Cloud micro- and macrophysical properties from ground-based remote sensing during the MOSAiC drift experiment

In the framework of the Multidisciplinary drifting Observatory for the Study of Arctic Climate Polarstern expedition, the Leibniz Institute for Tropospheric Research, Leipzig, Germany, operated the shipborne OCEANET-Atmosphere facility for cloud and aerosol observations throughout the whole year. OCEANET-Atmosphere comprises, amongst others, a multiwavelength Raman lidar, a microwave radiometer, and an optical disdrometer. A cloud radar was operated aboard Polarstern by the US Atmospheric Radiation Measurement program. These measurements were processed by applying the so-called Cloudnet methodology to derive cloud properties. To gain a comprehensive view of the clouds, lidar and cloud radar capabilities for low- and high-altitude observations were combined. Cloudnet offers a variety of products with a spatiotemporal resolution of 30 s and 30 m, such as the target classification, and liquid and ice microphysical properties. Additionally, a lidar-based low-level stratus retrieval was applied for cloud detection below the lowest range gate of the cloud radar. Based on the presented dataset, e.g., studies on cloud formation processes and their radiative impact, and model evaluation studies can be conducted.

Acclimation of subarctic vegetation to warming and increased cloudiness

Subarctic ecosystems are exposed to elevated temperatures and increased cloudiness in a changing climate with potentially important effects on vegetation structure, composition, and ecosystem functioning. We investigated the individual and combined effects of warming and increased cloudiness on vegetation greenness and cover in mesocosms from two tundra and one palsa mire ecosystems kept under strict environmental control in climate chambers. We also investigated leaf anatomical and biochemical traits of four dominant vascular plant species (Empetrum hermaphroditum, Vaccinium myrtillus, Vaccinium vitis-idaea, and Rubus chamaemorus). Vegetation greenness increased in response to warming in all sites and in response to increased cloudiness in the tundra sites but without associated increases in vegetation cover or biomass, except that E. hermaphroditum biomass increased under warming. The combined warming and increased cloudiness treatment had an additive effect on vegetation greenness in all sites. It also increased the cover of graminoids and forbs in one of the tundra sites. Warming increased leaf dry mass per area of V. myrtillus and R. chamaemorus, and glandular trichome density of V. myrtillus and decreased spongy intercellular space of E. hermaphroditum and V. vitis-idaea. Increased cloudiness decreased leaf dry mass per area of V. myrtillus, palisade thickness of E. hermaphroditum, and stomata density of E. hermaphroditum and V. vitis-idaea, and increased leaf area and epidermis thickness of V. myrtillus, leaf shape index and nitrogen of E. hermaphroditum, and palisade intercellular space of V. vitis-idaea. The combined treatment caused thinner leaves and decreased leaf carbon for V. myrtillus, and increased leaf chlorophyll of E. hermaphroditum. We show that under future warmer increased cloudiness conditions in the Subarctic (as simulated in our experiment), vegetation composition and distribution will change, mostly dominated by graminoids and forbs. These changes will depend on the responses of leaf anatomical and biochemical traits and will likely impact carbon gain and primary productivity and abiotic and biotic stress tolerance.

Persistence and Potential Atmospheric Ramifications of Ice-Nucleating Particles Released from Thawing Permafrost

Permafrost underlies approximately a quarter of the Northern Hemisphere and is changing amidst a warming climate. Thawed permafrost can enter water bodies through top-down thaw, thermokarst erosion, and slumping. Recent work revealed that permafrost contains ice-nucleating particles (INPs) with concentrations comparable to midlatitude topsoil. These INPs may impact the surface energy budget of the Arctic by affecting mixed-phase clouds, if emitted into the atmosphere. In two 3-4-week experiments, we placed 30,000- and 1000-year-old ice-rich silt permafrost in a tank with artificial freshwater and monitored aerosol INP emissions and water INP concentrations as the water's salinity and temperature were varied to mimic aging and transport of thawed material into seawater. We also tracked aerosol and water INP composition through thermal treatments and peroxide digestions and bacterial community composition with DNA sequencing. We found that the older permafrost produced the highest and most stable airborne INP concentrations, with levels comparable to desert dust when normalized to particle surface area. Both samples showed that the transfer of INPs to air persisted during simulated transport to the ocean, demonstrating a potential to influence the Arctic INP budget. This suggests an urgent need for quantifying permafrost INP sources and airborne emission mechanisms in climate models.

