Dynamics and energetics of the cloudy boundary layerin simulations of off-ice flow in the marginal ice zone

Peter Q. OlssonAlaska Experimental Forecast Facility, University of Alaska, Anchorage

Jerry Y. HarringtonGeophysical Institute, University of Alaska, Fairbanks

Abstract. The case under consideration occurred on March 4, 1993, and was observed aspart of the Radiation and Eddy Flux Experiment (REFLEX II) 1993 observationalcampaign northwest of Spitsbergen. The off-ice flow on this day brought very cold surfaceair temperatures (2358C) over a relatively warm ocean surface. The resultant latent andsensible surface heat fluxes produced intense convection and a thermal internal boundarylayer (TIBL) which deepened with distance from the ice edge. Two-dimensional cloud-resolving model (CRM) simulations were performed to determine the impact of variouscloud parameterizations on the structure and evolution of the TIBL. The model was ableto reproduce the observed thermal structure of the boundary layer to within theacknowledged limitations of the CRM approach. Sensitivity studies of cloud type showedthat inclusion of mixed-phase microphysics had a large impact of BL depth and structure.Radiative heating of the cloud near cloud base and cooling near cloud top along withlatent heat release were found to be significant sources of turbulence kinetic energy evenin the present case where very strong surface heat fluxes occur. Ice-phase precipitationprocesses rapidly depleted the BL of condensate, weakening the radiative thermal forcing.A further consequence of condensate depletion in the mixed-phase cloud was a less humidboundary layer that was able to maintain a larger surface latent heat flux and continuouslyextract heat through condensation and deposition. Not surprisingly, the presence of cloudshad a profound impact on the radiative budget at the surface, with the cloudy BLreducing surface radiative losses more that 60% over clear-sky values. Inclusion of the icephase significantly affected the radiative budget as compared to purely liquid clouds,illustrating the importance of ice-phase–radiative couplings for accurate simulations ofarctic clouds and boundary layer dynamics.

1. Introduction

The marginal ice zone (MIZ) is that region within which,more or less, total sea-ice coverage gives way to a generallyice-free ocean. From the geophysical standpoint the signifi-cance of the MIZ largely derives from dramatic changes inatmosphere-ocean interaction as one traverses this region. Sur-face properties vary considerably in the MIZ, providing sharpgradients in surface-atmosphere interactions. For example,snow-covered sea ice has a relatively high albedo and largesurface roughness in comparison to open water. More impor-tant is the stark contrast in surface latent and sensible heatfluxes from ice-covered to open ocean.

The response of the atmosphere to this variation in surfaceproperties and surface fluxes is quite varied and complicated,revealing sensitivity to the ambient stratification, large-scalewind direction, wind speed, shear profile, and cloud cover.Atmospheric flow over the MIZ coming from lower latitudes(so-called on-ice flow) typically has reached a quasi equilib-rium with the underlying open ocean and tends to be relativelywarm and moist. By contrast, off-ice flow in the MIZ, i.e., fromice toward open ocean, is typically very cold, dry, and extremely

stable, especially if it has “aged” for sufficient time to havecome into equilibrium with the underlying cryosphere [Curry,1983]. Such off-ice flow events are often referred to as “cold-air outbreaks” [e.g., Miura, 1986; Hein and Brown, 1988; Raash,1990] and are accompanied by intense convection, cloudiness,and boundary layer (BL) thermal modification.

Some effort has been made to conduct numerical simula-tions of atmosphere-ice-ocean interactions in the MIZ. Muchof the work to date has focused on development of thermalinternal boundary layers in off-ice flow [Raasch, 1990; Chlond,1992; Lupkes and Schultzen, 1996], momentum effects due tospatially varying surface drag coefficients [Overland et al., 1983;Kantha and Mellor, 1989], and the effects of varying large-scalewind direction on local circulations. Pinto and Curry [1995] andPinto et al. [1995] describe the evolution of a convective BLabove a polynya, an environment similar to off-ice flow in theMIZ. The modeling approaches have varied from slab-symmetric steady state boundary layer and one-dimensionalpredictive models to more complex primitive equation (PE)models.

In the work presented here, we simulate an observed case ofoff-ice flow. This case has been simulated with mesoscale res-olution by others [e.g., Lupkes and Schultzen, 1996]. Our workis, to the best of our knowledge, one of the first to consider indetail the role of multidimensional precipitating clouds in the

Copyright 2000 by the American Geophysical Union.

Paper number 1999JD901194.0148-0227/00/1999JD901194$09.00

JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 105, NO. D9, PAGES 11,889–11,899, MAY 16, 2000

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numerically simulated development of the convective bound-ary layer resulting from off-ice flow.

2. March 4, 1993, Cold-Air OutbreakThe case under consideration occurred on March 4, 1993,

and was observed as part of the Radiation and Eddy FluxExperiment (REFLEX II) 1993 observational campaign [Kott-meier et al., 1994] northwest of Spitsbergen. The off-ice flow onthis day brought very cold surface air temperatures (2358C)over a relatively warm ocean surface (Tss ; 08C). The result-ant latent and sensible surface heat fluxes (Fl and Fs) pro-duced intense convection and a thermal internal BL that deep-ened with distance from the ice edge (Figure 1).

