1. Introduction
Since the early 1990s the cooling influence of subtropical stratocumulus has been recognized as a major contributor to Earth's global-average energy budget (Stephens and Greenwald 1991; Hartmann et al. 1992). The importance of stratocumulus-topped boundary layers (STBLs) in polar climate only became clear during the Surface Heat Budget of the Arctic Ocean Experiment (SHEBA) (Uttal et al. 2002), which revealed that STBLs are prevalent and long lived in the Arctic. Arctic STBLs were found to consist of a combination of ice and liquid water even at temperatures significantly below freezing (Curry et al. 2000; Intrieri et al. 2002; Korolev and Isaac 2003; Shupe and Intrieri 2004; Verlinde et al. 2007; de Boer et al. 2011; McFarquhar et al. 2011). Despite the rapid depletion of liquid water due to the lower saturation vapor pressure of ice compared to liquid [the Wegener–Bergeron–Findeisen (WBF) mechanism] (Wegener 1911; Bergeron 1935; Findeisen 1938), Arctic mixed-phase stratocumulus (AMPS) were observed to persist for days (Shupe et al. 2006) owing to compensating feedbacks between the formation and growth of ice and cloud droplets, radiative cooling, turbulence, entrainment, and surface fluxes of heat and moisture (Morrison et al. 2012).
Owing to the presence of liquid water and related processes in these cloud systems, AMPS play an important role in determining the structure of the Arctic atmospheric boundary layer and magnitudes of surface energy budget terms (Herman and Goody 1976; Curry and Ebert 1992; Schweiger and Key 1994; Zhang et al. 1996; Walsh and Chapman 1998; Intrieri et al. 2002; Shupe and Intrieri 2004; Inoue et al. 2006; Shupe et al. 2013). For example, Zuidema et al. (2005) estimated that a springtime AMPS observed during SHEBA had a net surface cloud forcing of 41 W m−2 due to the presence of cloud water, which increased cloud emissivity and, thus, downwelling longwave radiation (Sun and Shine 1994; Intrieri et al. 2002; Hogan et al. 2003; Shupe and Intrieri 2004; Dong et al. 2010).
The environments in which subtropical and Arctic stratocumuli occur are substantially different. For example, AMPS are observed above both stable surface boundary layers and open water (Intrieri et al. 2002; Shupe et al. 2013), while subtropical stratocumulus typically occur over open ocean. Another difference between subtropical and Arctic stratocumulus is that in the Arctic specific humidity inversions (specific humidity increasing with height, hereafter referred to as humidity inversion) are frequently observed to occur coincident with temperature inversions near cloud top. This feature is due primarily to horizontal advection aloft and moisture depletion near the surface (Curry 1983; Curry et al. 1996; Tjernström et al. 2004; Sedlar et al. 2012). Further key differences owing to the presence of ice in AMPS are the rapid conversion of cloud to precipitation by the WBF mechanism, the impact of latent heat due to freezing, and sublimation of ice precipitation below cloud base due to the lower saturation vapor pressure of ice compared to liquid.
Previous studies based on observations (Curry et al. 1996; Tjernström et al. 2004; Sedlar et al. 2012) and cloud-resolving models (Solomon et al. 2011) suggest that humidity inversions play an important role in maintaining AMPS by providing moisture within the temperature inversion, which is entrained into the cloud system. We extend the findings of these previous studies by quantifying the relative role of cloud-top and subcloud-layer sources of moisture in the persistence of AMPS. We demonstrate that a similar quasi-equilibrium state is reached when either or both of the moisture sources are present. Specifically, we show that a humidity inversion is a sufficient but not a necessary condition for the maintenance of an AMPS. To do this we use a series of idealized large-eddy simulations (LESs) based on a case study from the Department of Energy Atmospheric Radiation Measurement Program’s Indirect and Semi-Direct Aerosol Campaign (ISDAC) (McFarquhar et al. 2011) near Barrow, Alaska.
The goal of this paper is to clarify important details of the moisture and moist static energy (MSE) budgets by examining the potential impact of ice in mixed-phase clouds, humidity inversions coincident with temperature inversions as a source of moisture for the cloud system, and the presence of cloud liquid water (
2. Theoretical framework from subtropical STBLs studies
To provide a theoretical framework for this study, we first present an overview of microphysical–dynamical–radiative feedbacks in subtropical marine STBLs. Idealized models of STBLs are primarily based on observations of subtropical cloud systems over relatively cold sea surface temperatures where the large-scale atmospheric circulation is characterized by subsidence on the order of 2–4 mm s−1 (Wood and Bretherton 2004). Warm, dry air in a temperature inversion caps the cloud layer and damps upward motion in cloud plumes that overshoot their level of neutral buoyancy.
