanisms have been studied in subtropical conditions where the trade winds advect the STBL toward the equator with warmer surfaces. The cold-air advection builds up the potential energy of the environment so that the decoupled STBLs are typically conditionally unstable. This allows for the development of cumulus (Cu) that often penetrates the Sc decks, forming Cu-coupled STBLs. In such a cloud regime, the Sc can interact with the surface through the conduits of the Cu convection so that whether or not to call the boundary layer “decoupled” has been controversial (Miller and Albrecht 1995; Stevens et al. 1998; Goren et al. 2018; Zheng et al. 2018; Zheng and Li 2019).
To reconcile the controversy, Zheng et al. (2020) added a new dimension, namely, low-level temperature advection, to the problem. Zheng et al. (2020) considered the coupling state of STBL in a spectrum of low-level temperature advection ranging from the extremely cold-air advection such as cold-air outbreaks to the warm-air advection in the warm sector of midlatitude cyclones. The STBLs embedded in cold-air advection flows are either fully coupled (i.e., well mixed) or Cu coupled. The unambiguously decoupled STBLs predominantly occur in warm-air advection conditions where the stable stratification is sufficiently strong to prohibit the cumulus coupling. This view is supported by ground-based observations from the Southern Ocean, northeast subtropical Pacific, and northeast Atlantic (Zheng et al. 2020). These observations show that, as the low-level flow shifts from cold to warm-air advection, the boundary layer turns from a Cu-coupled STBL to a considerably stably stratified STBL without Cu coupling (i.e., unambiguously decoupled STBL) (see the schematic diagram of Fig. 4 in Zheng et al. 2020).
Poorly understood is the unambiguously decoupled STBLs experiencing warm advection. In contrast to Cu-coupled STBLs, typical at subtropics, the STBLs under warm advection conditions receive scarce attention despite their potential abundance in midlatitudes1 (Agee 1987; Fletcher et al. 2016; Wall et al. 2017; Scott et al. 2020). This motivates the current study. In addition to testing the hypothesis that unambiguously decoupled STBLs are more likely to occur in warm-air advection conditions than the cold ones, we aim to elucidate the physics of STBL response to warm advection using idealized large-eddy simulations. By the “idealized,” we mean simulating an STBL over a doubly periodic domain with the sea surface temperature (SST) decreasing over time to mimic the influences of warm-air advection. This idealized setup is the same as the conventional LES studies of Sc-to-Cu transitions (Sandu and Stevens 2011; Van der Dussen et al. 2013; Bretherton and Blossey 2014), in which the SST increases over time. Such consistency allows for direct comparisons.
In addition to further the understanding of decoupling dynamics, another motivation is a lack of consensus on the role of horizontal temperature advection on low cloud radiative effects. Prior observations show that marine low clouds are considerably fewer and thinner under warmer air advection conditions (Norris and Iacobellis 2005; Myers and Norris 2015; Klein et al. 2017; Scott et al. 2020). Their interpretation is that the warm-advection-induced decoupling leads to less moisture supply from the sea surface to the clouds, thereby thinning the clouds. Contrasting pieces of evidence, however, exist. For example, Zheng and Li (2019) found that clouds can be very persistent even if they are decoupled from the sea surface under warm advection conditions, as shown by geostationary satellite images and ship-based remote sensing data. This finding is consistent with Goren et al. (2018), who found that precipitating marine clouds are more persistent in decoupled STBLs than coupled ones. Moreover, some studies show no statistically significant dependence of low cloud radiative effects on temperature advection in climate models (D. McCoy 2020, personal communications) and ground-based observations over midlatitude oceans (Naud et al. 2020). The mixed lines of evidence suggest a lack of understanding of the mechanism underlying the low-cloud response to warm-air advection.
In summary, this two-part study attempts to elucidate the physical mechanisms of warm-advection-induced decoupling (Part I) and its control on low-cloud radiative effects (Zhang et al. 2021, manuscript submitted to J. Atmos. Sci., hereafter Part II) by using idealized large-eddy simulations. Part I is dedicated to decoupling dynamics whereas Part II focuses on its implications for the low cloud feedback. Although the warm-air advection is our focus, our analyses are centered on comparing the results of warm-air advection with the cold-air advection (as the benchmark). This enables a clearer presentation of the new insights in the context of conventional knowledge. The next section introduces the LES model and the experiments. Section 3 shows the results, followed by the discussion and concluding remarks.
2. Large-eddy simulations
a. Model and case descriptions
We use the System for Atmospheric Modeling (SAM) model, version 6.11.3 (Khairoutdinov and Randall 2003). SAM uses liquid water static energy (hl), total nonprecipitating water mixing ratio (qt), and total precipitating water mixing ratio as prognostic thermodynamic scalars. We use the advection scheme developed by Smolarkiewicz and Grabowski (1990), the 1.5-order prognostic subgrid-scale model, a simplified (drizzle only) version of Khairoutdinov and Kogan’s (2000) microphysics scheme and RRTMG radiation (Iacono et al. 2008). Surface fluxes of temperature, moisture, and momentum are calculated by similarity theory.