Seasonal Variation of the Atmospheric Bacterial Community in the Greenlandic High Arctic Is Influenced by Weather Events and Local and Distant Sources

The Arctic is a hot spot for climate change with potentially large consequences on a global scale. Aerosols, including bioaerosols, are important players in regulating the heat balance through direct interaction with sunlight and indirectly, through inducing cloud formation. Airborne bacteria are the major bioaerosols with some species producing the most potent ice nucleating compounds known, which are implicated in the formation of ice in clouds. Little is known about the numbers and dynamics of airborne bacteria in the Arctic and even less about their seasonal variability. We collected aerosol samples and wet deposition samples in spring 2015 and summer 2016, at the Villum Research Station in Northeast Greenland. We used amplicon sequencing and qPCR targeting the 16S rRNA genes to assess the quantities and composition of the DNA and cDNA-level bacterial community. We found a clear seasonal variation in the atmospheric bacterial community, which is likely due to variable sources and meteorology. In early spring, the atmospheric bacterial community was dominated by taxa originating from temperate and Subarctic regions and arriving at the sampling site through long-range transport. We observed an efficient washout of the aerosolized bacterial cells during a snowstorm, which was followed by very low concentrations of bacteria in the atmosphere during the consecutive 4 weeks. We suggest that this is because in late spring, the long-range transport ceased, and the local sources which comprised only of ice and snow surfaces were weak resulting in low bacterial concentrations. This was supported by observed changes in the chemical composition of aerosols. In summer, the air bacterial community was confined to local sources such as soil, plant material and melting sea-ice. Aerosolized and deposited Cyanobacteria in spring had a high activity potential, implying their activity in the atmosphere or in surface snow. Overall, we show how the composition of bacterial aerosols in the high Arctic varies on a seasonal scale, identify their potential sources, demonstrate how their community sizes varies in time, investigate their diversity and determine their activity potential during and post Arctic haze.

Characterization of the Far Infrared Properties and Radiative Forcing of Antarctic Ice and Water Clouds Exploiting the Spectrometer-LiDAR Synergy

Optical and microphysical cloud properties are retrieved from measurements acquired in 2013 and 2014 at the Concordia base station in the Antarctic Plateau. Two sensors are used synergistically: a Fourier transform spectroradiometer named REFIR-PAD (Radiation Explorer in Far Infrared-Prototype for Applications and Developments) and a backscattering-depolarization LiDAR. First, in order to identify the cloudy scenes and assess the cloud thermodynamic phase, the REFIR-PAD spectral radiances are ingested by a machine learning algorithm called Cloud Identification and Classification (CIC). For each of the identified cloudy scenes, the nearest (in time) LiDAR backscattering profile is processed by the Polar Threshold (PT) algorithm that allows derivation of the cloud top and bottom heights. Subsequently, using the CIC and PT results as external constraints, the Simultaneous Atmospheric and Clouds Retrieval (SACR) code is applied to the REFIR-PAD spectral radiances. SACR simultaneously retrieves cloud optical depth and effective dimensions and atmospheric vertical profiles of water vapor and temperature. The analysis determines an average effective diameter of 28 μm with an optical depth of 0.76 for the ice clouds. Water clouds are only detected during the austral Summer, and the retrieved properties provide an average droplet diameter of 9 μm and average optical depth equal to four. The estimated retrieval error is about 1% for the ice crystal/droplet size and 2% for the cloud optical depth. The sensitivity of the retrieved parameters to the assumed crystal shape is also assessed. New parametrizations of the optical depth and the longwave downwelling forcing for Antarctic ice and water clouds, as a function of the ice/liquid water path, are presented. The longwave downwelling flux, computed from the top of the atmosphere to the surface, ranges between 70 and 220 W/m2. The estimated cloud longwave forcing at the surface is (31 ± 7) W/m2 and (29 ± 6) W/m2 for ice clouds and (64 ± 12) and (62 ± 11) W/m2 for water clouds, in 2013 and 2014, respectively. The total average cloud forcing for the two years investigated is (46 ± 9) W/m2.