Satellite images [Kottmeier et al., 1994] show the MIZ atabout 808N, with cellular convection over the open water andorganized rolls forming more or less orthogonal to the ice edgeas the BL deepens. The initial (over ice) atmospheric thermalprofile, typical of an atmospheric column that has been overthe pack ice for some time [Kahl, 1990], has an extremely stablelayer near 200 m (Du of 88C over 75 m) with a weaker stabilityabove and below. More details of the case are discussed byLupkes and Schultzen [1996].

3. Numerical SimulationsThe numerical model used here is the Regional Atmo-

spheric Modeling System (RAMS) [Pielke et al., 1992]. RAMShas been used for cloud-resolving model (CRM) simulations ofarctic stratus clouds over sea ice in warm [Olsson et al., 1998]and transition [Harrington et al., 1999] seasons and stratocu-mulus clouds at lower latitudes [e.g., Stevens et al., 1996]. Thecurrent version of the model includes the one-moment micro-physical scheme of Walko et al. [1995]. This scheme modelsmicrophysical processes by assuming that all hydrometeor spe-cies are distributed in size by a gamma distribution. The meanmass of each hydrometeor species (cloud drops, rain, pristineice, snow, aggregates, graupel, and hail) is predicted andevolves as a function of the local saturation. Thus this scheme

contains elements appropriate for simulation of the mixed-phase clouds expected to occur over the MIZ.

As with any parameterization of a complex physical process,the scheme has some important limitations. First of all, thenucleation of ice crystals in this case is mainly by heteroge-neous processes [Sassen and Dodd, 1988; Pruppacher and Klett,1997 (T , 2308C)]. The ice nucleation formulation [Meyers etal., 1992] used here may produce ice concentrations larger thanthose routinely observed in the Arctic [Harrington et al., 1999a].This would tend to give large precipitation fluxes and weakerBL dynamics. Additionally, the current model assumes that icenuclei (IN) are not removed from the atmosphere by sedimen-tation processes. In the absence of a source of new IN (forexample, by entrainment of air from above the cloud) thenumber of IN available in the BL for heterogeneous ice nu-cleation would be depleted, impacting precipitation fluxes. Weare currently studying the impact of IN concentrations onsimulated MIZ cloud processes [Harrington and Olsson, 1999].Finally, since individual crystal sizes are not resolved, ice pre-cipitation is based on the mean fall speed of the entire icedistribution function, effectively causing large crystals to pre-cipitate too slowly and small crystals to precipitate too rapidly.Typically, the net effect is a reduction of precipitation fluxesfrom the cloud, and greater in-cloud residence time of the icehydrometeors.

These problems can be mitigated using a more complexbin-resolving ice microphysical model [e.g., Reisin et al., 1996;Harrington and Olsson, 1999], but such an approach would becomputationally unfeasible for the present study, which is lessconcerned with the quantitative details of how ice microphys-ical processes impact convection than the qualitative differ-ences between liquid and mixed-phase clouds over the MIZ.The bulk microphysical model used here gives us an estimateof the relative significance of ice phase processes in the evo-lution of the BL over the MIZ. However, the above micro-physical limitations should be borne in mind because they mayimpact the quantitative differences described below.

The configuration used here also includes the two-streamradiation model described by Harrington et al. [1999a, 2000],which is physically consistent with both the liquid and the ice-phase microphysical parameterizations. For the liquid phase theradiation model assumes spherical water drops and uses Lorenz-Mie theory to compute the optical properties of the drops, whiletreatment of the ice phase is based on the modifications to anom-alous diffraction theory proposed by Mitchell et al. [1996]. Becauseof the low Sun angle at 808N during early March the effects ofsolar radiation were not included.

3.1. Experiment Design

As has been shown [Moeng et al., 1996; Bretherton et al.,1999], use of a two-dimensional cloud-resolving model struc-ture rather than the three-dimensional large-eddy simulation(LES) structure to simulate cloud-scale circulations clearlycompromises the turbulence structure, even in relatively iso-tropic cloud environments. It is unreasonable to expect a CRMto faithfully reproduce the observed cloud streeting seen here[Kottmeier et al., 1994] and in other cases of off-ice flow [e.g.,Hein and Brown, 1988; Hartmann et al., 1997] since the axes ofthe cloud rolls are oriented roughly parallel to the modeldomain. At the same time, it is not computationally feasible tosimulate even a significant portion of the 310 km domain withan LES approach. Therefore we chose a CRM framework thatallows us to simulate circulation features with scale lengths

Figure 1. Dropsonde profiles for the March 4, 1993, RE-FLEX-II case, with distances measured relative to ice edge.Also shown is the initial potential temperature profile used inthe numerical simulations.

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several times that of a LES domain, as these may effect thecloud evolution and BL structure.