We use a horizontal grid spacing of 35 m in a doubly periodic domain with a size of 42002 m2. We chose such a small domain size purely for computational efficiency. It should be too small to represent mesoscale convective circulation typical for precipitating STBLs. The STBLs studied here are weakly precipitating so that the influence of mesoscale dynamics should be minor. This is confirmed by a sensitivity test for a larger domain of 84002 m2 that yields nearly identical results (see the online supplementary material). The vertical grid spacing is set as 5 m in the cloud and inversion layer to resolve entrainment. The grid spacing stretches above ∼2400 m until the domain top of ∼4200 m, which is high enough for gravity wave damping. There is a total of 512 vertical grids. Previous studies suggest that the LES-simulated entrainment is less realistic for coarse vertical grids (Mellado 2017; Mellado et al. 2018). To examine whether a vertical grid spacing of 5 m is enough, we conduct a sensitivity test by changing the vertical grid size from 5 to 3 m, showing little sensitivities (supplementary material).
The base case for our simulations is the case from the Atlantic Stratocumulus Transition Experiment (ASTEX) (Albrecht et al. 1995). The ASTEX case has been a benchmark for LESs of the Sc-to-Cu transitions (Van der Dussen et al. 2013). The initial profiles are shown in the supplementary material. A unique aspect of the ASTEX case is that observations from an aircraft and balloons are “Lagrangian” for they follow the evolution of STBL air mass. This is particularly important for simulating the STBL response to horizontal temperature advection, for which the SST evolution along the airmass trajectory is the key driver. During the ASTEX, the SST increases by ∼4 K over the 40-h simulation of the ASTEX case. Such an increase in SST is widely regarded as the determinant driver of the cloud regime transition.
As stated in the introduction, we use a cold-air advection case as a benchmark for understanding the role of warm advection. To that end, we conduct two idealized experiments by simplifying the forcing of the original ASTEX case (Fig. 1). In the first experiment, we linearize the SST increase rate, yielding an SST increasing rate of 2.6 K day−1 (named “CADV”). The linearized CADV case well reproduces the evolution of the original ASTEX case [see Fig. 1 in Zheng et al. (2021)]. In the second experiment, we decrease the SST by 2.6 K day−1 to mimic the influence of warm-air advection (named “WADV”). To remove the influence of diurnal cycle, we set the solar zenith angle as the diurnal average of 68.72°. All other initial and forcing conditions are the same (Van der Dussen et al. 2013).
Time evolution of the sea surface temperature in the two simulations.
Citation: Journal of the Atmospheric Sciences 78, 12; 10.1175/JAS-D-21-0108.1
The WADV run is highly idealized. In the real world, the low-level horizontal temperature advection strongly couples with other synoptic variables. For example, warm-air advection is typically coincident with large-scale ascent motions whereas cold-air advection is more likely to occur in a subsiding atmosphere (Holton 1973; Norris and Klein 2000; Zheng et al. 2020). In that regard, it is unrealistic that the CADV and WADV start with the same initial conditions and experience the same large-scale forcing. But the purpose of this study is not to reproduce the real-world STBLs, but to understand the most essential physics behind the problem. All the existing hypotheses for STBL response to warm-air advection are centered on the stabilization effect of warm advection as the most determinant process (Norris and Iacobellis 2005; Klein et al. 2017; Scott et al. 2020). In other words, our current level of understanding does not allow for formulating a hypothesis sophisticated enough to account for every aspect of the problem. Thus, we consider our simulations a starting point for future more realistic numerical explorations.
b. Diagnostic statistics
With the
We determine the lifting condensation level (LCL) using the exact analytic formula developed by Romps (2017). The entrainment rate (we) is determined using the boundary layer mass budget equation: we = dzi/dt − wsub, in which the wsub is the large-scale subsidence rate at the boundary layer top.
3. Results
a. Time evolution
Figures 2 and 3 show the time evolution of selected outputs, which illustrate many characteristics of the STBL under the influence of warm-air advection. The warm-air advection substantially suppresses the surface latent and sensible heat fluxes (Figs. 2a,b). This lowers the turbulence level of the boundary layer, weakens the entrainment near the boundary layer top (Fig. 2d), and slows the deepening (or even shallowing) of the boundary layer (Fig. 2c). Such a contrast in surface fluxes, as will be evident later, is the most essential factor explaining most of the differences between the two simulations.
Time series of key variables of experiments CADV (blue) and WADV (red): (a) surface latent heat flux, (b) surface sensible heat flux, (c) main inversion height, (d) entrainment rate, (e) ΔBLhl/cp, (f) ΔBLqt, (g) sea surface temperature minus near-surface air temperature, and (h) EEW [Eq. (2)].
Citation: Journal of the Atmospheric Sciences 78, 12; 10.1175/JAS-D-21-0108.1
Time–height plots of key variables of experiments (left) CADV and (right) WADV. The black solid line, black dashed line, and gray dashed line are cloud-top height, cloud-base height, and lifting condensation level, respectively.
Citation: Journal of the Atmospheric Sciences 78, 12; 10.1175/JAS-D-21-0108.1
Figures 3a and 3b show the time–height plots of the cloud fraction for the two runs. The CADV presents a textbook-like Sc-to-Cu transition whereas the WADV shows a solid Sc deck persistent throughout the simulation. The persistence is primarily due to the weak entrainment drying, discussed in detail in Part II. Because the focus of this study is the boundary layer decoupling, we look at time evolution of hl and qt profiles (Figs. 3c–f). Both regimes show increasingly stably stratified boundary layers, but their geometries of stratification differ greatly, which can be more clearly seen from the sounding at a selected time of t = 30 h (Fig. 4). In CADV, the boundary layer is stratified into two well-mixed layers: the upper cloud-containing layer driven by radiative cooling and the bottom layer driven by surface heating. These two layers are separated by a weakly stratified layer. In WADV, however, the stratification concentrates near the surface, as seen from a well-defined temperature inversion in the lowest quarter of the boundary layer. Above the inversion is a well-mixed cloud-containing layer. The convection in this mixed layer is driven by cloud-top radiative cooling, suggested by the top-heavy structure of vertical velocity variance (Figs. 3h and 4c) and the negative vertical velocity skewness (Fig. 3j), an indicator of top-driven convection (Moeng and Rotunno 1990).
