Abstract

Data from the Arctic Ocean Experiment 2001 (AOE-2001) are used to study the vertical structure and diurnal cycle of the summertime central Arctic cloud-capped boundary layer. Mean conditions show a shallow stratocumulus-capped boundary layer, with a nearly moist neutrally stratified cloud layer, although cloud tops often penetrated into the stable inversion. The subcloud layer was more often stably stratified. Conditions near the surface were relatively steady, with a strong control on temperature and moisture by the melting ice surface.

A statistically significant diurnal cycle was found in many parameters, although weak in near-surface temperature and moisture. Near-surface wind speed and direction and friction velocity had a pronounced cycle, while turbulent kinetic energy showed no significant diurnal variability. The cloud layer had the most pronounced diurnal variability, with lowest cloud-base height midday followed by enhanced drizzle and temporarily higher cloud-top heights in the afternoon. This is opposite to the cycle found in midlatitude or subtropical marine stratocumulus. The cloud layer was warmest (coolest) and more (less) stably stratified midafternoon (midmorning), coinciding with the coolest (warmest) but least (most) stably stratified capping inversion layer.

It is speculated that drizzle is important in regulating the diurnal variability in the cloud layer, facilitated by enhanced midday mixing due to a differential diurnal variability in cloud and subcloud layer stability. Changing the Arctic aerosol climate could change these clouds to a more typical “marine stratocumulus structure,” which could act as a negative feedback on Arctic warming.

1. Introduction

Arctic climate change has been at the forefront of climate science during the last decade (cf., e.g., Arctic Climate Impacts Assessment; ACIA 2004). It has been well established that Arctic warming proceeds at a rate about twice that of global average warming (MacBean 2004; Serreze and Francis 2006) and this trend is projected to continue through this century (Kattsov and Källén 2004; Holland and Bitz 2003). A recent interdisciplinary study (Overpeck et al. 2005) concluded that the Arctic climate is currently on a trajectory toward a new superinterglacial state with significantly less snow and ice. The study goes on to conclude that, while this will have far-reaching effects on animal, plant, and human life, there are no obvious well-understood feedbacks within the Arctic system that can reverse or even slow down this trajectory.

Many feedbacks within the Arctic climate system are poorly understood and therefore uncertain. Perhaps the most uncertain, but potentially most important, feedbacks relate to clouds. In the Arctic, clouds are the most influential factor in determining the surface energy balance. An appropriate assessment of cloud feedbacks requires adequate climate modeling. ACIA concluded that current climate models are the least trustworthy in the Arctic (Kattsov and Källén 2004). Walsh et al. (2002) also points out problems with modeling of Arctic climate. Improved modeling requires improved understanding of processes that make the Arctic special. Such understanding relies on detailed observations.

Arctic clouds are dominated by low-level stratocumulus that, in contrast to similar marine clouds at more southerly locations, warm the surface (Intrieri et al. 2002b). The Arctic has a strong annual cycle in solar radiation, with a long winter night without sun and a summer season when the sun never sets. Potential feedbacks from the clouds will thus be different during different seasons. In winter, feedbacks affecting the longwave radiation properties of the clouds will be most important, such as changes in cloud-water phase and precipitation (e.g., Girard et al. 2005; Prenni et al. 2007). In summer, feedbacks affecting the cloud albedo will be important, such as changes in cloud-water content, precipitation, and cloud-droplet-number concentration (e.g., Twomey 1977). For both seasons, field studies have indicated that Arctic cloud properties differ from those at more southerly latitudes. Substantial fractions of liquid water appear in winter clouds even at very low temperatures (Intrieri et al. 2002a), while in summer the number and concentrations of cloud condensation nuclei (CCN), and therefore presumably of cloud droplets, are comparatively low (e.g., Heintzenberg et al. 2006).

Much has been learned about marine stratocumulus in general during the last decades, starting with pioneering studies by Nicholls (1984) and Nicholls and Leighton (1986) over the North Sea, continuing with important field experiments such as the First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment (FIRE: Albrecht et al. 1988), the Atlantic stratocumulus transition experiment (ASTEX: Albrecht et al. 1995) and the second Dynamics and Chemistry of Marine Stratocumulus field study (DYCOMS II: Stevens et al. 2003). Marine stratocumulus often feature a diurnal cycle such that clouds are the thickest during night and early morning, while solar radiation heats the cloud and evaporates cloud water, causing a minimum cloud thickness during afternoon (e.g., Turton and Nicholls 1987; Stull 1988; Duynkerke et al. 2004; Chlond et al. 2004). The corresponding cycle in the cloud-water path ensures that clouds are optically thinner when solar radiation is more intense. Rozendaal et al. (1995) estimated that ignoring this cycle leads to an overestimation of the surface cloud radiative forcing by almost 15%. Coupled to this cycle is a maximum in turbulent mixing through the entire boundary layer at night, driven by longwave radiation cloud-top cooling and buoyancy overturning. The top of the stratocumulus generally coincides with the inversion base; this is dictated by the strong radiative cooling at the cloud top (Tjernström and Rune 2003). Solar heating during the day offsets the cloud-top cooling and heats the cloud interior, causing lower turbulence intensities and often a decoupling of the cloud layer from the subcloud layer (Tjernström and Rune 2003; Duynkerke et al. 2004). Drizzle is most frequent during late night and early morning, when the cloud is thickest and contains the most water (Comstock et al. 2005).

Drizzle has long been recognized as a regulator of cloud water (e.g., Svensson et al. 2000). The importance of drizzle for the boundary layer structure was discussed in Stevens et al. (1998), concluding that enhanced drizzle in stratocumulus with strong wind shear stabilizes the boundary layer and changes the cloud structure from a well-mixed stratocumulus to a more shallow cumulus-convective-like structure. Stevens et al. (2005) and Petters et al. (2006) report on organized structures in stratocumulus off the U.S. West Coast called “pockets of open cells.” These are small cellular shallow convective structures with enhanced drizzle, imbedded in stratocumulus layers often with low droplet-number concentration and with higher moisture aloft.

Far less is known about the central Arctic boundary layer (ABL) and in modeling, for example, it is generally assumed they are similar to midlatitude clouds. This is because of a comparative lack of detailed observations from the Arctic (Uttal et al. 2002; Tjernström et al. 2004a; Tjernström 2005). Much of our understanding of Arctic processes derives from field experiments near the coasts around the Arctic Ocean, except for a few extensive programs on the Arctic pack ice, for example the Surface Heat Budget of the Arctic Ocean (SHEBA) Experiment (Uttal et al. 2002) and the Arctic Ocean Experiment 2001 (AOE-2001: Leck et al. 2004; Tjernström et al. 2004a).

The present paper focuses on the summer central Arctic stratocumulus-capped boundary layer. The data come from AOE-2001, which took place from mid-July through late August 2001. Some of the data are limited to a 3-week ice-drift period in August. From a preliminary analysis of AOE-2001 data, Tjernström (2005) concluded that the ABL was generally well mixed and that there was no significant diurnal cycle except for an unexpected—and unexplained—cycle in the lowest cloud-base height. Figure 1 shows a summary of results from the more careful analysis carried out here, which serves as a starting point for this discussion (see section 2 for a description of the analysis). This figure shows the median diurnal cycle of the lowest cloud-base and the capping inversion-base heights. Also shown is the median diurnal cycle of cloud-radar reflectivity. The lowest cloud base occurs before noon, 0900–1200 local time (LT), while the height to the base of the capping varies very little over the day. The cloud-radar reflectivity indicates the presence of clouds; strong echoes are assumed to be associated with precipitation. Cloud tops seem to often occur above the inversion base, and are temporarily the highest during the second half of the day, when the radar echo intensity also indicates more drizzle. This cycle appears to be almost opposite to what is found in marine stratocumulus at lower latitudes.

Fig. 1.