The two-dimensional model domain extends 310 km, per-pendicular to the ice edge and spanning both ice-covered (230km # x # 0 km) and open ocean (0 km , x # 280 km)surfaces (Figure 2). Following Lupkes and Schultzen [1996] wehave assumed horizontally homogeneous initial atmosphericconditions. The prescribed initial winds, an along-domainU0 5 9.4 m s21 and a cross-domain V0 5 26.6 m s21, areimplicitly assumed to be in geostrophic balance with a large-scale pressure gradient and are constant with height and time.Hence the Coriolis tendency is computed using only theageostrophic component of the horizontal winds. Horizontalhomogeneity is a significant idealization for a domain of thissize, as can be observed in the differences among the drop-sonde profiles above the BL in Figure 1. However, after de-velopment of the BL (shown later) the simulated heteroge-neous structure compares well with observations. Relativehumidity (RH) was set to a constant value of 50% as an initialcondition. Results after a few hours were insensitive to thisinitial choice so long as the overlying atmosphere was not closeenough to saturation to permit the forced vertical motions(e.g., gravity waves) to produce clouds. As in the work ofLupkes and Schultzen [1996], we imposed a gradient in seasurface temperature:

Tss~ x! 5 T0 1 bx ,

where b 5 0.019 K km21, and T0 5 Tss(0) 5 21.88C is thetemperature at the ice edge.

Unlike many CRM simulations of arctic boundary layerclouds [e.g., Olsson et al., 1998; Harrington et al., 1999a], use ofperiodic lateral boundary conditions cannot be justified due tothe surface horizontal heterogeneity and domain scale in thepresent study. Preliminary experiments using a single (notnested) CRM grid (Dx 5 80 m) showed physically unrealisticwinds near the outflow boundary. This problem arose becausethe lateral boundary formulation must deal with vertical veloc-ities of several meters per second produced both by convectiveeddies in the BL and by freely propagating gravity waves in theoverlying stable atmosphere. None of the available lateralboundary condition formulations produced satisfactory resultsat all heights.

This problem was ultimately circumvented by using a nested-grid approach with a coarser “parent grid” (grid 1, Dx 5 320m) containing the CRM (grid 2, Dx 5 80 m). In the 30 kmregion of grid 1 between the CRM and the outflow boundarythe surface heat flux was forced to a small value, and radiativeforcing was disabled. With this configuration, eddies could

easily transit from the CRM grid to grid 1, where they wouldgradually decay in intensity and propagate out the outflowboundary properly. This approach allowed convective eddies tobe correctly resolved in the region of interest (220 km , x #250 km) without sensitivity to an outflow BC formulation. Astretched grid was used in the vertical to maximize resolutionin the BL (Dz 5 40 m) while permitting the top boundary tobe dynamically well removed from the BL. A summary ofmodel geometric parameters appears in Table 1. The wholeanalysis in this paper is confined to the eddy-resolving grid 2unless otherwise noted.

3.2. Control Run and Sensitivity Studies

In the MIZ, several distinct processes have a significantimpact on the energetics and thermal structure of the BL:surface heat flux, entrainment and, in the presence of clouds,latent heat release, radiative warming at cloud base, and cool-ing near cloud top. In the presence of precipitating clouds,evaporation of larger hydrometeors in the subcloud layer mayalso have a substantial influence [Stevens et al., 1998]. Thoughthese diabatic processes can both warm and cool the BL, thevariation with height often (though not always) steepens thetemperature lapse rate and acts to destabilize the boundarylayer, which ultimately deepens by entraining air from aboveand within the inversion. The relative importance of each pro-cess to dynamic properties such as boundary layer growth andthe turbulence kinetic energy (TKE) budget depends on thespecific environment. In the case studied here, Lupkes andSchultzen [1996] have suggested that cloudiness plays a second-ary role. This is a reasonable assumption given the presence ofsuch a great initial disparity between Tss and the atmospherictemperature at the surface (Ts). This gradient produces largesurface sensible heat fluxes (near 400 W m22) which dominatethe TKE production and BL deepening in this case. A centralgoal of this study is to elucidate the importance of clouds inthis environment.

While frequently neglected by previous studies of BL pro-cesses in cold-air outbreaks, precipitation has been found toplay an important role in BL energetics and thermal stability.In other cases, where the main TKE production was due tocloud-induced radiative cooling rather than surface heating,simulated precipitation processes were shown to reduce TKEin the BL both for warm clouds [e.g., Olsson et al., 1998; Stevenset al., 1998] and for mixed-phase clouds [Rao and Agee, 1996;Harrington et al., 1999a].

To investigate the relative role clouds play in off-ice flow,several sensitivity studies were conducted using a hierarchy ofmicrophysical parameterizations of increasing complexity. The(somewhat arbitrarily defined) control (CT) run had liquidwater clouds with no precipitation processes activated. Thissimulation provides the simplest representation of clouds,

Figure 2. Diagram of the numerical experiment geometry.Regions A and B represent zones of interest over which hor-izontal averages are computed. See text for discussion of gridstructure.

Table 1. Model Geometric Parameters

Grid 1 Grid 2 (CRM)

Dx 320 m 80 mLateral domain 2303 280 km 2203 250 kmPoints in x 970 3374DzBL, m 40 40Vertical domain 03 8940 m 03 8940 mPoints in z 90 90

CRM, cloud-resolving model.

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without the added complexity of precipitation. (Simulationswere also conducted with a warm-rain (no ice species) modelthat includes precipitation [Feingold et al., 1998]. However theresults showed little difference in comparison to the no-precipitation (CT) simulations.) A similar configuration butwithout radiation effects (NR) considered the thermodynamic/dynamic impact of phase-change processes. To estimate theeffect of precipitation/evaporation and ice microphysics, amixed-phase (MP) precipitating cloud run was performed. A“dry” (DR) no-cloud simulation showed the effects of surfaceforcing in the absence of water in any phase. Table 2 containsa summary of the various runs, all of which were integrated for10 hours.

