CR7.1

Recent ice shelf retreat on the east coast of the Antarctic Peninsula has been principally attributed to atmospherically driven melt. However, previous studies on the largest of these ice shelves—Larsen C—have struggled to reconcile atmospheric forcing with observed melt. This study provides the first comprehensive quantification and explanation of the atmospheric drivers of melt across Larsen C, using 31‐months' worth of observations from Cabinet Inlet, a 6‐month, high‐resolution atmospheric model simulation and a novel approach to ascertain the surface energy budget (SEB) regime. The dominant meteorological controls on melt are shown to be the occurrence, strength, and warmth of mountain winds called foehn. At Cabinet Inlet, foehn occurs 15% of the time and causes 45% of melt. The primary effect of foehn on the SEB is elevated turbulent heat fluxes. Under typical, warm foehn conditions, this means elevated surface heating and melting, the intensity of which increases as foehn wind speed increases. Less commonly—due to cooler‐than‐normal foehn winds and/or radiatively warmed ice—the relationship between wind speed and net surface heat flux reverses. This explains the seemingly contradictory results of previous studies. In the model, spatial variability in cumulative melt across Larsen C is largely explained by foehn, with melt maxima in inlets reflecting maxima in foehn wind strength. However, most accumulated melt (58%) occurs due to solar radiation in the absence of foehn. A broad north‐south gradient in melt is explained by the combined influence of foehn and non‐foehn conditions.

How to cite: Elvidge, A., Kuipers Munneke, P., King, J., Renfrew, I., and Gilbert, E.: Atmospheric Drivers of Melt on Larsen C Ice Shelf: Surface Energy Budget Regimes and the Impact of Foehn, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-11110, https://doi.org/10.5194/egusphere-egu21-11110, 2021.

West Antarctica (WA), especially the Ross Ice Shelf (RIS), has experienced more frequent surface melting during austral summer over the past three decades. Surface melting will jeopardize the stability of ice shelves and cause potential ice loss in the future. We investigate four major melt cases over the RIS via Polar WRF simulations driven by ERA5 reanalysis data and MODIS observed albedo. Direct warm air advection, recurring foehn effect, and cloud/upper warm air introduced radiative warming are the three major regional causes of surface melting over WA. Warm marine air can warm the ice surface directly. With significant moisture transport occurring over more than 40% of the time during the melting period, the impact from net radiation can be amplified via the formation of low-level liquid water clouds. Consequently, extensive downward longwave radiation favors the melting expansion over the middle and coastal RIS. Also, for 3 of 4 melt cases, more than 50% of the melting period experiences foehn warming, which can cause a 2 – 4 ºC increase in surface temperature. Isentropic drawdown is usually the dominant foehn mechanism and contributes a 14 ºC temperature increase, especially when strong low-level blocking occurs on the upwind side. Foehn clearance and decreasing surface albedo respectively increase the downward shortwave radiation and decrease the upward shortwave radiation, significantly contributing to surface melting in areas like western Marie Byrd Land. Moreover, frequent foehn cases can enhance the turbulent mixing on the leeside and benefit sensible heat transfer when Froude number is around 1. With better understanding of the regional factors for the surface melting, the prediction of the future stability of West Antarctic Ice Shelves will be improved.

How to cite: Zou, X., Bromwich, D., Montenegro, A., Wang, S.-H., and Bai, L.: Major Surface Melting over the Ross Ice Shelf, Antarctica, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-6628, https://doi.org/10.5194/egusphere-egu21-6628, 2021.