A schematic representation of the diurnal cycle in the cloud layer showing the median cloud-base height (solid line), the median inversion-base height (dashed line) and median cloud-radar reflectivity (gray shading), from whole AOE-2001 expedition north of 85°N. See the text for a discussion.

Fig. 1.

A schematic representation of the diurnal cycle in the cloud layer showing the median cloud-base height (solid line), the median inversion-base height (dashed line) and median cloud-radar reflectivity (gray shading), from whole AOE-2001 expedition north of 85°N. See the text for a discussion.

2. Method

a. The experiment

The AOE-2001 took place during July and August 2001 (Tjernström et al. 2004a). The first short research station was set up southeast of Svalbard, Norway, on 5 July; two more stations in the marginal ice zone (MIZ) north of Svalbard, around 81°–82°N, and one open-water station northwest of Svalbard were set up before the researchers traversed the pack ice on board the icebreaker Oden toward the North Pole during the second half of July. Three additional short-term research stations were set up while the researchers were transecting the pack ice.

The main period for atmospheric research was conducted during a roughly 3-week-long ice drift, starting at ∼89°N, 01°W on 2 August and drifting passively to ∼88.2°N, 09°W on 21 August, with the icebreaker moored to the same ice floe. During this time, detailed boundary layer measurements were taken on the ice in addition to the ship-based remote sensing observations continuously taken on board the icebreaker during the entire expedition. Objectives and preliminary results were previously reported in Leck et al. (2004), Tjernström et al. (2004a), and Tjernström (2005).

b. Instrumentation

A complete discussion on the meteorological instrumentation is found in Tjernström et al. (2004a, b). The remote sensing instrumentation used here includes a cloud and precipitation S-band Doppler radar (White et al. 2000) deployed on the foredeck of Oden, and a scanning 5-mm passive radiometer (Westwater et al. 1999) deployed high to one side of the Oden superstructure with a ∼270° free view in the vertical plane across the path of the ship. A weather station, including a cloud-base ceilometer and a visibility sensor, was also continuously operated on board and soundings were released from the helipad. During the 3-week ice drift a mast was deployed on the ice, equipped with turbulence and profile instrumentation and some other instruments (wind direction, temperature, relative humidity, surface pressure, short- and longwave radiation, etc.).

c. Analysis

As far as possible, the analysis used observations from the entire experiment, limited to north of 85°N to ascertain that only data from within the central Arctic Ocean pack ice, well north of the open ocean or the marginal ice zone at ∼81°–82°N, were used. This was done to eliminate the influence of mesoscale motions triggered at the MIZ. For the near-surface data (for example, low-level temperature, stability, or radiation), only the ice-drift data were used, avoiding onboard in situ instruments that were likely to be affected by local effects from being on board a ship. Observations from the Oden weather station were used only to independently confirm results from observations near the ice surface.

The scanning radiometer provides 5-min-averaged temperature profiles to ∼1 km, with degrading resolution and accuracy with increasing height. Temperature observations from the mast on the ice, the onboard weather station, and from 6-hourly soundings were used to constrain the retrieval algorithm. These data were used to determine vertical ABL structure and to characterize the capping inversion layer. The temperature inversion analysis presented in Tjernström (2005) provided all significant inversion layers in each 5-min profile. These were screened to determine the main capping inversion when the automated routine picked out multiple inversions; in most profiles more than one inversion layer was detected (Tjernström 2005). The main inversion was mostly the strongest inversion (largest temperature jump: Tjernström 2005), but in ∼15% of the profiles there was a need to intervene; for example, when the algorithm selected a strong high-altitude inversion layer, clearly not associated with the ABL, as the main inversion. The height to the base and top of the inversion layer was determined according to the definitions in Andreas et al. (2000), based on the local vertical temperature gradient. The inversion-base height was used as a proxy for boundary layer height and was used to normalize the height in temperature profiles. The location of this sensor on the superstructure of the ship sometimes made the lowest one or two levels (<30 m) somewhat unreliable, as they may, depending on wind direction, have been affected by the proximity of the ship.

The S-band cloud-radar data were also automatically screened, excluding questionable data by requiring the Doppler velocity to be realistic and consistent through the lowest several hundred meters. Since the focus here is on stratocumulus, deep synoptic weather systems detected from high-altitude multiple levels of radar reflectivity were excluded. Note that we are unable to distinguish between cloud water and precipitation, and likewise between liquid and ice water, using only radar data. Therefore cloud-radar reflectivity can only be used qualitatively. We assume that high reflectivity is associated with precipitation; Doppler velocity also allows a means to distinguish between cloud water and precipitation, although it is different for liquid and frozen precipitation. We also assume that, over the entire experiment, liquid and frozen water occur somewhat randomly depending on the synoptic situation so that a diurnal signal in radar reflectivity is not due to a diurnal preference in the phase of cloud water or precipitation. Cloud boundaries were detected from a threshold reflectivity profile. With consistently very low cloud-base heights, the lowest cloud base was usually below the lowest range gate of the radar.

The cloud-base ceilometer had a tendency to report spurious very low cloud-base heights also when the bulk of the registrations indicated a well-defined elevated cloud layer and the visibility was good. The reason is not known but could be its location on the ship. Such data were eliminated by an algorithm where the 1-h-averaged cloud-base heights were defined as the heights indicated by the peak of the 1-h probability density functions (PDFs). This method also identifies the most significant cloud-base height in cases with multiple cloud layers. The visibility was also used in the algorithm, assuming that persistently very low cloud-base heights (essentially fog) were associated with lower visibility. The remaining accepted values during each 1-h interval also define the 1-h mean cloud fraction, using the ratio of the number of scans returning a valid cloud-base height to the total number of technically accepted scans.

For the turbulence data, observations from the sonic anemometers on the mast were sampled over 15-min intervals. These were tilt corrected and detrended before the analysis. The gradient Richardson number,1 Rig, was estimated from third-order log(z) polynomials fitted to 1-hourly averaged potential-temperature and wind-speed profiles from the mast; see Tjernström (2005) for a detailed discussion.

For the diurnal cycle, data were first high-pass filtered to remove variability at time scales longer than 24 h. The longer time scales were averaged to illustrate the mean conditions. The high-frequency data, here referred to as anomalies, were composited in 1-h windows according to the local time of the day2 (LT), and statistics were calculated for each hour. The diurnal cycle is illustrated using the median and the 5th, 25th, 75th, and 95th percentiles of the deviation from the diurnal mean, rather than using the mean and standard deviations. This provides a more robust measure, less sensitive to outliers in the data. The statistical significance of the median diurnal cycle (the median of the hourly anomalies) is tested using a 95% double-sided Student’s t test, usually shown as a gray band around the median in the graphs. Throughout this paper, “significant” is reserved for this particular meaning. When a straight (constant) line cannot be drawn inside the significance interval it is assumed that the null hypothesis—no diurnal cycle—can be rejected. Note that a diurnal cycle can, in this sense, be significant and still so small that it holds little or no meaning. The opposite is also possible; that a physically meaningful diurnal cycle exists, but is not statistically significant and therefore cannot be trusted. Note also that the temperature anomaly at a given normalized height is, strictly speaking, also a function of variations of the normalizing height. In practice this is unimportant since the inversion-base height typically varied on a much longer time scale. Thus, in practice, calculating the anomaly of the temperature or of the potential temperature makes no difference, as the normalization was always applied after the anomaly calculations. Sometimes, the diurnal mean is added to the anomaly to illustrate the real conditions. Very nonnormally distributed variables, such as visibility or cloud fraction, are illustrated either with contour plots of the probability of occurrence as a function of time of the day, or using the diurnal median without first removing the interdiurnal time scales. This is, for example, what is shown as an introductory illustration in Fig. 1.