4. Results4.1. Comparison With Observations

In this section we compare our results to the dropsondeobservations collected by the REFLEX II investigators. Sinceconfidence in the accuracy of the wind and humidity measure-ments is not high (K. Lupkes, personal communication, 1999),we limit these comparisons to the thermal structure. The sim-ulated profiles are 10 km spatial and 1 hour temporal averagescentered at the respective dropsonde locations. It should benoted that since the observations are effectively “point” mea-surements, we use them as a qualitative comparison method.

Near the ice edge, the BL is shallow, and the grid resolutionis insufficient to produce physically realistic eddy motions. Inthis region the simulations with cloud have profiles (notshown) with a warm bias as compared with observations. Asimilar warm bias with shallow BL depth was shown in thetwo-dimensional simulations of Hartmann et al. [1997]. Notethat we have assumed a perfectly delineated ice-ocean marginwhich in reality corresponds to 95% ice coverage. Hence thesimulated heat flux from ice-free ocean within 10 km of the iceedge probably overestimates the actual heat flux values butbecomes more realistic at greater distances from the ice edge.

Figure 3 shows vertical profiles of simulated mean potential

Figure 3. Profiles of u at 80 km, 132 km, 188 km, and 243 km. The observed (dropsonde) profile has nosymbols. The simulated profiles represent 10 km averages centered on the dropsonde locations.

Table 2. Summary of Sensitivity Runs

RunName Radiation Cloud Representation

CT yes liquid only, no precipitationMP yes mixed phaseNR no liquid only, no precipitationDR yes no condensate

CT, control; MP, mixed phase; NR, no radiation.

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temperature (u) and dropsondes for (a) 80 km, (b) 132 km, (c)188 km and (d) 243 km. At 80 km all the simulated profiles are18 to 28 warmer than observed, but the height of the inversionbases ( zi) in the simulated profiles are within 100 m of thedropsonde profile. At 132 km the simulated u values for thevarious cases bound those of the dropsonde from the surface tonear the top of the BL. The observed zi is lower than any of thesimulated cases; however, some mesoscale variability is evidentin these profiles. Such variability is suggested by the warmingabove zi by the time the flow has reached 132 km (compareFigures 1 and 3 (top right)).

At 188 km the observed sounding shows considerable struc-ture with several thermal regimes, probably due to the sam-pling of both updrafts and downdrafts during the dropsondedescent, and is therefore difficult to compare with the numer-ical results. Note, however, that the observed zi comparesfavorably with both the dry (DR) and the mixed-phase (MP)simulations. At 243 km, near the outflow boundary of theCRM grid, the simulated profiles, not surprisingly, show thegreatest degree of variation. Here again, the observed zi isclosest to DR and MP. Overall, the observed profile is warmerthan the simulations, a trend that continues well above the BLand hints at a large-scale horizontal heterogeneity in the ob-servation domain that was not initialized in the model simula-tions.

Curiously, while the observed profiles are fairly noisy, theysuggest at almost all locations a more stable temperature lapserate than that produced by the model. (We state this withcaution because numerous observations of this case were nottaken, thus we have no knowledge of the average state of theobserved BL.) This lapse-rate disparity is true even with theCT and NR runs, which have both saturated updrafts anddowndrafts, whereas the cloud streeting and cellular structureseen in satellite images implies that the actual downdrafts werelargely dry.

The observations reported by Hartmann et al. [1997] foranother off-ice flow event in the North Atlantic also showsomewhat more stable thermal profiles than simulated in thiscase, though there, the BL was warmer, yielding a bigger dif-ference between dry and saturated adiabatic lapse rates. Thediscrepancy between observations and simulated results obvi-ously cannot be ascribed to larger-scale horizontal variations,

and we suspect that it may be due to three-dimensional dy-namics (e.g., roll vortices) not captured with this numericalapproach. This notwithstanding, our results suggest that themodel, with its inherent limitations, is doing a reasonable jobof simulating the energetics responsible for BL developmentfor this case.

4.2. Intercomparison of Control and Sensitivity Studies

For these 10 hour simulations, the mean statistics (e.g.,TKE, zi, condensate mixing ratio) were typically quasi station-ary across the grid 2 domain after 8 hours. This is consistentwith the fact that the mean BL u-wind (along domain) com-ponent of 9.8 m s21 gives a cross-domain transport time ofabout 7.5 hours for a hypothetical atmospheric column. Thisbeing the case, even though the profiles in Figure 3 are con-temporaneous, they can also be viewed as an approximate timeseries for a given volume as it traverses the domain. Thisapproach will be used in the following discussion. Further-more, we will concentrate on spatial (25 km) and temporal (1hour) averages at two specific regions, region A from 75 to 100km and region B from 200 to 225 km (see Figure 2).

The u profiles for the various sensitivity profiles in Figure 3show a consistent picture as the BL develops, with CT beingthe coolest and MP typically being the warmest. Figures 4 and5 show mean profiles of condensate mixing ratio (rc) andradiative heating rate (Qr) in regions A and B.

