JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 108, NO. D10, 4312, doi: /2002jd002643, 2003

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1 JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 108, NO. D10, 4312, doi: /2002jd002643, 2003 Two-dimensional cloud-resolving modeling of the atmospheric effects of Arctic leads based upon midwinter conditions at the Surface Heat Budget of the Arctic Ocean ice camp Michael A. Zulauf and Steven K. Krueger Department of Meteorology, University of Utah, Salt Lake City, Utah, USA Received 11 June 2002; revised 25 November 2002; accepted 13 February 2003; published 29 May [1] A two-dimensional cloud-resolving model (CRM) is employed to examine the development of the convective plumes that may form in the vicinity of arctic leads and the impacts such plumes have upon the large-scale surface heat budget. Numerous observations of varying types from the Surface Heat Budget of the Arctic Ocean (SHEBA) project were used to construct an idealized clear-sky midwinter case. In a simulation containing a 3.2 km lead under the idealized conditions, a convective plume penetrated the extremely stable boundary layer to a depth of approximately 200 m, and a near-surface ice cloud propagated at least 50 km downwind. It is notable that similar cloud features were also observed at the SHEBA site near the times when active leads were in the vicinity, though it has not been established that they are, in fact, related. Vertical mixing and lead-induced circulations approximately doubled the simulated nearsurface wind speed over the lead, greatly increasing the turbulent heat fluxes compared with the initial conditions. The lead-generated plume increased downwelling longwave radiation significantly, substantially modifying the heat budget over the snow/ice surface. Results were compared with the commonly utilized large-scale mosaic parameterization. Owing to the lack of resolved leads and separate over-lead and oversnow profiles the mosaic simulation generated a shallower surface-based plume with fundamental differences in the surface heat budget. Finally, a small number of sensitivity experiments were run to investigate the relative importance of lead width, ice cover on freezing leads, and humidity of the ambient environment. Variations in these parameters had substantial impacts upon the turbulent heat fluxes above the lead and the cloud radiative forcing upon the downwind snow/ice surface. Typically, it was the balance between these two components that determined whether the large-scale net upward surface heat flux was impacted in a positive or negative sense. INDEX TERMS: 3307 Meteorology and Atmospheric Dynamics: Boundary layer processes; 3314 Meteorology and Atmospheric Dynamics: Convective processes; 0312 Atmospheric Composition and Structure: Air/sea constituent fluxes (3339, 4504); 3337 Meteorology and Atmospheric Dynamics: Numerical modeling and data assimilation; 3349 Meteorology and Atmospheric Dynamics: Polar meteorology; KEYWORDS: Arctic leads, convective plumes, surface fluxes Citation: Zulauf, M. A., and S. K. Krueger, Two-dimensional cloud-resolving modeling of the atmospheric effects of Arctic leads based upon midwinter conditions at the Surface Heat Budget of the Arctic Ocean ice camp, J. Geophys. Res., 108(D10), 4312, doi: /2002jd002643, Introduction [2] s are quasi-linear openings within the interior of the polar ice pack, primarily formed by ice deformation due to stresses incurred on the ice surface by winds and ocean currents. s may range in width from less than a meter up to tens of kilometers, and in length from hundreds of meters to hundreds of kilometers. Despite their typically Copyright 2003 by the American Geophysical Union /03/2002JD small widths, which cannot be directly resolved by largescale models, arctic leads can have a major impact upon the large-scale surface heat budget. [3] Whereas the open water or thin ice of recently formed leads typically only occupy 1 2% of the surface area of the central Arctic, they may be the dominant source of heat for the atmosphere during the arctic winter [Maykut, 1982]. Because of the extreme air-sea temperature differences (up to 40 K or more), very large fluxes of heat and moisture have been observed over leads. Andreas et al. [1979] measured sensible and latent heat fluxes in excess of 400 ACL 7-1

2 ACL 7-2 ZULAUF AND KRUEGER: MODELING THE EFFECTS OF ARCTIC LEADS Wm 2 and 130 W m 2, respectively, and larger values of fluxes are assumed under more extreme conditions. These enhanced fluxes often lead to the formation of convective plumes that may penetrate to substantial heights; under exceptional conditions they may rise thousands of meters and persist for hundreds of kilometers downwind [Schnell et al., 1989]. In addition to the direct effects of the nearsurface heat and moisture contained within the plumes, both liquid and ice phase condensate may have an impact upon the heat budget through radiative effects, even far removed from the original lead. -induced plumes have even been observed in NOAA and DMSP infrared satellite imagery [Fett et al., 1994]. Whereas most leads are on the order of m wide, during times of significant ice divergence they can reach widths of several kilometers: It is from these widest leads that the most persistent plumes can be expected. Large-scale lead-induced cloudiness of this type can significantly alter the surface IR radiation budget [Curry et al., 1993]. [4] A number of numerical modeling studies have focused upon different facets of the air-sea-ice interactions that occur in the vicinity of leads. Some examined the turbulent fluxes themselves over the leads, and how they might be parameterized in large-scale models in which the leads are not explicitly resolved. Alam and Curry [1997] developed a fetch dependent model to calculate surface fluxes, based upon a sea state parameterization and surface renewal theory. Alam and Curry [1998] further extended this work to include the freezing process, which again modifies the surface fluxes. Andreas and Cash [1999] analyzed observational data sets to determine the relationship between lead size and the transition from forced to free convection. Using this, they also developed a new algorithm for calculation of the turbulent fluxes of sensible and latent heat above leads. [5] Plume penetration height has been researched in several studies. Pinto et al. [1995] used a one-dimensional second-order turbulence closure model to simulate the development of a cloudy thermal internal boundary layer as cold environmental air flows over a wide lead or polynya, and also studied the impacts