Two moist conserved fields that can be used to define a well-mixed subtropical cloud system (i.e., without ice water) are total water mixing ratio
Constants and variables not defined in the text.
Following the formulations of mixed-layer models by Lilly (1968) and Bretherton and Wyant (1997), the mixed layer is composed of two parts: a cloud layer, in which air is saturated with respect to water, and a subsaturated subcloud layer from the base of the mixed layer to the lifting condensation level. In the cloud layer
Moist static energy in the mixed layer evolves owing to radiative heating and cooling and divergence of heat and moisture fluxes across the mixed-layer top and base. In the mixed-layer
Even though AMPS clearly form cloud-driven mixed layers, the derivation of an idealized mixed-layer model that includes ice processes remains a challenge. For example, liquid–ice water static energy,
3. Case description
This study focuses on a case derived from observations of a persistent single-layer Arctic mixed-phase stratocumulus cloud deck on 8 April 2008 during the Indirect and Semi-Direct Aerosol Campaign (McFarquhar et al. 2011). The Beaufort Sea was generally ice covered during this time, with significant areas of open water observed east of Barrow, Alaska. An early morning sounding made at 1734 UTC 8 April 2008 at Barrow is shown in Fig. 1. Surface temperature was approximately 265 K. An approximate 4-K temperature inversion with inversion base at 1.05 km was observed at this time, with static stabilities close to neutral within the cloud-driven mixed layer overlaying a stable surface layer with static stabilities greater than 2 K km−1 below 500 m. The water vapor mixing ratio
Measurements from ground-based, vertically pointing, 35-GHz cloud radar, micropulse cloud lidar, and dual-channel microwave radiometer (Shupe 2007) at Barrow indicated a cloud layer extending into the inversion by 100 m, a cloud base at 0.9 km, and cloud top at 1.15 km. Cloud ice water path (IWP), derived from cloud radar reflectivity measurements that have an uncertainty of up to a factor of 2 (Shupe et al. 2006), was 20–120 g m−2 within 10 min of the sounding. Cloud liquid water path (LWP), derived from dual-channel microwave radiometer measurements that have an uncertainty of 20–30 g m−2 (Turner et al. 2007), was 39–62 g m−2 within 10 min of the sounding.
Nested Weather Research and Forecasting (WRF) simulations of this case performed with an inner grid at LES resolution (Solomon et al. 2011) demonstrate that moisture is provided to the cloud system by a total water inversion at cloud top and that the mixed layer is decoupled from surface sources of moisture. In addition, the nested simulations indicate that
4. Design of LES studies
This study uses the large eddy simulation mode of the Advanced Research WRF model, version 3.3.1 [see Yamaguchi and Feingold (2012) for a detailed description of the LES mode and the statistics package]. Packages and parameterizations used in the model setup are listed in Table 2.
WRF LES model setup.
All simulations are run with a horizontal grid spacing of 50 m and vertical grid spacing of 10 m. The domain has 72 (x) × 72 (y) × 180 (z) grid points and is periodic in both the x and y directions. The top of the domain is at 1.8 km, which is 0.7 km above cloud top in this case. The model time step is 0.5 s.
The structure of the cloud layer is insensitive to changes in resolution and domain size. However, increasing the vertical and horizontal resolution by a factor of 2 results in an increase in LWP (IWP) by 5% (1%). Increasing the domain size by a factor of 2 in both the x and y directions results in an increase in LWP and IWP by less than 1%. The simulations are insensitive to a decrease in time step by a factor of 2 and a decrease in the acoustic Courant number by a factor of 2.
Sensible and latent heat fluxes between the ice-covered surface and atmosphere under the considered conditions are typically small (<10 W m−2). Thus, for simplicity, both sensible and latent surface heat fluxes are set to zero in these simulations. In addition, because of small shortwave heating rates at cloud top at the time of the sounding [1 K day−1 for shortwave compared to −100 K day−1 for longwave based on nested WRF simulations (Solomon et al. 2011)], solar radiation is set to zero. Solar radiation cannot be neglected when considering the diurnal evolution of the cloud layer. Simulations to test the impact of diurnally varying solar radiation indicate that during the day there is significant near-surface heating, which drives buoyant production of turbulence. The impact of these processes on the results presented in this paper will be investigated in a follow-up study focused on perturbations to the quasi-equilibrium state.