The simulations with liquid condensate but no sedimenta-tion (CT and NR) have rc profiles typical of nonprecipitatingarctic stratus clouds [e.g., Olsson et al., 1998]. In contrast to theslow and relatively inefficient production of drizzle-size drop-lets in liquid clouds the ice-phase processes in MP allow rapidvapor-deposition growth and aggregate collection that rapidlycreates hydrometeors with appreciable fall speeds [Harringtonet al., 1999a]. The impact of the efficient precipitation mech-anism is quite apparent, with MP showing an rc 30% or less ofthe adiabatic liquid water content profile seen in the simplerschemes. The effects of precipitation are also seen in Figure 4(region B) where, in contrast to CT and NR, precipitation nearthe surface gives a nonzero rc in the lowest few hundred metersof the domain.

The dependence of radiative heating rate on rc is clear inFigures 4 and 5, where cloud-top radiative cooling, and thus

Figure 4. Mean profiles of condensate rc averaged over 75–100 km and 200–225 km and the time period 9–10 hours.

Figure 5. Mean profiles of radiative heating rate Qr aver-aged over 75–100 km and 200–225 km and the time period9–10 hours, as in Figure 4.

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cloud-top destabilization, is shown to be much stronger in theCT case. It is also interesting to note that significant radiativewarming occurs at cloud base, especially for CT, and is causedby strong radiative emission from the warm ocean surface thatis being absorbed by the cooler cloud layer. This warming is anadded source of buoyancy generation, especially in CT. Theimpact of these diabatic processes on the horizontal meanTKE is shown in Figure 6. There appears to be a strong de-pendence of TKE on rc through the latent heating, especiallynear the top of the BL where CT and NR, with the largest rc,also exhibit the largest TKE. A moderate BL jet developed inall simulations (Figure 7). The intensity of the jet varied con-siderably with the strongest jets occurring in region B in CTand MP, the two runs with both condensate and radiativecooling.

Since cloud-top radiative cooling is strongest in CT andweakest in MP, it is tempting to conclude that this is the reasonfor the warmer BL in MP. However, this is not the case. As willbe shown later, the total radiative cooling of the BL is greatestin MP over most of the domain. The most likely reason for the

warmer BL in MP is the ice-phase processes that occur in thatsimulation. Latent heat of fusion adds more heat during thephase change process, and active precipitation removes thehydrometeor species from the cloud, sensibly heating the BL inthe process.

4.3. Mesoscale Features Near Ice Edge

One of the well-documented features of flows encounteringa rapid transition from rough to smooth surfaces is an accel-eration as the three-way balance among the pressure gradient,Coriolis, and frictional forces adjusts to the reduced drag [Raoet al., 1974], a situation that occurs here as the off-ice compo-nent of the flow moves from the relatively rough ice to theaerodynamically smoother open ocean [Overland et al., 1983;Reynolds, 1984]. Results from the one-layer model of Overlandet al. [1983] showed that this process can increase wind speedover the MIZ by about 10%, a result reproduced by the two-dimensional multilevel model of Kantha and Mellor [1989].Overland et al. [1983] suggested that the resulting divergencemay be responsible for the observed mesoscale banding of iceconcentrations in the MIZ [e.g., Muench and Charnell, 1977;Hakkinen, 1986].

Figure 8 shows contours of the off-ice flow for CT and MPnear the ice edge, with regions of horizontal convergence­u/­x , 22.0 3 1024 m21 shaded. In both cases the flowbecomes supergeostrophic with an increase of about 3 m s21

over the first 20 km of open water. This represents a largerincrease than reported by Overland et al. [1983] but is similar tothe “rough ice to open water” case in the work of Kantha andMellor [1989]. The magnitude of this increase depends on manylocal factors, including the roughness length associated withthe ice, height of inversion, and along-domain baroclinicityamong others.

Several differences are apparent in the two cases in Figure 8.The wind maxima over the ocean in MP is slightly stronger andextends much farther from the ice edge than CT. The rapid

Figure 6. Mean profiles of turbulent kinetic energy (TKE)averaged over 75–100 km and 200–225 km and the time period9–10 hours, as in Figure 4.

Figure 7. Mean profiles of the horizontal wind speed aver-aged over 75–100 km and 200–225 km and the time period9–10 hours, as in Figure 4.

Figure 8. Contours of along-domain wind u , near the iceedge for mixed phase (MP) and control (CT) at 8 hours.Regions where the horizontal divergence is less that 22.0 31024 m21 are shaded and the contour spacing is 0.5 m s21.Horizontal axis labeled in kilometers.

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deceleration and resulting convergence at about 30 km are theconsequence of “convective drag,” the efficient momentumtransfer to the surface by the stronger eddies in CT which areforced by cloud-top cooling as well as the surface heat flux. InCT the region of strong vertical shear, collocated with thethermal cap between 200 and 300 m, persists much fartheroceanward. Of all the sensitivity studies, this is seen only in CT.The strong radiative cooling associated with significant rc inthe region from 10 km onward initially inhibits vertical mixinguntil coherent eddy motions become established.

