ALBERT

Description: 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.

Description: For three austral summer seasons (2013–2016, each from December to February) aerosol particles arriving at the Belgian Antarctic research station Princess Elisabeth (PE) in Dronning Maud Land in East Antarctica were characterized. This included number concentrations of total aerosol particles (NCN) and cloud condensation nuclei (NCCN), the particle number size distribution (PNSD), the aerosol particle hygroscopicity, and the influence of the air mass origin on NCN and NCCN. In general NCN was found to range from 40 to 6700 cm−3, with a median of 333 cm−3, while NCCN was found to cover a range between less than 10 and 1300 cm−3 for supersaturations (SSs) between 0.1 % and 0.7 %. It is shown that the aerosol is dominated by the Aitken mode, being characterized by a significant amount of small, and therefore likely secondarily formed, aerosol particles, with 94 % and 36 % of the aerosol particles smaller than 90 and ≈35 nm, respectively. Measurements of the basic meteorological parameters as well as the history of the air masses arriving at the measurement station indicate that the station is influenced by both marine air masses originating from the Southern Ocean and coastal areas around Antarctica (marine events – MEs) and continental air masses (continental events – CEs). CEs, which were defined as instances when the air masses spent at least 90 % of the time over the Antarctic continent during the last 10 days prior to arrival at the measurements station, occurred during 61 % of the time during which measurements were done. CEs came along with rather constant NCN and NCCN values, which we denote as Antarctic continental background concentrations. MEs, however, cause large fluctuations in NCN and NCCN, with low concentrations likely caused by scavenging due to precipitation and high concentrations likely originating from new particle formation (NPF) based on marine precursors. The application of HYSPLIT back trajectories in form of the potential source contribution function (PSCF) analysis indicate that the region of the Southern Ocean is a potential source of Aitken mode particles. On the basis of PNSDs, together with NCCN measured at an SS of 0.1 %, median values for the critical diameter for cloud droplet activation and the aerosol particle hygroscopicity parameter κ were determined to be 110 nm and 1, respectively. For particles larger than ≈110 nm the Southern Ocean together with parts of the Antarctic ice shelf regions were found to be potential source regions. While the former may contribute sea spray particles directly, the contribution of the latter may be due to the emission of sea salt aerosol particles, released from snow particles from surface snow layers, e.g., during periods of high wind speed, leading to drifting or blowing snow. The region of the Antarctic inland plateau, however, was not found to feature a significant source region for aerosol particles in general or for cloud condensation nuclei measured at the PE station in the austral summer.

Description: The surface energy budget (SEB) of polar regions is key to understanding the polar amplification of global climate change and its worldwide consequences. However, despite a growing network of ground-based automatic weather stations that measure the radiative components of the SEB, extensive areas remain where no ground-based observations are available. Satellite remote sensing has emerged as a potential solution to retrieve components of the SEB over remote areas, with radar and lidar aboard the CloudSat and CALIPSO satellites among the first to enable estimates of surface radiative long-wave (LW) and short-wave (SW) fluxes based on active cloud observations. However, due to the small swath footprints, combined with a return cycle of 16 days, questions arise as to how CloudSat and CALIPSO observations should be optimally sampled in order to retrieve representative fluxes for a given location. Here we present a smart sampling approach to retrieve downwelling surface radiative fluxes from CloudSat and CALIPSO observations for any given land-based point-of-interest (POI) in polar regions. The method comprises a spatial correction that allows the distance between the satellite footprint and the POI to be increased in order to raise the satellite sampling frequency. Sampling frequency is enhanced on average from only two unique satellite overpasses each month for limited-distance sampling

Description: Local surface mass balance (SMB) measurements are crucial for understanding changes in the total mass of the Antarctic Ice Sheet, including its contribution to sea level rise. Despite continuous attempts to decipher mechanisms controlling the local SMB, a clear understanding of the separate components is still lacking, while snowfall measurements are almost absent. In this study, the different terms are quantified at the Princess Elisabeth (PE) station in Dronning Maud Land, East Antarctica. Furthermore, the relation between snowfall and accumulation at the surface is investigated. To achieve this, a unique collocated set of remote sensing instrumentation (Micro Rain Radar, ceilometer, Automatic Weather Station, among others) was established operating for an unprecedented time period of 37 months. Snowfall originates mainly from moist and warm air advected from lower latitudes associated with cyclone activity. However, snowfall events are much more common than accumulation events. During 38 % of the snowfall cases observed, the freshly-fallen snow is ablated by the wind during the course of the event. Generally, snow storms of longer duration have a higher chance to attain for accumulation at the local scale, while shorter events usually attain for ablation (on average 17 and 12 hours respectively). As such, SMB records cannot be considered a good proxy for snowfall at the local scale. Accumulation and ablation also occur during non-snowfall conditions. A large part of the accumulation at the station takes place when preceding snowfall events were occurring in upstream coastal areas. This fresh snow is easily picked up and transported in shallow drifting snow layers to more inland locations, even when wind speed is relatively low (