of microphysical and radiative processes upon this boundary layer [Pinto and Curry, 1995]. Glendening and Burk [1992] and Glendening [1994] used a three-dimensional large-eddy simulation (LES) model without clouds or radiative fluxes to investigate in detail the convective plumes that were generated over a 200-m-wide lead. They specifically examined the effect of varying the orientation of the large-scale wind to the lead upon plume penetration height. Alam and Curry [1995] utilized a two-dimensional lead-resolving model, also without clouds or radiative fluxes, to investigate the time evolution of the lead-induced circulations, and how they varied with lead width. [6] Burk et al. [1997] used a steady state two-dimensional boundary layer model, which did include clouds and radiative effects, to examine the development of the lead-induced plume not only directly above the lead, but downwind as well. They examined the ambient atmospheric conditions that could either aid or retard the formation of condensate plumes, and the effects that the freezing process might have upon these plumes. Zulauf and Krueger [2003] used a two-dimensional cloud-resolving model to investigate various factors which impact the depth to which the convective plumes penetrate; the factors included lead width, presence and nature of ambient winds, and inclusion of interactive radiative and microphysical effects. Parameterizations for predicting plume penetration height were investigated. [7] All of the aforementioned modeling studies dealt with the effects of plumes in the immediate vicinity of the lead; none examined the large-scale effects of leads upon the surface heat budget. In addition, none of the relatively few observational studies of leads and lead-induced plumes [e.g., Schnell et al., 1989] assessed their large-scale impacts on the heat budget. To better understand the large-scale effects of leads, we employed the two-dimensional University of Utah Cloud Resolving Model (UU CRM). Simulations were based on observations from the year-long Surface Heat Budget of the Arctic Ocean (SHEBA) experiment [Uttal et al., 2002]. The main component of the SHEBA experiment was the ice camp centered on a ship frozen into, and drifting with, the arctic ice pack. The experiment utilized surfacebased, aircraft, and satellite observations. [8] The large-scale atmospheric effects of leads are thought to be maximized during clear-sky, wintertime conditions. Under these conditions the radiative impacts of lead-induced cloudiness on the surface heat budget may be significant over a wide area. Because of this, our simulations were based upon conditions observed during a clear-sky period in mid January 1998 at the SHEBA ice camp. During this period a major ice-divergence event opened numerous leads in the vicinity of the ice camp. 2. Model Description [9] The University of Utah Cloud Resolving Model, first developed at UCLA by Krueger [1985], is used in this study. This model has been employed in numerous instances to investigate a wide variety of cloud systems [e.g., Krueger, 1988; Krueger and Bergeron, 1994; Krueger et al., 1995; Krueger, 2000; Zulauf and Krueger, 2003]. In particular, Zulauf and Krueger [2003] provide detailed information about the version used in this study, as well as further information on model validation, microphysics and radiation components, and capabilities of the thirdmoment turbulence closure. Additional modifications used in this study are described below. [10] Owing to very limited availability of information on large-scale forcing at the SHEBA ice camp (e.g., large-scale pressure gradients, advective tendencies of momentum, moisture, temperature, etc.) and the variations in surface conditions over a wide area, it was found to be very difficult to precisely match the simulated large-scale winds with those observed (particularly near the surface). Because of this, the Coriolis and large-scale pressure gradient accelerations were replaced with nudging terms in the horizontal momentum equations. Nudging applies accelerations to the wind fields to force the large-scale (i.e., horizontally-averaged) wind components toward observed or reference values. For example, the x velocity equation hi ¼... hui u n ; ð1þ t n

3 ZULAUF AND KRUEGER: MODELING THE EFFECTS OF ARCTIC LEADS ACL 7-3 where hui is the ensemble-mean (resolved scale) x velocity, hui is the horizontally averaged value for hui, u n is the observed or reference value of u that we wish to nudge toward, and t n is the nudging relaxation timescale. For the purposes of this study, t n was set to 2 h, a value that seems adequate to maintain the desired large-scale wind fields under relatively undisturbed conditions, yet does not overly constrain the solutions under changing conditions. An analogous equation governs the y velocity. All other largescale forcing tendencies (temperature, humidity, etc.) were set to zero. [11] For the two-dimensional simulations described herein, the horizontal grid spacing was 200 m. The vertical resolution was variable, with a minimum vertical spacing of 12 m at the surface, and an average vertical spacing of 18 m. The horizontal domain size was 51.2 km, and the vertical extent of the model was 1440 m (though the radiative component was supplemented with an arctic winter profile extending from the top of the CRM to the top of the atmosphere). In the simulations examined here, lead-generated plumes were confined to the lowest few hundred meters. Internal gravity waves, however, do propagate upward to the model top, and can be reflected. Fortunately, the strongest motions associated with gravity wave modes occurred at middle levels of the model domain. They had very little impact upon the wind fields near the surface, the area of interest. Based upon comparisons with different domain depths, which result in different gravity wave reflection characteristics, reflected gravity waves did not appear to affect the results significantly in the surface and near-surface regions. The lateral boundaries are periodic, and the top and bottom boundaries are rigid. The dynamics time step was 1.25 s; the time step for the radiative and snow/ice temperature profile calculations was 120 s. The simulations were run for 2 h, but most statistics were obtained at 1.5 h, which is approximately the time when the leadinduced plume began to wrap around the domain. 