Figure 9 shows w# zi, the column-mean vertical motion belowzi, in the region about the ice margin. All runs show a pro-nounced minima in w# zi just downwind from the ice edge,consistent with Overland et al. [1983] who found a decrease inzi in this region in their simulations. (The relatively coarse40 m vertical grid spacing in this work precludes such a featuresince zi at this distance from the ice edge is only about 5 pointsdeep.) This occurs as the horizontal flow accelerates over theopen ocean, giving divergent flow (­u/­ x . 0) and effectivelyremoving mass laterally from the BL portion of the atmo-spheric column. To maintain a quasi steady state, a compen-sating downward mass flow (w , 0) must occur in this region.The region of positive w# zi between 10 and 20 km in the otherruns shown in Figure 9 was not present in CT, suggestinganother possible mechanism for the more persistent verticalshear in this case.

5. DiscussionThe results in section 4, taken together, suggest that the

dynamical nature of the BL is significantly influenced by cloudmicrophysical/radiative properties. As atmospheric columnsmove from ice to water, all runs experience their strongestsensible heat flux Fs and latent heat flux Fl. Initially, there isno cloud in any of the runs, and the main source for buoyancyproduction is diabatic forcing at the surface. Once surfacewater vapor flux has moistened the developing BL sufficiently(typically between 15 and 35 km), optically thick clouds form inthose runs where condensation is allowed. (With a more real-istic MIZ ice-coverage configuration this distance would besomewhat larger.) As rc increases, the deepening BL experi-ences an increasing radiative flux divergence (cooling) at cloudtop and a radiative flux convergence (heating) at cloud basedue to the warm underlying ocean. Both regions of radiativeforcing act to destabilize the BL.

The simulated cloud morphologies showed significant differ-ences, especially at longer fetches where the differing micro-physical parameterizations had had several hours to manifest

themselves. Wind vectors and shaded contours of rc at 9 hoursare shown in Figure 10 (top) for CT and Figure 10 (bottom) forMP. At this distance the mixed phase cloud has a lower zi andless than 100% cloud coverage. Discrete precipitation shafts, inthe form of snow, are apparent as regions of nonzero rc ex-tending to the surface. The wind vectors suggest that the cloud-scale circulations in the control (CT) run are significantlylarger, in agreement with the TKE profiles.

5.1. TKE Production

The role of cloud-top radiative forcing in TKE generation isquite evident in Figure 6, with CT showing a cloud-top TKEmaximum nearly twice as large as any of the other runs. Al-though surface forcing is the primary mechanism for BL deep-ening and TKE production (surface heat fluxes are very largeand near 400 W m22), radiation and condensation also signif-icantly affect BL depth. As Figure 3 shows, the no-radiation(NR) simulation has a BL depth that is roughly intermediatebetween that of the control (CT) and the dry (DR) simulations.The NR simulation produces a BL with generally weaker TKEthan CT, especially in the upper portion of the domain whereradiative cooling helps to drive the circulations. This attests tothe importance of both radiative heating/cooling and latentheating in generating buoyancy and deepening the BL. Thatlatent heat release is an important factor in BL deepening isseen by comparing the DR simulation with CT and NR. By the

Figure 9. Column-mean vertical motion below zi near the iceedge in centimeters per second.

Figure 10. Total condensate rc and wind vectors for (top)CT and (bottom) MP at 9 hours. Contour interval is 0.05 gkg21, horizontal axis is distance from ice edge in kilometers,and vertical axis is height above sea level (asl) in meters. Thehorizontal component of the wind is multiplied by a factor of0.1 to emphasize the sense of vertical motion.

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time the flow has reached region B, TKE is of similar strengthin both NR and DR, however NR has a deeper BL.

Compared to other simulations with clouds, however, MPhas considerably less TKE throughout a more shallow BL, eventhough significant latent heat is released. In fact, MP generallyhas less TKE than DR even though MP shows definite regionsof radiative heating and cooling (Figure 5). This demonstrates theability of precipitation to inhibit convective motions and to reduceentrainment as discussed by Stevens et al. [1998]. Overall, theseresults are broadly consistent with other simulations of mixed-phase stratus [e.g., Rao and Agee, 1996; Harrington et al., 1999a].

5.2. Surface Energy Fluxes

Figure 11 shows 20 km average values of Fs, Fl, and surfacewind speed for the period 9–10 hours for each of the runs withcloud present. In all cases, a surface (lowest predicted level)

wind maximum occurred between 20 and 30 km from the iceedge. All runs experienced a maximum Fs of almost 650 Wm22 just leeward of the ice edge, with Fs decreasing rapidly toabout 400 W m22 after 100 km of exposure to the warm oceansurface. Fl for each run also peaked at about 200 W m22

between 20 and 60 km and then decreased slowly. In all casesthe surface winds decelerated as the BL deepened with increasingfetch. Sensible heating showed much less dependence on cloudparameterization type than Fl. The relationship between Fs andwind speed is evident in Figure 11, with MP having both thegreatest wind speed and the largest fluxes at all locations.