Profiles of (a) hl/Cp, (b) qt, and (c) vertical velocity variance for CADV (blue) and WADV (red) at t = 30 h. Ticks at the bottom of (a) are the sea surface temperatures.
Citation: Journal of the Atmospheric Sciences 78, 12; 10.1175/JAS-D-21-0108.1
Time series of the three EEW components in CADV (solid) and WADV (dashed).
Citation: Journal of the Atmospheric Sciences 78, 12; 10.1175/JAS-D-21-0108.1
Given that the entrainment cannot explain the decoupling in WADV, the near-surface cooling is the dominant decoupling factor. To understand what drives the near-surface cooling in WADV, we analyze the budgets of
Time–height plots of (a) total heating rate, (b) heating rate due to turbulence, (c) heating rate due to radiation, and (d) heating rate due to turbulence and radiation for WADV.
Citation: Journal of the Atmospheric Sciences 78, 12; 10.1175/JAS-D-21-0108.1
The thin layer of turbulent warming can be explained by the turbulence adjustment to the near-surface radiative cooling (Fig. 6c). What causes the abnormally large radiative cooling near the surface? According to the conventional knowledge about radiative transfer, we know that atmospheric radiative cooling has three contributing components: 1) exchange of radiative energy with underlying atmosphere, 2) exchange of radiative energy with overlying atmosphere, and 3) radiative energy escaping to space. In a typical atmosphere where temperature decreases with altitude, the first two components roughly cancel each other, leaving the “cooling-to-space” component the dominant one (Petty 2006). This is not the case here for the air near the surface: both the overlying and underlying air masses are cooler (Fig. 4a). Thus, exchanges of radiative energy in both directions cause loss of energy, considerably increasing the radiative cooling. Such a local cooling induces local convergence of turbulent flux as an adjustment process (Edwards 2009).
The aggregate role of the radiation and turbulence,
In summary, the stable stratifications of STBLs in CADV and WADV are explained by entrainment-induced warming and near-surface cooling (by turbulence and radiation), respectively. These two decoupling mechanisms can be conceptualized into a decoupling dipole: top-warming-driven versus bottom-cooling-driven decoupling.
b. The already decoupled phase
We have discussed processes leading to the decoupling in both regimes. Now we characterize the turbulent properties of STBLs in their already decoupled phases. Strictly speaking, there is no such thing as an equilibrium phase in our simulations because the SST keeps evolving and the STBL keeps responding. Here, we take model outputs at t = 30 h as representations of already decoupled STBLs for the two regimes. One justification for selecting t = 30 h is that the stratification degree at CADV already saturates at t = 30 h, suggesting a quasi-equilibrium state (Fig. 2e). In WADV, the STBL is still stratifying, but the qualitative characteristics of the STBL (e.g., thermodynamic structure, turbulence, and cloud properties) remain similar throughout the simulations. Selecting different times of the WADV run does not influence the main conclusion of this paper.
We first look at the three-dimensional (3D) visualization of the STBLs at t = 30 h (Fig. 7). To more clearly visualize the cloud–surface decoupling, we show the surface plots of the near-surface qt, defined as the top 1% of qt in the vertical (dark red surface). The CADV regime is characterized by intermittent Cu clouds penetrating the Sc deck, known as the Cu-coupled STBL. The contour of the near-surface qt extends vertically from the surface to the base of Cu. Through the conduit of Cu, the water from the sea surface feeds into the Sc deck. Such a feeding effect is absent in WADV. In WADV, there is only a single layer of solid Sc deck, completely separate from the surface humid air trapped near the surface. We provide movies of 2D fluid visualization for the two runs to aid in intuitively understanding the results (see animations 1 and 2 in the supplemental material).
Three-dimensional visualizations of cloud liquid water content at t = 30 h for the (a) CADV and (b) WADV experiments. The red surfaces are the contours of the top 1% qt in each column.
Citation: Journal of the Atmospheric Sciences 78, 12; 10.1175/JAS-D-21-0108.1
Such a difference in the cloud–surface interaction is augmented by vertical velocity fields at different levels. Figure 8 shows the vertical velocity at z = 10 m (left), z = 0.5zb (center), and z = zb (right). The turbulent flow near the surface of the CADV regime is relatively elongated, consistent with the typical flow structure in convective boundary layers (Moeng and Rotunno 1990). In WADV, however, the flow is more random with a less evident elongated pattern, typical for stratified flows (Mahrt 2014). At z = 0.5zb in the CADV, small patches of isolated updrafts (blobs of red colors) start to emerge. These updraft regions are more humid than the surrounding regions. This pattern resembles the typical “cumulus-like” convection: moist, narrow, and strong updrafts surrounded by drier, wider, and weaker subsidence (Bjerknes 1938). This is further supported by the positive skewness of vertical velocity, characteristic of surface-driven convection (Fig. 8h). In WADV, however, the “cumulus-like” convection is absent, as seen from a lack of concentrated updrafts. The skewness of vertical velocity is negative (Fig. 8h), suggesting a dominance of top-cooling-driven turbulence (Wyngaard 1987; Moeng and Rotunno 1990). Such a contrast in turbulence regime persists at z = zb.
