Orals: Tue, 29 Apr | Room 1.85/86
Antarctic coastal polynyas are ice-free areas forming in sea ice-covered regions, primarily driven by strong katabatic winds that push sea ice offshore. These polynyas enable ocean-to-atmosphere heat exchange, driving intense sea ice production and dense water formation. Despite their role in generating Antarctic Bottom Water (AABW), which constitutes 30-40% of global ocean volume, their atmospheric dynamics remain poorly understood.
This study investigates the atmospheric impacts of Antarctic coastal polynyas using high-resolution (3 km) WRF simulations, focusing on the Prydz Bay region, including the Cape Darnley (CDP) and Mackenzie Bay polynyas (MBP). A sensitivity experiment without polynya, highlights the significant atmospheric changes when polynyas are open: a major heat release toward the atmosphere (up to 1000 W·m⁻²) increases the air temperature (over 5.5°C), creates a low-pressure anomaly (-70 Pa), an acceleration of the surface winds (over 5 m·s⁻¹) and an intense atmospheric convection leading to a thicker boundary layer (+400 m) and more clouds. Two recirculation anomaly cells develop upstream and downstream of the polynya. An analysis of meridional wind trends reveals that the dynamical response of the atmosphere to the polynya opening is controlled by a balance between the pressure gradient forces, the advection and the vertical diffusion, reinforced by the strong vertical turbulent mixing above the polynya.
These results underline the substantial influence of polynyas on local atmospheric dynamics, and suggest potential feedback mechanisms that could influence polynya dynamics and consequently the AABW formation.
How to cite: Noel, M., Masson, S., and Rousset, C.: Atmospheric response to Antarctic coastal polynyas, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2877, https://doi.org/10.5194/egusphere-egu25-2877, 2025.
It has been widely documented that the East Antarctic heatwave (EAH) in March 2022 featured some of the largest positive temperature anomalies ever recorded anywhere on Earth. The heatwave was extraordinary in both extent and magnitude, where anomalies of at least 30°C were reached widely in the region. This study seeks to determine the likelihood of this event, the risk of even more extreme events occurring in the current state of the Antarctic climate; and whether events of a similar magnitude could occur elsewhere on the continent and at other times of year, with potentially more severe impacts for ice shelf stability. A large ensemble of seasonal hindcasts from multiple forecasting centres is used to assess the simulated occurrence of high temperature extremes over Antarctica, using a technique known as "UNprecedented Simulated Extremes using Ensembles" (UNSEEN).
The March 2022 EAH was outside the range of possible extreme temperatures suggested by the ensemble of hindcasts, signifying that events of this magnitude are incredibly rare. It is also shown with the ensemble that almost everywhere in Antarctica could experience unprecedented March heatwaves in the current climate, at least 5°C higher than has been observed. The UNSEEN method also suggests that temperature anomalies of a similar magnitude to those in the March 2022 EAH could occur widely across the continent in today’s climate. Therefore, Antarctic heatwaves on the scale of the 2022 event could occur almost anywhere, even though they have not yet been observed. This would be particularly problematic over the larger ice shelves of the Ross and Ronne-Filchner. If the extreme temperatures suggested by UNSEEN are realised here, it is shown that these ice shelves would be more susceptible to more frequent, or more severe, melting. This could ultimately result in weaker ice shelves, ice shelf collapse, and rising global sea levels.
How to cite: Suitters, C., Screen, J., and Catto, J.: Quantifying the risk of unprecedented Antarctic heatwaves, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4130, https://doi.org/10.5194/egusphere-egu25-4130, 2025.
Grain size variations impact the albedo and have consequence for the energy budget of the surface. The snow grain size in Antarctica follows a clear seasonal pattern: a summer increase and a winter decrease, which are conditioned by atmospheric processes —namely temperature, wind, snowfall— and by mechanisms acting inside the snowpack leading to water vapour transport thus causing the coarsening of the grains. This study focuses on the evolution of the grain size in the interior part of East Antarctica, where dry metamorphism occurs, by using satellite observations. For this, we use, as proxy for the snow grain size, the Grain Size Index (GSI) inferred from the 89 and 150 GHz radiometer observations collected by the Advanced Microwave Sounding Unit-B (AMSU-B) from 2000 to 2022. Four extreme increase in GSI have been identified over the Antarctic Plateau, along the highest ice divide. In these cases, the ERA5 reanalysis revealed an atmospheric blocking/ridge situation around the onsets of the summer growing of the grain size, conveying the relatively warm and moist air coming from the mid latitudes, often associated with atmospheric rivers. The snow dry metamorphism is facilitated conditions of weak wind, low temperature and low snowfall conditions during the following weeks, leading to grain growth. These conditions determine anomalous high value of the snow grain size at the end of summer. Theoretical analysis have been performed to investigate in detail the extreme snow grain size event happened near Dome Fuji during the summer 2019-2020. The simulations of the AMSU-B observations confirm that this extreme variation is mainly related to an increase in snow grain size. Results also highlighted a decrease in snow density during this event. This is supported by independent satellite observations at 1.4 and 36 GHz (from Soil Moisture and Ocean Salinity SMOS and Advanced Microwave Scanning Radiometer 2 AMSR-2, respectively), which showed synchronized variations related to an unusual change in surface snow density.