3. Results

a. Mean conditions

Typical conditions encountered during AOE-2001 were discussed in Tjernström et al. (2004a) and Tjernström (2005). Only a summary will be repeated here to provide a background to the analysis of the diurnal cycle. The experiment was affected by occasional synoptic weather systems, on average every 3–5 days. Between these, back trajectories show relatively steady background atmospheric conditions for several days (Tjernström et al. 2004a). While air sometimes originated directly from the open ocean to the south, with only a few days travel time over the pack ice, it was common that air spent 5–10 days over the ice before reaching the Oden. Air with a continental origin was rare.

With the exception of a brief period around 15 August [day of the year (DoY)3 227], near-surface temperatures remained between the melting points of fresh- and seawater, −1.8°–0.0°C, most of the time, with a preference for the upper limit. Relative humidity remained high, always above 94%. A colder episode around DoY 227, with temperatures down to −6°C (Tjernström 2005), is interesting since preliminary modeling using the Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS; Hodur 1997) regional model (Söderberg et al. 2006) suggests that it corresponds to the passing of an air mass with a clear-sky history. The fact that clear skies, at least in the model, seem to imply a negative net radiation is a sign of the approaching autumn freeze-up conditions; mid-August is typically at the end of the melt season. The median wind speed was ∼4 m s−1; winds occasionally rose to ∼10 m s−1.

These results from the shorter ice-drift mast data are consistent with the longer observation record on board Oden. Wind speeds measured on board at ∼35 m above the ice were somewhat higher with a median wind speed of ∼6 m s−1 and maximum values of 16–18 m s−1. The 35-m temperature PDF is very similar to that from the shorter mast record, only the temperature was on average somewhat lower, with a more even distribution between the two melting points.

The height to the lowest cloud base was often found at ∼70–100 m and cloud fraction was most often close to unity (Tjernström 2005). The cloud-top heights were often at ∼200–400 m, with a secondary peak in the PDF around 800–900 m (Fig. 2a). Higher cloud-top heights associated with synoptic-scale weather systems occurred only rarely. Similar low-level clouds at lower latitudes are often associated with subsidence; the preliminary model results show that, at the height of the observed inversion base, the vertical wind was most often around zero with about equal frequency of occurrence of positive and negative values (Fig. 2b); thus the conditions here are unlike those over, for example, the subtropical oceans.

Fig. 2.

The frequency of occurrence of (a) the lowest (solid) and highest (dashed) cloud-top heights, and (b) the vertical wind speed from a model simulation. The cloud-top heights are analyzed from a cloud radar, from the entire AOE-2001 expedition, north of 85°N, while the vertical wind speeds are taken from a model simulation of the ice drift, three weeks in August 2001 near the Pole.

Fig. 2.

The frequency of occurrence of (a) the lowest (solid) and highest (dashed) cloud-top heights, and (b) the vertical wind speed from a model simulation. The cloud-top heights are analyzed from a cloud radar, from the entire AOE-2001 expedition, north of 85°N, while the vertical wind speeds are taken from a model simulation of the ice drift, three weeks in August 2001 near the Pole.

The visibility was either poor, 200–2000 m was typical for the frequent fogs, or unexpectedly good, >20 km (Tjernström et al. 2004a). It was common to have a lowest cloud-base height below 100 m and still have visibility better than 20–40 km. In well-mixed conditions, a low cloud-base height is associated with a high near-surface relative humidity. At lower latitudes, below-cloud visibility often degrades in the presence of hygroscopic aerosol particles, swelling as they absorb water vapor. The fact that this did not happen here indicates a relative lack of such aerosols in the summer Arctic, consistent with aerosol observation onboard Oden, from this and previous similar Arctic expeditions (Heintzenberg et al. 2006).

Net surface solar radiation (Fig. 3a) was mostly around ∼25 W m−2, while net longwave radiation was usually around zero (Fig. 3b). In briefly clear conditions they peaked at ∼100 and ∼−70 W m−2, respectively (see, e.g., around DoY 220 and 227). The surface albedo over an undisturbed surface varied between 65% and 85%; the higher values occurred with new snow. Taking open water and melt ponds into account, this translates to an estimated area-averaged albedo of 55%–80% (not directly measured). Total surface net radiation was usually positive, ∼20 W m−2, infrequently dropping to ∼−40 W m−2 in clear-sky conditions (Fig. 3c). Analyzing all data during cloudy conditions (cloud fraction >90%) and reasonably clear conditions (cloud fraction <30%) separately gives a median net shortwave radiation of ∼25 and 45 W m−2, respectively, and a surface shortwave cloud-radiative forcing of ∼−20 W m−2. Net longwave radiation in cloudy conditions was close to zero, dropping to −50–−60 W m−2 in clear conditions, thus the surface longwave cloud-radiative forcing was ∼50 W m−2, making the total surface cloud-radiative forcing positive, at ∼30 W m−2, explaining why lower temperatures appear when the cloud cover broke up.

Fig. 3.

Time series of surface (a) net shortwave, (b) net longwave, and (c) total net radiation, in W m−2, for the ice-drift period, 2–21 Aug 2001. Each panel also includes an insert with the probability density function calculated for the same time period.

Fig. 3.

Time series of surface (a) net shortwave, (b) net longwave, and (c) total net radiation, in W m−2, for the ice-drift period, 2–21 Aug 2001. Each panel also includes an insert with the probability density function calculated for the same time period.

The high temporal resolution of temperature profiles from the scanning radiometer (>9000 5-min profiles from the entire AOE-2001) allows a statistical analysis of the vertical structure of the ABL and the capping inversion layer (see Tjernström 2005). The base of the main inversion layer is most commonly around ∼200 m and the inversion layer is ∼100–600 m thick. The strength of the inversion is most often only a few degrees Celsius, but very strong inversions occur, usually in connection to advection from the open ocean to the south. The mean ABL temperature (Fig. 4) is often somewhat below zero and −1°–4°C at the inversion-layer base. The temperature at the top of the inversion layer is more variable, from a few degrees higher than at the inversion-layer base occasionally reaching as high as 10°C.

Fig. 4.

Statistics from the entire AOE-2001 expedition north of 85°N, of the mean ABL temperature (solid), inversion-base (dashed), and inversion-top temperature (dotted), in °C.

Fig. 4.

Statistics from the entire AOE-2001 expedition north of 85°N, of the mean ABL temperature (solid), inversion-base (dashed), and inversion-top temperature (dotted), in °C.

Figure 5a shows the vertical temperature gradient against height, normalized by the inversion-base height, zi. Note that the “global” maximum probability for a zero gradient at z zi−1 = 1 is an artifact of the definition of the inversion-layer base combined with this scaling. Temperature gradients are mostly near ∼−0.006°C m−1, near the moist-adiabatic lapse rate, through z zi−1 ∼ 0.25–1.0 and more stable below. As the lowest cloud-base height was typically found around z zi−1 ∼ 0.2–0.3 (Fig. 5b), this indicates a two-layer structure where the cloud layer was often well mixed, while the subcloud layer was more stably stratified. The latter is consistent with surface-layer observations from the mast during the ice drift; the low-level stability was most often near neutral on the stable side, with a median Rig ∼ 0.05 at 5 m (Tjernström 2005). Cloud-top heights, on the other hand, varied more and often occurred at z zi−1 ∼ 1–2, indicating that clouds often penetrated into, instead of being capped by, the inversion (Tjernström 2005).

Fig. 5.

Statistics from the entire AOE-2001 expedition, north of 85°N, of the probability of (a) the vertical temperature gradient, in °C m−1, as a function of normalized height, and (b) normalized lowest cloud-base height (solid) and lowest cloud-top height (height). The moist adiabatic is indicated in (a) by the white dashed line. The height axes are scaled by the height to the base of the capping inversion.

Fig. 5.