Vertical velocity field at (left) z = 10 m, (center) z = 0.5zb, and (right) z = zb for the (a)–(c) CADV and (d)–(f) WADV. (g)–(i) The probability distribution functions of the vertical velocity for the two experiments. In (b), (c), (e), and (f), black contours correspond to the top 10% qt in each horizontal layer.
Citation: Journal of the Atmospheric Sciences 78, 12; 10.1175/JAS-D-21-0108.1
The flow visualizations (Figs. 7 and 8) suggest two distinctive convection regimes: surface-heating-driven cumulus-like convection for CADV versus top-cooling-driven stratocumulus-like convection for WADV. Such a difference can be more directly seen by conditionally sampling the parcels in rising (w > 0) and sinking motions (w < 0) (Fig. 9a). Figure 8a shows that the vertical velocity variance is considerably stronger for updrafts than downdrafts in CADV, suggesting a more determinant role of updrafts in driving the vertical mixing, whereas the opposite is true for WADV. Note that the cloud-top radiative cooling still contributes to driving the convection in the CADV, as seen from the local maxima of vertical velocity variance in the upper Sc layer. But even in such a Sc layer, the updrafts contribute more to the turbulence via penetration of the Cu convection.
Vertical profiles of (a) resolved vertical velocity variance, (b) moisture flux, (c) heat flux, and (d) buoyancy flux of updrafts (blue) and downdrafts (orange) for (left) CADV and (right) WADV. Horizontal black and gray dashed lines mark the base heights of stratocumulus decks and LCL, respectively.
Citation: Journal of the Atmospheric Sciences 78, 12; 10.1175/JAS-D-21-0108.1
The relative strength of updrafts and downdrafts makes a substantial difference to how heat and moisture are transported in the vertical (Figs. 9b,c). In CADV, the vertical transport of moisture is realized by updrafts that carry humidity from the sea surface upward, feeding the Sc deck (Fig. 9b). In contrast, in the WADV, the downdrafts play a more dominant role in the vertical exchange of moisture: downdrafts transport entrained dry air toward the surface. At z = zb of WADV, the supply of moisture via updrafts is close to zero, meaning that the Sc deck almost entirely decouples from the source of humidity from below.
A similar conclusion can be drawn from the heat flux (Fig. 9c). The heat flux profile is relatively more complex due to the influences of diabatic heating/cooling (i.e., radiation and precipitation) to which the turbulent flux must adjust (Stevens et al. 1998). Hence we focus on the subcloud layer where the diabatic heating/cooling is minimal. Both regimes show a downward transport of heat, but the transport in CADV is realized by updrafts, whereas, in WADV, the downdrafts drive the downward transports of warm entrained air.
In addition to the profiles of heat and moisture fluxes, it is informative to look at the buoyancy flux that dictates boundary layer energetics (Fig. 9d). In CADV, the buoyancy flux is mostly positive except near the LCL. Such a structure of buoyancy profile is consistent with the conventional wisdom based on the argument of hypothetical parcel trajectory [see Bretherton (1997) for details]. Again, the updrafts dominate the positive buoyant flux (less dense air rises), converting the potential energy of the environment to turbulent kinetic energy. Such a large buoyancy flux for updrafts is largely contributed by the water vapor. As seen in Fig. 9c, the heat flux for updrafts is negative throughout most of the boundary layer, which suggests cooler air ascending. The buoyancy of the ascending cool air stems from the concentration of water vapor, as seen from the strong qt flux in updrafts (Fig. 9b). In WADV, however, the cloud layer and subcloud layer exhibit opposite signs. In the cloud layer, the buoyancy flux is positive, contributed by both updrafts and downdrafts through latent heating and diabatic cooling, respectively. The downdrafts, again, contribute more. In the subcloud layer, the buoyancy flux is slightly negative. Such a dipole-like geometry of buoyancy flux profile resembles that of the heat flux (Fig. 9c), suggesting the contribution of buoyancy from water vapor is insignificant, especially in the subcloud layer.
So what drives the downward motion of the warm air if the water vapor effect does not contribute? From the perspective of the heat budget constraint, the warm air must descend somewhere in the subcloud layer in order to transfer heat from the atmosphere into the sea surface, a necessary consequence of WADV (warm air overlying cold surface). Then what are the underlying mechanisms? We explain it using the argument from Schubert et al. (1979a), who stress the role of the pressure field. The central idea is that the pressure gradient force propels the air overturning, transferring the warm air downward to the top of the surface stable layer. The warm air mass at the top of the surface stable layer is eventually delivered to the surface by preexisting TKE (e.g., mechanically driven). The effect of pressure transport can be more clearly illustrated by the
Vertical profiles of
Citation: Journal of the Atmospheric Sciences 78, 12; 10.1175/JAS-D-21-0108.1
c. On the formation of double-layer stratiform clouds
From observations, under warm-air advection conditions, often found are double-layer stratiform clouds, with the upper layer capped by the major temperature inversion and the lower layer close to the surface, often manifested as fog (Zheng et al. 2020; M. Smalley and S. Klein 2020, personal communications). It is, thus, important to understand why our WADV experiment does not develop a stratus near surface.