Global atmospheric reanalyses are frequently used to drive ocean-ice models but few data are available to assess the quality of these products in the Antarctic sea ice zone. We utilise measurements from three drifting buoys that were deployed on sea ice in the southern Weddell Sea in the austral summer of 2016 to validate the representation of near-surface atmospheric conditions in the ERA-Interim and ERA5 reanalyses produced by the European Centre for Medium Range Weather Forecasts (ECMWF). The buoys carried sensors to measure atmospheric pressure, air temperature and humidity, wind speed and direction, and downwelling shortwave and longwave radiation. One buoy remained in coastal fast ice for most of 2016 while the other two drifted northward through the austral winter and exited the pack ice during the following austral summer. Comparison of buoy measurements with reanalysis data indicates that both reanalyses represent the surface pressure field in this region accurately. Reanalysis temperatures are, however, biased warm by around 2 °C in both products, with the largest biases seen at the lowest temperatures. We suggest that this bias is a result of the simplified representation of sea ice in the reanalyses, in particular the lack of an insulating snow layer on top of the ice. We use a simple surface energy balance model to investigate the impact of the reanalysis biases on sea ice thermodynamics.

How to cite: King, J., Marshall, G., Colwell, S., Allen-Sader, C., and Phillips, T.: Validation of atmospheric reanalyses over the Weddell Sea, Antarctica, using observations from drifting buoys, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10127, https://doi.org/10.5194/egusphere-egu21-10127, 2021.

Rapid and deep descent in the tropopause (the so-called tropopause folding; TF) is often observed in the extratropics. Previous studies pointed out that the frequency of deep TF is maximized along the coast of Antarctica. However, the dynamics of TF in the Antarctic region have not yet been studied adequately. In the present study, the extreme TF in the Antarctic are examined using the state-of-art reanalysis data to clarify the uniqueness of TF in the Antarctic.

First, the distribution of TF frequency in the extra-tropics of the Southern hemisphere is examined. In austral winter, extreme TF often occurs along the coast of Antarctica. Around Syowa Station (69.0S, 39.6E), the frequency of extreme TF is maximized in August while the frequency is small in austral summer. It is interesting that the coast of Antarctica is located to the south of the maximum of the synoptic-scale eddy kinetic energy. This implies that the maximum of TF frequency along the coast of Antarctica cannot be explained only by the geographical distribution of the storm track.

Next, to examine the dynamics of the extreme TF events along the coast of Antarctica, we perform composite analyses of the extreme TF events at Syowa Station. When the negative anomaly of tropopause height is maximized, the significant downwelling is observed at the location of the extreme TF. From the analyses using the quasi-geostrophic Q-vector, it is found that the divergence of the Q-vector is observed around Syowa Station. The distribution of Q-vector is explained by the local westerly jet and strengthening of the frontal structure associated with a synoptic low-pressure system extending west-east centered at 70°S over Antarctica. The mechanism of the low-pressure system extending along the coast of Antarctica based on ray-tracing theory under the WKB approximation is also discussed.

How to cite: Kohma, M., Mizukoshi, M., and Sato, K.: Dynamical analysis of extreme tropopause folding events in the coastal region of Antarctica, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9763, https://doi.org/10.5194/egusphere-egu21-9763, 2021.

Land surface temperature is an important factor for permafrost modelling as well as for understanding the dynamics of Antarctic terrestrial ecosystems (Bockheim et al. 2008). In the South Shetland Islands the distribution of permafrost is complex (Vieira et al. 2010) and the use of remote sensing data is essential since the installation and maintenance of an extensive network of ground-based stations are impossible. Therefore, it is important to evaluate the applicability of satellites and sensors by comparing data with in-situ observations. In this work, we present the results from the analysis of land surface temperatures from Barton Peninsula, an ice-free area in King George Island (South Shetlands). We have studied the period from March 1, 2019 to January 31, 2020 using data from the Moderate Resolution Imaging Spectroradiometer (MODIS) Land Surface Temperature (LST) and in-situ data from 6 ground temperature loggers. MOD11A1 and MYD11A1 products, from TERRA and AQUA satellites, respectively, were used, following the application of MODIS quality filters. Given the scarce number of high-quality data as defined by MODIS, all average LST with error ≤ 2K were included. Dates with surface temperature below -20ºC, which are rare in the study area, and dates when the difference between MODIS and in-situ data exceeded 10ºC were also examined. In both cases, those days on which MOD09GA/MYD09GA products showed cloud cover were eliminated. Eight in-situ ground temperature measurements per day were available, from which the one nearest to the time of satellite overpass was selected for comparison with MODIS-LST. The results obtained show a better correlation with daytime data than with nighttime data. Specifically, the best results are obtained with daytime data from AQUA (R² between 0.55 and 0.81). With daytime data, correlation between MODIS-LST and in-situ data was verified with relative humidity (RH) values provided by King Sejong weather station, located in the study area. When RH is lower, the correlation between LST and in-situ data improves: we obtained correlation coefficients between 0.6 - 0.7 for TERRA data and 0.8 - 0.9 for AQUA data with RH values lower than 80%. The results suggest that MODIS can be used for temperature estimation in the ice-free areas of the Maritime Antarctic.

