The amount of ice present in clouds can affect cloud lifetime, precipitation and radiative properties 1,2 . The formation of ice in clouds is facilitated by the presence of airborne ice nucleating particles 1,2 . Sea spray is one of the major global sources of atmospheric particles, but it is unclear to what extent these particles are capable of nucleating ice 3-11 . Sea spray aerosol contains large amounts of organic material that is ejected into the atmosphere during bubble bursting at the organically enriched sea-air interface or sea surface microlayer [12][13][14][15][16][17][18][19] . Here we show that organic material in the sea surface microlayer nucleates ice under conditions relevant for mixed-phase cloud and high-altitude ice cloud formation. The ice nucleating material is likely biogenic and less than ~0.2 μm in size. We find that exudates separated from cells of the marine diatom T. Pseudonana nucleate ice and propose that organic material associated with phytoplankton cell exudates is a likely candidate for the observed ice nucleating ability of the microlayer samples. Global model simulations of marine organic aerosol in combination with our measurements suggest that marine organic material may be an important source of ice nucleating particles in remote marine environments such as the Southern Ocean, North Pacific and North Atlantic.Atmospheric ice nucleating particles (INPs) allow ice to nucleate heterogeneously at higher temperatures or lower relative humidity than is typical for homogeneous ice nucleation. Heterogeneous ice nucleation proceeds via different pathways depending on temperature and humidity. In low altitude mixed-phase clouds, INPs are commonly immersed in supercooled liquid droplets and freezing can occur on them at temperatures between -36 and 0°C 2 . At higher altitudes and lower temperatures (<-36°C) where cirrus clouds form, nucleation occurs below water saturation, proceeding by homogeneous, deposition or immersion-in-solution nucleation 1 . Understanding the sources of atmospheric INPs is important because they affect cloud lifetime, cloud albedo and precipitation 1,2 . Recent modelling work has shown that the ocean is potentially an important source of biogenic atmospheric INPs particularly in remote, high latitude regions 9,10 . However, it has never been directly shown that there is a source of atmospheric INPs associated with organic material found in marine waters or sea-spray aerosol.Organic material makes up a substantial fraction of sub-micron sea-spray aerosol and it is estimated that 10±5 Tg yr -1 of primary organic sub-micron aerosol is emitted from marine sources globally 12 . Rising bubbles scavenge surface active organic material from the water column at their interfaces and this process facilitates the formation of the organic enriched sea-air interface known as the sea surface microlayer (SML). This organic material is ejected into the atmosphere during bubble bursting resulting in sea spray aerosol containing similar organic material to that of the microlaye...

Abstract. On average, airborne aerosol particles cool the Earth's surface directly by absorbing and scattering sunlight and indirectly by influencing cloud reflectivity, life time, thickness or extent. Here we show that over the central Arctic Ocean, where there is frequently a lack of aerosol particles upon which clouds may form, a small increase in aerosol loading may enhance cloudiness thereby likely causing a climatologically significant warming at the ice-covered Arctic surface. Under these low concentration conditions cloud droplets grow to drizzle sizes and fall, even in the absence of collisions and coalescence, thereby diminishing cloud water. Evidence from a case study suggests that interactions between aerosol, clouds and precipitation could be responsible for attaining the observed low aerosol concentrations.

Snow surface and sea-ice energy budgets were measured near 87.5°N during the Arctic Summer Cloud Ocean Study (ASCOS), from August to early September 2008. Surface temperature indicated four distinct temperature regimes, characterized by varying cloud, thermodynamic and solar properties. An initial warm, melt-season regime was interrupted by a 3-day cold regime where temperatures dropped from near zero to -7°C. Subsequently mean energy budget residuals remained small and near zero for 1 week until once again temperatures dropped rapidly and the energy budget residuals became negative. Energy budget transitions were dominated by the net radiative fluxes, largely controlled by the cloudiness. Variable heat, moisture and cloud distributions were associated with changing airmasses. Surface cloud radiative forcing, the net radiative effect of clouds on the surface relative to clear skies, is estimated. Shortwave cloud forcing ranged between -50 W m -2 and zero and varied significantly with surface albedo, solar zenith angle and cloud liquid water. Longwave cloud forcing was larger and generally ranged between 65 and 85 W m -2 , except when the cloud fraction was tenuous or contained little liquid water; thus the net effect of the clouds was to warm the surface. Both cold periods occurred under tenuous, or altogether absent, low-level clouds containing little liquid water, effectively reducing the cloud greenhouse effect. Freeze-up progression was enhanced by a combination of increasing solar zenith angles and surface albedo, while inhibited by a large, positive surface cloud forcing until a new air-mass with considerably less cloudiness advected over the experiment area.

Several recent studies have utilized a Haar wavelet covariance transform to provide automated detection of the boundary layer top from lidar backscatter profiles by locating the maximum in the covariance profiles. This approach is effective where the vertical gradient in the backscatter is small within and above the boundary layer, and where the inversion is sharp and well defined. These near-ideal conditions are often not met, particularly under stable stratification where the inversion may be deep and is sometimes ill defined, and vertical gradients are common. Here the effects of vertical gradients and inversion depth on the covariance transform are examined. It is found that a significant dilation-dependent bias in the determination of the boundary layer top may result when using the published method. An alternative approach is developed utilizing multiple wavelet dilations, and is capable of identifying both the upper and lower limits of the backscatter transition zone associated with the inversion while remaining insensitive to mean vertical gradients in the background signal. This approach enables more detailed information on the small-scale structure of the inversion and entrainment zone to be retrieved than is possible using existing techniques.