A hypothesis that naturally arises is that, in the WADV run, the near-surface temperature inversion is not sufficiently strong to sustain high humidity (by trapping water vapor within it). To test this hypothesis, we run additional simulations by altering the forcing parameters for the WADV. First, we double the Tadv from 2.6 to 5.2 K day−1, denoted as “WADV5.2.” The expectation is that if the SST cools rapidly enough, the near-surface inversion may be strong enough to form fogs. Second, we decrease the large-scale divergence from 5 × 10−6 to 3 × 10−6, denoted as “WADV Div3.” We expect that, for weaker subsidence, the boundary layer deepens more rapidly, enhancing the warming of the upper boundary layer, which strengthens the near-surface temperature inversion.
Figure 11 shows the cross sections of cloudiness of the two experiments. A double-layer stratiform cloud emerges in the WADV Div3, but not in WADV5.2 (only a tiny number of small clouds below the Sc deck). The bottom panel of Fig. 11 shows the sounding at t = 30 h. The filled circles mark the heights of the near-surface temperature inversion, zli, determined as the level of the local maxima of liquid water potential temperature variance (Yamaguchi and Randall 2008). We find that both new experiments generate stronger near-surface inversions than the WADV (Fig. 11c), consistent with our expectations. However, a strong temperature inversion does not necessarily increase the qt: relative to WADV, the qt within the inversion is higher in WADV Div3, but lower in WADV5.2 (Fig. 11d). For this reason, the WADV5.2 does not develop enough high RH to form a cloud (Fig. 11e).
Time–height plots of cloud fraction for (a) WADV5.2 and (b) WADV Div3, and vertical profiles of (c) hl/Cp, (d) qt, and (e) relative humidity for the WADV, WADV5.2, and WADV Div3. The solid dots mark the zli.
Citation: Journal of the Atmospheric Sciences 78, 12; 10.1175/JAS-D-21-0108.1
To understand what drives the difference in the qt, we consider the atmosphere from the surface to the zli as a bulk layer and take the
Time series of (a)
Citation: Journal of the Atmospheric Sciences 78, 12; 10.1175/JAS-D-21-0108.1
In summary, weaker subsidence favors the emergence of double-layer stratiform clouds because weaker subsidence allows for more rapid boundary layer deepening, which warms the upper boundary layer, enhancing the near-surface temperature inversion. The stronger near-surface temperature inversion traps the moisture within, eventually elevating the RH to unity. Stronger warm advection (i.e., more rapid sea surface cooling) does not necessarily favor the formation of such secondary stratus because a cooler sea surface facilitates the downward transport of moisture from the atmosphere into the sea. This acts to dry the near-surface air, preventing the formation of clouds. This argument may become less tenable when the surface cooling is strong enough to significantly change the transport behavior.
4. Summary
We have investigated the response of a stratocumulus-topped boundary layer (STBL) to a cooling sea surface by using idealized large-eddy simulations. The decreasing sea surface temperature mimics the influence of low-level warm-air advection (WADV). In addition to characterizing the basic turbulence structure of the boundary layer in WADV, we are particularly interested in testing an unproven hypothesis: an unambiguous decoupling between stratocumulus clouds and the surface can be achieved in WADV flow, but not in cold advection (CADV) flow because the latter favors cumulus-induced coupling while the former does not (Zheng and Li 2019; Zheng et al. 2020). To examine this argument, we investigate the decoupling physics of an STBL experiencing WADV and compare the results with that in CADV. We found the followings:
An STBL tends to become stably stratified in both WADV and CADV conditions, but their driving mechanism is dramatically different. The stratification in CADV is caused by the enhanced entrainment warming (i.e., the “deepening-warming” theory by Bretherton and Wyant 1997) whereas, in WADV, it is driven by cooling of the bottom boundary layer due to radiative cooling and loss of heat to the sea surface via turbulent transport. The difference in the driving mechanism constitutes a decoupling dipole: top-warming driven versus bottom-cooling driven.
The surface cooling in the WADV condition causes a temperature inversion in the lower boundary layer. Above the inversion is a well-mixed cloud-containing layer whose convection is driven by the cloud-top radiative cooling. This is different from the temperature structure in CADV that has two well-mixed layers separated by a conditionally unstable layer.
The difference in the boundary layer thermodynamics between WADV and CADV significantly alters the turbulence and cloud regimes. Unlike the emergence of cumulus-coupled stratocumulus in CADV, the WADV simulation manifests a single stratocumulus deck that is persistent, horizontally homogeneous, relatively quiet, and unambiguously decoupled from the moisture source of the sea surface. Such a cloud pattern is a consequence of a lack of surface fluxes, leaving the cloud-top cooling the only driver of convection.
Due to the lack of surface fluxes, the buoyancy flux profile in WADV manifests a dipole pattern: positive in the cloud layer and weakly negative in the subcloud layer. This, in combination with the profile of the pressure covariation with the vertical velocity, dictates that the cloud layer does work to the subcloud layer to pump up the air, maintaining the convective circulation. Such a cloud-containing mixed layer, however, cannot extend down to the surface because of the strong near-surface inversion sustained by the surface cooling. This is, again, in contrast to the convective circulation in CADV that is not only driven by cloud-top cooling but also surface heating that propels strong updrafts responsible for the bulk of the heat and moisture transports.