How to cite: Stefanini, C., Macelloni, G., Leduc-Leballeur, M., Favier, V., Pohl, B., and Picard, G.: Extreme increases in snow grain size on the Antarctic Plateau from Satellite Observations and Ice Sheet-Atmosphere Interactions, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5718, https://doi.org/10.5194/egusphere-egu25-5718, 2025.
The case of a strong heat anomaly around Pine Island Bay is examined. This region of west Antarctica is well known for its rapidly thinning and accelerating marine-terminating glaciers. Polar-WRF model simulations were used to investigate the atmospheric structure, dynamic and energy fluxes of this event at high spatial resolution. The modeling discovered a hot spot that formed due to the development of relatively large-scale foehn phenomena at the basin of Pine Island Glacier (PIG). The thickness of the positive temperature layer over this region can exceed 1 km with a maximum of +8ºC. The layering of several warm air masses, accompanied by atmospheric rivers, causes significant liquid precipitation over coastal glaciers and ice shelves. In such rare cases precipitation makes the main contribution to heat flux directed from atmosphere to the surface. The flux can reach up to 400 W m-2 in the form of latent heat (which may release later). Direct heat transfer is also contributing to surface warming as a negligible part of the heat balance. We also tried to estimate a nonlinear dependence of precipitation heat fluxes in relation to atmosphere warming. Finally, Noah LSM used in WRF model has some simplicities that make it not an ideal instrument for estimation of precipitation heat fluxes in polar regions. Although precipitation distribution and local wind patterns are sensitive to topography representation and demand high model resolution for estimation accuracy.
How to cite: Pishniak, D., Gilbert, E., Pysarenko, L., and Orr, A.: Melting energy sources in rainfall conditions over Pine Island Bay, Antarctica., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12116, https://doi.org/10.5194/egusphere-egu25-12116, 2025.
Southern Hemisphere sea ice area (SH SIA) exhibited weak increases from the early 1980s until 2015 when it abruptly dropped, setting record low values in 2017, 2022, and 2023. The reasons for the rapid declines in SH SIA remain open to debate, with potential explanations ranging from changes in tropical Pacific climate, warming of the high latitude subsurface ocean, and contemporaneous variations in the extratropical atmospheric circulation. Here we provide novel insights into the role of the extratropical atmospheric circulation in driving year-to-year and long-term changes in Antarctic sea ice, with a focus on the influence of the Southern annular mode (SAM) on recent trends in SH sea ice area. The influence of the SAM on SH SIA exhibits a more pronounced seasonal variation than that indicated in previous work: during the annual sea ice minimum, anomalous circumpolar westerlies associated with the positive polarity of the SAM lead to increases in SH SIA that persistent for several months. In contrast, during the annual sea ice maximum, anomalous circumpolar westerlies associated with the positive polarity of the SAM lead to pronounced decreases in Antarctic sea ice that persist for up to a year. In terms of annual-mean SH SIA, by far the largest impacts arise from variations in the atmospheric circulation during the sea ice maximum. As a result, changes in the SAM during the sea ice maximum have had a marked impact on long-term changes in SH SIA. These linkages are robust in both observationally constrained data products and modeled data, with additional results exploring how this relationship changes as the mean state of the climate changes under global warming.
How to cite: Boehm, C., Thompson, D. W. J., and Blanchard-Wrigglesworth, E.: The Key Role of the Southern Annular Mode During the Seasonal Sea Ice Maximum in Recent Antarctic Sea Ice Loss, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13164, https://doi.org/10.5194/egusphere-egu25-13164, 2025.
In 2016, Antarctic sea ice experienced a regime shift when a persisting decreasing trend emerged from a relatively stable annual cycle. Drivers of the sea ice regime shift and future projections of Southern Ocean sea ice remain unresolved. One possible contributing phenomena are atmospheric rivers (ARs), which are long, narrow, and transient features responsible for the majority of global poleward water vapor transport. Though infrequent over Antarctica, ARs wield a substantial influence on the Antarctic ice mass balance. Previous studies highlight their significance, attributing 35% of the interannual precipitation variability over the Antarctic Ice Sheet (AIS) to ARs. The interaction between ARs and Antarctic sea ice has not been as clearly defined. Our ongoing work uses ERA5 reanalysis data, results from an AR tracking algorithm, and passive microwave sea ice concentration data from 1980 to 2023 to examine the relationship between ARs and Antarctic sea ice, especially in the context of the changing sea ice state. In this study, we explore the relationship between AR activity and sea ice area at a region and seasonal scale, then analyse the contribution of ARs to precipitation over sea ice and how that contribution has changed through the 40-year study period. On average, ARs can be attributed with 11% of total precipitation, 11% of snowfall, and 13% of rain over Antarctic sea ice. While the AR contribution to sea ice snowfall is fairly consistent through the year, the predominant AR contribution to rain rotates around the Southern Ocean sequentially by season. The strongest signal of AR precipitation over sea ice is in the Weddell Sea winter, when ARs constitute 25% of winter rain. The trends of these contributions vary by season and by region. For example, while AR precipitation on sea ice has an increasing trend across all types of precipitation in each season in the Weddell Sea, the opposite is true for the Ross Sea. These findings underscore the importance of the AR interaction with Antarctic sea ice, particularly in the context of seasonal and regional variability and change. This work will improve our understanding of the spatiotemporal variability and trends of ARs as precipitation mechanisms, which is vital for understanding and predicting sea ice mass balance in a changing climate.