3. Predicting the Snow/Ice Surface Temperature [12] Most previous studies that investigated the impacts of lead-induced circulations simply ignored the surface energy balance. They typically specified a constant temperature for the snow/ice surface [Glendening and Burk, 1992; Burk et al., 1997], and not allowed it to evolve under changing conditions. Alternatively, some models, such as that of the ECMWF treat the snow/ice as an isothermal slab [e.g., Beesley et al., 2000]. Even though the temperature in the slab is allowed to evolve, it responds extremely slowly to varying atmospheric conditions. Whereas these simple methods are likely to be adequate for examining the local plume dynamics, they are insufficient for investigating the effects of leads on the surface heat budget over a large area. [13] In reality, the wintertime sea ice is typically covered with a layer of highly insulating snow. Because of this, the snow surface temperature rapidly responds to changing atmospheric conditions. To determine the evolving surface temperature we modified the CRM to diagnose it using the energy balance at the surface: The conductive heat flux through the snow/ice is balanced by the surface fluxes of Figure 1. Conductive heat flux at surface is calculated using the internal snow/ice temperature profile, which is integrated in time using the one-dimensional heat equation. longwave radiation and turbulent fluxes of sensible and latent heat [e.g., Ebert and Curry, 1993]: F cd ¼ ðir " IR # ÞþS þ E: ð2þ In equation (2), F cd is the conductive heat flux at the airsnow interface, IR" and IR# are the upward and downward IR radiative surface fluxes, S is the surface sensible heat flux, and E is the surface latent heat flux. The surface temperature T sfc is diagnosed to ensure that equation (2) is satisfied. As the simulations are designed to approximate wintertime arctic conditions, solar radiation is not present. [14] With the exception of IR#, all of the terms in equation (2) depend directly on T sfc ; obviously, the budget can not be accurately modeled by treating this variable as a constant. Within the CRM s radiation model, IR" and IR# are the broadband fluxes, covering the portion of the wavenumber spectrum from 1 to 2200 cm 1. As with all atmospheric models that incorporate non-trivial domain sizes, it is not feasible to resolve all relevant scales of motion, thus the turbulent fluxes S and E are diagnosed by a bulk aerodynamic surface flux parameterization [Deardorff, 1972; Businger, 1973; Zulauf, 2001]. The conductive heat flux through the ice and snow, F cd, is a function of the internal temperature profile, which must be modeled prognostically. Because the vertical temperature gradients in the snow/ice layers are much larger than the horizontal gradients (with the exception of the limited areas on the margins of leads), the internal temperatures may be integrated in time using the one-dimensional heat conduction ¼ 2 ; where r, c, and k are the local values of density, heat capacity, and thermal conductivity for the ice and snow layers (these are specified in section 4.) Similarly, T and F cd represent local values of temperature and heat flux in the snow/ice layer. The boundary conditions are given by T melt, the temperature of the seawater beneath the ice, and T sfc, which is diagnosed as described above to satisfy equation (2). The surface heat budget is displayed schematically in Figure 1. ð3þ

4 ACL 7-4 ZULAUF AND KRUEGER: MODELING THE EFFECTS OF ARCTIC LEADS Figure 2. Surface fluxes over ice-covered leads as a function of ice thickness. [15] To integrate equation (3), a relatively simple procedure is adequate, because the internal temperature profile does not evolve quickly, and is typically smooth. The profiles are discretized with 10 points specified in the ice layer and 10 points in the snow layer. The implicit and unconditionally stable Crank-Nicolson method [Chow, 1983] is used to advance the solution with a 120 s time step. The vertical resolution within the snow and ice pack is determined by the thickness of these layers, as given by section 4. The initial temperature profiles in the ice and snow layers are specified to be in equilibrium with the atmospheric and radiative conditions present at simulation initiation. This simply means that the conductive heat flux through the snow/ice layers is constant in the vertical (i.e., linear profiles in each layer, no time rate of change), and that the conductive heat flux at the surface is balanced by the net upward heat flux into the atmosphere. We found that for simulations of the type we investigated, the top several cm of the snow layer respond quickly to changing ambient conditions, and thereafter the simulations were not overly sensitive to the temperature profiles below. Additionally, numerous tests of the snow/ice temperature model were completed to verify the fidelity of this component. By supplying the model with specified forcing and comparing with analytical solutions, we were able to confirm that the system correctly conserves heat, recovers the equilibrium temperature profile dictated by constant conditions, and responds to changing conditions on the appropriate diffusive timescales. [16] An additional benefit of predicting the surface temperature in this way is the easy investigation of the impacts of lead freezing upon the surface fluxes. While the CRM does not explicitly include the freezing process, by specifying thin ice layers with no overlying snow (essentially snapshots during the freezing process), we can examine the impacts of freezing upon the surface heat budget, For thin layers, the temperature profile will be very near equilibrium with the environment; this means that the time rate of change of temperature within the profile will be very nearly zero, as will also be the vertical gradient of the conductive heat flux. Figure 2 displays the equilibrium surface fluxes above a lead covered by various ice thicknesses. [17] The ambient conditions used to calculate this balance were fairly typical of the clear-sky midwinter conditions observed at the SHEBA site (e.g., E. L. Andreas et al., SHEBA: Tower, 20m flux multi-level msmts (PRELIMI- NARY), , 1999): IR# = 140 W m 2, T air = 240 K, RH = 80% with respect to liquid water, a 10-m wind speed U of 5 ms 1, and a surface roughness z 0 of 0.2 mm. As the ice thickness goes to zero, T sfc approaches T melt, the surface sensible heat flux S is greater than 430 W m 2, the latent heat flux E is approximately 100 W m 2, IR" is greater than 300 Wm 2, and thus the conductive heat flux at the surface F cd (also the net surface heat flux) is approximately 700 W m 2. Owing to the exponential dependence of the saturation vapor pressure upon temperature, the latent heat flux decreases much more rapidly as the ice thickness increases (proportionately) than the other fluxes. For a layer of ice 2.5 cm thick, S decreases approximately 22% when compared with an uncovered lead; the fractional decrease in E is twice as high at 45%. 