A secondary stratiform cloud (or fog) can form in the lower boundary layer in WADV if the large-scale subsidence weakens. The mechanism is that the STBL deepens more rapidly if the subsidence is weaker. The intrusion of the STBL into warmer free atmosphere weakens the buoyancy jump across the boundary layer top, enhancing the entrainment of overlying warm air into the boundary layer. The warming enhances the temperature gradient between the warm boundary layer and the cold ocean. This strengthens the near-surface temperature inversion, trapping more water vapor within the layer, raising the relative humidity to unity. Interestingly, increasing the cooling rate of sea surface temperature does not necessarily cause the formation of the fog. The reason is that colder sea surface enhances the negative moisture gradient between the air in contact with the sea surface and the overlying air. This causes a more rapid loss of moisture from the near-surface air to the sea, thereby suppressing the fog formation.
Zheng et al. (2020) reported that stratocumulus clouds experiencing warm-air advection occupy more than 25% of the samples of single-layer stratocumulus collected during two midlatitude field campaigns.
Acknowledgments
This study is supported by the Department of Energy (DOE) Atmospheric System Research program (DE-SC0018996). S.-S. Lee is also supported by the National Research Foundation of Korea (NRF) grant funded by the South Korean government (MSIT) (Grant NRF2020R1A2C1003215). The authors acknowledge the University of Maryland supercomputing resources (http://hpcc.umd.edu) made available for conducting the research reported in this paper. We thank Marat Khairoutdinov for maintaining the SAM code and Peter Blossey for helping with setting up the ASTEX case. We thank three anonymous reviewers for their constructive comments. The SAM model code is available at http://rossby.msrc.sunysb.edu/∼marat/SAM.html. The simulation data are available at https://doi.org/10.5281/zenodo.5548436. The codes used to reproduce the results can be obtained from https://github.com/youtongzheng/Zheng_2021_JAS_WADV_part1.
REFERENCES
Agee, E. M., 1987: Mesoscale cellular convection over the oceans. Dyn. Atmos. Oceans, 10, 317–341, https://doi.org/10.1016/0377-0265(87)90023-6.
Albrecht, B. A., C. S. Bretherton, D. Johnson, W. H. Schubert, and A. S. Frisch, 1995: The Atlantic Stratocumulus Transition Experiment—ASTEX. Bull. Amer. Meteor. Soc., 76, 889–904, https://doi.org/10.1175/1520-0477(1995)076<0889:TASTE>2.0.CO;2.
Bjerknes, J., 1938: Saturated-adiabatic ascent of air through dry-adiabatically descending environment. Quart. J. Roy. Meteor. Soc., 64, 325–30.
Bretherton, C. S., 1997: Convection in stratocumulus-topped atmospheric boundary layers. The Physics and Parameterization of Moist Atmospheric Convection, Springer, 127–142.
Bretherton, C. S., and M. C. Wyant, 1997: Moisture transport, lower-tropospheric stability, and decoupling of cloud-topped boundary layers. J. Atmos. Sci., 54, 148–167, https://doi.org/10.1175/1520-0469(1997)054<0148:MTLTSA>2.0.CO;2.
Bretherton, C. S., and P. N. Blossey, 2014: Low cloud reduction in a greenhouse-warmed climate: Results from Lagrangian LES of a subtropical marine cloudiness transition. J. Adv. Model. Earth Syst., 6, 91–114, https://doi.org/10.1002/2013MS000250.
Bretherton, C. S., J. Uchida, and P. N. Blossey, 2010: Slow manifolds and multiple equilibria in stratocumulus-capped boundary layers. J. Adv. Model. Earth Syst., 2, 14, https://doi.org/10.3894/JAMES.2010.2.14.
Caldwell, P., and C. S. Bretherton, 2009: Response of a subtropical stratocumulus-capped mixed layer to climate and aerosol changes. J. Climate, 22, 20–38, https://doi.org/10.1175/2008JCLI1967.1.
Caldwell, P., C. S. Bretherton, and R. Wood, 2005: Mixed-layer budget analysis of the diurnal cycle of entrainment in southeast Pacific stratocumulus. J. Atmos. Sci., 62, 3775–3791, https://doi.org/10.1175/JAS3561.1.
Edwards, J. M., 2009: Radiative processes in the stable boundary layer: Part I. Radiative aspects. Bound.-Layer Meteor., 131, 105–126, https://doi.org/10.1007/s10546-009-9364-8.
Fletcher, J. K., S. Mason, and C. Jakob, 2016: A climatology of clouds in marine cold air outbreaks in both hemispheres. J. Climate, 29, 6677–6692, https://doi.org/10.1175/JCLI-D-15-0783.1.
Goren, T., D. Rosenfeld, O. Sourdeval, and J. Quaas, 2018: Satellite observations of precipitating marine stratocumulus show greater cloud fraction for decoupled clouds in comparison to coupled clouds. Geophys. Res. Lett., 45, 5126–5134, https://doi.org/10.1029/2018GL078122.
Hahn, C. J., and S. G. Warren, 2007: A gridded climatology of clouds over land (1971–96) and ocean (1954–97) from surface observations worldwide. CDIAC Rep. ORNL/CDIAC-153, 71 pp., https://doi.org/10.3334/CDIAC/cli.ndp026e.