The concentration of ice nuclei acting in deposition and condensation freezing modes is relaxed to a value of 1.0 L−1, the mean from measurements using the continuous flow diffusion chamber (McFarquhar et al. 2011), with ice nucleation rate equations developed in Morrison et al. (2011) and Ovchinnikov et al. (2011). The aerosol accumulation mode is specified with concentrations of 165 cm−3, modal diameter of 0.2 μm, and geometric standard deviation of 1.4 μm (based on in situ ISDAC measurements).
The dotted lines in Fig. 1 show the initial profiles used for the control simulation. Note that the profile overlaying
Figure 2 shows the initial total water profiles used for the sensitivity studies. These profiles are designed to identify the impact of moisture sources above and below the mixed layer on the dynamics of the cloud system. Core simulations for this study are
Control run: initial total water as shown in Fig. 1;
DryAbove run: same as Control, except that total water decreased to 0.5 g kg−1 above inversion base;
DryBelow run: same as Control, except that total water below the base of the cloud-driven mixed layer linearly reduced to 1 g kg−1 at the surface;
DryAbove&Below run: total water decreased to 0.5 g kg−1 above inversion base and reduced linearly from the base of the cloud-driven mixed layer to the surface.
Horizontally averaged fields output every minute from the statistics package are used in the analysis. Conditional averages are used to calculate averages in updrafts and downdrafts, where an updraft is defined as having a vertical velocity greater than zero at the base of the cloud layer. The mixed layer is defined as the region where the liquid–ice water static energy is approximately constant with height. We define the boundaries of the mixed-layer top and base to occur where the slope of liquid–ice static energy exceeds 5 × 10−3 and 1 × 10−3 K m−1, respectively. Cloud top and base are defined as the heights where
Since well-mixed layers are vertically homogenous for moist-conserved variables, evolution of mixed-layer quantities with no internal sources or sinks can be described by fluxes of these quantities through the top and bottom mixed-layer boundaries. Thus, mixed-layer MSE and
5. Results
a. Control simulation with and without ice
Figure 3 shows liquid water path (LWP) and ice plus LWP [total water path (TWP)] for the first 12 h of Control (black line) compared to NoIce (red line). Control equilibrates after 4 h with an approximate LWP of 37 g m−2 and TWP of 64 g m−2, giving a liquid fraction (LWP/TWP) of 0.6. Interestingly, NoIce follows a similar TWP trajectory until hour 4. The addition of ice processes in Control causes
1) Simulation without ice (NoIce)
While NoIce is similar to subtropical stratocumulus in condensate phase and in the presence of a well-mixed layer (Figs. 4a,b), it differs by not having the mixed layer extend to the surface, by having a
(i) Water fluxes
The
Although
(ii) Energy fluxes
Figures 5b, 5d, and 5f show that radiative fluxes, entrainment due to subsidence, and turbulent eddies contribute to the positive MSE fluxes at the mixed-layer top, which are a factor of 5–6 larger than at the mixed-layer base, resulting in negative MSE tendencies in the mixed layer (dMSE/dt in the mixed layer = −3 × 10−5 K s−1). Different from subtropical systems, the largest negative tendencies occur just below cloud top, which in this case is above the mixed-layer top and within the temperature inversion.