As might be expected, a much greater sensitivity to cloudtype exists for Fl. Aside from wind speed differences, a furtherfactor contributes to the enhanced Fl seen in MP. The aver-aged rc profiles (Figure 4) in region B suggest that in contrastto CT and NR, cloud extends to the surface in MP, implyingsaturated surface conditions with respect to ice in the mixed-phase case. As seen earlier however (Figure 10), the near-surface portion of the mean rc comes from concentrated pre-cipitation shafts interspersed with subsaturated regions.Average near-surface values of water vapor mixing ratio (rv) inthis region are about 0.9 and 0.7 g kg21 for CT and MP,respectively, with MP having a mean RH less than 80% (withrespect to liquid water) in the lowest 500 m of the BL. Theability to deplete accumulated water substance through pre-cipitation evidently allows MP to maintain a larger Fl andcontinuously extract heat through condensation and deposition.

5.3. BL Depth and Bulk Energetics

Figure 12 shows averaged plots of condensate path (conden-sate mass integrated through the column) and zi for each runduring the period 9–10 hours. CT, with its strong eddies, showsthe greatest deepening due to stronger entrainment, while DRwith its smaller TKE shows the lowest zi across the domain. Asexpected, CT and NR track most closely since the physical pro-cesses are most similar. The effect of efficient solid-phase precip-itation is quite striking as MP shows both the smallest condensatepath and the smallest zi growth rates across the domain.

Figure 13 has plots of the perturbation dry static energy(DSE):

Figure 11. Averages of surface wind speed (top), latent heatflux Fl (middle), and sensible heat flux Fs (bottom) for theperiod 9–10 hours. All points represent mean values for a 20km (250 points) region centered on the point.

Figure 12. Condensate path and inversion height zi averagedspatially over 25 km increments and temporally over the period9–10 hours.

Figure 13. Integrated perturbation dry static energy (DSE)and integrated perturbation latent heating (LE) averaged as inFigure 12.

OLSSON AND HARRINGTON: SIMULATIONS OF OFF-ICE FLOW11,896

DSE 5 F E0

z~ p02225 mbar!

r~cpT 1 gz! dzG 2 DSE0 (1)

integrated vertically through the lowest 225 mbar of the do-main and then averaged spatially in 25 km increments andtemporally over the period 9–10 hours. DSE is a perturbationquantity in that the integral in (1) is computed for the initialstate (DSE0) and then subtracted to derive the perturbedvalue. The pressure depth of 225 mbar spans about 2400 m andwas purposely chosen to exceed zi in every column, thus elim-inating the contribution of entrainment of potentially warmerair across inversion. The constant pressure depth ensures, inthe hydrostatic limit, that the same amount of mass is consid-ered in each column permitting meaningful comparison be-tween simulations. The perturbation latent energy with respectto the frozen state LE,

LE 5 F E0

z~ p02225 mbar!

r~qv Lv 1 ~qv 1 ql! Lf! dzG2 LE0, (2)

was computed in a similar manner, where qv is the specifichumidity of water vapor, and ql is the liquid water specifichumidity. The sum of DSE and LE is the perturbation moiststatic energy (MSE).

The DSE is a measure of how the BL has sensibly heated.Throughout the domain, the mixed-phase run MP has thelargest DSE, while maintaining a lower zi than either of theliquid-only cloud simulations. The large DSE is the conse-quence of several factors: the greater Fs discussed earlier, theextra latent heat release due to liquid 3 ice conversions, andweaker radiative cooling near cloud top as the result of frac-tional cloudiness and depletion of rc by precipitation. Theability of MP to release latent heat and then lose hydrometeorsto the surface, as compared to the repeated recycling of con-densate through updrafts and downdrafts in the nonprecipitat-ing clouds, has an obvious effect on the DSE. The minimalimpact of latent heating without precipitation is evident in thesimilar DSE of DR and NR, while the effect of strong radiativecooling at cloud top is quite apparent when comparing CT andNR.

By far, the largest LE of all the runs is found in DR. Ofcourse, water vapor in this case is simply a passive tracer, andnone of this potential heating could be realized. In contrast,MP consistently shows the lowest LE as it was quite efficient inconverting latent to sensible heat. The DR profile is a goodestimate of the cumulative latent energy available for heatingin the no-precipitation cases but is clearly an underestimate ofthe cumulative latent energy that could be liberated in MP,since the dry downdrafts maintained a stronger Fl than waspossible in the other cases.

5.4. Radiative Energy Balance

In addition to altering BL structure, cloudiness also plays animportant climatological role in modulating the radiative en-ergy budget of the ocean surface. The top panel in Figure 14shows the net (downwelling minus upwelling) surface longwaveflux fs for CT, MP, and DR for the period 9–10 hours. CT andDR represent two possible extremes, though in all cases thesurface is cooling through radiative exchange as Tss is muchwarmer than the overlying atmosphere. In cloudless DR thesurface loses near 150 W m22 through longwave emission. Theradiative properties of liquid clouds in CT represent another

extreme. Here optically thick clouds greatly inhibit radiativecooling, and net longwave losses are reduced to less than 50 Wm22.

The alterations in cloud structure produced by ice precipi-tation in MP result in fs intermediate to CT and DR. Initially,both CT and MP have similar surface fluxes, but the moretenuous, broken cloud deck in MP significantly affects thesurface radiative budget in the region from the ice edge toabout 150 km, illustrating the indirect impact of cloud struc-ture on the convective BL. In the region from 150 to 250 kmthe surface radiative losses in CT and MP are nearly identical.Although broken cloud cover in MP here does allow a certainpercentage of the surface to radiate freely to space, anotherportion of this region has optically thick precipitation shaftsthat extend to the surface. These surface regions “experience”a warmer atmosphere, both because the BL is warmer in MPthan CT and because the neutral to superadiabatic lapse ratehas temperatures decreasing rapidly with height. That theseregions of clear-sky cooling and low cloud base warming es-sentially cancel in this portion of the domain to produce aneffect similar to CT in this region of the domain is thus coin-cidental.