4. Observed Conditions at SHEBA Ice Camp and Model Initialization [18] The SHEBA project made available a broad spectrum of observation types, many of which are useful for initializing, forcing, and evaluating numerical simulations. During the clear-sky ice-divergence period of interest to this article, however, we found that we could not truly design a complete case study which would include all of the types of data that we would require for forcing and evaluation. Instead, we decided to use what was available to develop a simulation under typical conditions Model Initialization [19] Several types of observations were used to initialize the CRM. A number of instrument platforms were available (portable automated mesonet or PAM sites, rawinsondes, flux tower, etc.) to specify the atmospheric state. We decided that rawinsondes would be the primary data source because of the direct nature of their measurements of the atmospheric column. We examined atmospheric soundings from rawinsondes (R. E. Moritz, Soundings, PRELIM Ice Camp NCAR/GLAS raobs (ASCII), edu/cgi-bin/codiac/dss?13.202, 1999) for the month of January The similarity of the soundings under clear-sky conditions was evident. [20] Figure 3 displays the air temperature, relative humidity, wind speed, and wind direction profiles observed at the SHEBA ice camp (approximately 74.8 N, W) on 18 January These were typical of this time period. The dashed lines indicate the simplified profiles used to initialize the CRM. Note that the profiles have been simplified to a larger extent for the relative humidity and the wind direction. They were the most variable compared with other quantities observed during similar clear-sky conditions. The simplified profiles are fairly representative of the average conditions. [21] Some interesting features are apparent in Figure 3. The temperature profile displays a surface-based inversion with a temperature increase of approximately 10 C in the lowest 250 m. From that level up to 1000 m, the atmosphere is nearly isothermal. Because of the extremely stable strati-

5 ZULAUF AND KRUEGER: MODELING THE EFFECTS OF ARCTIC LEADS ACL 7-5 Figure 3. Observed atmospheric soundings from SHEBA rawinsondes for 18 January 1998, 2316 UTC. Dashed lines indicate the simplified profiles used in initializing the CRM. fication, it is unlikely that convective plumes will be able to penetrate to large altitudes. [22] Figure 3 shows that there is significant vertical wind shear in both speed and direction. Vertical mixing due to leadinduced convection would increase the near-surface wind speeds, thereby increasing the magnitude of the turbulent surface fluxes. The low near-surface wind speed and strong vertical shear is also confirmed by flux tower measurements (E. L. Andreas et al., SHEBA: Tower, 20m flux multi-level msmts (PRELIMINARY), codiac/dss?13.101, 1999), which show typical wind speeds at the 2.5 m level ranging from 2 to 3 m s 1. The wave-like patterns in the rawinsonde s wind speed and direction profiles are most likely the result of internal gravity waves. [23] As we emphasized in section 3, the surface heat budget (i.e., surface temperature) depends upon the thicknesses of the ice and snow layers. At the SHEBA ice camp, thickness measurements of ice (D. Perovich, SHEBA: Ice Camp (PRELIMINARY) Ice Thickness msmts, ) and snow (D. Perovich, SHEBA: Ice Camp (PRELIMINARY) Snowdepth msmts, dss?13.511, 1998) were made at a number of PAM sites. Measured ice thicknesses ranged from less than 1 m above recently refrozen leads to more than 3 m in areas of ridging. The snow depth varied from less than 10 cm to nearly 1 m. We used typical values of 2 m of ice and 30 cm of snow for simulating a mid January case. [24] In order to use equation (3) to simulate the evolution of the internal temperature and heat flux profiles, values are needed for r, c, and k for both the ice and snow layers. Whereas Ebert and Curry [1993] used temperature-dependent values of these thermodynamic quantities, we decided that for our short duration simulations, constant values would be adequate. On the basis of the ambient conditions and the parameterizations utilized by Ebert and Curry [1993], the density, heat capacity, and thermal conductivity for the ice layer were assigned values of kg m 3, J kg 1 K 1, and 2.0 W m 1 K 1, respectively. For the snow layer, the values obtained in this way for density and heat capacity were kg m 3 and J kg 1 K 1. In addition, measurements were made at SHEBA of bulk snow thermal conductivity [Sturm and Holmgren, 1999]. On the basis of the measurements and upward revisions to account for the effect of in-snow convection (M. Sturm, private correspondence, 1999), we used the value of 0.2 W m 1 K 1. This value of k is somewhat lower than most measured values. This can be ascribed to the existence of unusually large quantities of depth hoar in the snow pack formed by the extreme temperature gradients across the layer. [25] The surface flux parameterization depends upon surface roughness. Over the snow/ice surface, the roughness can vary with many factors: ridging, broken ice, snow drifts, etc. Since these factors are not easily accommodated on simulations of this scale, the bulk value measured under similar conditions during the LEADEX experiment was

6 ACL 7-6 ZULAUF AND KRUEGER: MODELING THE EFFECTS OF ARCTIC LEADS Figure 4. The 60 km 60 km SAR images from (a) 17 January and (b) 20 January 1998 (rotated so north is at top). The ship is at center. Note the large wedge-shaped lead several kilometers to the east. Copyright # 1998 by Canadian Space Agency. used, m[persson et al., 1997]. For reasons of expediency, we used a constant value of m over the water surface of an open lead, rather than a fetch or seastate-dependent value such as used by Alam and Curry [1998]. Finally, the surface temperature of the water is defined as a constant, 2 C, because the CRM does not presently simulate the lead freezing process Observations of s During SHEBA [26] Owing to the perpetual darkness of the polar winter, very few direct observations of wintertime leads are available from SHEBA. The existence of leads, as well as their size and location, were verified, however, through the use of various types of remote sensing. Very detailed images were obtained through the use of synthetic aperture radar (SAR) (RADARSAT Images of SHEBA, distributed by H. Stern, Copyright # 1998 by Canadian Space Agency, SAR imagery processed at the Alaska SAR Facility (Fairbanks) and distributed through the SHEBA Project Office (Seattle)). Figure 4 displays SAR imagery from the Canadian RADARSAT satellite for 17 January and 20 January [27] These images clearly display the opening of a large lead approximately 15 km to the east (and approximately upwind based on the large-scale wind field) of the SHEBA ice camp. In the second image, the lead has attained a width of up to 8 km, though the portion directly upwind of the ice camp is closer to 3 4 km wide. In addition, other leads have opened in the vicinity as well. Furthermore, the rawinsonde data (as well as the PAM station data, etc.) show that the predominant large-scale surface wind is from a northeasterly direction, so that the near-surface air crossed the large lead (and others nearby) nearly perpendicularly prior to reaching the SHEBA site. Satellite IR imagery may also be used to provide useful information of lead coverage over wide areas. [28] For atmospheric and surface conditions such as these, it would not be surprising to see some signature of the large leads and associated convective plumes in the observations at the ice camp. Lidar imagery (J. Intrieri, SHEBA: LIDAR, ETL DABUL System; Quick-look PRELIMINARY data from Ice Camp, dss?13.302, 1999) from 20 January (Figure 5), displays a possible consequence of the large new openings in the ice. A low-level cloud layer was observed from approximately 0400 UTC to 2000 UTC. The cloud base was typically 100 to 200 m above the surface, with a thickness of up to approximately 200 m. Unfortunately, owing to the localized nature of the observations taken at the SHEBA site, it is impossible to know for certain if these clouds are indeed related to the lead activity. 5. Resolved Simulation [29] On the basis of the conditions described in section 4, a series of simulations was executed. The basic simulation featured a 3.2-km-wide lead in a 51.2 km domain. The lead fraction of 6.25% is larger than the average value of 1 2%, but may be more representative of the conditions during icedivergence events such as that observed near the SHEBA ice camp around 20 January The orientation of the simulated lead relative to the large-scale wind field corresponds to that of the large lead that occurred upwind of the SHEBA site. [30] Figure 6 displays vertical cross sections from the basic simulation described above; the fields are displayed at 1.5 hours and include the change from the initial conditions in water vapor mixing ratio, the total cloud ice mixing ratio, the change in potential temperature, and the net upward IR

7 ZULAUF AND KRUEGER: MODELING THE EFFECTS OF ARCTIC LEADS ACL 7-7 Figure 5. Lidar imagery from the SHEBA site for 20 January radiative flux. The potential temperature and the mixing ratios have increased to heights of about 200 m; effects observed above 200 m are primarily due to gravity waves, which propagate vertically and approximately 20 km downwind. An elevated plume composed primarily of cloud ice extends approximately 45 km downwind of the lead. Though the lead-induced plume is in general mixed-phase, the vast majority of the condensate is in the form of cloud ice. The cloud ice mixing ratio is typically over 1 order of magnitude greater than the snow mixing ratio, and more than 2 orders of magnitude greater than the liquid cloud water mixing ratio. The plume s radiative signature is seen Figure 6. Contour plots displaying results from the basic resolved lead simulation at 1.5 hours: (a) change in water vapor mixing ratio from initial conditions (g kg 1 ), (b) cloud ice mixing ratio (g kg 1 ), (c) change in potential temperature ( C), and (d) net upward longwave radiative flux (W m 2 ).

8 ACL 7-8 ZULAUF AND KRUEGER: MODELING THE EFFECTS OF ARCTIC LEADS Table 1. Average Surface Fluxes Over s for Various Simulations a Initial Resolved Mosaic 1.6-km 6.4-km Thin Ice Low RH S ld E ld IR" ld IR# ld Net IR ld Net " flux a All values are in W m 2. The columns correspond with the following simulations: the initial conditions for the basic simulation, the basic resolved lead simulation, the mosaic method parameterization, a 1.6- km-wide resolved lead, a 6.4-km-wide resolved lead, a resolved lead covered by a thin 2.5-cm ice layer, and a resolved lead with a lower initial relative humidity. Except for the initial column all results are calculated at 1.5 hours. Table 2. Average Surface Fluxes Over Snow/Ice for Various Simulations a Initial Resolved Mosaic 1.6-km 6.4-km Thin Ice Low RH S ice E ice IR" ice IR# ice Net IR ice Net " flux a All values are in W m 2. Columns refer to simulations as described in Table 1. Table 3. Large-Scale Surface Flux Averages for Various Simulations a Initial Resolved Mosaic 1.6-km 6.4-km Thin Ice Low RH S ls E ls IR" ls IR# ls Net IR ls Net " flux a All values are in W m 2. Columns refer to simulations as described in Table 1. in the plot of the net upward IR. Downwind of the lead over the snow/ice surface, increased downward IR emissions from the atmosphere (due to the cloud ice plume) have substantially decreased the net upward IR flux at the surface. Even though the ambient conditions, modeling assumptions, and lead characteristics are rather different than those of Burk et al. [1997], the lead-generated plumes of that study share some similar characteristics with that shown in Figure 6; these similarities include plume penetration height, downwind extent of the plume, and condensate mixing ratios. There are significant differences, however, though these could easily be explained by differences in atmospheric conditions. [31] Whereas Figure 6 displays the effects of the leadinduced plume at 1.5 hours in a qualitative sense, Tables 1, 2, and 3 quantify them. [32] In each of these tables, the first column of numbers, labeled initial, refers to the initial conditions for the basic simulation described above; the second column, labeled resolved, corresponds with values obtained by the basic simulation at 1.5 hours. Subsequent columns will be addressed in following sections. Table 1 shows the sensible, latent, upwelling longwave, downwelling longwave, net longwave, and net upward heat fluxes at the surface averaged over the lead. Tables 2 and 3 display the same fluxes, except averaged over the snow/ice surface or over the surface of the entire domain, respectively. [33] The initial results are included for the purpose of comparison with the resolved lead simulation, as well as those of the other simulations. The values in the initial columns are those calculated at the initiation of the simulation, and as such no feedbacks exist between the overwater fluxes and the over-snow fluxes. None of the other feedbacks yet exist that might modify the fluxes over time