Hartmann, D. L., M. E. Ockert-Bell, and M. L. Michelsen, 1992: The effect of cloud type on Earth’s energy balance: Global analysis. J. Climate, 5, 1281–1304, https://doi.org/10.1175/1520-0442(1992)005<1281:TEOCTO>2.0.CO;2.
Holton, J. R., 1973: An introduction to dynamic meteorology. Amer. J. Phys., 41, 752–754, https://doi.org/10.1119/1.1987371.
Iacono, M. J., J. S. Delamere, E. J. Mlawer, M. W. Shephard, S. A. Clough, and W. D. Collins, 2008: Radiative forcing by long-lived greenhouse gases: Calculations with the AER radiative transfer models. J. Geophys. Res., 113, D13103, https://doi.org/10.1029/2008JD009944.
Jones, C., C. Bretherton, and P. Blossey, 2014: Fast stratocumulus time scale in mixed layer model and large eddy simulation. J. Adv. Model. Earth Syst., 6, 206–222, https://doi.org/10.1002/2013MS000289.
Khairoutdinov, M., and Y. Kogan, 2000: A new cloud physics parameterization in a large-eddy simulation model of marine stratocumulus. Mon. Wea. Rev., 128, 229–243, https://doi.org/10.1175/1520-0493(2000)128<0229:ANCPPI>2.0.CO;2.
Khairoutdinov, M., and D. A. Randall, 2003: Cloud resolving modeling of the ARM summer 1997 IOP: Model formulation, results, uncertainties, and sensitivities. J. Atmos. Sci., 60, 607–625, https://doi.org/10.1175/1520-0469(2003)060<0607:CRMOTA>2.0.CO;2.
Klein, S. A., A. Hall, J. R. Norris, and R. Pincus, 2017: Low-cloud feedbacks from cloud-controlling factors: A review. Shallow Clouds, Water Vapor, Circulation, and Climate Sensitivity, Springer, 135–157.
Lilly, D. K., 1968: Models of cloud-topped mixed layers under a strong inversion. Quart. J. Roy. Meteor. Soc., 94, 292–309, https://doi.org/10.1002/qj.49709440106.
Mahrt, L., 2014: Stably stratified atmospheric boundary layers. Annu. Rev. Fluid Mech., 46, 23–45, https://doi.org/10.1146/annurev-fluid-010313-141354.
Mellado, J. P., 2017: Cloud-top entrainment in stratocumulus clouds. Annu. Rev. Fluid Mech., 49, 145–169, https://doi.org/10.1146/annurev-fluid-010816-060231.
Mellado, J. P., C. S. Bretherton, B. Stevens, and M. C. Wyant, 2018: DNS and LES for simulating stratocumulus: Better together. J. Adv. Model. Earth Syst., 10, 1421–1438, https://doi.org/10.1029/2018MS001312.
Miller, M. A., and B. A. Albrecht, 1995: Surface-based observations of mesoscale cumulus–stratocumulus interaction during ASTEX. J. Atmos. Sci., 52, 2809–2826, https://doi.org/10.1175/1520-0469(1995)052<2809:SBOOMC>2.0.CO;2.
Moeng, C.-H., and R. Rotunno, 1990: Vertical-velocity skewness in the buoyancy-driven boundary layer. J. Atmos. Sci., 47, 1149–1162, https://doi.org/10.1175/1520-0469(1990)047<1149:VVSITB>2.0.CO;2.
Myers, T. A., and J. R. Norris, 2015: On the relationships between subtropical clouds and meteorology in observations and CMIP3 and CMIP5 models. J. Climate, 28, 2945–2967, https://doi.org/10.1175/JCLI-D-14-00475.1.
Naud, C. M., J. F. Booth, A. Protat, K. Lamer, R. Marchand, and G. M. McFarquhar, 2020: Boundary layer cloud controlling factors in the midlatitudes: Southern versus northern ocean clouds. 2020 AGU Fall Meeting, Virtual, Amer. Geophys. Union, Abstract A195-02.
Nicholls, S., 1984: The dynamics of stratocumulus: Aircraft observations and comparisons with a mixed layer model. Quart. J. Roy. Meteor. Soc., 110, 783–820, https://doi.org/10.1002/qj.49711046603.
Nicholls, S., and J. Leighton, 1986: An observational study of the structure of stratiform cloud sheets: Part I. Structure. Quart. J. Roy. Meteor. Soc., 112, 431–460, https://doi.org/10.1002/qj.49711247209.
Norris, J. R., and S. A. Klein, 2000: Low cloud type over the ocean from surface observations. Part III: Relationship to vertical motion and the regional surface synoptic environment. J. Climate, 13, 245–256, https://doi.org/10.1175/1520-0442(2000)013<0245:LCTOTO>2.0.CO;2.
Norris, J. R., and S. F. Iacobellis, 2005: North Pacific cloud feedbacks inferred from synoptic-scale dynamic and thermodynamic relationships. J. Climate, 18, 4862–4878, https://doi.org/10.1175/JCLI3558.1.
Petty, G. W., 2006: A First Course in Atmospheric Radiation. 2nd ed. Sundog Publishing, 459 pp.
Romps, D. M., 2017: Exact expression for the lifting condensation level. J. Atmos. Sci., 74, 3891–3900, https://doi.org/10.1175/JAS-D-17-0102.1.
Sandu, I., and B. Stevens, 2011: On the factors modulating the stratocumulus to cumulus transitions. J. Atmos. Sci., 68, 1865–1881, https://doi.org/10.1175/2011JAS3614.1.
