Arctic Clouds Research Articles

A modelling study of the continuous ice formation in an autumnal Arctic mixed-phase cloud case

An autumnal Arctic mixed-phase cloud case from the Mixed-Phase Arctic Cloud Experiment is simulated with the Weather Research and Forecasting model with a prognostic ice-nucleating particle (INP) formulation to investigate the mechanisms sustaining the continuous ice formation. When the model is run with only primary ice production (PIP) processes, it needs 100 times the observed INP concentration to reproduce the observations. When a secondary ice production (SIP) process, i.e., droplet shattering when supercooled droplets freeze heterogeneously, is added, the model needs 50 times the observed INP concentration to reproduce the observations. Two factors are found to reduce the INP concentration required to reproduce the observations. First, as the cloud moves over the open ocean, the cloud top rises quickly, resulting in a cloud top entrainment rate of ~3.0 cm s−1, which is 4 times as large as that in previous large-eddy simulations of the same case. More INPs can hence be entrained into the cloud. Second, INPs are recycled when ice crystals are completely sublimated below the cloud base. Sensitivity tests show that INP recycling reduces the required INP concentration by a factor of 4. In addition, offline tests show that another two SIP processes, i.e., droplet shattering when supercooled droplets collect small ice crystals and breakup during ice-ice collision, do not substantially contribute to the ice formation in this case.

Lidar measurements of thin laminations within Arctic clouds

Abstract. Very thin ( < 10 m) laminations within Arctic clouds have been observed in all seasons using the Canadian Network for the Detection of Atmospheric Change (CANDAC) Rayleigh–Mie–Raman lidar (CRL) at the Polar Environment Atmospheric Research Laboratory (PEARL; located at Eureka, Nunavut, in the Canadian High Arctic). CRL's time (1 min) and altitude (7.5 m) resolutions from 500 m to greater than 12 km altitude make these measurements possible. We have observed a variety of thicknesses for individual laminations, with some at least as thin as the detection limit of the lidar (7.5 m). The clouds which contain the laminated features are typically found below 4 km, can last longer than 24 h, and occur most frequently during periods of snow and rain, often during very stable temperature inversion conditions. Results are presented for range-scaled photocounts at 532 and 355 nm, ratios of 532∕355 nm photocounts, and the 532 nm linear depolarization parameter, and with context provided by twice-daily Eureka radiosonde temperature and relative humidity profiles.

RMetS National Meeting – Arctic prediction in a changing climate: understanding key processes and challenges

RMetS National Meeting – Arctic prediction in a changing climate: understanding key processes and challenges

Year‐Round In Situ Measurements of Arctic Low‐Level Clouds: Microphysical Properties and Their Relationships With Aerosols

AbstractTwo years of continuous in situ measurements of Arctic low‐level clouds have been made at the Mount Zeppelin Observatory (78°56′N, 11°53′E), in Ny‐Ålesund, Spitsbergen. The monthly median value of the cloud particle number concentration (Nc) showed a clear seasonal variation: Its maximum appeared in May–July (65 ± 8 cm−3), and it remained low between October and March (8 ± 7 cm−3). At temperatures warmer than 0 °C, a clear correlation was found between the hourly Nc values and the number concentrations of aerosols with dry diameters larger than 70 nm (N70), which are proxies for cloud condensation nuclei (CCN). When clouds were detected at temperatures colder than 0 °C, some of the data followed the summertime Nc to N70 relationship, while other data showed systematically lower Nc values. The lidar‐derived depolarization ratios suggested that the former (CCN‐controlled) and latter (CCN‐uncontrolled) data generally corresponded to clouds consisting of supercooled water droplets and those containing ice particles, respectively. The CCN‐controlled data persistently appeared throughout the year at Zeppelin. The aerosol‐cloud interaction index (ACI = dlnNc/(3dlnN70)) for the CCN‐controlled data showed high sensitivities to aerosols both in the summer (clean air) and winter–spring (Arctic haze) seasons (0.22 ± 0.03 and 0.25 ± 0.02, respectively). The air parcel model calculations generally reproduced these values. The threshold diameters of aerosol activation (Dact), which account for the Nc of the CCN‐controlled data, were as low as 30–50 nm when N70 was less than 30 cm−3, suggesting that new particle formation can affect Arctic cloud microphysics.