How to cite: Linscott, G., Parker, C., Boisvert, L., and Valkonen, E.: Extreme Precipitation in the Cyrosphere: Atmospheric River Interaction with Antarctic Sea Ice, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14582, https://doi.org/10.5194/egusphere-egu25-14582, 2025.
We present 4 retrospective hindcasts using PARASO, a five-component (ice sheet, ocean, sea ice, atmosphere, and land) fully coupled regional climate model over an Antarctic circumpolar domain: a control run forced at its boundaries with reanalysis data from ERA5 and ORAS5, and an ensemble of 3 members forced by 3 different EC-Earth global hindcasts. The ERA5 driven hindcast is shown to accurately simulate the increase in maximum sea ice extent observed prior to 2014. This trend being absent from the EC-Earth driven hindcasts, with strong intra-ensemble agreement, suggests a large influence of mid-latitude forcings, rather than a misrepresentation of local processes in global models. We analyse other factors possibly contributing to the diverging sea ice trends, such as ocean temperature and large-scale circulation patterns, and the spatial pattern of these sea ice changes. It is shown that all simulations display a sea ice retreat in the Amundsen Sea, which has previously been shown to be related to the intensification of the Amundsen Sea Low. Similarly, they all display an increase in sea ice extent in the Indian ocean sector, off of Enderby Land and the Amery Ice Shelf. However, the spatial extent of these areas differs between the ERA5 and EC-Earth driven hindcasts, and the trend diverges around the Antarctic Peninsula and in the Weddell Sea.
Furthermore, we explore how the diverging sea ice extent trends are translating into diverging evaporation trends, which in turn results in diverging moisture transport and surface mass balance trends for the Antarctic continent, even though all hindcasts once again agree on an increasing trend of moisture transport from the mid-latitudes. It is demonstrated that the EC-Earth driven hindcasts agree on most trends affecting the surface climate in Antarctica and the Southern Ocean, both in intensity and spatial pattern. However, the trends seen over the continent are less consistent between the EC-Earth ensemble members, compared to the ones seen over the Southern Ocean, indicating a larger influence of internal variability.
How to cite: Sauerland, F., Huot, P.-V., Marchi, S., Goosse, H., and van Lipzig, N.: EC-Earth- and ERA5-driven retrospective ensemble hindcasts with the fully coupled ice-sheet–ocean–sea ice–atmosphere–land circum-Antarctic model PARASO, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17914, https://doi.org/10.5194/egusphere-egu25-17914, 2025.
The vertical temperature structure controls atmospheric stability and is a key component for surface energy exchange. However, in situ data for validation of re-analysis data or process studies remain scarce in the Arctic. We collected 130 vertical temperature profiles up to 500 m above ground using uncrewed aerial vehicles (UAVs) over different surface types (ice, snow-free tundra, open water) around the Villum Research Station (VRS) in Northeast Greenland. The VRS is adjacent to Flade Isblink, the largest peripheral ice cap in Greenland. To assess the accuracy of our approach, we conducted 50 ascents and descents next to a meteorological mast equipped with temperature sensors at 2 m, 8 m, 20 m and 80 m above ground. Our UAV-based approach shows good agreement with the mast, with about 90% of the measurements being within the sensor accuracy of 0.6°C. Furthermore, we find a robust agreement between the UAV data and the Copernicus Arctic Regional Reanalysis (CARRA) data set (mean absolute difference of 1°C; r= 0.59) depending on the prevailing wind direction. To understand the influence of different surface properties on the vertical temperature structures and their temporal changes, we focus on daily CARRA data for June, July and August between 1991 and 2024. We show that differences in air temperature between regions of snow-free tundra and glacier ice maximize in July and find the maximum altitude up to which the atmosphere is significantly (α = 0.05) controlled by surface properties at about 100 m above ground. Next, we use K-means clustering to categorize temperature gradients above this threshold of 100 m and 500 m to analyze the associated large-scale atmospheric conditions. We are able to distinguish 5 clusters from the temperature gradients related to distinct patterns of large-scale atmospheric conditions of 850 hPa temperature and 500 hPa geopotential height. These preliminary results suggest that the temperature structures of the lowest 100 m of the troposphere are significantly controlled by surface properties and consequently by the fraction of snow cover in the tundra. Above 100 m, temperature gradients are driven by large-scale synoptic conditions. Finally, we study the effect of surface properties and large-scale circulation on the mass balance of the Flade Isblink ice cap using the Modèle Atmosphérique Régional (MAR).
How to cite: Fipper, J., Abermann, J., Sasgen, I., and Schöner, W.: Drivers and impacts of the vertical structure of the troposphere at Villum Research Station, Northeast Greenland, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7154, https://doi.org/10.5194/egusphere-egu25-7154, 2025.