References:

Bockheim, J. G., Campbell, I. B., Guglielmin, M., and López- Martınez, J.: Distribution of permafrost types and buried ice in ice free areas of Antarctica, in: 9th International Conference on Permafrost, 28 June–3 July 2008, Proceedings, University of Alaska Press, Fairbanks, USA, 2008, 125–130.

Vieira, G.; Bockheim, J.; Guglielmin, M.; Balks, M.; Abramov, A. A.; Boelhouwers, J.; Cannone, N.; Ganzert, L.; Gilichinsky, D. A.; Goryachkin, S.; López-Martínez, J.; Meiklejohn, I.; Raffi, R.; Ramos, M.; Schaefer, C.; Serrano, E.; Simas, F.; Sletten, R.; Wagner, D. Thermal State of Permafrost and Active-layer Monitoring in the Antarctic: Advances During the International Polar Year 2007-2009. Permafr. Periglac. Process. 2010, 21, 182–197.

Acknowledgements

This work was made possible by an internship at the IGOT, University of Lisbon, Portugal, funded by the Principality of Asturias (code EB20-16).

How to cite: Corbea-Pérez, A., Vieira, G., Recondo, C., Baptista, J., F.Calleja, J., and Lee, H.: Evaluating the potential of MODIS-LST for monitoring ground surface temperatures in the Maritime Antarctic (Barton Peninsula, King George Island, Antarctic). , EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10415, https://doi.org/10.5194/egusphere-egu21-10415, 2021.

The Greenland Ice Sheet (GrIS) has been losing mass at an accelerated rate in the last few decades, of which, approximately 50% is related to surface melting and runoff (Imbie Team, 2020). Since the mid 2010’s, the highest melt anomalies were found in the northeast of Greenland, where the North East Greenland Ice Stream drains 8 - 12 % of the GrIS. Unsurprisingly, the vast majority of melting occurs in the summer months, however the increasing trend in air temperatures is larger in winter. Similarly, very warm winter periods have been observed recently in the north of Greenland and Arctic Ocean. Due to our previous focus on summer melting, our understanding of glacial hydrology and surface mass balance in winter is still poor.

Here, we present the frequency and amount of surface melting and precipitation, as simulated by the Modèle Atmosphérique Régional (MAR) at 15 km spatial resolution (from 1980 to 2018) and the COupled Snowpack and Ice surface energy and mass balance model in PYthon (COSIPY) at 1 km spatial resolution (from 2014 to 2018). Observations from two automatic weather stations are also used to analyse the meteorological setting. We find that both periods of winter melt and extreme precipitation are related to the presence of atmospheric rivers along the east coast of Greenland and in the Atlantic Ocean (specifically in the Greenland Sea and Fram Strait). On average, the detection of atmospheric rivers in the vicinity of the northeast of Greenland leads to a daily warming of +8°C and can raise temperatures to the melting point for a short period of time. We also present the changes in precipitation type (rainfall vs snowfall), from 1980 to 2018 from both MAR and the ERA5 reanalysis product, which are related to atmospheric rivers and passing storms.

How to cite: Turton, J., Mattingly, K., and Mölg, T.: The influence of atmospheric rivers on winter melt and accumulation in the northeast of Greenland., EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-6137, https://doi.org/10.5194/egusphere-egu21-6137, 2021.

