Infrasound propagation in the Arctic

This report summarizes results of the basic research project “Infrasound Propagation in the Arctic.” The scientific objective of this project was to provide a baseline understanding of the characteristic horizontal propagation distances, frequency dependencies, and conditions leading to enhanced propagation of infrasound in the Arctic region. The approach emphasized theory and numerical modeling as an initial step toward improving understanding of the basic phenomenology, and thus lay the foundation for productive experiments in the future. The modeling approach combined mesoscale numerical weather forecasts from the Polar Weather Research and Forecasting model with advanced acoustic propagation calculations. The project produced significant advances with regard to parabolic equation modeling of sound propagation in a windy atmosphere. For the polar low, interesting interactions with the stratosphere were found, which could possibly be used to provide early warning of strong stratospheric warming events (i.e., the polar vortex). The katabatic wind resulted in a very strong low-level duct, which, when combined with a highly reflective icy ground surface, leads to efficient long-distance propagation. This information is useful in devising strategies for positioning sensors to monitor environmental phenomena and human activities.

Seasonal dispersal of fjord meltwaters as an important source of iron and manganese to coastal Antarctic phytoplankton

Glacial meltwater from the western Antarctic Ice Sheet is hypothesized to be an important source of cryospheric iron, fertilizing the Southern Ocean, yet its trace-metal composition and factors that control its dispersal remain poorly constrained. Here we characterize meltwater iron sources in a heavily glaciated western Antarctic Peninsula (WAP) fjord. Using dissolved and particulate ratios of manganese to iron in meltwaters, porewaters, and seawater, we show that surface glacial melt and subglacial plumes contribute to the seasonal cycle of iron and manganese within a fjord still relatively unaffected by climate-change-induced glacial retreat. Organic ligands derived from the phytoplankton bloom and the glaciers bind dissolved iron and facilitate the solubilization of particulate iron downstream. Using a numerical model, we show that buoyant plumes generated by outflow from the subglacial hydrologic system, enriched in labile particulate trace metals derived from a chemically modified crustal source, can supply iron to the fjord euphotic zone through vertical mixing. We also show that prolonged katabatic wind events enhance export of meltwater out of the fjord. Thus, we identify an important atmosphere–ice–ocean coupling intimately tied to coastal iron biogeochemistry and primary productivity along the WAP.

Improving surface melt estimation over the Antarctic Ice Sheet using deep learning: a proof of concept over the Larsen Ice Shelf

Accurately estimating the surface melt volume of the Antarctic Ice Sheet is challenging and has hitherto relied on climate modeling or observations from satellite remote sensing. Each of these methods has its limitations, especially in regions with high surface melt. This study aims to demonstrate the potential of improving surface melt simulations with a regional climate model by deploying a deep learning model. A deep-learning-based framework has been developed to correct surface melt from the regional atmospheric climate model version 2.3p2 (RACMO2), using meteorological observations from automatic weather stations (AWSs) and surface albedo from satellite imagery. The framework includes three steps: (1) training a deep multilayer perceptron (MLP) model using AWS observations, (2) correcting Moderate Resolution Imaging Spectroradiometer (MODIS) albedo observations, and (3) using these two to correct the RACMO2 surface melt simulations. Using observations from three AWSs at the Larsen B and C ice shelves, Antarctica, cross-validation shows a high accuracy (root-mean-square error of 0.95 mm w.e. d−1, mean absolute error of 0.42 mm w.e. d−1, and a coefficient of determination of 0.95). Moreover, the deep MLP model outperforms conventional machine learning models and a shallow MLP model. When applying the trained deep MLP model over the entire Larsen Ice Shelf, the resulting corrected RACMO2 surface melt shows a better correlation with the AWS observations for two out of three AWSs. However, for one location (AWS 18), the deep MLP model does not show improved agreement with AWS observations; this is likely because surface melt is largely driven by factors (e.g., air temperature, topography, katabatic wind) other than albedo within the corresponding coarse-resolution model pixels. Our study demonstrates the opportunity to improve surface melt simulations using deep learning combined with satellite albedo observations. However, more work is required to refine the method, especially for complicated and heterogeneous terrains.