Statistics from the entire AOE-2001 expedition, north of 85°N, of the probability of (a) the vertical temperature gradient, in °C m−1, as a function of normalized height, and (b) normalized lowest cloud-base height (solid) and lowest cloud-top height (height). The moist adiabatic is indicated in (a) by the white dashed line. The height axes are scaled by the height to the base of the capping inversion.

b. The near-surface diurnal cycle

At a quick glance, it seems easy to reject the idea of a diurnal variation in near-surface temperature (Fig. 6a), as was indeed done in Tjernström (2005). However, a closer inspection reveals that the statistical significance of the small temperature variation is very high. The gray-shaded 95% confidence interval in Fig. 6a is so narrow that it is almost entirely covered by the solid black median line. Moreover, the 25th and 75th percentiles follow the median closely, indicating that the diurnal anomaly variation is robust. The diurnal temperature range is, however, very small with only slightly higher temperature from noon until ∼1800–1900 LT. The relative humidity anomaly (Fig. 6b) is somewhat higher at the night, 2300–0300 LT, and marginally higher than the diurnal average 1000–2300 LT, but drops significantly around ∼0900 LT. The diurnal range is small, only ∼1%, but should be considered in the context of a total range for the entire expedition of only ∼5% (95%–100%). The diurnal variability thus accounts for a fair portion of the total variability. The wind speed (Fig. 6c) has a pronounced diurnal cycle of about ∼1 m s−1 peak to peak, with lower wind speeds ∼1000–1800 LT and higher wind speeds ∼0000–0900 LT. This should also be contrasted to the 4 m s−1 overall median value. The wind direction shows a significant diurnal variation (Fig. 6d) such that there is a smaller boundary-layer turning angle to the geostrophic wind during the day (∼0800–2000 LT) than during the night.

Fig. 6.

The diurnal anomaly for the ice-drift period, 2–21 Aug 2001, of some near-surface parameters: (a) temperature, in °C, and (b) relative humidity in %, both at 4.7 m, and (c) scalar wind speed, in m s−1, and (d) wind direction, in degrees, both at 18 m. The panels show the median value (solid) and the 95% confidence interval (gray shaded), the 25th and 75th percentiles (dashed), and the 5th and 95th percentiles (dotted). In (d) the 5th and 95th percentiles are omitted to gain resolution in the plot, as the variability of the wind direction is significantly larger than for the other variables.

Fig. 6.

The diurnal anomaly for the ice-drift period, 2–21 Aug 2001, of some near-surface parameters: (a) temperature, in °C, and (b) relative humidity in %, both at 4.7 m, and (c) scalar wind speed, in m s−1, and (d) wind direction, in degrees, both at 18 m. The panels show the median value (solid) and the 95% confidence interval (gray shaded), the 25th and 75th percentiles (dashed), and the 5th and 95th percentiles (dotted). In (d) the 5th and 95th percentiles are omitted to gain resolution in the plot, as the variability of the wind direction is significantly larger than for the other variables.

The low-level stability, illustrated by Rig (Fig. 7a), is somewhat smaller ∼0900–1800 LT and larger during the night, consistent with the changes in wind direction (the median Rig is ∼0.05). The surface net radiation (Fig. 7b) varies over the day, but only a little: the total peak-to-peak variation is <10 W m−2 (using data from the very few clear episodes indicates a cloud-free diurnal variability of net solar radiation of ∼±20 W m−2). Interestingly, the diurnal cycle is not sinusoidally symmetric around local noon, as would be expected if it had been a function only of the varying solar zenith angle over the day with no diurnal cycle in the cloud layer. Instead, the maximum appears ∼1000 LT with lower afternoon values than during symmetrically corresponding times in the morning. Assuming a sinusoidal function with a peak at local noon fitted to the early portion of the day, and comparing the accumulated net radiation at the surface to that from Fig. 7a, gives a deficit of some 5%–10%, compared to the symmetric case. This is slightly smaller and opposite compared to the effect of the diurnal cycle in subtropical marine stratocumulus (Rozendaal et al. 1995). In terms of shortwave cloud-radiative forcing it represents only ∼1–2 W m−2.

Fig. 7.

As in Fig. 6 but showing (a) Rig at 5 m, (b) net surface radiation, in W m−2, (c) the friction velocity, in m s−1, and (d) the turbulent surface sensible heat flux, in W m−2. In (a) the 5th and 95th percentiles are omitted to gain resolution as the variability of the Rig is significantly larger than for the other variables.

Fig. 7.

As in Fig. 6 but showing (a) Rig at 5 m, (b) net surface radiation, in W m−2, (c) the friction velocity, in m s−1, and (d) the turbulent surface sensible heat flux, in W m−2. In (a) the 5th and 95th percentiles are omitted to gain resolution as the variability of the Rig is significantly larger than for the other variables.

The friction velocity,4 u*, exhibits a pronounced cycle (Fig. 7c) consistent with the wind speed variation (Fig. 6c); the median value was ∼0.18 m s−1. The median anomaly of the turbulent sensible heat flux,5 ρcp, varies little during most of the day (Fig. 7d); the median value is close to zero, varying mostly within ±10 W m−2. It is intriguing, however, that the diurnal anomaly features a statistically significant peak of ∼4 W m−2 around ∼0900–1300 LT, coincident to when many other variables seem to deviate from the diurnal median values. Near-surface turbulent kinetic energy6 (TKE) and the vertical-to-horizontal variance ratio, (+ )−1, both show weak but not significant diurnal variation (not shown) with midday maximums. There is, thus, an indication of slightly more TKE during the day and that more of the TKE then resides in the vertical wind speed variance. Together with the changes in stability (Rig) and wind direction, this can be speculated as an indication of more buoyancy-dominated turbulence during this time, maybe nonlocally generated and imported from the cloud layer above. Note that all turbulence observations were taken close to the surface (z < 20 m).

c. The cloud-layer diurnal cycle

The anomaly of the lowest cloud-base height (Fig. 8a) has a pronounced diurnal variability with a negative anomaly of ∼50 m during ∼1000–1500 LT followed by a smaller positive anomaly during late afternoon and into the evening, ∼1500–2000 LT. The total magnitude is not large. Recall, however, that the cloud-base height was usually <100 m and the anomaly thus represents at least 50% of the cloud-base height. It is also worth noting that Fig. 8a shows the median anomaly; the mean anomaly is similar but shows a larger magnitude (e.g., Tjernström 2005, his Fig. 6c). The significance is higher (narrower gray band) during the largest negative anomaly, but lower in late afternoon and evening. Moreover, two periods with the lowest significance occur just before and after the midday negative anomaly.

Fig. 8.

Statistics from entire AOE-2001 expedition north of 85°N, of the diurnal cycle in (a) the lowest cloud-base height anomaly, in meters, and (b) the cloud fraction, showing the median (black), the 95% confidence interval (gray shaded), and the 25th and 75th percentiles (dashed). Note that the 5th and 95th percentiles are omitted due to the large overall variability.

Fig. 8.

Statistics from entire AOE-2001 expedition north of 85°N, of the diurnal cycle in (a) the lowest cloud-base height anomaly, in meters, and (b) the cloud fraction, showing the median (black), the 95% confidence interval (gray shaded), and the 25th and 75th percentiles (dashed). Note that the 5th and 95th percentiles are omitted due to the large overall variability.

This figure can be interpreted as follows: The midday negative anomaly is robust, occurring around this time on most days. The lowest significance (widest significance interval) just before and after indicates that timing of the onset and end of the anomaly differ on different days or possibly shift gradually over time. The smaller positive anomaly in the afternoon and into the evening [∼1600–2000 (2300) LT] is also less significant. We speculate that these higher-than-median cloud-base heights during the second half of the day occur more randomly during this period. This interpretation is supported by the 5th and 95th percentiles of the cloud-base height anomaly (omitted in Fig. 8a), which deviates more from the median around ∼0600 LT and during 1600–2100 LT. In particular, the 95th percentile indicates infrequent substantially higher cloud-base heights ∼1600–2100 LT that do not appear during morning. This is consistent with the 25th percentile for the cloud fraction (Fig. 8b). Although the diurnal cloud-fraction variability is not significant, the 25th percentile has much lower values than the median ∼1600–2200 LT. In summary, there is systematically a lower cloud-base height in the middle of the day and higher and more variable cloud-base heights later in the day, sometimes with a broken cloud field.