Arctic Summer Airmass Transformation, Surface Inversions, and the Surface Energy Budget

During the Arctic Clouds in Summer Experiment (ACSE) in summer 2014 a weeklong period of warm-air advection over melting sea ice, with the formation of a strong surface temperature inversion and dense fog, was observed. Based on an analysis of the surface energy budget, we formulated the hypothesis that, because of the airmass transformation, additional surface heating occurs during warm-air intrusions in a zone near the ice edge. To test this hypothesis, we explore all cases with surface inversions occurring during ACSE and then characterize the inversions in detail. We find that they always occur with advection from the south and are associated with subsidence. Analyzing only inversion cases over sea ice, we find two categories: one with increasing moisture in the inversion and one with constant or decreasing moisture with height. During surface inversions with increasing moisture with height, an extra 10–25 W m−2of surface heating was observed, compared to cases without surface inversions; the surface turbulent heat flux was the largest single term. Cases with less moisture in the inversion were often cloud free and the extra solar radiation plus the turbulent surface heat flux caused by the inversion was roughly balanced by the loss of net longwave radiation.

A Process-Based Climatological Evaluation of AIRS Level 3 Tropospheric Thermodynamics over the High-Latitude Arctic

AbstractMeasurements from spaceborne sensors have the unique capacity to fill spatial and temporal gaps in ground-based atmospheric observing systems, especially over the Arctic, where long-term observing stations are limited to pan-Arctic landmasses and infrequent field campaigns. The AIRS level 3 (L3) daily averaged thermodynamic profile product is widely used for process understanding across the sparsely observed Arctic atmosphere. However, detailed investigations into the accuracy of the AIRS L3 thermodynamic profiles product using in situ observations over the high-latitude Arctic are lacking. To address this void, we compiled a wealth of radiosounding profiles from long-term Arctic land stations and included soundings from intensive icebreaker-based field campaigns. These are used to evaluate daily mean thermodynamic profiles from the AIRS L3 product so that the community can understand to what extent such data records can be applied in scientific studies. Results indicate that, while the mid- to upper-troposphere temperature and specific humidity are captured relatively well by AIRS, the lower troposphere is susceptible to specific seasonal, and even monthly, biases. These differences have a critical influence on the lower-tropospheric stability structure. The relatively coarse vertical resolution of the AIRS L3 product, together with infrared radiation through persistent low Arctic cloud layers, leads to artificial thermodynamic structures that fail to accurately represent the lower Arctic atmosphere. These thermodynamic errors are likely to introduce artificial errors in the boundary layer structure and analysis of associated physical processes.

Meteorological conditions during the ACLOUD/PASCAL field campaign near Svalbard in early summer 2017

Abstract. The two concerted field campaigns, Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD) and the Physical feedbacks of Arctic planetary boundary level Sea ice, Cloud and AerosoL (PASCAL), took place near Svalbard from 23 May to 26 June 2017. They were focused on studying Arctic mixed-phase clouds and involved observations from two airplanes (ACLOUD), an icebreaker (PASCAL) and a tethered balloon, as well as ground-based stations. Here, we present the synoptic development during the 35-day period of the campaigns, using near-surface and upper-air meteorological observations, as well as operational satellite, analysis, and reanalysis data. Over the campaign period, short-term synoptic variability was substantial, dominating over the seasonal cycle. During the first campaign week, cold and dry Arctic air from the north persisted, with a distinct but seasonally unusual cold air outbreak. Cloudy conditions with mostly low-level clouds prevailed. The subsequent 2 weeks were characterized by warm and moist maritime air from the south and east, which included two events of warm air advection. These synoptical disturbances caused lower cloud cover fractions and higher-reaching cloud systems. In the final 2 weeks, adiabatically warmed air from the west dominated, with cloud properties strongly varying within the range of the two other periods. Results presented here provide synoptic information needed to analyze and interpret data of upcoming studies from ACLOUD/PASCAL, while also offering unprecedented measurements in a sparsely observed region.