Seasonal Variations of Arctic Low-Level Clouds and Its Linkage to Sea Ice Seasonal Variations

Using CALIPSO-CloudSat-Clouds and the Earth's Radiant Energy System-Moderate Resolution Imaging Spectrometer data set, this study documents the seasonal variation of sea ice, cloud, and atmospheric properties in the Arctic (70°N-82°N) for 2007-2010. A surface-type stratification-consisting Permanent Ocean, Land, Permanent Ice, and Transient Sea Ice-is used to investigate the influence of surface type on low-level Arctic cloud liquid water path (LWP) seasonality. The results show significant variations in the Arctic low-level cloud LWP by surface type linked to differences in thermodynamic state. Subdividing the Transient Ice region (seasonal sea ice zone) by melt/freeze season onset dates reveals a complex influence of sea ice variations on low cloud LWP seasonality. We find that lower tropospheric stability is the primary factor affecting the seasonality of cloud LWP. Our results suggest that variations in sea ice melt/freeze onset have a significant influence on the seasonality of low-level cloud LWP by modulating the lower tropospheric thermal structure and not by modifying the surface evaporation rate in late spring and midsummer. We find no significant dependence of the May low-level cloud LWP peak on the melt/freeze onset dates, whereas and September/October low-level cloud LWP maximum shifts later in the season for earlier melt/later freeze onset regions. The Arctic low cloud LWP seasonality is controlled by several surface-atmosphere interaction processes; the importance of each varies seasonally due to the thermodynamic properties of sea ice. Our results demonstrate that when analyzing Arctic cloud-sea ice interactions, a seasonal perspective is critical.

Biogenic Sources of Ice Nucleating Particles at the High Arctic Site Villum Research Station

The radiative balance in the Arctic region is sensitive to in-cloud processes, which principally depend on atmospheric aerosols, including ice nucleating particles (INPs). High temperature INPs (active at ≥-15 °C) are common in the Arctic. While laboratory and limited in situ studies show that the high-temperature active INPs are associated with bioaerosols and biogenic compounds, there is still little quantitative insight into the Arctic biogenic INPs and bioaerosols. We measured concentrations of bioaerosols, bacteria, and biogenic INPs at the Villum Research Station (VRS, Station Nord) in a large number of snow (15) and air (51) samples. We found that INPs active at high subzero temperatures were present both in spring and summer. Air INP concentrations were higher in summer (18 INP m^-3 at ≥-10 °C) than in spring (<4 INP m^-3 at ≥-10 °C), when abundant INPs were found in snowfall (1.4 INP mL^-1 at ≥-10 °C). Also, in summer, a significantly higher number of microbial and bacterial cells were present compared to the spring. A large proportion (60%-100%) of INPs that were active between -6 °C and -20 °C could be deactivated by heating to 100 °C, which was indicative of their predominantly proteinaceous origin. In addition, there was a significant linear regression between the summer air concentrations of INPs active at ≥-10 °C and air concentrations of bacterial-marker-genes (p < 0.0001, R² = 0.999, n = 6), pointing at bacterial cells as the source of high-temperature active INPs. In conclusion, the majority of INPs was of proteinaceous, and possibly of bacterial, origin and was found in air during summer and in snowfall during springtime.

Glucose as a Potential Chemical Marker for Ice Nucleating Activity in Arctic Seawater and Melt Pond Samples

Recent studies pointed to a high ice nucleating activity (INA) in the Arctic sea surface microlayer (SML). However, related chemical information is still sparse. In the present study, INA and free glucose concentrations were quantified in Arctic SML and bulk water samples from the marginal ice zone, the ice-free ocean, melt ponds, and open waters within the ice pack. T₅₀ (defining INA) ranged from -17.4 to -26.8 °C. Glucose concentrations varied from 0.6 to 51 μg/L with highest values in the SML from the marginal ice zone and melt ponds (median 16.3 and 13.5 μg/L) and lower values in the SML from the ice pack and the ice-free ocean (median 3.9 and 4.0 μg/L). Enrichment factors between the SML and the bulk ranged from 0.4 to 17. A positive correlation was observed between free glucose concentration and INA in Arctic water samples (T₅₀(°C) = (-25.6 ± 0.6) + (0.15 ± 0.04)·Glucose(μg/L), R_P = 0.66, n = 74). Clustering water samples based on phytoplankton pigment composition resulted in robust but different correlations within the four clusters (R_P between 0.67 and 0.96), indicating a strong link to phytoplankton-related processes. Since glucose did not show significant INA itself, free glucose may serve as a potential tracer for INA in Arctic water samples.