A Model-Based Climatology of Low-Level Jets in the Weddell Sea Region of the Antarctic

Low-level jets (LLJs) are climatological features in polar regions. It is well known that katabatic winds over the slopes of the Antarctic ice sheet are associated with strong LLJs. Barrier winds occurring, e.g., along the Antarctic Peninsula may also show LLJ structures. A few observational studies show that LLJs occur over sea ice regions. We present a model-based climatology of the wind field, of low-level inversions and of LLJs in the Weddell Sea region of the Antarctic for the period 2002–2016. The sensitivity of the LLJ detection on the selection of the wind speed maximum is investigated. The common criterion of an anomaly of at least 2 m/s is extended to a relative criterion of wind speed decrease above and below the LLJ. The frequencies of LLJs are sensitive to the choice of the relative criterion, i.e., if the value for the relative decrease exceeds 15%. The LLJs are evaluated with respect to the frequency distributions of height, speed, directional shear and stability for different regions. LLJs are most frequent in the katabatic wind regime over the ice sheet and in barrier wind regions. During winter, katabatic LLJs occur with frequencies of more than 70% in many areas. Katabatic LLJs show a narrow range of heights (mostly below 200 m) and speeds (typically 10–20 m/s), while LLJs over the sea ice cover a broad range of speeds and heights. LLJs are associated with surface inversions or low-level lifted inversions. LLJs in the katabatic wind and barrier wind regions can last several days during winter. The duration of LLJs is sensitive to the LLJ definition criteria. We propose to use only the absolute criterion for model studies.

Transit boosting of trans-Channel katabatic winds by depressions associated with west European storms tracks: impact on Pleistocene loess deposits.

Onshore and offshore sedimentological, geochemical, geomorphological, paleontological and geochronological studies of loess deposits located under and around the English Channel revealed that they were transported by katabatic winds generated by the British-Irish Ice Sheet. Katabatic winds, which are low-altitude wind flows, were able to jump over the low southern British hills but were stopped by the higher Brittany and Normandy hills. This regional topography is interrupted by a north-south corridor linking the northern and southern shores of Brittany where loess propagated down to the mouth of Loire River. This long transit shows that the total distance travelled by the katabatic wind was around 750 kilometres, which represents an unusual distance for the propagation of this wind under continental conditions. Strong similarities with Antarctica and Greenland, where well documented cases of katabatic winds are known, show that the transit of the trans-Channel katabatic winds were strongly enhanced by the seasonal drift of storms propagating in an eastward direction along the axis of the English Channel. This increasing strength of the North-South katabatic flux was probably at the origin of the transport of loess particles down to the mouth of Loire River.

Automated mapping of the seasonal evolution of surface meltwater and its links to climate on the Amery Ice Shelf, Antarctica

Surface meltwater is widespread around the margin of the Antarctic Ice Sheet and has the potential to influence ice-shelf stability, ice-dynamic processes and ice-albedo feedbacks. Whilst the general spatial distribution of surface meltwater across the Antarctic continent is now relatively well known, our understanding of the seasonal and multi-year evolution of surface meltwater is limited. Attempts to generate robust time series of melt cover have largely been constrained by computational expense or limited ice surface visibility associated with mapping from optical satellite imagery. Here, we implement an existing meltwater detection method alongside a novel method for calculating visibility metrics within Google Earth Engine. This enables us to quantify uncertainty induced by cloud cover and variable image data coverage, allowing us to automatically generate time series of surface melt area over large spatial and temporal scales. We demonstrate our method on the Amery Ice Shelf region of East Antarctica, analysing 4,164 Landsat 7 and 8 optical images between 2005 and 2020. Results show high interannual variability in surface meltwater cover, with mapped cumulative lake area totals ranging from 384 km2 to 3898 km2 per melt season. However, by incorporating image visibility assessments into our results, we estimate that cumulative total lake areas are on average 42 % higher than minimum mapped values, highlighting the importance of accounting for variations in image visibility when mapping lake areas. In a typical melt season, total lake area remains low throughout November and early December, before increasing, on average, by an order of magnitude during the second half of December. Peak lake area most commonly occurs during January, before decreasing during February as lakes freeze over. We show that modelled melt predictions from a regional climate model provides a good indication of lake cover in the Amery region, and that annual lake coverage is strongly associated with phases of the Southern Annular Mode (SAM); surface melt is typically highest in years with a negative austral summer SAM index. Furthermore, we suggest that melt-albedo feedbacks modulate the spatial distribution of meltwater in the region, with the exposure of blue ice from persistent katabatic wind scouring influencing the susceptibility of melt ponding. Results demonstrate how our method could be scaled up to generate a multi-year time series record of surface water extent from optical imagery at a continent-wide scale.