in the resolved lead simulation (cloud radiative forcing, increased levels of water vapor, lead-induced circulations, etc.) It is worth noting that the fluxes are also the same as would be calculated over unbroken water surfaces (with no adjacent snow/ice), and over unbroken snow/ice surface (with no adjacent water). [34] Over the lead, the surface sensible heat flux is extremely large, 486 W m 2 initially and 691 W m 2 after 1.5 hours. The latent heat flux, though only about one quarter the magnitude, is also very significant and increases similarly. The large upward radiative flux is due to the warmth of the water surface, which does not change. The downwelling radiative flux increases as a plume develops over the lead, but even at 1.5 hours it is only approximately half the upwelling value. The warmth of the plume is due in part to the heat released by the lead, and in part due to its elevated location within the thermal inversion. Summing these components yields extremely large values for net upward heat flux at the surface, 779 W m 2 at initiation, and 1000 W m 2 at 1.5 hours. [35] To further illustrate the complex nature of the surface heat budget and its associated feedbacks, Tables 4 and 5 include some quantities which determine the magnitudes of the fluxes shown in Tables 1 3. These quantities include the near-surface wind speed U, the near-surface air temperature T air, the surface temperature T sfc, and the sky temperature T sky. T sky is simply the blackbody temperature for the downwelling IR at the surface (assuming an emissivity of unity). Table 4 displays these quantities averaged over the leads, while Table 5 shows them averaged over the snow/ice surface. [36] The fluxes shown in Table 2 over the snow/ice surface are radically different from those over the lead. Initially, the average surface temperature of the snow is Table 4. Relevant Quantities for Forcing Fluxes, Averaged Over s for Various Simulations a Initial Resolved Mosaic 1.6-km 6.4-km Thin Ice Low RH U, ms T air, K T sfc, K T sky, K a Columns refer to simulations as described in Table 1.

9 ZULAUF AND KRUEGER: MODELING THE EFFECTS OF ARCTIC LEADS ACL 7-9 Table 5. Relevant Quantities for Forcing Fluxes, Averaged Over Snow/Ice for Various Simulations a Initial Resolved Mosaic 1.6-km 6.4-km Thin Ice Low RH U, ms T air, K T sfc, K T sky, K a Columns refer to simulations as described in Table 1. approximately 43 C; after 1.5 hours the average surface temperature of the snow has risen to 40 C. This leads to surface sensible heat fluxes of 15 W m 2 and 14 W m 2 at initiation and after 1.5 h, respectively, and surface latent heat fluxes of 0 and 1 Wm 2. Owing to the lower IR" (relative to the lead), the net IR is much lower over the snow/ice surface, both at initiation and at 1.5 h. At the later time, IR# is less over the snow/ice than over the lead, but it is still enhanced by the overlying lead-induced plume relative to the initial clear-sky conditions. This large plume-induced increase in IR# (between initiation and 1.5 h) is responsible for a decrease in the net upward heat flux from 16 W m 2 to 5 W m 2. [37] A striking feature at 1.5 hours is the approximate doubling of near-surface wind speed over the lead compared to the initial conditions; the winds over the snow/ice surface are enhanced as well, though to a much lesser extent. This increase is due to both to the existence of a lead-scale circulation, which enhances inflow, and to vertical mixing of higher-momentum air down to the surface. This strongly enhanced near-surface wind is a major factor in the large values of the turbulent fluxes. [38] To determine the large-scale effects of the lead and the lead-induced plume, the surface fluxes are domain-averaged. These large-scale fluxes are displayed in Table 3. Despite the fact that the lead fraction is only 6.25%, the presence of the lead has a profound effect upon the large-scale surface fluxes. At 1.5 hours the large-scale turbulent fluxes of sensible and latent heat are both positive, 30 and 10 W m 2, respectively, and the net IR is 27 W m 2. These combine for a large-scale net upward surface heat flux of 67 W m 2. Though not shown here, after 1.5 hours the effects of the lead-induced plume are enhanced due to wrap-around of the air previously warmed and moistened by contact with the lead. This is analogous to what would be seen in the presence of a series of leads in proximity to each other. 6. Parameterization of Effects [39] Owing to the fact that small-scale features such as leads cannot be directly resolved by large-scale models, their effects must be parameterized if they are to be included. We examined a common parameterization method, the results of which are included in Tables 1 5 under the columns labeled mosaic. [40] The mosaic method uses a one-dimensional version of the CRM. Surface fluxes are calculated over open water and snow/ice surfaces using the same evolving largescale atmospheric properties. In turn, the large-scale properties are modified by these surface fluxes, using the lead fraction to specify the proportions of the over-water and over-snow fluxes. In addition, clouds may develop, along with their attendant radiative feedbacks. The mosaic method is commonly used in large-scale models [e.g., Koster and Suarez, 1996]. [41] Figure 7 compares domain-averaged (i.e., largescale) profiles from the mosaic method with the basic resolved lead simulation at 1.5 hours, and with initial conditions for both. Plots of wind speed, air temperature, water vapor mixing ratio, and cloud ice mixing ratio are shown. By comparing the wind speeds in the simulations to the initial conditions, we found that both the resolved and mosaic simulations transport higher-momentum air toward the surface and lower-momentum air away. The resolved simulation, however, mixes over a somewhat deeper portion of the atmosphere than does the mosaic run. This signature is apparent in the other fields as well. In addition, the lowest m of the mosaic temperature and water vapor profiles develop into near mixed layers, features not present in the resolved lead case. The average surface air temperature and water vapor mixing ratio are substantially higher in the mosaic simulation; this has significant impacts upon the mosaic surface fluxes. Perhaps most notably, the mosaic simulation creates a surface based cloud, whereas the resolved lead simulation produces an elevated cloud ice plume (as also shown in Figure 6, and similar in appearance to the lidar imagery in Figure 5). [42] The differences shown in Figure 7 between the resolved and the mosaic simulations are also apparent in the surface fluxes