Figures 5e and 5f show the approximate linear change in net
(iii) Buoyancy fluxes
Evaporation at the cloud base in downdrafts exceeds condensation in updrafts (Fig. 6b) because of the continual flux of
(iv) Sensitivity to sedimentation and latent heating
Removing sedimentation removes the
When both sedimentation and latent heating are removed, the cloud system shows no indication of collapsing. LWP increases and the cloud system extends farther into the inversion relative to NoSedimentation (Figs. 7b,d). The essential difference between NoSedimentation and NoSedimentation–NoLH is that potential temperature is the conserved and well-mixed field in the mixed layer in the absence of latent heating (as opposed to equivalent potential temperature when latent heating is allowed). This causes temperatures to be colder in the cloud layer, which reduces the saturation vapor pressure, reducing
2) Effect of ice (Control)
(i) Water fluxes
The initial conditions in Control specify increased moisture below the mixed layer. Therefore, the advective
It is important to note that
In the NoIce cloud layer away from the cloud top and base, condensation almost balances evaporation, and net horizontally averaged latent heating is a weak cooling. Latent heating is also small within the cloud layer in Control owing to a balance between net cooling from liquid processes and depositional warming associated with the WBF process (e.g., Korolev and Mazin 2003; Fig. 6b), that is, the depletion of
Similar to nested WRF simulations of the same case (Solomon et al. 2011), turbulence advects
(ii) MSE fluxes
Radiative fluxes at cloud top and base are similar for Control and NoIce because, although NoIce has more condensate (resulting in a larger flux jump at cloud top), Control is warmer (seen as a larger flux within cloud) and has smaller droplets (not shown). As a result, radiation cools the mixed layer of both simulations roughly equally (Fig. 5b). Total MSE fluxes are roughly linear across the mixed layer (as required for MSE in this region to remain independent of height), though Control exhibits slight deviations because MSE is not conserved during freezing (Fig. 5f).
(iii) Buoyancy fluxes
As demonstrated in NoSedimentation–NoLH, latent heating is playing a limited role in driving buoyancy fluxes in these simulations. However, including ice processes causes a reduction in buoyancy fluxes in the subcloud layer and a larger jump at the cloud-layer base (Fig. 6a) owing to the increase in condensation in updrafts relative to evaporation in downdrafts at cloud base (Fig. 6b).
b. Impact of removing the humidity inversion
Figure 8 shows the evolution of LWP and IWP for Control and the three sensitivity simulations defined in section 4 with
1) Quasi-equilibrium state
DryAbove reaches quasi-equilibrium after 9 h. In this quasi-equilibrium-state LWP in DryAbove is within 6% of Control while IWP is significantly less than Control (~30%). IWP in DryAbove continually increases until ~19 h while IWP in Control continually decreases after peaking at 5 h, resulting in similar TWP by 20 h. Also, while the cloud base height is essentially stationary in Control, the cloud base in DryAbove descends at a rate of 0.08 m s−1 as increased TKE (Fig. 10b) allows the mixed layer to tap more effectively into the moisture source below mixed-layer base.
By 9 h the inversion layer in DryAbove has moistened relative to the overlying air, with a weak humidity inversion forming just below cloud top (Fig. 11d). As a result, the cloud layer extends into the inversion with maximum liquid water content at the mixed-layer top, similar to Control (Fig. 11c). This moistening of the inversion in DryAbove during the adjustment to the quasi-equilibrium state causes a larger decrease in MSE and
2) Water fluxes
The impact at mixed-layer top of reducing overlying
The weak humidity inversion is maintained in DryAbove by a downgradient transport of
3) MSE fluxes
Both radiation and turbulence contribute to an increased upward moist static energy flux through the top of the mixed layer in DryAbove compared to Control (Figs. 12b,d,f). Radiative flux increases over Control because of overlying air having a higher (colder) effective longwave emission level under drier conditions (Caldwell and Bretherton 2009). Advective MSE flux at mixed-layer top increases primarily owing to an increase in the turbulent transport of MSE (Fig. 12d) resulting from increased TKE (Fig. 10b). At mixed-layer base DryAbove and Control have similar weakly positive radiative and MSE fluxes. The net result of reducing
4) Buoyancy fluxes
Because entrainment drying in DryAbove is stronger than in Control, evaporative cooling is enhanced in downdrafts (Figs. 12c,d). As mentioned before, drier overlying air also makes radiative cooling at the mixed-layer top stronger (Fig. 12b). These factors result in larger buoyancy fluxes in DryAbove than Control, producing significantly larger TKE (Fig. 10b). Evaporative cooling of entrained air is visible in Figs. 10c and 10d as negative spikes near cloud top. Despite this enhancement and larger TKE, inversion-base entrainment is weaker (evident by a lower mixed-layer top) because the mixed layer is colder and, hence, the inversion is more stable to erosion by entrainment compared to Control.
c. Impact of reducing surface-layer moisture sources
Reducing specific humidity below the cloud-driven mixed layer (DryBelow) causes LWP to divergence from Control after ~50 min (Fig. 8), that is, after resolved turbulence develops and air from below the mixed layer is entrained into the cloud system. This reduces condensational warming in updrafts, which damps buoyancy fluxes and decreases cloud-top TKE. Weaker radiative cooling in DryBelow may also contribute to the weaker TKE and buoyancy fluxes within the cloud layer. Note that this divergence occurs before ice processes are allowed to begin.