How Much Do Clouds Mask the Impacts of Arctic Sea Ice and Snow Cover Variations? Different Perspectives from Observations and Reanalyses

Decreasing sea ice and snow cover are reducing the surface albedo and changing the Arctic surface energy balance. How these surface albedo changes influence the planetary albedo is a more complex question, though, that depends critically on the modulating effects of the intervening atmosphere. To answer this question, we partition the observed top of atmosphere (TOA) albedo into contributions from the surface and atmosphere, the latter being heavily dependent on clouds. While the surface albedo predictably declines with lower sea ice and snow cover, the TOA albedo decreases approximately half as much. This weaker response can be directly attributed to the fact that the atmosphere contributes more than 70% of the TOA albedo in the annual mean and is less dependent on surface cover. The surface accounts for a maximum of 30% of the TOA albedo in spring and less than 10% by the end of summer. Reanalyses (ASR versions 1 and 2, ERA-Interim, MERRA-2, and NCEP R2) represent the annual means of surface albedo fairly well, but biases are found in magnitudes of the TOA albedo and its contributions, likely due to their representations of clouds. Reanalyses show a wide range of TOA albedo sensitivity to changing sea ice concentration, 0.04–0.18 in September, compared to 0.11 in observations.

Regions of open water and melting sea ice drive new particle formation in North East Greenland

Atmospheric new particle formation (NPF) and growth significantly influences the indirect aerosol-cloud effect within the polar climate system. In this work, the aerosol population is categorised via cluster analysis of aerosol number size distributions (9–915 nm, 65 bins) taken at Villum Research Station, Station Nord (VRS) in North Greenland during a 7 year record (2010–2016). Data are clustered at daily averaged resolution; in total, we classified six categories, five of which clearly describe the ultrafine aerosol population, one of which is linked to nucleation events (up to 39% during summer). Air mass trajectory analyses tie these frequent nucleation events to biogenic precursors released by open water and melting sea ice regions. NPF events in the studied regions seem not to be related to bird colonies from coastal zones. Our results show a negative correlation (r = −0.89) between NPF events and sea ice extent, suggesting the impact of ultrafine Arctic aerosols is likely to increase in the future, given the likely increased sea ice melting. Understanding the composition and the sources of Arctic aerosols requires further integrated studies with joint multi-component ocean-atmosphere observation and modelling.

New insight of Arctic cloud parameterization from regional climate model simulations, satellite-based and drifting station data

Cloud observations from the CloudSat and CALIPSO satellites helped to explain the reduced total cloud cover (Ctot) in the atmospheric regional climate model HIRHAM5 with modified cloud physics. Arctic climate conditions are found to be better reproduced with (1) a more efficient Bergeron-Findeisen process and (2) more generalized subgrid-scale variability of total water content. As a result, the annual cycle of Ctot is improved over sea ice, associated with an almost 14% smaller area average than in the control simulation. The modified cloud scheme reduces the Ctot bias with respect to the satellite observations. Except for autumn, the cloud reduction over sea ice improves low-level temperature profiles compared to drifting station data. The HIRHAM5 sensitivity study highlights the need for improving accuracy of low-level (< 700m) cloud observations, as these clouds exert a strong impact on the near-surface climate.

An assessment of phytoplankton primary productivity in the Arctic Ocean from satellite ocean color/in situ chlorophyll-a based models

We investigated 32 net primary productivity (NPP) models by assessing skills to reproduce integrated NPP in the Arctic Ocean. The models were provided with two sources each of surface chlorophyll-a concentration (chlorophyll), photosynthetically available radiation (PAR), sea surface temperature (SST), and mixed-layer depth (MLD). The models were most sensitive to uncertainties in surface chlorophyll, generally performing better with in situ chlorophyll than with satellite-derived values. They were much less sensitive to uncertainties in PAR, SST, and MLD, possibly due to relatively narrow ranges of input data and/or relatively little difference between input data sources. Regardless of type or complexity, most of the models were not able to fully reproduce the variability of in situ NPP, whereas some of them exhibited almost no bias (i.e., reproduced the mean of in situ NPP). The models performed relatively well in low-productivity seasons as well as in sea ice-covered/deep-water regions. Depth-resolved models correlated more with in situ NPP than other model types, but had a greater tendency to overestimate mean NPP whereas absorption-based models exhibited the lowest bias associated with weaker correlation. The models performed better when a subsurface chlorophyll-a maximum (SCM) was absent. As a group, the models overestimated mean NPP, however this was partly offset by some models underestimating NPP when a SCM was present. Our study suggests that NPP models need to be carefully tuned for the Arctic Ocean because most of the models performing relatively well were those that used Arctic-relevant parameters.