Atmospheric Rivers (ARs), narrow filaments of concentrated water vapor transport, have direct impacts on the surface mass balance (SMB) of the western Greenland Ice Sheet through increased summer melting in the ablation area and increased snowfall in higher altitudes. Here, we show that an additional effect of ARs on SMB comes from the development of föhn winds, whereby the air is adiabatically warmed as it descends. As ARs pass over the ice sheet and deposit precipitation in northwest Greenland, the air subsequently flows down the leeward slope and the warm, dry conditions contribute to increased melting in the northeast, and more specifically on the Nioghalvfjerdsfjorden (or 79N) Glacier.

We identify föhn conditions using an automated detection algorithm applied to MAR and RACMO2 regional climate model output. These data are paired with an AR detection algorithm and self-organizing map (SOM) classification applied to MERRA-2 and ERA5 reanalyses, in order to investigate connections between regional circulation patterns, ARs, föhn winds, and ice sheet SMB. We find that föhn conditions and associated surface melt are increased for periods of 1–3 days after anomalous southerly and southwesterly water vapor transport by ARs through Baffin Bay and the Nares Strait. Approximately 70% of the ARs which make landfall in the northwest sector of Greenland lead to the development of föhn winds on the northeast coast. The frequency of AR-induced föhn conditions in the northeast has increased in the last 40 years, in line with an increase in the strongest ARs in the northwest. We also find that anomalous northerly moisture transport from the Lincoln Sea generates enhanced melt in the lowest (0–500m) elevations of northeast Greenland, while below-average surface melt occurs during all other identified moisture transport regimes.

How to cite: Mattingly, K., Turton, J., Wille, J., Fettweis, X., and Noël, B.: The contribution of föhn winds to northeast Greenland summer melt and their relationship with atmospheric rivers, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8002, https://doi.org/10.5194/egusphere-egu21-8002, 2021.

The development of the HARMONIE model system has led to huge advances in numerical weather prediction, including over Greenland where a numerical weather prediction (NWP) model is used to forecast daily surface mass budget over the Greenland ice sheet as presented on polarportal.dk. The new high resolution Copernicus Arctic Reanalysis further developed the possibilities in HARMONIE with full 3DVar data assimilation and extended use of quality-controlled local observations. Here, we discuss the development and current status of the climate version of the HARMONIE Climate model (HCLIM). The HCLIM system has opened up the possibility for flexible use of the model at a range of spatial scales using different physical schemes including HARMONIE-AROME, ALADIN and ALARO for different spatial and temporal resolutions and assimilating observations, including satellite data on sea ice concentration from ESA CCI+, to improve hindcasts. However, the range of possibilities means that documenting the effects of different physics and parameterisation schemes is important before widespread application. 

Here, we focus on HCLIM performance over the Greenland ice sheet, using observations to verify the different plausible set-ups and investigate biases in climate model outputs that affect the surface mass budget (SMB) of the Greenland ice sheet. 

The recently funded Horizon 2020 project PolarRES will use the HCLIM model for very high resolution regional downscaling, together with other regional climate models in both Arctic and Antarctic regions, and our analysis thus helps to optimise the use of HCLIM in the polar regions for different modelling purposes.

How to cite: Mottram, R., Landgren, O., Anker Pedersen, R., Pagh Nielsen, K., Bøssing Christensen, O., Olesen, M., Boberg, F., Hansen, N., Amstrup, B., and Yang, X.: Physics, Resolution and Data Assimilation: Making sense of Greenland climate and ice sheet Surface Mass Balance with HARMONIE Climate, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-16100, https://doi.org/10.5194/egusphere-egu21-16100, 2021.