1) Quasi-equilibrium state
In DryBelow, a quasi-equilibrium state is reached when the rate of ice production slows, after which both IWP and LWP continually increase at a rate less than 0.4 g m−2 h−1. In the quasi-equilibrium state at 9 h, DryBelow and Control have similar (within 15%)
2) Water fluxes
In DryBelow and Control, downward precipitation flux exceeds upward advective
3) Buoyancy fluxes
Drying the bottom of the mixed layer reduces buoyant enhancement of updrafts and downdrafts by latent heating, reducing the buoyancy flux (Fig. 15a). As a result, mixed-layer-top entrainment decreases relative to cloud-top radiative cooling (evident as a reduction in inversion height in Fig. 15). This causes subcloud buoyancy flux to increase.
d. Decreasing moisture sources above and below the mixed layer
Figure 8 clearly shows that reducing moisture aloft or in the surface layer impacts the evolution of the cloud system, yet these two cases reach a similar quasi-equilibrium state to Control, with LWPs within 9%. However, Fig. 8 also shows that, when dry air is entrained from both above and below (DryAbove&Below), the cloud system never reaches a quasi-equilibrium state and slowly decays at a rate of dLWP/dt = −0.3 g m−2 h−1. In addition, there is no loss of moisture because of precipitation to the surface. Thus, in DryAbove&Below the steady decline of the cloud system (decreasing LWP and IWP) is due to the steady detrainment of moisture above and below the cloud and a very small precipitation flux across the mixed-layer base that evaporates before reaching the surface. It is interesting to note that the cloud system does not reach a threshold during the 20-h simulation, where turbulence cannot maintain the production of
Comparing DryAbove&Below to DryAbove at 9 h (Fig. 16), it is clear that the cloud layer thins when surface-layer moisture is reduced (Figs. 16a,b). The thinning in DryAbove&Below is due to the dominance of subsidence drying over weak turbulent
LWP in DryAbove&Below is 80% smaller than DryAbove at 9 h (Fig. 8). The more rapid decrease in LWP in DryAbove&Below (after an initial adjustment) is due to an integrated positive
6. Summary and discussion
In this study, we used a series of idealized large-eddy simulations to quantify the relative impact of cloud top and subcloud-layer sources of moisture on the microphysical–radiative–dynamical feedbacks in an Arctic mixed-phase stratocumulus cloud system, focusing on a case derived from observations of a persistent single-layer AMPS cloud deck during ISDAC. Moisture and moist static energy budgets were used to examine the potential impact of ice in mixed-phase clouds, humidity inversions coincident with temperature inversions as a source of moisture for the cloud system, and the presence of
In this study, AMPS were found to have remarkable insensitivity to changes in moisture source. When the overlying air is initially dried, radiative cooling and turbulent entrainment increase moisture import from the surface layer. When the surface layer is initially dried, reduction in mixed-layer
A number of specific cloud processes were examined here to determine their roles in the moisture and MSE budgets. The inclusion of ice processes was found to
lead to a quasi-equilibrium state with constant TWP;
diminish
by the WBF mechanism [since MSE in the mixed layer decreases at the same rate in NoIce and Control, the cloud layer in Control has similar (same saturation vapor pressure) but less liquid water]; decrease cooling rates in the subcloud layer owing to similar MSE tendencies and increased depletion of
by the growth of ice; create a moisture sink at the mixed-layer base due to precipitation;
redistribute
in the subcloud layer, moving vapor from the base of the cloud layer to the lower subcloud and surface layers; maintain cloud-base height by causing the cloud system to descend slower owing to the WBF mechanism;
lead to diminished buoyancy flux, primarily in the subcloud layer, and TKE because of less evaporation in downdrafts, primarily due to depositional warming associated with ice processes.
moisten the inversion by detraining cloud water and evolve into a quasi-equilibrated state with similar LWP (and less IWP) to Control;
increase MSE and radiative fluxes at mixed-layer top, causing the mixed layer to cool faster;
increase turbulence (in spite of slightly decreasing LWP) owing to increased radiative fluxes and enhanced evaporation (condensation) in downdrafts (updrafts);
reduce
in the mixed layer; slow the growth of ice mass and precipitation;
cause the mixed layer and cloud-layer base to descend and deepen faster;
lead to cloud maintenance via transport of
from below the mixed layer.