of Tables 1, 2, and 3. Above the lead surface, the higher surface temperature and humidity of the mosaic run combine with a lower near-surface wind speed to yield lower sensible and latent heat fluxes. The mosaic simulation s lower near-surface wind speed over the lead appears to be due both to the lack of a lead-scale circulation and to lesser vertical mixing compared with that over the lead of the resolved case. [43] Whereas the constant water temperature ensures that IR" is identical for the two methods, the low-level, and thus relatively cool, cloud produced in the mosaic run generates a lower value of IR# than does the elevated cloud in the resolved simulation. Therefore the net upward IR flux values over the lead are larger for the mosaic simulation than for the resolved. Despite this, the differences in the turbulent fluxes are even greater, which leads to the total upward heat flux being greater for the resolved than for the mosaic. [44] Over the snow/ice surface (Table 2), the turbulent fluxes are quite different for the resolved and mosaic cases. The relatively warm and moist near-surface air of the mosaic case approximately doubles the negative values of the sensible and latent heat fluxes. The large downward sensible heat flux of the mosaic simulation leads to a warmer snow/ice surface temperature, and thus a slightly higher IR" than for the resolved. Nonetheless, the mosaic case s highly negative turbulent fluxes lead to a low value of the net upward heat flux. [45] An interesting feature is apparent when comparing IR# over the different surfaces for the mosaic simulation. Because this simulation is one-dimensional, the same atmospheric conditions exist above the lead as above the snow/ice surface. At first glance, it would be expected that

10 ACL 7-10 ZULAUF AND KRUEGER: MODELING THE EFFECTS OF ARCTIC LEADS Figure 7. Domain-averaged initial conditions and results at 1.5 hours of wind speed, air temperature, water vapor mixing ratio, and cloud ice mixing ratio for both the resolved and mosaic simulations. this would require the same value for the downwelling longwave above the different surfaces. Instead, IR# is actually slightly higher above the warm surface of the lead. This is caused by backscattering (reflection) of the larger IR" over the warm lead by the simulated cloud. [46] The differences between the resolved and mosaic fluxes are also striking when examined as a large-scale average based upon a lead fraction of 6.25% (Table 3). The average turbulent fluxes calculated by the mosaic method are quite low when compared to the resolved turbulent fluxes because of both lower nearsurface wind speed (compared with that over the resolved lead) and higher near-surface air temperatures. On the other hand, the mosaic net upward IR fluxes are larger than for the resolved lead case. The decreases in the turbulent fluxes are greater, however, and the net upward heat flux is less for the mosaic case than for the resolved lead case. [47] An additional consequence of the differences in calculation and application of the heat fluxes between the resolved and mosaic simulations is the difference in the evolution of the convective plumes as they advect away from the lead over unbroken snow/ice. Since the plume from the mosaic simulation is surface-based, it might be expected that the heat and moisture released by the plume would be reabsorbed by the snow/ice more quickly than it would be for the resolved simulation, in which the plume is elevated. Figure 8 displays the evolution of the cloud ice profiles after the leads are closed at 1.5 hours, mimicking downwind evolution. At 3 hours (1.5 hours after lead closure), the cloud ice mixing ratios of both the resolved Figure 8. Time evolution of cloud ice profiles for both the resolved lead and mosaic simulations.

11 ZULAUF AND KRUEGER: MODELING THE EFFECTS OF ARCTIC LEADS ACL 7-11 Figure 9. Domain-averaged initial conditions and results at 1.5 hours of wind speed, air temperature, water vapor mixing ratio, and cloud ice mixing ratio for resolved lead simulations with varying lead widths. and mosaic plumes have been reduced to a fraction of their maximum values, though the decrease is greater for the mosaic run. At 4.5 hours, there is no longer any cloud ice remaining in the mosaic profile, but measurable cloud ice remains for the resolved profile until after 6 hours. The difference in radiative impacts due to the plumes is initially substantial, though it decreases over time (i.e., distance from the lead). Immediately after lead closure at 1.5 h, the net IR at the surface is 10.6 W m 2 greater for the mosaic simulation than for the resolved. At 3, 4.5, and 6 hours the differences have decreased to 2.6, 1.3, and 0.8 W m 2, respectively. It is important to remember that these relatively small values are actually significant fractions of the initial net upward heat flux over snow/ice. Additionally, at 10 m s 1 (the approximate wind speed at plume elevation) the plumes would have advected to cover a substantial area during this time. 7. Sensitivity Studies [48] The results shown thus far obviously apply only to a relatively small region of parameter space. A change in any one of the numerous environmental or lead characteristics might produce significantly different results. Changes in the large-scale atmospheric conditions or radiative forcing might substantially alter the surface energy balance. Similarly, changing the properties of the lead could modify that balance as well. Any of these factors, either large-scale or lead-scale, might also evolve in time, leading to a timedependent solution. In an attempt to examine some of the possible variations that might exist and to gauge the effects of such changes, a small number of additional simulations were performed. The changes examined were halving and doubling the lead width, including a thin ice layer on the lead, and reducing the large-scale relative humidity. These are all some of the variations that would commonly occur under typical midwinter conditions Width [49] Obviously, for different lead widths the total amount of heat and moisture released by the lead per unit time to the atmosphere will vary. -induced circulations and vertical mixing, both related to lead width, can increase the nearsurface wind speed, and thus the magnitude of the surface turbulent fluxes. Figure 9 displays some results at 1.5 hours from simulations involving 1.6- and 6.4-km-wide resolved leads, along with the initial conditions and results from the original 3.2-km-wide resolved lead. The domain size and grid resolution are the same as for the original 3.2-km-wide resolved lead simulation; only the fraction of the domain