The surface radiation budget is an essential component of the total energy exchange between the atmosphere and the Earth’s surface. Measurements of radiative fluxes near/on ice surfaces are sparse in the polar regions, including on the Greenland Ice Sheet (GrIS), and the effects of cloud on radiative fluxes are still poorly studied. In this work, we assess the impacts of cloud on radiative fluxes using two metrics: the longwave-equivalent cloudiness, derived from long-wave radiation measurements, and the cloud transmittance factor, obtained from short-wave radiation. The metrics are applied to radiation data from two automatic weather stations located over the bare ground near the ice front of Helheim (HG) and Jakobshavn Isbræ (JI) on the GrIS. Comparisons of meteorological parameters, surface radiation fluxes, and cloud metrics show significant differences between the two sites. The cloud transmittance factor is higher at HG than at JI, and the incoming short-wave radiation in the summer at HG is 50.0 W m−2 larger than at JI. Cloud metrics derived at the two sites reveal   a high dependency on the wind direction. The total cloud radiative effect (CREnet) generally increases during melt season at the two stations due to long-wave CRE enhancement by cloud fraction.  CREnet decreases from May to June and increases afterward, due to the strengthened short-wave CRE. The annually averaged CREnet were 3.0 ± 7.4 W m-2 and 1.9 ± 15.1 W m−2 at JI and HG.  CREnet estimated from AWS indicates that clouds cool the JI and HG during melt season at different rates.

How to cite: Djoumna, G., Mernild, S. H., and Holland, D.: Cloud effects on surface radiation balance at Helheim and Jakobshavn Glaciers (Greenland) using ground-based observations , EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8103, https://doi.org/10.5194/egusphere-egu21-8103, 2021.

Single extreme weather events such as intense storms or blocks can have a major impact on polar surface temperatures, the formation and melting rates of sea-ice, and, thus, on minimum and maximum sea-ice extent within a particular year. Anomalous weather conditions on the time scale of an entire season, for example resulting from an unusual sequence of storms, can affect the polar energy budget and sea-ice coverage even more. Here, we introduce the concept of an extreme season in a distinct region using an EOF analysis in the phase space spanned by anomalies of a set of surface parameters (surface temperature, precipitation, surface solar and thermal radiation and surface heat fluxes). To focus on dynamical instead of climate change aspects, we define anomalies as departures of the seasonal mean from a transient climatology. The goal of this work is to study the dynamical processes leading to such anomalous seasons in the polar regions, which have not yet been analysed. Specifically, we focus here on a detailed analysis of Arctic extreme seasons and their underlying atmospheric dynamics in the ERA5 reanalysis data set.

We find that in regions covered predominantly by sea ice, extreme seasons are mostly determined by anomalies of atmospheric dynamical features such as cyclones and blocking. In contrast, in regions including large areas of open water the formation of extreme seasons can also be partially due to preconditioning during previous seasons, leading to strong anomalies in the sea ice concentration and/or sea surface temperatures at the beginning of the extreme season.

Two particular extreme season case studies in the Kara-Barents Seas are discussed in more detail. In this region, the winter of 2011/12 shows the largest positive departure of surface temperature from the background warming trend together with a negative anomaly in the sea ice concentration. An analysis of the synoptic situation shows that the strongly reduced frequency of cold air outbreaks compared to climatology combined with several blocking events and the frequent occurrence of cyclones transporting warm air into the region favored the continuous anomalies of both parameters. In contrast, the winter of 2016/17, which shows a positive precipitation anomaly and negative anomaly in the surface energy balance, was favored by a strong surface preconditioning. An extremely warm summer and autumn in 2016 caused strongly reduced sea ice concentrations and increased sea surface temperatures in the Kara-Barents Seas at the beginning of the winter, favoring increased air-sea fluxes and precipitation during the following months.

Our results reveal a high degree of variability of the processes involved in the formation of extreme seasons in the Arctic. Quantifying and understanding these processes will also be important when considering climate change effects in polar regions and the ability of climate models in reproducing extreme seasons in the Arctic and Antarctica.

How to cite: Hartmuth, K., Papritz, L., Boettcher, M., and Wernli, H.: Dynamics and drivers of extreme seasons in the Arctic region, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-1521, https://doi.org/10.5194/egusphere-egu21-1521, 2021.