Radiative energy exchange also has a significant impact onthe overall heating of the BL. The bottom panel of Figure 14shows 20 km averages of integrated net flux divergence:

F i 5 E0

zi ­f

­ z dz ,

which is the rate of total radiative energy gain (or loss) in theBL. The cloudless BL in DR shows a deficit of only a few Wm22. In CT, total radiative loss of the BL is greatest at about30 km and decreases with distance from the ice edge. Thereason for this decrease is that the total amount of radiativeheating at cloud base increases, while the total amount of cloudtop cooling remains approximately constant, as the cloud ad-vects further over the open ocean (Figure 5). This effect is dueto the fact that close to the ice edge (Figure 4) the cloud isquite optically thick near the ocean surface, and this producesa narrow region of radiative heating at cloud base. At furtherdistances from the ice edge, cloud base is much more tenuousand less optically thick, thus the heating from the surface

Figure 14. Net surface longwave flux fs (top) and integratednet flux divergence, FI (bottom) averaged spatially over 20 kmincrements and temporally over the period 9–10 hours.

11,897OLSSON AND HARRINGTON: SIMULATIONS OF OFF-ICE FLOW

(which is stronger because of the warmer temperatures) iseffectively absorbed over a greater depth.

In the case of MP the opposite is apparently true. Figure 5shows that the amount of radiation absorbed from the surfacedoes not change much, while cloud top cooling continues toincrease as the cloud is advected farther over the ocean. Thusas Figure 14 shows, radiative cooling of the BL increases withdistance from the ice edge. It is apparent from these resultsthat the warmer BL for case MP shown in Figure 3 (bottomright) must be largely due to greater latent heat release causedby the existence of the ice phase.

6. Summary and ConclusionsThe results presented demonstrate the complex interactions

between microphysical processes and cloud-scale dynamicsthat produce the atmospheric BL thermal structure found overthe MIZ in off-ice flow. The two-dimensional cloud-resolvingsimulations presented here, while lacking the three-dimen-sional roll structure seen in observations of this and othercold-air outbreaks, were able to produce a BL evolution similarto the observations. The model also reproduced many otherfeatures seen in such cases, such as supergeostrophic flow nearthe ice edge and a weak BL jet.

All u profiles consistently show a superadiabatic layer in thelowest 200 m, a consequence of Fs . 300 W m22 over thewarm ocean. The control (CT) and no-radiation (NR) runsboth have a significant liquid water content and accompanyingmoist-adiabatic profile. The dry run is nearly neutral through-out the BL, and the mixed-phase case, with its broken cloudcover, also has a nearly dry-adiabatic mean thermal profile.Radiative heating of the cloud near cloud base and coolingnear cloud top along with latent heat release were found to besignificant sources of the TKE even in the present case wherevery strong surface heat fluxes occur.

Sensitivity studies of cloud type showed that inclusion ofmixed-phase microphysics had a large impact of BL depth andstructure. Ice-phase precipitation processes rapidly depletedthe BL of condensate, weakening the radiative thermal forcing.A further consequence of condensate depletion was the abilityof the mixed-phase cloudy BL to maintain a larger surfacelatent heat flux. This ultimately resulted in a warmer BL andwould also act to cool the ocean surface, though such impactswere not considered in this study. Not surprisingly, the pres-ence of clouds had a profound impact on the radiative budgetat the surface, with the cloudy BL reducing surface radiativelosses more that 60% over clear-sky values. Inclusion of the icephase significantly affected the radiative budget as comparedto purely liquid clouds, illustrating the importance of ice-phase–radiative couplings for accurate simulations of arcticclouds and boundary layer dynamics.

In summation, it is clear that cloud dynamical processes canplay an important role in the boundary layer over the marginalice zone, even in cases of strong surface forcing. To be physi-cally accurate, numerical models need to account for this.Beyond their most obvious role in the regional or global radi-ative budgets, clouds impact on dynamical processes, such asTKE production, surface shearing stresses, and surface fluxesin a climatically significant way.

Acknowledgments. This work was supported by the InternationalArctic Research Center. Some of the modeling and analysis softwareused herein was developed under the support of NSF grant OPP-

9732733 and from the Arctic Region Supercomputing Center and SGICray Research University Research under Development Grant Pro-gram 50115-366270. We would also like to acknowledge the support ofthe Alaska Experimental Forecast Center, University of Alaska, An-chorage, during preparation of this manuscript.

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J. Y. Harrington, Geophysical Institute, University of Alaska, Fair-banks, Alaska 99701.

P. Q. Olsson, Alaska Experimental Forecast Facility, 2811 MerrillField Drive, Anchorage, Alaska 99501. (olsson@aeff.at.uaa.alaska.edu)

(Received March 12, 1999; revised October 6, 1999;accepted November 19, 1999.)

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