Greenland's contribution to global mean sea level exhibits decadal variability, driven by interannual surface mass balance (SMB) changes. In this study, we attribute historical Greenland SMB changes to radiative forcings using the Community Earth System Model version 2 Large Ensemble and its single-forcing Large Ensemble simulations (CESM2-LE and CESM2-SFLE), which enables separation of impacts from greenhouse gases and aerosols. We quantify the contribution of radiative forcings to Greenland SMB changes by estimating univariate and multivariate detection and attribution scaling factors through Bayesian total least squares regression implemented via Markov Chain Monte Carlo (MCMC). The MCMC formulation allows us to quantify the uncertainty of the scaling factors using prior knowledge from observation-based simulations and reconstructions, as well as CESM2-LE and CESM2-SFLE. Our results indicate that historical Greenland SMB changes can be attributed to anthropogenic forcings, including anthropogenic aerosols, which affect decadal scale variability superimposed on the greenhouse gas-driven long-term trend. However, CESM2 tends to underestimate the relative contribution of each individual forcing to observed historical Greenland SMB changes. To explore potential reasons for this underestimation, we test a few hypotheses, including the role of internal variability. Our analysis demonstrates that internal variability plays only a minor role in the underestimation of the forced Greenland SMB changes due to individual forcings. Additionally, we find that Greenland runoff changes, rather than precipitation changes, explain both the SMB changes and the underestimation of attributable portions to individual forcings. Our findings emphasize the confounding role of aerosol forcing on the historical SMB trajectory but also highlight outstanding questions regarding the ability of climate models to correctly parse such influences. We will discuss the implications of these issues and steps to address them.
How to cite: Kuo, Y.-N., Culberg, R., and Lehner, F.: Assessing the portion of historical Greenland surface mass balance change attributable to anthropogenic forcing and its uncertainties, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15676, https://doi.org/10.5194/egusphere-egu25-15676, 2025.
The Arctic is a key component of the Earth’s climate system and has received much attention in recent years due to it’s above-average warming (Arctic Amplification). Furthermore, we know that the Arctic is not a closed system, but is influenced by atmospheric transport from lower latitudes, a fact that for example can be observed during spring when polluted air transported from lower latitudes regularly leads to a reduction in visibility (Arctic Haze).
In order to better understand the observed warming and pollution events we investigate circulation and transport patterns in the Arctic by calculating residence times, following air particle trajectories to and from the Arctic, and studying the dynamical characteristics of the Polar Dome. For our investigation we employ a newly created Lagrangian Reanalysis (LARA) dataset which is based on global simulations with the Lagrangian Particle Dispersion Model FLEXPART forced with ERA5 reanalysis data for the period 1940 to 2023.
Similar to a previous study we find average Arctic residence times in the order of one (January) to two weeks (July). Preliminary results indicate that these residence times have changed most during the transition months, especially in spring (e.g., shorter Arctic residence times in April at present than in the mid-20th century). However, we find strong spatial differences in residence times and in their changes over time. In this presentation we aim to discuss the seasonal and spatial characteristic of the residence times, investigate potential pollution source regions, explore the dynamical characteristics of the Polar Dome, and analyze how all of this has changed between 1940 and 2023. Furthermore, we plan to investigate the relation of observed dynamical changes to changes in sea ice, North Atlantic Oscillation, and other observations.
How to cite: Plach, A., Bakels, L., and Stohl, A.: Exploring atmospheric transport into the Arctic 1940 to 2023 - A Lagrangian Perspective, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15824, https://doi.org/10.5194/egusphere-egu25-15824, 2025.
Posters on site: Tue, 29 Apr, 16:15–18:00 | Hall X5
Since 1995, the Institute for Marine and Atmospheric research Utrecht (IMAU) at Utrecht University has operated automatic weather stations (AWS) at 20 different locations on the Antarctic ice sheet. In cooperation with multiple institutes, AWS were installed in Dronning Maud Land, on the East Antarctic Plateau, on the remnants of the Larsen B ice shelf, and on the Larsen C and Roi Baudouin ice shelves. Besides standard meteorological observations (wind speed, wind direction, air temperature, humidity, surface pressure), these stations also recorded the four components of net surface radiation, as well as surface height change. That allows for a reliable estimation of the surface energy balance (SEB) and surface mass balance (SMB) at hourly temporal resolution. Due to the harsh climatic conditions and limited number of maintenance visits, the data require a thorough quality control procedure and specific sensor corrections.
Here we present the corrections that were applied to the measurements, as well as the procedure that was implemented to flag suspicious samples. We give an overview of the first quantification of the long-term variability in SEB components, as well as the strong contrast between the high-melt locations near the grounding lines of ice shelves and the dry interior of the Antarctic ice sheet. In total, 152 station-years of observations are available, of which 78% are non-flagged simultaneous observations of all meteorological and radiation parameters.
This dataset may be used for the evaluation of climate models and for the interpretation and validation of remote sensing products, but also for the quantification of climatological changes and for process understanding in general. The data are openly available at https://doi.pangaea.de/10.1594/PANGAEA.974080.