Removing the moisture source below the cloud was found to
reduce the buoyancy jump at the cloud-layer base by reducing condensation in updrafts;
reduce the negative
tendency in the mixed layer; produce less ice due to lower humidity in the subcloud layer;
produce a quasi-equilibrated state with similar LWP (and less IWP) to Control.
The simulations of Arctic stratocumulus presented in this paper differ from liquid-only subtropical stratocumulus in that cloud-top radiative cooling is not collocated with the mixed-layer top in these Arctic simulations. Because the inversion layer is strongly stable, buoyancy flux between cloud top and mixed-layer top remains negative, preventing radiative-cooling-induced turbulence from incorporating inversion-zone cloud into the mixed layer. Also, a positive subcloud buoyancy flux in the current simulations suggests that separation between the inversion and cloud top reduces the efficiency with which turbulence generation is translated to entrainment of warm overlying air. Existent entrainment parameterizations assume mixed-layer and cloud top are collocated [see discussion in Stevens (2002)], so they may not be appropriate for AMPS. Modifying existent parameterizations to account for balances in AMPS detailed in this paper is interesting future work.
Acknowledgments
The authors thank Graham Feingold and three anonymous reviewers for constructive comments. This research was supported by the Office of Science (BER), U.S. Department of Energy (DE-FG01-05ER63965) and the National Science Foundation (ARC-1023366).
REFERENCES
Abdul-Razzak, H., and S. J. Ghan, 2000: A parameterization of aerosol activation: 2. Multiple aerosol types. J. Geophys. Res., 105, 6837–6844.
Bergeron, T., 1935: On the physics of clouds and precipitation. Proces Verbaux de l‘Association de Meteorologie, International Union of Geodesy and Geophysics, 156–178.
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.
Bretherton, C. S., P. N. Blossey, and J. Uchida, 2007: Cloud droplet sedimentation, entrainment efficiency, and subtropical stratocumulus albedo. Geophys. Res. Lett., 34, L03813, doi:10.1029/2006GL027648.
Caldwell, P., and C. S. Bretherton, 2009: Large-eddy simulation of the diurnal cycle in southeast Pacific stratocumulus. J. Atmos. Sci., 66, 432–449.
Collins, W. D., and Coauthors, 2004: Description of the NCAR Community Atmosphere Model (CAM 3.0). NCAR Tech. Note NCAR/TN-464+STR, 226 pp. [Available online at http://www.cesm.ucar.edu/models/atm-cam/docs/description/description.pdf.]
Curry, J., 1983: On the formation of continental polar air. J. Atmos. Sci., 40, 2278–2292.
Curry, J., and E. E. Ebert, 1992: Annual cycle of radiation fluxes over the Arctic Ocean: Sensitivity to cloud optical properties. J. Climate, 5, 1267–1280.
Curry, J., W. B. Rossow, D. Randall, and J. L. Schramm, 1996: Overview of Arctic cloud and radiation characteristics. J. Climate, 9, 1731–1764.
Curry, J., and Coauthors, 2000: FIRE Arctic Clouds Experiment. Bull. Amer. Meteor. Soc., 81, 5–30.
de Boer, G., H. Morrison, M. D. Shupe, and R. Hildner, 2011: Evidence of liquid dependent ice nucleation in high-latitude stratiform clouds from surface remote sensors. Geophys. Res. Lett., 38, L01803, doi:10.1029/2010GL046016.
de Roode, S. R., and Q. Wang, 2007: Do stratocumulus clouds detrain? FIRE I data revisited. Bound.-Layer Meteor., 122, 479–491.
Dong, X., B. Xi, K. Crosby, C. N. Long, R. S. Stone, and M. D. Shupe, 2010: A 10 year climatology of Arctic cloud fraction and radiative forcing at Barrow, Alaska. J. Geophys. Res., 115, D17212, doi:10.1029/2009JD013489.
Dyer, A. J., and B. B. Hicks, 1970: Flux-gradient relationships in the constant flux layer. Quart. J. Roy. Meteor. Soc., 96, 715–721.
Findeisen, W., 1938: Kolloid-meteorologische Vorgange bei Neiderschlagsbildung. Meteor. Z., 55, 121–133.