Marine and terrestrial influences on ice nucleating particles during continuous springtime measurements in an Arctic oilfield location

Abstract. Aerosols that serve as ice nucleating particles (INPs) have the potential to modulate cloud microphysical properties and can therefore impact cloud radiative forcing (CRF) and precipitation formation processes. In remote regions such as the Arctic, aerosol–cloud interactions are severely understudied yet may have significant implications for the surface energy budget and its impact on sea ice and snow surfaces. Further, uncertainties in model representations of heterogeneous ice nucleation are a significant hindrance to simulating Arctic mixed-phase cloud processes. We present results from a campaign called INPOP (Ice Nucleating Particles at Oliktok Point), which took place at a US Department of Energy Atmospheric Radiation Measurement (DOE ARM) facility in the northern Alaskan Arctic. Three time- and size-resolved aerosol impactors were deployed from 1 March to 31 May 2017 for offline ice nucleation and chemical analyses and were co-located with routine measurements of aerosol number and size. The largest particles (i.e., ≥ 3 µm or “coarse mode”) were the most efficient INPs by inducing freezing at the warmest temperatures. During periods with snow- and ice-covered surfaces, coarse mode INP concentrations were very low (maximum of 6 × 10−4 L−1 at −15 ∘C), but higher concentrations of warm-temperature INPs were observed during late May (maximum of 2 × 10−2 L−1 at −15 ∘C). These higher concentrations were attributed to air masses originating from over open Arctic Ocean water and tundra surfaces. To our knowledge, these results represent the first INP characterization measurements in an Arctic oilfield location and demonstrate strong influences from mineral and marine sources despite the relatively high springtime pollution levels. Ultimately, these results can be used to evaluate the anthropogenic and natural influences on aerosol composition and Arctic cloud properties.

The Arctic Cloud Puzzle: Using ACLOUD/PASCAL Multiplatform Observations to Unravel the Role of Clouds and Aerosol Particles in Arctic Amplification

AbstractClouds play an important role in Arctic amplification. This term represents the recently observed enhanced warming of the Arctic relative to the global increase of near-surface air temperature. However, there are still important knowledge gaps regarding the interplay between Arctic clouds and aerosol particles, and surface properties, as well as turbulent and radiative fluxes that inhibit accurate model simulations of clouds in the Arctic climate system. In an attempt to resolve this so-called Arctic cloud puzzle, two comprehensive and closely coordinated field studies were conducted: the Arctic Cloud Observations Using Airborne Measurements during Polar Day (ACLOUD) aircraft campaign and the Physical Feedbacks of Arctic Boundary Layer, Sea Ice, Cloud and Aerosol (PASCAL) ice breaker expedition. Both observational studies were performed in the framework of the German Arctic Amplification: Climate Relevant Atmospheric and Surface Processes, and Feedback Mechanisms (AC)3 project. They took place in the vicinity of Svalbard, Norway, in May and June 2017. ACLOUD and PASCAL explored four pieces of the Arctic cloud puzzle: cloud properties, aerosol impact on clouds, atmospheric radiation, and turbulent dynamical processes. The two instrumented Polar 5 and Polar 6 aircraft; the icebreaker Research Vessel (R/V) Polarstern; an ice floe camp including an instrumented tethered balloon; and the permanent ground-based measurement station at Ny-Ålesund, Svalbard, were employed to observe Arctic low- and mid-level mixed-phase clouds and to investigate related atmospheric and surface processes. The Polar 5 aircraft served as a remote sensing observatory examining the clouds from above by downward-looking sensors; the Polar 6 aircraft operated as a flying in situ measurement laboratory sampling inside and below the clouds. Most of the collocated Polar 5/6 flights were conducted either above the R/V Polarstern or over the Ny-Ålesund station, both of which monitored the clouds from below using similar but upward-looking remote sensing techniques as the Polar 5 aircraft. Several of the flights were carried out underneath collocated satellite tracks. The paper motivates the scientific objectives of the ACLOUD/PASCAL observations and describes the measured quantities, retrieved parameters, and the applied complementary instrumentation. Furthermore, it discusses selected measurement results and poses critical research questions to be answered in future papers analyzing the data from the two field campaigns.