Impacts of strong wind events on sea ice and water mass properties in Antarctic coastal polynyas

Strong offshore wind events (SOWEs) occur frequently near the Antarctic coast during austral winter. These wind events are typically associated with passage of synoptic- or meso-scale cyclones, which interact with the katabatic wind field and affect sea ice and oceanic processes in coastal polynyas. Based on numerical simulations from the coupled Finite Element Sea-ice Ocean Model (FESOM) driven by the CORE-II forcing, two coastal polynyas along the East Antarctica coast––the Prydz Bay Polynya and the Shackleton Polynya are selected to examine the response of sea ice and oceanic properties to SOWEs. In these polynyas, the southern or western flanks of cyclones play a crucial role in increasing the offshore winds depending on the local topography. Case studies for both polynyas show that during SOWEs, when the wind speed is 2–3 times higher than normal values, the offshore component of sea ice velocity can increase by 3–4 times. Sea ice concentration can decrease by 20–40%, and sea ice production can increase up to two to four folds. SOWEs increase surface salinity variability and mixed layer depth, and such effects may persist for 5–10 days. Formation of high salinity shelf water (HSSW) is detected in the coastal regions from surface to 800 m after 10–15 days of the SOWEs, while the HSSW features in deep layers exhibit weak response on the synoptic time scale. HSSW formation averaged over winter is notably greater in years with longer duration of SOWEs.

Seasonal dispersal of fjord meltwaters as an important source of iron to coastal Antarctic phytoplankton

Glacial meltwater from the western Antarctic Ice Sheet is hypothesized to be an important source of cryospheric iron, fertilizing the Southern Ocean, yet its trace metal composition and factors which control its dispersal remain poorly constrained. Here we characterize meltwater iron sources in a heavily glaciated western Antarctic Peninsula (WAP) fjord. Using dissolved and particulate ratios of manganese-to-iron in meltwaters, porewaters, and seawater, we show that glacial melt and subglacial plumes contribute to the seasonal cycle of bioavailable iron within a fjord still relatively unaffected by climate change-induced glacial retreat. Organic ligands derived from the phytoplankton bloom and the glaciers bind dissolved iron and facilitate the solubilization of particulate iron downstream. Using a numerical model, we show that plumes generated by outflow from the subglacial hydrologic system, enriched in labile particulate trace metals derived from a chemically-modified crustal source, can supply the surface through vertical mixing, and that prolonged katabatic wind events enhance export of meltwater out of the fjord. Thus, we identify an important atmosphere-ice-ocean coupling intimately tied to coastal iron biogeochemistry and primary productivity along the WAP.

Monitoring Icequakes in East Antarctica with the Raspberry Shake

We evaluate the performance of the low-cost seismic sensor Raspberry Shake (RS) to identify and monitor icequakes (which occur when glacial ice experiences brittle deformation) in extreme environments. In January 2020, three RS3D sensors were installed on a katabatic wind-scoured blue ice area (BIA) close to the Princess Elisabeth Antarctica research station in Dronning Maud Land, East Antarctica. The sensors were configured for Antarctic deployment and placed in insulated enclosures to protect them from harsh weather systems. The RS network (installed in a triangular array) performed well in the cold and with rapid air temperature change, as diurnal temperatures fluctuated from a high of 0.0°C to a minimum temperature of −15.0°C. Although battery connectivity issues in one unit limit full triangulation of seismic signals, and high background noise may mask some seismic signals, data from the RS2 unit reveals that 2936 icequakes were detected over a 10-day period. The temporal occurrence of these icequakes, combined with satellite-derived surface temperature measurements and automatic weather station data, suggest that diurnal fluctuations in solar radiation control ice surface temperature changes, driving thermal contraction of the ice. Seismic investigations like these can therefore provide information on the thermal state and ice fracture mechanics of ablation zones such as BIAs. Our work highlights the potential application of the RS (after minimal modification) in glaciated environments where equipment often needs to be portable, temporary and lightweight, and able to perform in extreme weather conditions.