How to cite: Van Tiggelen, M., Smeets, P., Reijmer, C., Kuipers Munneke, P., and van den Broeke, M.: 30 years of Antarctic weather station observations by the IMAU network (1995-2025), EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9051, https://doi.org/10.5194/egusphere-egu25-9051, 2025.
Antarctica and the Southern Ocean have an important role in Earth's climate, influencing global heat balance and carbon uptake. Recent anomalies, such as drastic sea ice decline, anomalous snowfall, and unprecedented heat waves challenge our understanding of the region's climate response. Both internal (local processes) and external (influence from lower latitudes) factors have been suggested as drivers of this variability, but the relative contributions of these remain unknown due to the lack of observations as well as shortcomings in climate models. We aim to enhance the understanding of this system by making use of recent advances in causal effect estimation. Going beyond correlation, causal network reconstruction aims to detect cause-effect links and their strength from observational datasets, including satellite records and reanalysis data. For selected sectors of Antarctica, the interconnections between ice sheet surface mass balance (SMB), sea ice, ocean temperature, and meridional transport of heat and water from lower latitudes are examined and causal relationships identified and quantified.
How to cite: Berghald, S., Van Lipzig, N., Goosse, H., and Lhermitte, S.: Interconnections between the components of the Antarctic climate system: a causal inference approach, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9646, https://doi.org/10.5194/egusphere-egu25-9646, 2025.
Denman Glacier Basin, a critical region for studying polar ice dynamics and climate change impacts, is heavily influenced by the combination of topographic and atmospheric conditions, particularly experiencing strong downslope winds. This study examines the structure and variability of near-surface winds in the basin, focusing on the influence of large-scale circulation, synoptic weathers, and local orographic effects. Through high-resolution atmospheric simulation experiments, we demonstrate the forced components of near-surface winds during prevalent synoptic systems in the area, quantifying the roles of large-scale and locally driven forces in shaping wind structure and variability. We also conduct perturbation experiments with topographies of varying resolutions to examine the orographic controls on the spatial climatology of downslope winds, in response to a range of synoptic systems typical to the region. Our findings can be used to clarify uncertainties in interpreting snow accumulation variability in ice cores and determining whether modern regional mass balance trends result from increased glacial discharge or shifts in synoptic circulation. This research findings will be used to interpret the Denman Glacier discharge, snow accumulation over the basin, aiding in the interpretation of recent ice core data collected in the recent field season.
How to cite: Wang, Z., Menviel, L., Sen Gupta, A., Goodwin, I., Chen, Z., and Caton Harrison, T.: Coupled Influence of Synoptic Weather and Topographic Control on Near-surface Wind Variability in the Denman Glacier Basin, East Antarctica, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14448, https://doi.org/10.5194/egusphere-egu25-14448, 2025.
This study investigates the characteristics and mechanisms of strong winds at Jang Bogo Station (74°37'S, 164°12'E) in Terra Nova Bay, East Antarctica, using 8 years (2015-2022) of Automated Synoptic Observation System (ASOS) data and ERA5 reanalysis data. Analysis of strong wind patterns reveals two distinct strong wind regimes: southwesterly (180-270°) and northwesterly (270-360°) winds. Strong wind events show clear seasonal variation, with peak frequencies occurring in March and July. Synoptic analysis using ERA5 reanalysis data indicates that these strong winds are primarily driven by the interaction between the Amundsen Sea Low and the Antarctic continental high pressure system. The intensity and positioning of these pressure systems significantly influence both wind direction and speed at Jang Bogo Station. Notably, the strongest winds (top 1%) are predominantly northwesterly, associated with enhanced pressure gradients near the station. Case studies of extreme wind events reveal two distinct generating mechanisms: one associated with intense pressure gradients from passing cyclonic systems, and another linked to katabatic flows descending from the Antarctic interior. These findings provide important insights into the wind regime of Terra Nova Bay and contribute to our understanding of Antarctic meteorological patterns, which has implications for both operational forecasting and regional climate studies.
How to cite: Kwon, H., Choi, Y., and Park, S.-J.: Characteristics of Strong Winds at Jang Bogo Station in East Antarctica: An 8-Year Observational Study, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16387, https://doi.org/10.5194/egusphere-egu25-16387, 2025.
In December, 2011 the REFIR-PAD Fourier transform spectroradiometer was installed in Concordia Station, Antarctica to perform continuous monitoring of the atmospheric downwelling emitted radiance in the middle-far infrared region. The spectroradiometer is supported by several auxiliary instruments to monitor ground and sky conditions and, since 2020, by a compact lidar sensor to provide cloud structure in the lower troposphere and boundary layer region, thus establishing a complete and integrated set of sensors for the monitoring of the Antarctic troposphere.
The main product in the data set provided by the observing system consists in high-resolution spectral radiances measured in the 100-1500 cm-1 region with a 0.4 cm-1 resolution. This allows us not only to separate the contributions to the radiation budget due to H2O, CO2, O3 and clouds, but also to retrieve vertical profiles of water vapor and temperature, columnar amounts of minor constituents and cloud properties through a data inversion process.
The production of a consistent long-term dataset needs to front multiple challenges which are intrinsic in long period continuous operation in extreme environment, methods for the correction of systematic effects and to perform automatic data quality assessment had been developed in order to be able to make the data available for use by the atmospheric science community.