Evidence for Changes in Arctic Cloud Phase Due to Long‐Range Pollution Transport

AbstractReduced precipitation rates allow pollution within air parcels from midlatitudes to reach the Arctic without being scavenged. We use satellite and tracer transport model data sets to evaluate the degree of supercooling required for 50% of a chosen ensemble of low‐level clouds to be in the ice phase for a given meteorological regime. Our results suggest that smaller cloud droplet effective radii are related to higher required amounts of supercooling but that, overall, pollution plumes from fossil fuel combustion lower the degree of supercooling that is required for freezing by approximately 4 °C. The relationship between anthropogenic plumes and the freezing transition temperature from liquid to ice remains to be explained.

Simulated and observed horizontal inhomogeneities of optical thickness of Arctic stratus

Abstract. Two-dimensional horizontal fields of cloud optical thickness τ derived from airborne measurements of solar spectral, cloud-reflected radiance are compared with semi-idealized large eddy simulations (LESs) of Arctic stratus performed with the Consortium for Small-scale Modeling (COSMO) atmospheric model. The measurements were collected during the Vertical Distribution of Ice in Arctic Clouds (VERDI) campaign carried out in Inuvik, Canada, in April/May 2012. The input for the LESs is obtained from collocated airborne dropsonde observations of a persistent Arctic stratus above the sea-ice-free Beaufort Sea. Simulations are performed for spatial resolutions of 50 m (1.6 km × 1.6 km domain) and 100 m (6.4 km × 6.4 km domain). Macrophysical cloud properties, such as cloud top altitude and vertical extent, are well captured by the COSMO simulations. However, COSMO produces rather homogeneous clouds compared to the measurements, in particular for the simulations with coarser spatial resolution. For both spatial resolutions, the directional structure of the cloud inhomogeneity is well represented by the model. Differences between the individual cases are mainly associated with the wind shear near cloud top and the vertical structure of the atmospheric boundary layer. A sensitivity study changing the wind velocity in COSMO by a vertically constant scaling factor shows that the directional, small-scale cloud inhomogeneity structures can range from 250 to 800 m, depending on the mean wind speed, if the simulated domain is large enough to capture also large-scale structures, which then influence the small-scale structures. For those cases, a threshold wind velocity is identified, which determines when the cloud inhomogeneity stops increasing with increasing wind velocity.