The median cloud-radar reflectivity (Fig. 1) has a maximum in the lowest gates (∼200 m) around ∼1100–1500 LT, thus starting somewhat after the onset of the lower cloud-base heights, here illustrated by the median cloud-base height (not the median anomaly). The elevated low-level radar reflectivity stretches into the evening. Extracting median cloud-top heights from the median radar reflectivity is not straightforward (the median height to a threshold reflectivity is not the same as the height to the threshold of the median reflectivity). Still, the appearance of stronger median reflectivity at higher altitudes indicates that cloud-top heights from noon and onward to midnight are at least temporarily higher, while before noon they occur more steadily around 200–300 m. Note also that the median inversion-base height shows very little diurnal variation. The higher radar reflectivity in the afternoon is consistent with the secondary maximum in the cloud-top height PDF (Fig. 2a).

Figure 9 shows results from the cloud radar in more detail, using the second lowest range gate at ∼200 m. There is a significant diurnal cycle in the reflectivity anomaly, of >2 dBZe peak to peak, in particular ∼1000–1800 LT. The absolute reflectivity typically lies in the range −10–0 dBZe, which is somewhat low compared to drizzling subtropical stratocumulus (5–10 dBZe: e.g., Comstock et al. 2005). In some synchronization with this there is also a negative anomaly in the radar Doppler velocity, giving an indication of the fall velocity of the hydrometeors (Fig. 9b). The diurnal peak-to-peak variability is ∼<0.3 m s−1; the median absolute fall velocities were typically O(<1.0 m s−1), which is not atypical for drizzling stratocumulus. Together with the reflectivity anomaly this suggests an enhanced drizzle from ∼1000–1100 LT through early evening, compared to conditions during late night through morning.

Fig. 9.

Diurnal cycle of median anomaly of (a) cloud-radar reflectivity, in dBZe, and (b) cloud-radar Doppler velocity, in m s−1, from the second lowest gate of the S-band cloud and precipitation radar (∼200 m), using data from the entire AOE-2001 expedition north of 85°N. The gray-shaded area indicates the 95% confidence interval.

Fig. 9.

Diurnal cycle of median anomaly of (a) cloud-radar reflectivity, in dBZe, and (b) cloud-radar Doppler velocity, in m s−1, from the second lowest gate of the S-band cloud and precipitation radar (∼200 m), using data from the entire AOE-2001 expedition north of 85°N. The gray-shaded area indicates the 95% confidence interval.

The frequency of occurrence of visibility was examined to indicate the occurrence of fog as a proxy for subcloud-layer moisture. Visibility data during strong precipitation episodes, as observed with a so-called “present weather” detector, were excluded. Using the classical definition of fog (visibility <1 km), fogs were most common during the night, ∼1800–0300 LT, in particular ∼1900–2200 LT. Note that relative humidity is also slightly higher at night (Fig. 6b). Together, this can be taken as an indication of a low-level buildup of water vapor from surface evaporation during the night. During 1200–1800 LT there was practically always good visibility.

d. The diurnal cycle of the vertical thermal structure

Diurnal composites of temperature and temperature gradient vertical structure, and their anomalies, are shown in Figs. 10 and 11. The lower portion of the ABL, presumably most often the subcloud layer (see Fig. 5b), has a weak cycle (Fig. 11a) with maximum temperatures before local noon (Fig. 10a; note that below z zi−1 ∼ 0.05 may be questionable), consistent with the maximum in the surface net radiation around ∼1000 LT (Fig. 7a). The maximum temperature is pushed later in the day in the upper part of the ABL, inside the cloud, and maximum temperature occurs as late as 2100 LT (Figs. 10a and 11a), followed by a rapid cooling, and lowest temperature occurs ∼0100–0300 LT. Thus the low-level temperature anomaly is out of phase with that in the upper parts of the ABL.

Fig. 10.

Time–height cross section of the diurnal cycle of (a) the median temperature profile, in °C, and (b) the median temperature-gradient profile, in °C m−1 × 100. The data are from the entire AOE-2001 expedition, north of 85 °N. In (a) the means of all profiles are added to the diurnal variation.

Fig. 10.

Time–height cross section of the diurnal cycle of (a) the median temperature profile, in °C, and (b) the median temperature-gradient profile, in °C m−1 × 100. The data are from the entire AOE-2001 expedition, north of 85 °N. In (a) the means of all profiles are added to the diurnal variation.

Fig. 11.

The diurnal cycle of the median (a), (c) temperature anomaly (in °C) and (b), (d) temperature gradient anomaly (in °C m−1 × 100). The results are averaged over different layers: (a) and (b) inside the ABL (“Lower” is z zi−1 < 0.25, “Middle” is 0.25 < z zi−1 < 0.75, and “Upper” is 0.75 < z zi−1 < 1.0), and (c) and (d) through the lowest troposphere (“PBL” is 0.1 < z zi−1 < 1.0, “IL” is 1 < z zi−1 < 2, and “FT” is 2 < z zi−1 < 3). The gray-shaded area indicates the 95% confidence interval and the data are taken from the entire expeditions north of 85°N.

Fig. 11.

The diurnal cycle of the median (a), (c) temperature anomaly (in °C) and (b), (d) temperature gradient anomaly (in °C m−1 × 100). The results are averaged over different layers: (a) and (b) inside the ABL (“Lower” is z zi−1 < 0.25, “Middle” is 0.25 < z zi−1 < 0.75, and “Upper” is 0.75 < z zi−1 < 1.0), and (c) and (d) through the lowest troposphere (“PBL” is 0.1 < z zi−1 < 1.0, “IL” is 1 < z zi−1 < 2, and “FT” is 2 < z zi−1 < 3). The gray-shaded area indicates the 95% confidence interval and the data are taken from the entire expeditions north of 85°N.

The lower portion of the ABL is slightly less stably stratified in the morning until noon and is more stable the second half of the day; compare Fig. 5d for the surface layer that has the opposite cycle. The bulk of the ABL is significantly more well mixed ∼0000–1200 LT when it is also the coolest, and vice versa ∼1200–2100 LT (Figs. 10b and 11b). Note that the largest stability changes occur inside what is likely the cloud layer, while the largest temperature variability is found at the ABL top. The inversion layer (1 < z zi−1 < 2) is the warmest ∼1200–1800 LT, before the largest warming of the ABL ∼ 1500–2200 LT. The inversion stability, on the other hand, is the lowest ∼1500–2300 LT (Fig. 11d). This coincides with the largest ABL stability, but also with the warmest upper ABL and with the occurrence of enhanced radar reflectivity above the inversion base. The upper ABL is thus warmest and the most stably stratified at the time when the inversion layer is cooler and less stably stratified.

4. Discussion

It is useful here to first review briefly the diurnal cycle of marine stratocumulus at more southerly latitudes. For that case the cloud-layer diurnal cycle is clearly driven by the variation in solar radiation. During the night there is a strong radiative cooling at the cloud top, generating negatively buoyant air parcels sinking through the boundary layer, keeping the boundary layer well mixed often all the way to the surface. During the day solar radiation heats the cloud layer, offsetting the cloud-top longwave cooling and casing evaporation of cloud water. This makes the cloud layer thinner and frequently alters cloud-base and subcloud stratification such that the cloud layer decouples from the subcloud boundary layer.