Fridlind, A. M., A. S. Ackerman, G. McFarquhar, G. Zhang, M. R. Poellot, P. J. DeMott, A. J. Prenni, and A. J. Heymsfield, 2007: Ice properties of single-layer stratocumulus during the Mixed-Phase Arctic Cloud Experiment: 2. Model results. J. Geophys. Res., 112, D24202, doi:10.1029/2007JD008646.
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.
Herman, G., and R. Goody, 1976: Formation and persistence of summertime Arctic stratus clouds. J. Atmos. Sci., 33, 1537–1553.
Hogan, R., P. Francis, H. Flentje, A. Illingworth, M. Quante, and J. Pelon, 2003: Characteristics of mixed-phase clouds. I: Lidar, radar and aircraft observations from CLARE’98. Quart. J. Roy. Meteor. Soc., 129, 2089–2116.
Inoue, J., J. Liu, J. O. Pinto, and J. A. Curry, 2006: Intercomparison of Arctic regional climate models: Modeling clouds and radiation for SHEBA in May 1998. J. Climate, 19, 4167–4178.
Intrieri, J. M., C. W. Fairall, M. D. Shupe, P. O. G. Persson, E. Andreas, P. S. Guest, and R. E. Moritz, 2002: An annual cycle of Arctic surface cloud forcing at SHEBA. J. Geophys. Res., 107, 8039, doi:10.1029/2000JC000439.
Korolev, A. V., and G. Isaac, 2003: Phase transformation of mixed-phase clouds. Quart. J. Roy. Meteor. Soc., 129, 19–38, doi:10.1256/qj.01.203.
Korolev, A. V., and I. P. Mazin, 2003: Supersaturation of water vapor in clouds. J. Atmos. Sci., 60, 2957–2974.
Lilly, D. K., 1968: Models of cloud-topped mixed layers under a strong inversion. Quart. J. Roy. Meteor. Soc., 94, 292–309.
McFarquhar, G. M., and Coauthors, 2011: Indirect and Semi-Direct Aerosol Campaign (ISDAC): The impact of Arctic aerosols on clouds. Bull. Amer. Meteor. Soc., 92, 183–201.
Monin, A. S., and A. M. Obukhov, 1954: Basic laws of turbulent mixing in the atmosphere near the ground. Tr. Geofiz. Inst., Akad. Nauk SSSR, 24, 163–187.
Morrison, H., and J. O. Pinto, 2005: Mesoscale modeling of springtime Arctic mixed-phase stratiform clouds using a new two-moment bulk microphysics scheme. J. Atmos. Sci., 62, 3683–3704.
Morrison, H., G. Thompson, and V. Tatarskii, 2009: Impact of cloud microphysics on the development of trailing stratiform precipitation in a simulated squall line: Comparison of one- and two-moment schemes. Mon. Wea. Rev., 137, 991–1007.
Morrison, H., and Coauthors, 2011: Intercomparison of cloud model simulations of Arctic mixed-phase boundary layer clouds observed during SHEBA/FIRE-ACE. J. Adv. Model. Earth Syst, 3, M05001, doi:10.1029/2011MS000066.
Morrison, H., G. de Boer, G. Feingold, J. Harrington, M. D. Shupe, and K. Sulia, 2012: Resilience of persistent Arctic mixed-phase clouds. Nat. Geosci., 5, 11–17.
Ovchinnikov, M., A. Korolev, and J. Fan, 2011: Effects of ice number concentration on dynamics of a shallow mixed-phase stratiform cloud. J. Geophys. Res., 116, D00T06, doi:10.1029/2011JD015888.
Paulson, C. A., 1970: The mathematical representation of wind speed and temperature profiles in the unstable atmospheric surface layer. J. Appl. Meteor., 9, 857–861.
Schweiger, A. J., and J. R. Key, 1994: Arctic Ocean radiative fluxes and cloud forcing estimates from the ISCCP C2 cloud dataset. J. Appl. Meteor., 33, 948–963.
Sedlar, J., M. D. Shupe, and M. Tjernström, 2012: On the relationship between thermodynamic structure, cloud top, and climate significance in the Arctic. J. Climate, 25, 2374–2393.
Shupe, M. D., 2007: A ground-based multiple remote-sensor cloud phase classifier. Geophys. Res. Lett., 34, L2209, doi:10.1029/2007GL031008.
Shupe, M. D., and J. M. Intrieri, 2004: Cloud radiative forcing of the Arctic surface: The influence of cloud properties, surface albedo, and solar zenith angle. J. Climate, 17, 616–628.