A model intercomparison of CCN-limited tenuous clouds in the high Arctic

Abstract. We perform a model intercomparison of summertime high Arctic (> 80∘ N) clouds observed during the 2008 Arctic Summer Cloud Ocean Study (ASCOS) campaign, when observed cloud condensation nuclei (CCN) concentrations fell below 1 cm−3. Previous analyses have suggested that at these low CCN concentrations the liquid water content (LWC) and radiative properties of the clouds are determined primarily by the CCN concentrations, conditions that have previously been referred to as the tenuous cloud regime. The intercomparison includes results from three large eddy simulation models (UCLALES-SALSA, COSMO-LES, and MIMICA) and three numerical weather prediction models (COSMO-NWP, WRF, and UM-CASIM). We test the sensitivities of the model results to different treatments of cloud droplet activation, including prescribed cloud droplet number concentrations (CDNCs) and diagnostic CCN activation based on either fixed aerosol concentrations or prognostic aerosol with in-cloud processing. There remains considerable diversity even in experiments with prescribed CDNCs and prescribed ice crystal number concentrations (ICNC). The sensitivity of mixed-phase Arctic cloud properties to changes in CDNC depends on the representation of the cloud droplet size distribution within each model, which impacts autoconversion rates. Our results therefore suggest that properly estimating aerosol–cloud interactions requires an appropriate treatment of the cloud droplet size distribution within models, as well as in situ observations of hydrometeor size distributions to constrain them. The results strongly support the hypothesis that the liquid water content of these clouds is CCN limited. For the observed meteorological conditions, the cloud generally did not collapse when the CCN concentration was held constant at the relatively high CCN concentrations measured during the cloudy period, but the cloud thins or collapses as the CCN concentration is reduced. The CCN concentration at which collapse occurs varies substantially between models. Only one model predicts complete dissipation of the cloud due to glaciation, and this occurs only for the largest prescribed ICNC tested in this study. Global and regional models with either prescribed CDNCs or prescribed aerosol concentrations would not reproduce these dissipation events. Additionally, future increases in Arctic aerosol concentrations would be expected to decrease the frequency of occurrence of such cloud dissipation events, with implications for the radiative balance at the surface. Our results also show that cooling of the sea-ice surface following cloud dissipation increases atmospheric stability near the surface, further suppressing cloud formation. Therefore, this suggests that linkages between aerosol and clouds, as well as linkages between clouds, surface temperatures, and atmospheric stability need to be considered for weather and climate predictions in this region.

Characteristic Atmospheric Radiative Heating Rate Profiles in Arctic Clouds as Observed at Barrow, Alaska

AbstractA 2-yr cloud microphysical property dataset derived from ground-based remote sensors at the Atmospheric Radiation Measurement site near Barrow, Alaska, was used as input into a radiative transfer model to compute radiative heating rate (RHR) profiles in the atmosphere. Both the longwave (LW; 5–100 μm) and shortwave (SW; 0.2–5 μm) RHR profiles show significant month-to-month variability because of seasonal dependence in the vertical profiles of cloud liquid and ice water contents, with additional contributions from the seasonal dependencies of solar zenith angle, water vapor amount, and temperature. The LW and SW RHR profiles were binned to provide characteristic profiles as a function of cloud type and liquid water path (LWP). Single-layer liquid-only clouds are shown to have larger (10–30 K day−1) LW radiative cooling rates at the top of the cloud layer than single-layer mixed-phase clouds; this is due primarily to differences in the vertical distribution of liquid water between the two classes. However, differences in SW RHR profiles at the top of these two classes of clouds are less than 3 K day−1. The absolute value of the RHR in single-layer ice-only clouds is an order of magnitude smaller than in liquid-bearing clouds. Furthermore, for double-layer cloud systems, the phase and condensed water path of the upper cloud strongly modulate the radiative cooling both at the top and within the lower-level cloud. While sensitivity to cloud overlap and phase has been shown previously, the characteristic RHR profiles are markedly different between the different cloud classifications.

Isolating the Liquid Cloud Response to Recent Arctic Sea Ice Variability Using Spaceborne Lidar Observations

AbstractWhile the radiative influence of clouds on Arctic sea ice is known, the influence of sea ice cover on Arctic clouds is challenging to detect, separate from atmospheric circulation, and attribute to human activities. Providing observational constraints on the two‐way relationship between sea ice cover and Arctic clouds is important for predicting the rate of future sea ice loss. Here we use 8 years of CALIPSO (Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observations) spaceborne lidar observations from 2008 to 2015 to analyze Arctic cloud profiles over sea ice and over open water. Using a novel surface mask to restrict our analysis to where sea ice concentration varies, we isolate the influence of sea ice cover on Arctic Ocean clouds. The study focuses on clouds containing liquid water because liquid‐containing clouds are the most important cloud type for radiative fluxes and therefore for sea ice melt and growth. Summer is the only season with no observed cloud response to sea ice cover variability: liquid cloud profiles are nearly identical over sea ice and over open water. These results suggest that shortwave summer cloud feedbacks do not slow long‐term summer sea ice loss. In contrast, more liquid clouds are observed over open water than over sea ice in the winter, spring, and fall in the 8 year mean and in each individual year. Observed fall sea ice loss cannot be explained by natural variability alone, which suggests that observed increases in fall Arctic cloud cover over newly open water are linked to human activities.