The Arctic has warmed during the recent observational record and is projected to keep warming through the end of the 21^st century in nearly every future emissions scenario and global climate model. This will drive continued thawing of permafrost-rich soils, alter the partitioning of rain versus snow events, and greatly affectthe water cycle and land-surface processes across the Arctic. However, previous analyses of these impacts using dynamical models have relied on global climate model output or relatively coarse regional climate model simulations. In the coarse simulations, projections of changes to the water cycle and land-surface processes in areas of complex orography and high land-surface heterogeneity, which are characteristic of many regions in the Arctic, may thus be limited. 

Here, we discuss recent work examining high-resolution regional climate simulations over Alaska and NW Canada. Completed and upcoming simulations have been and will be run at a 4 km grid spacing, which is sufficient to resolve orography across this region’s mountain ranges. The initial simulation results are very encouraging and show the regional climate model yields a realistic representation of the seasonal and spatial evolution of precipitation, temperature, and snowpack compared to previous studies across Alaska and other Arctic regions. A paired future climate simulation uses the Pseudo-Global Warming (PGW) approach, where the end of century ensemble mean monthly climate perturbations (CMIP5 RCP8.5) are used to incorporate the thermodynamic effects of future warming into the present-day climate as represented by ERA-Interim reanalysis data. Changes in major components of the hydroclimate (e.g. precipitation, temperature, snowfall, snowpack) are projected to sometimes be significant in this future scenario. For example, the seasonal snow cover in some regions is projected to mostly disappear. However, there are also projected increases in snowpack in historically very cold areas (e.g. high elevations) that are able to stay cold enough in the future to support snowfall and snowpack.

Finally, we will present a new effort to couple an advanced land-surface model, the Community Terrestrial Systems Model (CTSM), within the Regional Arctic Systems Model (RASM) in an effort to better represent complex land-surface and subsurface (e.g. permafrost, streamflow availability timing and temperatures) processes for climate change impact studies. CTSM is a complex physically based land-surface model that is able to represent multiple snow layers, a complex canopy, and multiple soil layers including organic matter and frozen soils, which enables us to explicitly represent spatial variability in the regional hydroclimate and land states (e.g. permafrost) at relatively high spatial resolutions relative to other simulations (4 km land and atmosphere grids).  Successful coupling of CTSM within RASM has been completed and we will discuss some preliminary land-atmosphere coupled test results.

How to cite: Newman, A., Cheng, Y., Musselman, K., Craig, A., Swenson, S., Hamman, J., and Lawrence, D.: High-Resolution Regional Climate Simulations of Arctic Hydroclimatic Change, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-6085, https://doi.org/10.5194/egusphere-egu21-6085, 2021.

Superimposed on a strong observed decline in Arctic sea ice extent there is large inter-annual variability. Recent research indicates that atmospheric temperature fluctuations are the main drivers for this variability. They can result both from local ocean heat release and from poleward atmospheric energy transport. Previous studies have emphasised a significant warming effect associated with latent energy transport into the Arctic region. In particular this is due to enhanced greenhouse effect associated with the convergence of the humidity transport over the Arctic. While previously some sea ice minima events have been linked to anomalous moist air convergence, a systematic study of this linkage between energy transport and sea ice variability was missing. Through a regression analysis we here investigate the coupling between transport anomalies of both latent and dry-static energy and sea ice anomalies. From the state-of-the-art ERA5 reanalysis product the latent and dry-static transport over the Arctic boundary (70°N) is calculated. The transport is then split into transport by planetary and synoptic-scale waves using a Fourier decomposition. Lagged regression analysis of sea ice concentration anomalies on the transport anomalies reveal the statistical linkage between the occurrence of sea ice anomalies after transport events. The results show that latent energy transport as compared to that of dry-static energy induces a much stronger decrease in sea ice concentration. One day after maximum of the latent transport event by planetary waves, sea-ice concentration shows a significant decrease lasting up to at least 45 days. In addition, the energy transport by planetary waves shows a greater effect on the sea ice concentration than transport by synoptic-scale waves. Hence, this study emphasizes the important impact of latent energy transport by planetary waves on the sea ice variability.