An example of the results that can be obtained exploiting the advantage of long term measurement and high temporal resolution provided by the dataset is the identification and analysis of extreme events: not only it is possible to perform a detailed analysis of the most prominent events on an hourly timescale, but also it is possible to search the dataset for the occurrence and statistics of minor events that could be of similar origin.
How to cite: Bianchini, G., Di Natale, G., Palchetti, L., and De Pas, M.: Decadal time series of high-resolution downwelling spectral radiancemeasurements from Concordia Station, Antarctica, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3313, https://doi.org/10.5194/egusphere-egu25-3313, 2025.
Altitude-driven gradients of air temperature, humidity, wind, and surface mass balance play a critical role in understanding glacier-climate interactions, particularly in regions of rapid environmental change like the Arctic. In this study, we compare datasets from Alfred Wegener’s last expedition to the west coast of Greenland in 1930/31 with a modern measurement network established at the same locations in 2022. This unique comparison offers insights into how the atmospheric and glacial conditions have changed within a century.
The measurement network consists of one automatic weather station at the coast over bare ground in vicinity of the outlet glacier Qaamarujup Sermia and another at 940 m a.sl. on the Greenland Ice Sheet. For both locations observations exist during the Wegener expedition and since 2022. Additionally, temperature and humidity sensors and surface mass balance measurements distributed between these two points provide high-resolution spatial data.
The observed gradients in air temperature, humidity, wind speed, and wind direction are analysed at multiple temporal scales, from diurnal cycles to annual variations. Preliminary results show that the air temperature gradient between the coastal and the glacier station follows a seasonal cycle by being the smallest in spring (on average –6.5 °C) and the largest in winter (on average –11°C). Although this is true in the historic and modern dataset, the gradient in spring is colder in 2023 and 2024 with –7.0°C and –6.7°C respectively versus –5.7°C in 1931. The summer gradient is warmer in the modern dataset from -8.3°C in 1930, -9.3°C in 1931 to -7.7°C in 2023 and -7.8°C in 2024.
Our goal is to understand the key factors shaping these gradients, including the influence of large-scale atmospheric patterns such as the Greenlandic Blocking Index and North Atlantic Oscillation and the prevailing regional conditions identified through self-organizing maps. By comparing historical and modern datasets, we further examine how changes in glacier geometry and a frontal retreat of approximately 2 km since the 1930s have shaped climatic gradients. A particular focus is placed on whether this influence is more pronounced at the coastal or the glacier station.
This work contributes to the broader understanding of how glacier-climate interactions are influenced by both local and large-scale factors and underscores the value of historic observational records in assessing climate change impacts.
How to cite: Schalamon, F. R., Nicholson, L., Scher, S., Trügler, A., Schöner, W., and Abermann, J.: Glacier-Climate Interactions across Time: A West Greenland Case Study , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10147, https://doi.org/10.5194/egusphere-egu25-10147, 2025.
The Arctic is experiencing changes in precipitation, both in terms of amount and phase, due to rising temperatures. Key mechanisms contributing to these changes include increased poleward moisture transport and higher ocean evaporation resulting from the shrinking sea ice cover. In autumn, changes in precipitation over the sea ice can influence its growth by altering the insulation between the ocean and the atmosphere. A reduction in snow cover (which has lower insulating properties) enables the ocean to cool faster by releasing heat into the atmosphere, thus promoting sea ice growth. In spring, variations in snowfall and rainfall can affect the sea ice albedo, influencing its melting rate. Using the regional climate model MAR, which includes a complex snow scheme, we examine trends in precipitation and snow depth over the Arctic sea ice during the growth season. We also conduct sensitivity tests to assess the response of snow depth to changes in sea ice thickness.
How to cite: Lambin, C., Kittel, C., Maure, D., Noël, B., and Fettweis, X.: Evolution of precipitations and snow depth over the Arctic sea ice modeled by the regional climate model MAR, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12294, https://doi.org/10.5194/egusphere-egu25-12294, 2025.
How are polar-to-midlatitude teleconnections represented in recent large ensembles of coupled climate model simulations? And how do they evolve with global warming? Using the rich information on internal variability available from large ensembles, we investigate the relationship between sea ice amount and atmospheric circulation for both Arctic and Antarctic sea ice variability in CESM2 and ACCESS-ESM1-5, using a composite analysis. We find that the links between sea ice and sea level pressure (SLP), the midlatitude jet stream and temperature depend on the region in which sea ice varies, for instance with low Barents-Kara sea ice in January being associated with a positive North Atlantic Oscillation SLP pattern and high pressure over Northern Eurasia. These circulation patterns persist with increased levels of global warming, until around 3 or 4°C when they start to evolve in some cases, as sea ice starts to disappear. Surface air temperatures are anomalously high around the region of sea ice retreat with varying patterns of remote cooling elsewhere. Lagged analysis shows that sea-ice circulation relationships when the atmosphere leads sea ice are very similar to the instantaneous relationships, suggesting that the latter largely reflects the atmospheric patterns leading to reduced sea ice. For positive lags (sea ice leading the atmosphere), for some regions the SLP teleconnections persist in a weakened state for subsequent months, whilst for others they evolve, e.g. into a negative Arctic Oscillation response for Barents-Kara sea ice reduction. However, results for positive lags differ between the two models examined. SLP relationships with Antarctic sea ice are model dependent, but feature a negative Southern Annular Mode pattern in ACCESS-ESM1-5. In CESM2, we find a less zonally symmetric pattern which also consists of high pressure over the pole in Autumn and Winter.