Shupe, M. D., S. Y. Matrosov, and T. Uttal, 2006: Arctic mixed phase cloud properties derived from surface-based sensors at SHEBA. J. Atmos. Sci., 63, 697–711.
Shupe, M. D., P. O. G. Persson, I. M. Brooks, M. Tjernström, J. Sedlar, T. Mauritsen, S. Sjogren, and C. Leck, 2013: Cloud and boundary layer interactions over the Arctic sea-ice in late summer. Atmos. Chem. Phys. Discuss.,13, 13 191–13 244.
Skamarock, W. C., and Coauthors, 2008: A description of the Advanced Research WRF version 3. NCAR Tech. Note NCAR/TN-475+STR, 113 pp. [Available online at http://www.mmm.ucar.edu/wrf/users/docs/arw_v3.pdf.]
Solomon, A., M. D. Shupe, P. O. G. Persson, and H. Morrison, 2011: Moisture and dynamical interactions maintaining decoupled Arctic mixed-phase stratocumulus in the presence of a humidity inversion. Atmos. Chem. Phys., 11, 10 127–10 148.
Stephens, G. L., and T. J. Greenwald, 1991: Observations of the Earth’s radiation budget in relation to atmospheric hydrology. Part II: Cloud effects and cloud feedback. J. Geophys. Res., 96, 15 325–15 340.
Stevens, B., 2002: Entrainment in stratocumulus topped mixed layers. Quart. J. Roy. Meteor. Soc., 128, 2663–2690.
Sun, Z., and K. Shine, 1994: Studies of the radiative properties of ice and mixed-phase clouds. Quart. J. Roy. Meteor. Soc., 120, 111–137.
Tjernström, M., and R. G. Graversen, 2009: The vertical structure of the lower Arctic troposphere analysed from observations and ERA-40 reanalysis. Quart. J. Roy. Meteor. Soc., 135, 431–443.
Tjernström, M., C. Leck, P. O. G. Persson, M. L. Jensen, S. P. Oncley, and A. Targino, 2004: The summertime Arctic atmosphere: Meteorological measurements during the Arctic Ocean Experiment 2001. Bull. Amer. Meteor. Soc., 85, 1305–1321.
Turner, D. D., S. A. Clough, J. C. Liljegren, E. E. Clothiaux, K. Cady-Pereira, and K. L. Gaustad, 2007: Retrieving precipitable water vapor and liquid water path from Atmospheric Radiation Measurement (ARM) program’s microwave radiometers. IEEE Trans. Geosci. Remote Sens., 45, 3680–3690.
Uttal, T., and Coauthors, 2002: Surface heat budget of the Arctic Ocean. Bull. Amer. Meteor. Soc., 83, 255–275.
Verlinde, H., and Coauthors, 2007: The Mixed-Phase Arctic Cloud Experiment. Bull. Amer. Meteor. Soc., 88, 205–221.
Walsh, J. E., and W. L. Chapman, 1998: Arctic cloud-radiation temperature associations in observational data and atmospheric reanalyses. J. Climate, 11, 3030–3045.
Wang, H., W. C. Skamarock, and G. Feingold, 2009: Evaluation of scalar advection schemes in the Advanced Research WRF model using large-eddy simulations of aerosol–cloud interactions. Mon. Wea. Rev., 137, 2547–2558.
Wegener, A., 1911: Thermodynamik der Atmosphare. J. A. Barth, 311 pp.
Wood, R., 2012: Stratocumulus clouds. Mon. Wea. Rev., 140, 2373–2423.
Wood, R., and C. S. Bretherton, 2004: Boundary layer depth, entrainment, and decoupling in the cloud-capped subtropical and tropical marine boundary layer. J. Climate, 17, 3576–3588.
Yamaguchi, T., and G. Feingold, 2012: Technical note: Large-eddy simulation of cloudy boundary layer with the Advanced Research WRF model. J. Adv. Model. Earth Syst., 4, M09003, doi:10.1029/2012MS000164.
Zhang, T., K. Stamnes, and S. A. Bowling, 1996: Impact of clouds on surface radiative fluxes and snowmelt in the Arctic and subarctic. J. Climate, 9, 2110–2123.
Zuidema, P., and Coauthors, 2005: An Arctic springtime mixed phase cloudy boundary layer observed during SHEBA. J. Atmos. Sci., 62, 160–176.