How to cite: Hofsteenge, M. G., Graversen, R. G., and Rydsaa, J. H.: Impact of latent and dry-static atmospheric energy transport on the Arctic sea ice variability, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-6594, https://doi.org/10.5194/egusphere-egu21-6594, 2021.

The effects of Arctic cyclones on sea ice are the subject of many papers, however aside from individual case studies, few address the heterogeneity in the spatial pattern of the sea ice response.

We composite atmospheric conditions from ERA5 reanalysis and satellite sea ice concentrations on Arctic cyclones using a storm-centered approach to reveal the typical atmosphere and sea ice responses at different bearings and distances relative to an Arctic cyclone.

Asymmetry in the pattern of the sea ice concentration response to cyclones is revealed, with increased growth/reduced melt to the west of cyclones and decreased growth/increased melt to the east.

In part, this is explained by heterogeneity in the spatial patterns of atmospheric temperature and cloud fraction associated with cyclones, which result in heterogeneity in patterns of the surface energy fluxes.

Using the CICE sea ice model forced with prescribed atmospheric reanalysis from the Japan Meteorological Agency, we reveal the relative importance of the dynamic and thermodynamic forcing of cyclones on sea ice, as well as the spatial patterns of each. The dynamic and thermodynamic responses of sea ice concentration to cyclones are comparable in magnitude, however dynamic processes dominate the response of sea ice thickness.

These results highlight and explain important details often missed when answering “do cyclones cause an increase or decrease sea ice?”, as it appears the answer is both.

How to cite: Clancy, R., Bitz, C., Blanchard-Wrigglesworth, E., and McGraw, M.: Drivers of the Spatial Pattern of Arctic Sea Ice Response to Arctic Cyclones, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8130, https://doi.org/10.5194/egusphere-egu21-8130, 2021.

Marine Cold Air Outbreaks (MCAOs) are common features above the open water surfaces of the Nordic Seas. They are characterized by marked vertical temperature gradients, which typically persist over several days, and strongly shape air-sea heat exchanges, convection, weather and boundary layer characteristics in the affected region. Based on the novel ERA-5 reanalysis product, we are analyzing climatological and recent aspects of MCAOs in the Fram Strait region of the North Atlantic, which is a “hot spot” particularly during winter and early spring. MCAOs in Fram Strait occur preferably when persistent low pressure systems occupy Northern Scandinavia and the Barents/Kara Sea, which exerts strong zonal pressure gradients across Fram Strait. Based on the vertical gradients of potential temperature, occurrence frequencies of MCAOs of different strengths are investigated.  It is found that MCAOs of moderate strength occur at an average of 7-9 days per month between December and March, while especially strong MCAOs occur at an average of 1-3 days in that time. Regarding the former, March is the only month for which a significant trend of +1.7 days/month/decade was found over the 1979-2020 period. While regional MCAO expression is dependent on both the relative location of the ice edge and on the atmospheric circulation, MCAO increase in Fram Strait in March can be explained mainly with the latter and the associated zonal pressure gradient.

February and March 2020 serve as examples of particularly strong and persistent MCAOs in Fram Strait. The record-breaking strong polar vortex at that time, which had received global attention in the media and literature, had left its associated footprint in near surface and tropospheric circulation fields, hence providing anomalous northerly flow across the ice edge in Fram Strait. While this clearly shaped MCAOs in Fram Strait, associated anomalies were also observed in the North Atlantic Sea Ice edge, and were even detected in upper air profiles and sea ice conditions on Svalbard.

For the detailed study of such northerly advection events, atmospheric data gathered during the year-long MOSAiC expedition 2019/2020 in the central Arctic are expected to provide valuable information in the upstream direction of the anomalies in Fram Strait.

How to cite: Dahlke, S., Solbes, A., and Maturilli, M.: Marine cold air outbreaks in Fram Strait – General increase in March and a special case in 2020, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14537, https://doi.org/10.5194/egusphere-egu21-14537, 2021.