12 ACL 7-12 ZULAUF AND KRUEGER: MODELING THE EFFECTS OF ARCTIC LEADS containing the lead (i.e., the lead fraction) has been modified. Tables 1 5 list the various surface fluxes and related quantities for these simulations under the columns labeled 1.6 km and 6.4 km. [50] As the lead width is reduced, the plume height and the lead-induced circulation strength are also reduced. These effects are evident in Figure 9. In particular, with a 1.6-km-wide lead, the plume height is slightly more than 100 m, substantially less than the plume height for the 3.2- km-wide lead. For the 1.6-km-wide lead, the warming and moistening of the atmosphere is also reduced. The weaker lead-scale circulation and vertical mixing in this case reduces the average near-surface wind speed and turbulent fluxes over the lead, shown in Tables 4 and 1. The decrease in upward surface turbulent heat fluxes is partially offset by a lower IR# due to the lower, cooler, and thinner ice cloud plume. [51] Over the snow/ice surface, the turbulent fluxes for the 1.6-km-wide lead case are very nearly the same as for the 3.2-km-wide lead. The differences occur mainly in the radiative fluxes. Again, IR# is decreased, which lowers T sfc and thus decreases IR". This increases the net upward IR flux over the snow/ice. Because the lead fraction varies for the different width leads, the domain-averaged fluxes are not directly comparable. A large-scale net upward heat flux may be computed using the lead fraction of the original simulation (6.25%) and the flux components from Tables 1 2. This yields a large-scale net upward heat flux of 69 W m 2 for the 1.6-km-wide lead, an increase of 2 W m 2 compared to the 3.2-km-wide lead. This analysis assumes that the average fluxes would remain unchanged over the water and the snow/ice surfaces with a different lead fraction. [52] Figure 9 also displays the effects of a doubling in lead width to 6.4 km. The plume height increases by approximately 50 m for the wider lead when compared to the 3.2-km-wide lead. The heating and moistening effects are larger as well. The turbulent fluxes over the 6.4-kmwide lead increase by approximately 10%, despite a decrease in the average air-sea temperature difference. However, the thicker and warmer ice cloud plume produced by the wider lead increases IR# over the lead significantly. The result is that the net upwelling heat flux over the wider lead is nearly 7% larger than for the 3.2-km-wide lead. [53] In the wide-lead simulation, the turbulent fluxes change little over the snow/ice surface, as was also the case for the narrow-lead simulation. Owing to the wide lead s more extensive ice cloud plume, IR# increases significantly and modifies the total heat budget over the snow/ice surface. Whereas the net heat flux over the snow/ice was upward for the 3.2-km-wide lead, for the 6.4-km-wide lead it is downward. If the large-scale average is calculated using the flux components from Tables 1 2 and the original 6.25% lead fraction, the resulting large-scale net upward heat flux is 63 W m 2, a decrease of 4 W m 2 compared to the 3.2-km-wide lead Ice Cover [54] Open leads eventually close, either through the same ice dynamical processes that open them, or through freezing. The freezing process can progress rather quickly after a lead opens [Alam and Curry, 1998; Pinto et al., 1999]. In spite of this, Figure 2 indicates that significant surface fluxes can still occur over ice-covered leads. To examine the effects of the freezing process on the large-scale surface fluxes, a simulation was run using the basic 3.2-km-wide lead, except with the lead covered by a thin, 2.5-cm-thick layer of ice. The results are tabulated in Tables 1 5 under the heading of thin ice. [55] Over the lead, the thin layer of ice insulates the warm water from the cold atmosphere, following the energy balance described in equation (2). The surface temperature over open water is constant at T melt,or 2 C, while the average surface temperature over the ice-covered lead is diagnostically determined to be 12 C at 1.5 hours. As a result of the colder surface and a slightly reduced nearsurface wind speed, the surface sensible heat fluxes over the frozen lead are 19% less than for the unfrozen lead. However, the latent heat fluxes are 53% less because of the rapid falloff in saturation vapor mixing ratio of the surface at colder temperatures. The lower-saturation vapor pressure over ice compared to that over water contributes only minimally. Furthermore, the lower T sfc significantly reduces IR", while the lower cloud ice content of the leadinduced plume also reduces IR#. The net upward IR flux over the lead is reduced by 15%. The net upward heat flux over the lead is reduced by 24% (to 759 W m 2 ) compared with the open lead. [56] The turbulent fluxes over the snow/ice surface are not appreciably different from those in the ice-free lead simulation. The lower cloud ice content of the plume leads to a 9% decrease in IR#, and associated lesser decreases in T sfc and IR". The net effect on the radiative balance is a substantial increase in the net upward IR flux, which increases the net upward heat flux over the snow/ice by 120%. [57] Averaged over the entire domain, the individual components of the surface fluxes when the lead is icecovered are all less in magnitude compared to when the lead is ice-free. The largest fractional difference occurs in the latent heat flux. A larger decrease in IR# than IR", however, leads to an increase in the net upward IR flux at the surface. Despite that increase, the net upward heat flux is diminished by 13% for the thin ice case when compared with the icefree lead Relative Humidity [58] The final sensitivity study involved reducing the relative humidity of the initial conditions. To obtain the initial water vapor mixing ratio profile for this simulation, we used the relative humidity profile displayed in Figure 3 and the saturation mixing ratio over ice, rather than over liquid as used for all other simulations. Since the difference between saturation vapor pressures over ice and liquid is strongly dependent upon temperature, the difference in initial mixing ratios between the present and original simulations varies with altitude. In the lower and colder portions of the domain where the direct effects of the leadinduced plume are seen, the low RH mixing ratio ranges from 71% to 79% of the mixing ratios in the original simulation. Above 500 m the fraction is nearly constant at approximately 80%. [59] The decrease in water vapor in the overlying atmosphere produces a slight reduction in the initial IR#. At the