High Sensitivity of Arctic Liquid Clouds to Long‐Range Anthropogenic Aerosol Transport

AbstractThe rate of warming in the Arctic depends upon the response of low‐level microphysical and radiative cloud properties to aerosols advected from distant anthropogenic and biomass‐burning sources. Cloud droplet cross‐section density increases with higher concentrations of cloud condensation nuclei, leading to an increase of cloud droplet absorption and scattering radiative cross sections. The challenge of assessing the magnitude of the effect has been decoupling the aerosol impacts on clouds from how clouds change solely due to natural meteorological variability. Here we address this issue with large, multi‐year satellite, meteorological, and tracer transport model data sets to show that the response of low‐level clouds in the Arctic to anthropogenic aerosols lies close to a theoretical maximum and is between 2 and 8 times higher than has been observed elsewhere. However, a previously described response of arctic clouds to biomass‐burning plumes appears to be overstated because the interactions are rare and modification of cloud radiative properties appears better explained by coincident changes in temperature, humidity, and atmospheric stability.

Active sensor synergy for arctic cloud microphysics

In this study, we focus on the retrieval of liquid and ice-phase cloud microphysics from spaceborne and ground-based lidar-cloud radar synergy. As an application of the cloud retrieval algorithm developed for the EarthCARE satellite mission (JAXA-ESA) [1], the derived statistics of cloud microphysical properties in high latitudes and their relation to the Arctic climate are investigated.

Elucidating the Role of Anthropogenic Aerosols in Arctic Sea Ice Variations

AbstractObservations show that the Arctic sea ice cover has been shrinking at an unprecedented rate since the 1970s. Even though the accumulation of greenhouse gases in the atmosphere has been closely linked with the loss of Arctic sea ice, the role of atmospheric aerosols in past and future Arctic climate change remains elusive. Using a state-of-the-art fully coupled climate model, the authors assess the equilibrium responses of the Arctic sea ice to the different aerosol emission scenarios and investigate the pathways by which aerosols impose their influence in the Arctic. These sensitivity experiments show that the impacts of aerosol perturbations on the pace of sea ice melt effectively modulate the ocean circulation and atmospheric feedbacks. Because of the contrasting evolutions of particulate pollution in the developed and developing countries since the 1970s, the opposite aerosol forcings from different midlatitude regions are nearly canceled out in the Arctic during the boreal summer, resulting in a muted aerosol effect on the recent sea ice changes. Consequently, the greenhouse forcing alone can largely explain the observed Arctic sea ice loss up to the present. In the next few decades, the projected alleviation of particulate pollution in the Northern Hemisphere can contribute up to 20% of the total Arctic sea ice loss and 0.7°C surface warming over the Arctic. The authors’ model simulations further show that aerosol microphysical effects on the Arctic clouds are the major component in the total aerosol radiative forcing over the Arctic. Compared to the aerosol-induced energy imbalance in lower latitudes outside the Arctic, the local radiative forcing by aerosol variations within the Arctic, due to either local emissions or long-range transports, is more efficient in determining the sea ice changes and Arctic climate change.