How to cite: Iles, C., Samset, B., and Lund, M.: Polar-to-midlatitude teleconnections in a warming world: Statistical relationships from large ensembles, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13156, https://doi.org/10.5194/egusphere-egu25-13156, 2025.
In situ meteorological data are essential for a better understanding of the ongoing environmental changes in the Arctic. In order to increase the scientific value of discussions on understanding the actual state of environmental change in a given area, it is necessary to appropriately remove the anomalous values recorded due to external factors resulting from low temperature and icing. Here we present methods for quality control (QC) of meteorological observation datasets from two automatic weather stations in northwest Greenland, where drastic glaciological and meteorological environmental changes have occurred. The stations were installed in the accumulation area of the Greenland Ice Sheet (SIGMA-A site, 1490 m a.s.l.) and near the equilibrium line of the Qaanaaq Ice Cap (SIGMA-B site, 944 m a.s.l.). We describe the two-step sequence of QC procedures we used to produce increasingly reliable data sets by masking erroneous records. This method was developed for the climatic conditions of Greenland, however, it is designed to be as universally applicable as possible, with a basis in meteorology and glaciology, and with the intention of removing the subjectivity of the person performing the QC. The QC is divided into two processes: Initial Control and Secondary Control. Initial Control removes values that violate physical laws and also serves as a preliminary process to improve the accuracy of Secondary Control. Secondary Control removes abnormal values using stricter statistical criteria than Initial Control. As a result of this two-step process, controlled by scientifically objective criteria, we were able to successfully remove erroneous data sets and greatly reduce the time required for QC. In addition, by using a generally applicable process, we were able to successfully establish an algorithm that could be applied to multiple sites. The data sets from both the SIGMA-A and SIGMA-B sites were classified into three levels (Level 1.1 to Level 1.3) according to the stage of data processing. Level 1.1 is the so-called raw data, in which the data for the period when the logger was stopped are masked (processed to flag them as missing or abnormal), the so-called raw data. Level 1.2 and Level 1.3 are datasets to which Initial Control and Secondary Control have been applied to the Level 1.1 and Level 1.2 datasets, respectively, and the Level 1.3 dataset is a dataset from which all abnormal values have been removed. These datasets have been archived in the Arctic Data Archive System (ADS) operated by the National Institute of Polar Research in Japan (e.g., Level 1.3 dataset: SIGMA-A - https://doi.org/10.17592/001.2022041303 and SIGMA-B - https://doi.org/10.17592/001.2022041306).
How to cite: Nishimura, M., Aoki, T., Niwano, M., Matoba, S., Tanikawa, T., Yamasaki, T., Yamaguchi, S., and Fujita, K.: Quality-controlled meteorological datasets from SIGMA automatic weather stations in northwest Greenland, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13984, https://doi.org/10.5194/egusphere-egu25-13984, 2025.
As global mean temperatures exceeded the 1.5 °C threshold in 2024, the urgency to better quantify the impacts of global warming, including sea level rise contributions from polar ice sheets, has intensified. The Greenland Ice Sheet (GrIS) has experienced significant mass loss over recent decades, primarily driven by surface melting, a process expected to accelerate under continued warming. Surface melt is influenced by a combination of factors and complex interactions between atmosphere and ice sheet surface, but simulating these processes using coupled climate models is computationally expensive and often impractical.
In this study, we develop a graph neural network (GNN) as an emulator for GrIS surface melt, trained on output from the Community Earth System Model version 2 (CESM2), which explicitly calculates surface melt through a downscaled surface energy balance framework. GNNs are uniquely suited to this task, as they capture spatial and relational dependencies across the ice sheet, enabling the emulator to reproduce spatially resolved melt fields and identify the influence of key atmospheric patterns.
We will first evaluate the emulator’s performance in replicating CESM2 simulated melt under different climatic conditions and employ explainability techniques to identify the relative importance of key atmospheric patterns in driving surface melt. This work aims to demonstrate the utility of machine learning emulators in enhancing our understanding of GrIS surface melt dynamics and advancing projections of sea level rise under future climate scenarios.
How to cite: Yin, Z., Subramanian, A., and Datta, R.: Emulating Greenland Ice Sheet Surface Melt Using Graph Neural Networks, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15568, https://doi.org/10.5194/egusphere-egu25-15568, 2025.
In recent decades, the Arctic has warmed nearly four times faster than the global average, undergoing profound changes as a result. A key factor in this accelerated warming is the meridional transport of atmospheric water vapour. Particularly, intense intrusions of moisture and heat, so-called atmospheric rivers (ARs), are rare phenomena to reach the high latitudes, but can have severe impacts on the Arctic environment.