July 2012 Greenland melt extent enhanced by low-level liquid clouds

Melting of the world's major ice sheets can affect human and environmental conditions by contributing to sea-level rise. In July 2012, an historically rare period of extended surface melting was observed across almost the entire Greenland ice sheet, raising questions about the frequency and spatial extent of such events. Here we show that low-level clouds consisting of liquid water droplets ('liquid clouds'), via their radiative effects, played a key part in this melt event by increasing near-surface temperatures. We used a suite of surface-based observations, remote sensing data, and a surface energy-balance model. At the critical surface melt time, the clouds were optically thick enough and low enough to enhance the downwelling infrared flux at the surface. At the same time they were optically thin enough to allow sufficient solar radiation to penetrate through them and raise surface temperatures above the melting point. Outside this narrow range in cloud optical thickness, the radiative contribution to the surface energy budget would have been diminished, and the spatial extent of this melting event would have been smaller. We further show that these thin, low-level liquid clouds occur frequently, both over Greenland and across the Arctic, being present around 30-50 per cent of the time. Our results may help to explain the difficulties that global climate models have in simulating the Arctic surface energy budget, particularly as models tend to under-predict the formation of optically thin liquid clouds at supercooled temperatures--a process potentially necessary to account fully for temperature feedbacks in a warming Arctic climate.

The central role of diminishing sea ice in recent Arctic temperature amplification

The rise in Arctic near-surface air temperatures has been almost twice as large as the global average in recent decades-a feature known as 'Arctic amplification'. Increased concentrations of atmospheric greenhouse gases have driven Arctic and global average warming; however, the underlying causes of Arctic amplification remain uncertain. The roles of reductions in snow and sea ice cover and changes in atmospheric and oceanic circulation, cloud cover and water vapour are still matters of debate. A better understanding of the processes responsible for the recent amplified warming is essential for assessing the likelihood, and impacts, of future rapid Arctic warming and sea ice loss. Here we show that the Arctic warming is strongest at the surface during most of the year and is primarily consistent with reductions in sea ice cover. Changes in cloud cover, in contrast, have not contributed strongly to recent warming. Increases in atmospheric water vapour content, partly in response to reduced sea ice cover, may have enhanced warming in the lower part of the atmosphere during summer and early autumn. We conclude that diminishing sea ice has had a leading role in recent Arctic temperature amplification. The findings reinforce suggestions that strong positive ice-temperature feedbacks have emerged in the Arctic, increasing the chances of further rapid warming and sea ice loss, and will probably affect polar ecosystems, ice-sheet mass balance and human activities in the Arctic.

A climatologically significant aerosol longwave indirect effect in the Arctic

The warming of Arctic climate and decreases in sea ice thickness and extent observed over recent decades are believed to result from increased direct greenhouse gas forcing, changes in atmospheric dynamics having anthropogenic origin, and important positive reinforcements including ice-albedo and cloud-radiation feedbacks. The importance of cloud-radiation interactions is being investigated through advanced instrumentation deployed in the high Arctic since 1997 (refs 7, 8). These studies have established that clouds, via the dominance of longwave radiation, exert a net warming on the Arctic climate system throughout most of the year, except briefly during the summer. The Arctic region also experiences significant periodic influxes of anthropogenic aerosols, which originate from the industrial regions in lower latitudes. Here we use multisensor radiometric data to show that enhanced aerosol concentrations alter the microphysical properties of Arctic clouds, in a process known as the 'first indirect' effect. Under frequently occurring cloud types we find that this leads to an increase of an average 3.4 watts per square metre in the surface longwave fluxes. This is comparable to a warming effect from established greenhouse gases and implies that the observed longwave enhancement is climatologically significant.