Abstract. Observations from the Arctic Summer CloudOcean Study (ASCOS), in the central Arctic sea-ice pack in late summer 2008, provide a detailed view of cloudatmosphere-surface interactions and vertical mixing processes over the sea-ice environment. Measurements from a suite of ground-based remote sensors, near-surface meteorological and aerosol instruments, and profiles from radiosondes and a helicopter are combined to characterize a weeklong period dominated by low-level, mixed-phase, stratocumulus clouds. Detailed case studies and statistical analyses are used to develop a conceptual model for the cloud and atmosphere structure and their interactions in this environment.Clouds were persistent during the period of study, having qualities that suggest they were sustained through a combination of advective influences and in-cloud processes, with little contribution from the surface. Radiative cooling near cloud top produced buoyancy-driven, turbulent eddies that contributed to cloud formation and created a cloud-driven mixed layer. The depth of this mixed layer was related to the amount of turbulence and condensed cloud water. Coupling of this cloud-driven mixed layer to the surface boundary layer was primarily determined by proximity. For 75 % of the period of study, the primary stratocumulus cloud-driven mixed layer was decoupled from the surface and typically at a warmer potential temperature. Since the near-surface temperature was constrained by the ocean-ice mixture, warm temperatures aloft suggest that these air masses had not significantly interacted with the sea-ice surface. Instead, backtrajectory analyses suggest that these warm air masses advected into the central Arctic Basin from lower latitudes. Moisture and aerosol particles likely accompanied these air masses, providing necessary support for cloud formation. On the occasions when cloud-surface coupling did occur, back trajectories indicated that these air masses advected at low levels, while mixing processes kept the mixed layer in equilibrium with the near-surface environment. Rather than contributing buoyancy forcing for the mixed-layer dynamics, the surface instead simply appeared to respond to the mixedlayer processes aloft. Clouds in these cases often contained slightly higher condensed water amounts, potentially due to additional moisture sources from below.

In the central Arctic Ocean the formation of clouds and their properties are sensitive to the availability of cloud condensation nuclei (CCN). The vapors responsible for new particle formation (NPF), potentially leading to CCN, have remained unidentified since the first aerosol measurements in 1991. Here, we report that all the observed NPF events from the Arctic Ocean 2018 expedition are driven by iodic acid with little contribution from sulfuric acid. Iodic acid largely explains the growth of ultrafine particles (UFP) in most events. The iodic acid concentration increases significantly from summer towards autumn, possibly linked to the ocean freeze-up and a seasonal rise in ozone. This leads to a one order of magnitude higher UFP concentration in autumn. Measurements of cloud residuals suggest that particles smaller than 30 nm in diameter can activate as CCN. Therefore, iodine NPF has the potential to influence cloud properties over the Arctic Ocean.

Abstract. Understanding the rapidly changing climate in the Arctic is limited by a lack of understanding of underlying strong feedback mechanisms that are specific to the Arctic. Progress in this field can only be obtained by process-level observations; this is the motivation for intensive ice-breakerbased campaigns such as the Arctic Summer Cloud-Ocean Study (ASCOS), described here. However, detailed field observations also have to be put in the context of the largerscale meteorology, and short field campaigns have to be analysed within the context of the underlying climate state and temporal anomalies from this.To aid in the analysis of other parameters or processes observed during this campaign, this paper provides an overview of the synoptic-scale meteorology and its climatic anomaly during the ASCOS field deployment. It also provides a statistical analysis of key features during the campaign, such as key meteorological variables, the vertical structure of the lower troposphere and clouds, and energy fluxes at the surface. In order to assess the representativity of the ASCOS results, we also compare these features to similar observations obtained during three earlier summer experiments in the Arctic Ocean: the AOE-96, SHEBA and AOE-2001 expeditions.We find that these expeditions share many key features of the summertime lower troposphere. Taking ASCOS and the previous expeditions together, a common picture emerges with a large amount of low-level cloud in a well-mixed shallow boundary layer, capped by a weak to moderately strong inversion where moisture, and sometimes also cloud top, penetrate into the lower parts of the inversion. Much of the boundary-layer mixing is due to cloud-top cooling and subsequent buoyant overturning of the cloud. The cloud layer may, or may not, be connected with surface processes depending on the depths of the cloud and surface-based boundary layers and on the relative strengths of surface-shear and cloud-generated turbulence. The latter also implies a connection between the cloud layer and the free troposphere through entrainment at cloud top.

A method of estimating dissipation rates from a vertically pointing Doppler lidar with high temporal and spatial resolution has been evaluated by comparison with independent measurements derived from a balloonborne sonic anemometer. This method utilizes the variance of the mean Doppler velocity from a number of sequential samples and requires an estimate of the horizontal wind speed. The noise contribution to the variance can be estimated from the observed signal-to-noise ratio and removed where appropriate. The relative size of the noise variance to the observed variance provides a measure of the confidence in the retrieval. Comparison with in situ dissipation rates derived from the balloon-borne sonic anemometer reveal that this particular Doppler lidar is capable of retrieving dissipation rates over a range of at least three orders of magnitude.This method is most suitable for retrieval of dissipation rates within the convective well-mixed boundary layer where the scales of motion that the Doppler lidar probes remain well within the inertial subrange. Caution must be applied when estimating dissipation rates in more quiescent conditions. For the particular Doppler lidar described here, the selection of suitably short integration times will permit this method to be applicable in such situations but at the expense of accuracy in the Doppler velocity estimates. The two case studies presented here suggest that, with profiles every 4 s, reliable estimates of can be derived to within at least an order of magnitude throughout almost all of the lowest 2 km and, in the convective boundary layer, to within 50%. Increasing the integration time for individual profiles to 30 s can improve the accuracy substantially but potentially confines retrievals to within the convective boundary layer. Therefore, optimization of certain instrument parameters may be required for specific implementations.