In contrast, in the summer Arctic the sun is present all day—albeit at a high zenith angle and with a weak diurnal cycle. Thus, the solar radiation is likely not sufficiently strong to evaporate parts of the cloud during the day, and Arctic stratocumulus should thus behave more like the nighttime marine stratocumulus farther south. For the first part of the day, this also seems to be the case in the sense that the cloud layer is relatively constant and also the most well mixed, presumably by cloud-top cooling. The subcloud layer, on the other hand, seems more independent of the cloud layer most of the day and cloud-induced turbulent mixing does not seem to make it to the surface. During late night and into the morning, the cloud layer cools to become the coolest at 0200–0900 LT. It is also the most well mixed around midmorning, ∼0800–1100 LT; this is likely also when the cloud is the most turbulent. The subcloud layer has a more constant temperature, warming slightly with a maximum temperature around local noon.

We hypothesize that during midmorning the upper layer has cooled, and the lower layer has warmed, sufficiently that the stability between the two lower layers becomes small enough to allow cloud-top-induced turbulent mixing down to the surface. We further hypothesize that the layer decoupling during the night creates a shallow and stable near-surface sublayer that allows for an accumulation of moisture. A higher nighttime relative humidity and a preference for fog formation indicate a near-surface accumulation of water vapor. The enhanced midmorning turbulence mixes this additional moisture through the entire ABL, as indicated by the peak in sensible heat flux and the sudden drop in near-surface relative humidity around this time. This contributes to the lowering of the cloud base. The consequently increased cloud-water path facilitates subsequent warming of the cloud layer into the evening, by release of latent heat and possibly also increased absorption of solar radiation.

The second half of the diurnal cycle, particularly cloud tops appearing well into the inversion as indicated by the cloud radar, is more difficult to explain. The cloud radar indicates a drizzle maximum during this time. An increase in cloud water presumably contributes to enhanced drizzle in this CCN-sparse environment. The height to the base of the inversion layer, where subtropical stratocumulus would have the cloud top (e.g., Tjernström and Rune 2003), however, only shows a very slight and not statistically significant increase around ∼1500–1800 LT (Fig. 1). The higher cloud-top heights in the afternoon are thus inconsistent with this quasi-steady inversion-layer structure within a midlatitude or subtropical stratocumulus context. It is unlikely that a second cloud layer aloft appears at the same time on most of the days. A more likely explanation is that the boundary layer air temporally overcomes the stability of the inversion layer; either the cloud top penetrates into the inversion layer, or the mixing of moist and cool ABL air into the already moist inversion layer (e.g., Tjernström 2005) causes local cloud formation. This happens at a time when the cloud layer is the warmest and the inversion layer is the least stable. With the often quite moist inversion layer (in contrast to typical subtropical stratocumulus; Tjernström 2005), cloud tops penetrating into the inversion layer would not necessarily evaporate.

The only available humidity profiles that could be used to clarify this are from radiosoundings. These are of poorer quality and are only performed every six hours, which is not frequent enough to allow a reliable analysis of the diurnal cycle. If the jump in the equivalent potential temperature,7 θe, is sufficiently small, this would facilitate mixing of ABL cloud air into the inversion. Analyzing this jump across the inversion layer shows, although not conclusively, that the 1800 and 0000 UTC (note that UTC ∼ LT) soundings somewhat more often had smaller θe jumps than the 0600 and 1200 UTC soundings (Fig. 12a), however, always remaining positive. Higher-frequency boundary layer temperature variability can be estimated from the radiometer data. The standard deviation of the mean ABL temperature sampled over 1-h periods (Fig. 12b) has an insignificant diurnal cycle, with possibly somewhat higher values ∼07000–1200 LT (when the enhanced turbulent mixing occurs). The 95th percentile is, however, larger during the evening, indicating infrequently higher values. Over the entire AOE-2001 north of 85°N, the standard deviation of temperatures averaged over 0.2 < z zi−1 < 0.9 is >0.25°C for ∼20% of the time. Thus, 20% of the time, temperature variations as large as O(1 K) are possible. This would at least sometimes be sufficient to overcome the stability of the inversion layer. The presence of symmetric instability, or slantwise convection (Holton 2004, p. 279), could enhance shallow convection, in particular with the high Coriolis-parameter values in the Arctic. This mechanism allows unstable slantwise motions even in a vertically absolutely stable environment, provided favorable wind conditions exist (a negative moist potential vorticity). However, wind-profile information is not continuously available from any of the AOE-2001 instrument systems, and horizontal wind gradients cannot be obtained at all from these single-column observations.

Fig. 12.

Some statistics concerning the likelihood of ABL air to be able to penetrate the capping inversion showing (a) relative probability of the jump in equivalent potential temperature, in K, across the capping inversion for 1800 and 0000 UTC (solid) and 0600 and 1200 UTC (dashed) soundings, and (b) the diurnal cycle of the mean ABL temperature standard deviation, in K.

Fig. 12.

Some statistics concerning the likelihood of ABL air to be able to penetrate the capping inversion showing (a) relative probability of the jump in equivalent potential temperature, in K, across the capping inversion for 1800 and 0000 UTC (solid) and 0600 and 1200 UTC (dashed) soundings, and (b) the diurnal cycle of the mean ABL temperature standard deviation, in K.

5. Conclusions

This study analyzes late summer 2001 central Arctic boundary layer conditions, with a focus on the diurnal cycle. The vertical boundary layer structure is a shallow, cloud-capped ABL with cloud-base heights around 100 m or lower, and cloud tops at 200–400 m, associated with a capping inversion layer. Cloud tops often penetrated into this inversion. There is a clear distinction between a typically well-mixed cloudy upper and a somewhat more stably stratified subcloud boundary layer. The inversion layer is often weak except with warm-air advection directly from the open ocean. Average conditions near the surface are strongly forced by the thermodynamics of the melting surface (Tjernström et al. 2004a, 2005).

A statistically significant diurnal cycle through the boundary layer was found in many variables, although very weak for near-surface variables, except in wind speed and direction, and in net surface radiation. The cloud layer has a stronger diurnal cycle, although still much weaker than in lower-latitude cloud-capped marine boundary layers. The interesting finding is that the cloud-layer diurnal cycle here is the opposite of that found in, for example, subtropical cloud-capped marine boundary layers (e.g., Duynkerke et al. 2004). Cloud-base heights are lowest in the middle of the day, cloud-top heights are, at least temporarily, higher in the afternoon and evening and there also seems to be an afternoon-to-evening maximum in drizzle. The fact that the variability is quite low near the surface, in spite of larger variability higher in the boundary layer and a quite large free-troposphere variability (Tjernström et al. 2004a), also calls into question the usefulness of surface observations for understanding the Arctic climate, at least in summer.

Significant phases of the cloud-layer diurnal cycle are the thickening of the clouds before local noon, followed by enhanced drizzle, and later a transformation of the cloud layer from a purely stratiform to a more cumulus-convective-like structure, with temporarily lower cloud fraction and higher cloud-top heights during afternoon and early evening. Stevens et al. (1998) concluded that enhanced drizzle in a marine stratocumulus with a strong wind shear has precisely these effects. Layer depths are shallower in the Arctic than in their study; however, this may be a consequence of stronger Coriolis forcing at a northerly location. In their studies of pockets of open cells, Stevens et al. (2005) and Petters et al. (2006) conclude that organized drizzling structures seem to occur within stratocumulus with lower-than-usual droplet-number concentration and higher-than-normal moisture aloft; these indicators are also present here. Stevens et al. (2005) suggest an intriguing hypothesis: that the larger-scale atmosphere is capable of supporting more than one boundary layer structure, depending on, for example, the likelihood to support drizzle. Drizzle formation is governed by cloud microphysics. Assuming that a low droplet concentration in the Arctic favors drizzle and, moreover, that the diurnal cycle makes drizzle more likely during the afternoon and early evening, it is conceivable that the diurnal cycle found in the Arctic is also due to an organized dynamical structure, favored only during parts of the diurnal cycle. More detailed direct observations of cloud microphysical properties are required to test these hypotheses. Detailed reasonably long-term observations of summer central Arctic stratocumulus microphysics do, to our knowledge, not exist.