Description: Blowing snow impacts Antarctic ice sheet surface mass balance by snow redistribution and sublimation. However, numerical models poorly represent blowing snow processes, while direct observations are limited in space and time. Satellite retrieval of blowing snow is hindered by clouds and only the strongest events are considered. Here, we develop a blowing snow detection (BSD) algorithm for ground-based remote-sensing ceilometers in polar regions and apply it to ceilometers at Neumayer III and Princess Elisabeth (PE) stations, East Antarctica. The algorithm is able to detect (heavy) blowing snow layers reaching 30 m height. Results show that 78 % of the detected events are in agreement with visual observations at Neumayer III station. The BSD algorithm detects heavy blowing snow 36 % of the time at Neumayer (2011–2015) and 13 % at PE station (2010–2016). Blowing snow occurrence peaks during the austral winter and shows around 5 % interannual variability. The BSD algorithm is capable of detecting blowing snow both lifted from the ground and occurring during precipitation, which is an added value since results indicate that 92 % of the blowing snow is during synoptic events, often combined with precipitation. Analysis of atmospheric meteorological variables shows that blowing snow occurrence strongly depends on fresh snow availability in addition to wind speed. This finding challenges the commonly used parametrizations, where the threshold for snow particles to be lifted is a function of wind speed only. Blowing snow occurs predominantly during storms and overcast conditions, shortly after precipitation events, and can reach up to 1300 m a. g. l.  in the case of heavy mixed events (precipitation and blowing snow together). These results suggest that synoptic conditions play an important role in generating blowing snow events and that fresh snow availability should be considered in determining the blowing snow onset.

Description: Continuous measurements of blowing snow are scarce, both in time and space. Satellites now provide the opportunity to derive blowing snow occurrences, transport and sublimation rates over Antarctica. However, little ground truth is available to validate these retrievals. The recent application of ceilometers for detection of blowing snow frequencies provides an opportunity to validate the satellite retrievals of blowing snow frequencies at the Princess Elisabeth and Neumayer stations, East Antarctica for the 2011–2016 time period. A routine to detect blowing snow occurrence from remote sensing ceilometers has been developed at those locations. Thanks to their ground-based location, ceilometers are able to detect blowing snow events in the presence of clouds and precipitation, which can be missed by the satellite, since optically thick clouds impede the penetration of the signal. This is important, since ≈ 90 % of blowing snow happens under cloudy conditions at Neumayer and Princess Elisabeth station and represent 30 % of all cloudy conditions at both stations. Although both detection methods have their limitations, 10 % (4 %) of the measurements at Princess Elisabeth (and Neumayer) are identified as blowing snow by the satellite but not by the ceilometer, likely due to differences in sensors, limitation of the surface identification by the satellite, or the spatial inhomogeneity of the blowing snow event. While the satellite blowing snow retrieval is a useful product, further investigation is needed to reduce the uncertainties on blowing snow frequencies associated with clouds.

Description: Precipitation over Antarctica is the main term in the surface mass balance of the Antarctic ice sheet, which is crucial for the future evolution of the sea level worldwide. Precipitation, however, remains poorly documented and understood mainly because of a lack of observations in this extreme environment. Two observatories dedicated to precipitation have been set up at the Belgian station Princess Elisabeth (PE) and at the French station Dumont d'Urville (DDU) in East Antarctica. Among other instruments, both sites have a vertically pointing micro rain radar (MRR) working at the K band. Measurements have been continuously collected at DDU since the austral summer of 2015–2016, while they have been collected mostly during summer seasons at PE since 2010, with a full year of observation during 2012. In this study, the statistics of the vertical profiles of reflectivity, vertical velocity, and spectral width are analyzed for all seasons. Vertical profiles were separated into surface precipitation and virga to evaluate the impact of virga on the structure of the vertical profiles. The climatology of the study area plays an important role in the structure of the precipitation: warmer and moister atmospheric conditions at DDU favor the occurrence of more intense precipitation compared with PE, with a difference of 8 dBZ between both stations. The strong katabatic winds blowing at DDU induce a decrease in reflectivity close to the ground due to the sublimation of the snowfall particles. The vertical profiles of precipitation velocity show significant differences between the two stations. In general, at DDU the vertical velocity increases as the height decreases, while at PE the vertical velocity decreases as the height decreases. These features of the vertical profiles of reflectivity and vertical velocity could be explained by the more frequent occurrence of aggregation and riming at DDU compared to PE because of the lower temperature and relative humidity at the latter, located further in the interior. Robust and reliable statistics about the vertical profile of precipitation in Antarctica, as derived from MRRs for instance, are necessary and valuable for the evaluation of precipitation estimates derived from satellite measurements and from numerical atmospheric models.