Schubert, W. H., J. S. Wakefield, E. J. Steiner, and S. K. Cox, 1979a: Marine stratocumulus convection. Part I: Governing equations and horizontally homogeneous solutions. J. Atmos. Sci., 36, 1286–1307, https://doi.org/10.1175/1520-0469(1979)036<1286:MSCPIG>2.0.CO;2.
Schubert, W. H., J. S. Wakefield, E. J. Steiner, and S. K. Cox, 1979b: Marine stratocumulus convection. Part II: Horizontally inhomogeneous solutions. J. Atmos. Sci., 36, 1308–1324, https://doi.org/10.1175/1520-0469(1979)036<1308:MSCPIH>2.0.CO;2.
Scott, R. C., T. A. Myers, J. R. Norris, M. D. Zelinka, S. A. Klein, M. Sun, and D. R. Doelling, 2020: Observed sensitivity of low cloud radiative effects to meteorological perturbations over the global oceans. J. Climate, 33, 7717–7734, https://doi.org/10.1175/JCLI-D-19-1028.1.
Smolarkiewicz, P. K., and W. W. Grabowski, 1990: The multidimensional positive definite advection transport algorithm: Nonoscillatory option. J. Comput. Phys., 86, 355–375, https://doi.org/10.1016/0021-9991(90)90105-A.
Stevens, B., 2006: Bulk boundary-layer concepts for simplified models of tropical dynamics. Theor. Comput. Fluid Dyn., 20, 279–304, https://doi.org/10.1007/s00162-006-0032-z.
Stevens, B., W. R. Cotton, G. Feingold, and C.-H. Moeng, 1998: Large-eddy simulations of strongly precipitating, shallow, stratocumulus-topped boundary layers. J. Atmos. Sci., 55, 3616–3638, https://doi.org/10.1175/1520-0469(1998)055<3616:LESOSP>2.0.CO;2.
Uchida, J., C. Bretherton, and P. Blossey, 2010: The sensitivity of stratocumulus-capped mixed layers to cloud droplet concentration: Do LES and mixed-layer models agree?. Atmos. Chem. Phys., 10, 4097–4109, https://doi.org/10.5194/acp-10-4097-2010.
Van der Dussen, J., and Coauthors, 2013: The GASS/EUCLIPSE model intercomparison of the stratocumulus transition as observed during ASTEX: LES results. J. Adv. Model. Earth Syst., 5, 483–499, https://doi.org/10.1002/jame.20033.
Wakefield, J. S., and W. H. Schubert, 1981: Mixed-layer mode simulation of eastern North Pacific stratocumulus. Mon. Wea. Rev., 109, 1952–1968, https://doi.org/10.1175/1520-0493(1981)109<1952:MLMSOE>2.0.CO;2.
Wall, C. J., D. L. Hartmann, and P.-L. Ma, 2017: Instantaneous linkages between clouds and large-scale meteorology over the Southern Ocean in observations and a climate model. J. Climate, 30, 9455–9474, https://doi.org/10.1175/JCLI-D-17-0156.1.
Wood, R., 2007: Cancellation of aerosol indirect effects in marine stratocumulus through cloud thinning. J. Atmos. Sci., 64, 2657–2669, https://doi.org/10.1175/JAS3942.1.
Wood, R., 2012: Stratocumulus clouds. Mon. Wea. Rev., 140, 2373–2423, https://doi.org/10.1175/MWR-D-11-00121.1.
Wyngaard, J., 1987: A physical mechanism for the asymmetry in top-down and bottom-up diffusion. J. Atmos. Sci., 44, 1083–1087, https://doi.org/10.1175/1520-0469(1987)044<1083:APMFTA>2.0.CO;2.
Yamaguchi, T., and D. A. Randall, 2008: Large-eddy simulation of evaporatively driven entrainment in cloud-topped mixed layers. J. Atmos. Sci., 65, 1481–1504, https://doi.org/10.1175/2007JAS2438.1.
Zhang, Y., B. Stevens, and M. Ghil, 2005: On the diurnal cycle and susceptibility to aerosol concentration in a stratocumulus-topped mixed layer. Quart. J. Roy. Meteor. Soc., 131, 1567–1583, https://doi.org/10.1256/qj.04.103.
Zheng, Y., and Z. Li, 2019: Episodes of warm-air advection causing cloud-surface decoupling during the MARCUS. J. Geophys. Res. Atmos., 124, 12 227–12 243, https://doi.org/10.1029/2019JD030835.
Zheng, Y., D. Rosenfeld, and, Z. Li, 2018: The relationships between cloud top radiative cooling rates, surface latent heat fluxes, and cloud-base heights in marine stratocumulus. J. Geophys. Res. Atmos., 123, 11 678–11 690, https://doi.org/10.1029/2018JD028579.
Zheng, Y., D. Rosenfeld, and Z. Li, 2020: A more general paradigm for understanding the decoupling of stratocumulus-topped boundary layers: The importance of horizontal temperature advection. Geophys. Res. Lett., 47, e2020GL087697, https://doi.org/10.1029/2020GL087697.
Zheng, Y., H. Zhang, and Z. Li, 2021: Role of surface latent heat flux in shallow cloud transitions: A mechanism-denial LES study. J. Atmos. Sci., 78, 2709–2723, https://doi.org/10.1175/JAS-D-20-0381.1.