The Effect of Ice Nuclei Efficiency on Arctic Mixed-Phase Clouds from Large-Eddy Simulations

Abstract The effects of ice nuclei (IN) efficiency on the persistent ice formation in Arctic mixed-phase clouds (AMCs) are investigated using a large-eddy simulation model, coupled to a bin microphysics scheme with a prognostic IN formulation. In the three cases where the IN efficiency is high, ice formation and IN depletion are fast. When the IN concentration is 1 and 10 g−1, IN are completely depleted and the cloud becomes purely liquid phase before the end of the 24-h simulation. When the IN concentration is 100 g−1, the IN supply is sufficient but the liquid water is completely consumed so that the cloud dissipates quickly. In the three cases when the IN efficiency is low, ice formation is negligible in the first several hours but becomes significant as the temperature is decreased through longwave cooling. Before the end of the simulation, the cloud is in mixed phase when the IN concentration is 1 and 10 g−1 but dissipates when the IN concentration is 100 g−1. In the case where two types of IN are considered, ice formation persists throughout the simulation. Analysis shows that as the more efficient IN are continuously removed through ice formation, the less efficient IN gradually nucleate more ice crystals because the longwave cooling decreases the cloud temperature. This mechanism is further illustrated with a simple model. These results indicate that a spectrum of IN efficiency is necessary to maintain the persistent ice formation in AMCs.

The Response of Simulated Arctic Mixed‐Phase Stratocumulus to Sea Ice Cover Variability in the Absence of Large‐Scale Advection

AbstractThis study examines the responses of Arctic mixed‐phase stratocumulus boundary layer to sea ice cover variability near the sea ice margins using large eddy simulations. The simulations are conducted for two different atmospheric conditions, based on observations from the Surface Heat Budget of the Arctic Ocean Experiment (SHEBA) (100% sea ice‐covered) and the Mixed‐Phase Arctic Cloud Experiment (M‐PACE) (open ocean). The effect of sea ice cover variability is investigated for both atmospheric conditions by conducting a series of simulations prescribed with varying amounts of sea ice cover and no large‐scale advection. As sea ice cover amount decreases, the SHEBA boundary layer deepens and becomes decoupled. The relative strength of turbulence driven by surface heating to that driven by cloud top radiative cooling increases. Cloud ice and snow grow more efficiently than cloud liquid with moisture transported from the lower boundary layer. On the other hand, as sea ice cover amount increases, the M‐PACE boundary layer becomes shallower and more coupled with the surface as turbulence mainly driven by cloud top radiative cooling. Moisture supply from the surface is reduced, while cloud droplets are generated from turbulence at cloud top with little ice formation. In both atmospheric conditions, the boundary layer turbulence structure is modified according to change in the relative strength of boundary layer turbulent sources as sea ice amount changes, resulting in the growth/decay of the cloud layer. Simulations with smaller sea ice cover amounts are associated with more cloud ice but not necessarily more cloud liquid.

Depolarization calibration and measurements using the CANDAC Rayleigh–Mie–Raman lidar at Eureka, Canada

Abstract. The Canadian Network for the Detection of Atmospheric Change (CANDAC) Rayleigh–Mie–Raman lidar (CRL) at Eureka, Nunavut, has measured tropospheric clouds, aerosols, and water vapour since 2007. In remote and meteorologically significant locations, such as the Canadian High Arctic, the ability to add new measurement capability to an existing well-tested facility is extremely valuable. In 2010, linear depolarization 532 nm measurement hardware was installed in the lidar's receiver. To minimize disruption in the existing lidar channels and to preserve their existing characterization so far as is possible, the depolarization hardware was placed near the end of the receiver cascade. The upstream optics already in place were not optimized for preserving the polarization of received light. Calibrations and Mueller matrix calculations are used to determine and mitigate the contribution of these upstream optics on the depolarization measurements. The results show that with appropriate calibration, indications of cloud particle phase (ice vs. water) through the use of the depolarization parameter are now possible to a precision of ±0.05 absolute uncertainty ( ≤ 10 % relative uncertainty) within clouds at time and altitude resolutions of 5 min and 37.5 m respectively, with higher precision and higher resolution possible in select cases. The uncertainty is somewhat larger outside of clouds at the same altitude, typically with absolute uncertainty ≤ 0.1. Monitoring changes in Arctic cloud composition, including particle phase, is essential for an improved understanding of the changing climate locally and globally.