So what does this diurnal cycle mean? Assuming the absence of a diurnal cycle, with night and early-morning conditions prevailing, would increase the available radiation at the surface by only 1–2 W m2. This is likely too small to be of primary climatic relevance, or at least small enough that the inherent uncertainties in this study make an interpretation precarious. The assumed ingestion of water is important for the drizzle formation, but the drizzle also depletes the cloud water during the evening and night, and this variation likely drives the diurnal temperature differences between the cloud and subcloud layer necessary for the water vapor ingestion in the first place. Putting the observed diurnal cycle in this context, it is perhaps most important in indicating a unique interaction between cloud microphysics and cloud dynamics in the current CCN-sparse Arctic conditions.

We suggest that an increased aerosol-number concentration could change these conditions by inhibiting drizzle formation. Less drizzle would increase cloud water and more CCN would additionally reduce cloud-droplet sizes. Both these factors should act to increase the cloud albedo and therefore decrease the positive cloud radiative forcing at the surface. With higher and more constant cloud-water content, less solar radiation would penetrate to the surface. Since the diurnal variation in incoming solar radiation is small, the diurnal cycle would likely vanish, resulting in a more constant cloud layer with a higher cloud-water path and a higher cloud albedo.

What could cause such a change? Anthropogenic emissions of aerosols or aerosol precursors can have an effect, although there is efficient scavenging in the MIZ (e.g., Leck et al. 2001; Nilsson 1996). The MIZ is biologically very active during summer, with a high production of dimethylsulfide (DMS), dependent on release of nutrients from the melting ice; DMS is an important aerosol precursor. Leck and Bigg (1999, 2005) suggest another, local, mechanism for aerosol-particle production to explain observations in the central Arctic. This also relies on biologic activity dependent on nutrients released by melting ice, but in open water leads inside the pack ice. A warmer climate with a longer melt season and a reduced ice fraction also inside the pack ice could, with this mechanism, enhance this biological activity and therefore biogenic aerosol-particle production in the central Arctic. If this were to happen, it could alter the boundary layer and cloud dynamics toward the more subtropical stratocumulus–like optically thick structure, with less drizzle, more cloud water, and a higher cloud albedo without a diurnal cycle. This would constitute a negative feedback on Arctic warming.

Acknowledgments

The Arctic Ocean Experiment 2001 was made possible by several grants, from the Swedish Research Council (formerly Natural Research Council of Sweden), the Knut and Alice Wallenberg Foundation, and from the Swedish Polar Research Secretariat, who also provided the icebreaker Oden and the logistics for the experiment. The author thanks Caroline Leck for coordinating the atmospheric experiment, Ola Persson for providing the remote sensing instruments, and Bertil Larsson and Eric Erixon for operating the weather station and the radiosoundings on board Oden. Scott Abbot operated the remote sensing instruments, while Allen White and Vladimir Leuskiy performed the postprocessing of the remote sensing data used here. Thanks also to the crew of Oden and to fellow participants in the AOE-2001. Discussions and help with the manuscript by Gunilla Svensson and Thorsten Mauritsen are appreciated. Comments by anonymous reviewers greatly improved the manuscript. This work was performed while the author was a Visiting Fellow at the Cooperative Institute of Research in the Environmental Sciences (CIRES) at the University of Colorado and at NOAA/ESRL, Boulder, Colorado.