In this study, we examine an AR pair in April 2020 using a combination of Eulerian and Lagrangian methods alongside observational data from Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. The event consisted of two distinct ARs that followed separate pathways - one across Siberia and the other across the Atlantic - before converging in the central Arctic within the span of one week. Large-scale atmospheric circulation patterns associated with these ARs show a combination of low and high pressure systems on the flanks of the ARs, channelling moisture and heat northward. Notably, our results show that the Siberian AR was linked to extreme heat anomalies, whereas the Atlantic AR primarily transported abundant moisture.
Backward air parcel trajectories calculated using LAGRANTO provide new insights into the complex dynamics of Arctic ARs, revealing details of their distinct pathways and moisture source regions. Analysis of these trajectories also uncovers a strong connection between the observed sea ice melt in the Barents-Kara Sea and the interaction of an AR with the ice edge, underscoring the significant influence of ARs on the Arctic climate system.
How to cite: Aviles Podgurski, L. E., Martineau, P., Lu, H., Yamamoto, A., Phillips, T., Bracegirdle, T., Maycock, A. C., Orr, A., Fleming, A., Hogg, A. E., and Muszynski, G.: Pathways of Atmospheric Rivers in the Arctic: Dynamics, Moisture Transport, and Impacts on Sea Ice during April 2020, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15984, https://doi.org/10.5194/egusphere-egu25-15984, 2025.
Clouds modulate the net radiative flux interacting with both shortwave and longwave radiation, but the uncertainties regarding their effect in polar regions are especially high, because ground observations are lacking and evaluation through satellites is made difficult by the high surface reflectance. In this work, the radiative regimes and sky conditions for five different stations, two in the Arctic (Ny-Ålesund, 78.92°N, 11.93°E, Barrow, 71.32°N, 156.61° W) and four in Antarctica (Neumayer, 70.68°S, 8.27°W; Syowa, 69.01°S, 39.58°E; South Pole, 90°S, 0°E ; DomeC, 75.01°S, 123.33°E) will be presented, considering the decade between 2010 and 2020. Measurements of broadband shortwave and longwave radiation components (both downwelling and upwelling) are collected within the frame of the Baseline Surface Radiation Network (BSRN) (Driemel et al. 2018). Observations, together with identification of the clear sky and overcast conditions will be compared with ERA5 reanalysis (Herschbach et al., 2023). Furthermore, the identified conditions based on estimated cloud fraction will serve as labels for a machine learning classification task, leveraging algorithms such as Random Forest and Long Short-Term Memory (LSTM) networks (i.e. Zeng et al., 2021; Sedlar et al., 2021). These models incorporate features including global and diffuse shortwave radiation, downward longwave radiation, solar zenith angle, surface air temperature, relative humidity, and the ratio of water vapor pressure to surface temperature. The Random Forest model will also compute feature importance, identifying the most influential variables in predicting sky conditions and providing insights into the relationships between these meteorological factors.
Bibliography
Driemel et al. (2018): Baseline Surface Radiation Network (BSRN): structure and data description (1992–2017).
Riihimaki et al. (2019): Radiative Flux Analysis (RADFLUXANAL) Value-Added Product.
Hersbach, H. et al. (2023): ERA5 hourly data on single levels from 1940 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS)
Zeng, Z. et al. (2021): Estimation and Long-term Trend Analysis of Surface Solar Radiation in Antarctica: A Case Study of Zhongshan Station. Adv. Atmos. Sci. 38, 1497–1509.
Sedlar, J. et al. (2021): Development of a Random-Forest Cloud-Regime Classification Model Based on Surface Radiation and Cloud Products. J. Appl. Meteor. Climatol., 60, 477–491.
How to cite: Cavaliere, A., Frangipani, C., Baracchi, D., Becherini, F., Lupi, A., Mazzola, M., Pulimeno, S., Shullani, D., and Vitale, V.: Surface radiation budget data in a bipolar perspective: observations, comparison and exploiting for products., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11681, https://doi.org/10.5194/egusphere-egu25-11681, 2025.
This study examines long-term climatic and hydrological trends in River Oulankajoki, in Finland. The aim is to understand the impacts of changing climate conditions on river systems. Using 57 years (1966–2023) of daily air temperature and snow depth data from the Finnish Meteorological Institute (FMI) and hydrological observations from the Finnish Environment Institute (SYKE), the analysis incorporates longwave (LW) and shortwave (SW) radiation data from ERA5, accessed through Google Earth Engine (GEE). The Mann-Kendall trend test was employed to detect significant temporal changes, that reveals a significant decreasing trend in both air temperature values and discharge Phase Change Timing (i.e., PCT) over the study period. The results show that the river ice break-up timing has been shifting about 3-weeks in time, meaning that the break-up season occurs earlier than 57 years ago. These changes indicate potential shifts in regional climate dynamics, likely influenced by global climate change. Correlation heatmaps showed strong positive relationships between air temperature (AT) and river ice Break-Up Days (i.e., BUDs).
How to cite: Jalali Shahrood, A., Ahrari, A., and Torabi Haghighi, A.: Assessment of Long-Term Climatic, Hydrological, and River Ice Dynamics in River Oulankajoki , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3634, https://doi.org/10.5194/egusphere-egu25-3634, 2025.