Description: The Antarctic continent is a vast desert, the coldest and the most unknown area on Earth. It contains the Antarctic ice sheet, the largest continental water reservoir on Earth that could be affected by the current global warming, leading to sea level rise. The only significant supply of ice is through precipitation, which can be observed from the surface and from space. Remote sensing observations of the coastal regions and the inner continent using CloudSat radar give an estimated rate of snowfall but with uncertainties twice as large as each single measured value, whereas climate models give a range from half to twice the time and spatial average observations. The aim of this study is the evaluation of the vertical precipitation rate profiles of CloudSat radar by comparison with two surface-based Micro-Rain Radars (MRR), located at the coastal French Dumont d'Urville station and at the Belgian Princess Elisabeth station, located in the Dronning Maud Land escarpment zone, respectively. This in turn leads to a better understanding and reassessment of CloudSat uncertainties. We compared a total of four precipitation events, two per station, when CloudSat overpassed within 10 km of the stations and we compared these two different data sets at each vertical level. The correlation between both datasets is near-perfect, even though climatic and geographic conditions are different for the stations. Using different CloudSat and MRR vertical levels, we obtain 10km-space and seconds-short-time CloudSat uncertainties from −24 % up to +21 %. This confirms the robustness of the CloudSat retrievals of snowfall over Antarctica above the blind zone and justifies further analyses of this dataset.

Description: In situ observations of snowfall over the Antarctic Ice Sheet are scarce. Currently, continent-wide assessments of snowfall are limited to information from the Cloud Profiling Radar on board the CloudSat satellite, which has not been evaluated up to now. In this study, snowfall derived from CloudSat is evaluated using three ground-based vertically profiling 24 GHz precipitation radars (Micro Rain Radars: MRRs). Firstly, using the MRR long-term measurement records, an assessment of the uncertainty caused by the low temporal sampling rate of CloudSat (one revisit per 2.1 to 4.5 days) is performed. The 10–90th-percentile temporal sampling uncertainty in the snowfall climatology varies between 30 % and 40 % depending on the latitudinal location and revisit time of CloudSat. Secondly, an evaluation of the snowfall climatology indicates that the CloudSat product, derived at a resolution of 1∘ latitude by 2∘ longitude, is able to accurately represent the snowfall climatology at the three MRR sites (biases 

Description: The Antarctic continent is a vast desert and is the coldest and the most unknown area on Earth. It contains the Antarctic ice sheet, the largest continental water reservoir on Earth that could be affected by the current global warming, leading to sea level rise. The only significant supply of ice is through precipitation, which can be observed from the surface and from space. Remote-sensing observations of the coastal regions and the inner continent using CloudSat radar give an estimated rate of snowfall but with uncertainties twice as large as each single measured value, whereas climate models give a range from half to twice the space–time-averaged observations. The aim of this study is the evaluation of the vertical precipitation rate profiles of CloudSat radar by comparison with two surface-based micro-rain radars (MRRs), located at the coastal French Dumont d'Urville station and at the Belgian Princess Elisabeth station located in the Dronning Maud Land escarpment zone. This in turn leads to a better understanding and reassessment of CloudSat uncertainties. We compared a total of four precipitation events, two per station, when CloudSat overpassed within 10 km of the station and we compared these two different datasets at each vertical level. The correlation between both datasets is near-perfect, even though climatic and geographic conditions are different for the two stations. Using different CloudSat and MRR vertical levels, we obtain 10 km space-scale and short-timescale (a few seconds) CloudSat uncertainties from −13 % up to +22 %. This confirms the robustness of the CloudSat retrievals of snowfall over Antarctica above the blind zone and justifies further analyses of this dataset.