REFERENCES

REFERENCES
ACIA
,
2004
:
Impacts of a Warming Arctic: Arctic Climate Impact Assessment.
Cambridge University Press, 139 pp
.
Albrecht
,
B. A.
,
D. A.
Randall
, and
S.
Nicholls
,
1988
:
Observations of marine stratocumulus clouds during FIRE.
Bull. Amer. Meteor. Soc.
,
69
,
618
626
.
Albrecht
,
B. A.
,
C. S.
Bretherton
,
D.
Johnson
,
W. H.
Schubert
, and
A. S.
Frisch
,
1995
:
The Atlantic Stratocumulus Experiment—ASTEX.
Bull. Amer. Meteor. Soc.
,
76
,
889
904
.
Andreas
,
E.
,
K. J.
Klaffey
, and
A. P.
Makshtas
,
2000
:
Low level atmospheric jets and inversions over the western Weddell Sea.
Bound.-Layer Meteor.
,
97
,
459
486
.
Chlond
,
A.
,
F.
Muller
, and
I.
Sednev
,
2004
:
Numerical simulation of the diurnal cycle of marine stratocumulus during FIRE—An LES and SCM modelling study.
Quart. J. Roy. Meteor. Soc.
,
130
,
3297
3321
.
Comstock
,
K. K.
,
C. S.
Bretherton
, and
S. E.
Yuter
,
2005
:
Mesoscale variability and drizzle in southeast Pacific stratocumulus.
J. Atmos. Sci.
,
62
,
3792
3807
.
Duynkerke
,
P. G.
, and
Coauthors
,
2004
:
Observations and numerical simulations of the diurnal cycle of the EUROCS stratocumulus case.
Quart. J. Roy. Meteor. Soc.
,
130
,
3269
3296
.
Girard
,
E.
,
J-P.
Blanchet
, and
Y.
Dubois
,
2005
:
Effects of arctic sulphuric acid aerosols on wintertime low-level atmospheric ice crystals, humidity and temperature at Alert, Nunavut.
Atmos. Res.
,
73
,
131
148
.
Heintzenberg
,
J.
,
C.
Leck
,
W.
Birmili
,
B.
Wehner
, and
M.
Tjernström
,
2006
:
Aerosol number-size distributions during clear and fog periods in the summer high Arctic: 1991, 1996, and 2006.
Tellus
,
58B
,
41
50
.
Hodur
,
R. M.
,
1997
:
The Naval Research Laboratory’s Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS).
Mon. Wea. Rev.
,
125
,
1414
1430
.
Holland
,
M. M.
, and
C. M.
Bitz
,
2003
:
Polar amplification of climate change in coupled models.
Climate Dyn.
,
21
,
221
232
.
Holton
,
J. R.
,
2004
:
An Introduction to Dynamic Meteorology.
4th ed. Elsevier Academic, 507 pp
.
Intrieri
,
J. M.
,
C. W.
Fairall
,
M. D.
Shupe
,
P. O. G.
Persson
,
E. L.
Andreas
,
P. S.
Guest
, and
R. E.
Moritz
,
2002a
:
An annual cycle of Arctic surface cloud forcing at SHEBA.
J. Geophys. Res.
,
107
.
8039, doi:10.1029/2000JC000439
.
Intrieri
,
J. M.
,
M. D.
Shupe
,
T.
Uttal
, and
B. J.
McCarty
,
2002b
:
An annual cycle of Arctic cloud characteristics observed by radar and lidar at SHEBA.
J. Geophys. Res.
,
107
.
8030, doi:10.1029/2000JC000423
.
Kattsov
,
V. M.
, and
E.
Källén
,
2004
:
Future climate change: Modeling and scenarios for the Arctic.
Impacts of a Warming Arctic: Arctic Climate Impacts Assessment, S. J. Hassol, Ed., Cambridge University Press, 99–150
.
Leck
,
C.
, and
E. K.
Bigg
,
1999
:
Aerosol production over remote marine areas—A new route.
Geophys. Res. Lett.
,
26
,
3577
3580
.
Leck
,
C.
, and
E. K.
Bigg
,
2005
:
Source and evolution of the marine aerosol—A new perspective.
Geophys. Res. Lett.
,
32
.
L19803, doi:10.1029/2005GL023651
.
Leck
,
C.
,
E. D.
Nilsson
,
E. K.
Bigg
, and
L.
Bäcklin
,
2001
:
Atmospheric program on the Arctic Ocean Expedition 1996 (AOE-96): An overview of scientific goals, experimental approach, and instruments.
J. Geophys. Res.
,
106
,
32051
32067
.
Leck
,
C.
,
M.
Tjernström
,
P.
Matrai
, and
E.
Swietlicki
,
2004
:
Microbes, clouds and climate: Can marine microorganisms influence the melting of the Arctic pack ice?
Eos, Trans. Amer. Geophys. Union
,
85
,
25
36
.
MacBean
,
G.
,
2004
:
Arctic climate—Past and present.
Impacts of a Warming Arctic: Arctic Climate Impacts Assessment, S. J. Hassol, Ed., Cambridge University Press, 21–60
.
Nicholls
,
S.
,
1984
:
The dynamics of stratocumulus: Aircraft observations and comparisons with a mixed layer model.
Quart. J. Roy. Meteor. Soc.
,
110
,
783
820
.
Nicholls
,
S.
, and
J.
Leighton
,
1986
:
An observational study of the structure of stratiform cloud streets. Part I: Structure.
Quart. J. Roy. Meteor. Soc.
,
112
,
431
460
.
Nilsson
,
E. D.
,
1996
:
Planetary boundary layer structure and air mass transport during the International Arctic Ocean Expedition 1991.
Tellus
,
48B
,
178
196
.
Overpeck
,
J. T.
, and
Coauthors
,
2005
:
Arctic system on trajectory to new, seasonally ice-free state.
Eos, Trans. Amer. Geophys. Union
,
86
,
309
316
.
Petters
,
M. D.
,
J. R.
Snider
,
B.
Stevens
,
G.
Vali
,
I.
Faloona
, and
L. M.
Russell
,
2006
:
Accumulation mode aerosol, pockets of open cells, and particle nucleation in the remote subtropical Pacific marine boundary layer.
J. Geophys. Res.
,
111
.
D02206, doi:10.1029/2004JD005694
.
Prenni
,
A. J.
, and
Coauthors
,
2007
:
Can ice-nucleating aerosols affect arctic seasonal climate?
Bull. Amer. Meteor. Soc.
,
88
,
541
550
.
Rozendaal
,
M. A.
,
C. B.
Leovy
, and
S. A.
Klein
,
1995
:
An observational study of diurnal variations of marine stratiform cloud.
J. Climate
,
8
,
1795
1809
.
Serreze
,
M.
, and
J. A.
Francis
,
2006
:
The Arctic amplification debate.
Climatic Change
,
76
.
doi:10.1007/s10584-005-9017-y
.
Söderberg
,
S.
,
M.
Tjernström
, and
M.
Žagar
,
2006
:
Modeling the summer Arctic boundary layer.
Polar Mar. Res.
,
520
,
107
111
.
Stevens
,
B.
,
W. R.
Cotton
,
G.
Feingold
, and
C-H.
Moeng
,
1998
:
Large-eddy simulations of strongly precipitating, shallow, stratocumulus-topped boundary layers.
J. Atmos. Sci.
,
55
,
3616
3638
.
Stevens
,
B.
, and
Coauthors
,
2003
:
Dynamics and chemistry of marine stratocumulus—DYCOMS-II.
Bull. Amer. Meteor. Soc.
,
84
,
579
593
.
Stevens
,
B.
,
G.
Vali
,
K.
Comstock
,
R.
Wood
,
M. C.
van Zanten
,
P. H.
Austin
,
C. S.
Bretherton
, and
D. H.
Lenschow
,
2005
:
Pockets of open cells and drizzle in marine stratocumulus.
Bull. Amer. Meteor. Soc.
,
86
,
51
57
.
Stull
,
R. B.
,
1988
:
An Introduction to Boundary Layer Meteorology.
Kluwer Academic, 666 pp
.
Svensson
,
G.
,
M.
Tjernström
, and
D.
Koračin
,
2000
:
The sensitivity of a stratocumulus transition: Model simulations of the ASTEX first Lagrangian.
Bound.-Layer Meteor.
,
95
,
57
90
.
Tjernström
,
M.
,
2005
:
The summer Arctic boundary layer during the Arctic Ocean Experiment 2001 (AOE-2001).
Bound.-Layer Meteor.
,
117
,
5
36
.
Tjernström
,
M.
, and
A.
Rune
,
2003
:
The turbulence structure of stratocumulus during the ASTEX first Lagrangian experiment.
Quart. J. Roy. Meteor. Soc.
,
129
,
1071
1100
.
Tjernström
,
M.
,
C.
Leck
,
P. O. G.
Persson
,
M. L.
Jensen
,
S. P.
Oncley
, and
A.
Targino
,
2004a
:
The summertime Arctic atmosphere: Meteorological measurements during the Arctic Ocean Experiment 2001.
Bull. Amer. Meteor. Soc.
,
85
,
1305
1321
.
Tjernström
,
M.
,
C.
Leck
,
P. O. G.
Persson
,
M. L.
Jensen
,
S. P.
Oncley
, and
A.
Targino
,
2004b
:
Experimental equipment: A supplement to the summertime Arctic atmosphere: Meteorological measurements during the Arctic Ocean Experiment 2001.
Bull. Amer. Meteor. Soc.
,
85
,
ES14
ES18
.
Turton
,
J. D.
, and
S.
Nicholls
,
1987
:
A study of the diurnal variation of stratocumulus using a multiple mixed layer model.
Quart. J. Roy. Meteor. Soc.
,
113
,
969
1009
.
Twomey
,
S.
,
1977
:
The influence of pollution on the shortwave albedo of clouds.
J. Atmos. Sci.
,
34
,
1149
1152
.
Uttal
,
T.
, and
Coauthors
,
2002
:
Surface heat budget of the Arctic Ocean.
Bull. Amer. Meteor. Soc.
,
83
,
255
275
.
Walsh
,
J. E.
,
V. M.
Kattsov
,
W. L.
Chapman
,
V.
Govorkova
, and
T.
Pavlova
,
2002
:
Comparison of Arctic climate simulations by uncoupled and coupled global models.
J. Climate
,
15
,
1429
1446
.
Westwater
,
E. R.
,
Y.
Han
,
V. G.
Irisov
,
V.
Leuskiy
,
E. N.
Kadygrov
, and
S. A.
Viazankin
,
1999
:
Remote sensing of boundary layer temperature profiles by a scanning 5-mm microwave radiometer and RASS: Comparison experiments.
J. Atmos. Oceanic Technol.
,
16
,
805
818
.
White
,
A. B.
,
J. R.
Jordan
,
B. E.
Martner
,
F. M.
Ralph
, and
B. W.
Bartram
,
2000
:
Extending the dynamic range of an S-band radar for cloud and precipitation studies.
J. Atmos. Oceanic Technol.
,
17
,
1226
1234
.

Footnotes

Corresponding author address: Michael Tjernström, Department of Meteorology, Stockholm University, SE-106 91, Stockholm, Sweden. Email: michaelt@misu.su.se

1

Here Rig = (g0)(∂Θ/∂z)/((∂U/∂z))2, where Θ is the potential temperature, U is scalar wind speed, and z is the height above the surface.

2

The ice drift was initiated near the Greenwich meridian, and never deviated far from this; UTC is thus often a good approximation to the local time (LT). For the analysis of the diurnal cycle all data were time adjusted to LT, using UTC and the location of the icebreaker. When discussing the time of the day, phrases like “daytime” and “nighttime” always refer to the local time even though night did not occur in the sense that the sun was always above the horizon.

3

DoY means Day of the Year, with DoY = 1.0 at 0000 UTC 1 January.

4

Here u* = (−)1/2, where u and w are the turbulent fluctuations of the alongwind and vertical wind-speed components, respectively, and the overbar represents an average.

5

Here ρcp, where θ is the turbulent fluctuations of potential temperature, ρ is the density of air, and cp is the heat capacity of dry air at constant pressure.

6

TKE = 0.5 (+ + ), where υ is the turbulent fluctuations of the cross-stream-wise wind-speed component.

7

Here Θe = Θ + (LΘ/CpT)q, Θ is the potential temperature, q is the specific water vapor, and T is the temperature at the lifting condensation level.