Warm water of open ocean origin on the continental shelf of the Amundsen and Bellingshausen Seas causes the highest basal melt rates reported for Antarctic ice shelves with severe consequences for ...the ice shelf/ice sheet dynamics. Ice shelves fringing the broad continental shelf in theWeddell and Ross Seas melt at rates orders ofmagnitude smaller. However, simulations using coupled ice–ocean models forced with the atmospheric output of the HadCM3 SRES-A1B scenario run (CO₂ concentration in the atmosphere reaches 700 ppmv by the year 2100 and stays at that level for an additional 100 years) show that the circulation in the southern Weddell Sea changes during the twenty-first century. Derivatives of Circumpolar Deep Water are directed southward underneath the Filchner–Ronne Ice Shelf, warming the cavity and dramatically increasing basal melting. To find out whether the open ocean will always continue to power the melting, the authors extend their simulations, applying twentieth-century atmospheric forcing, both alone and together with prescribed basal mass flux at the end of (or during) the SRES-A1B scenario run. The results identify a tipping point in the southern Weddell Sea: once warm water flushes the ice shelf cavity a positive meltwater feedback enhances the shelf circulation and the onshore transport of open ocean heat. The process is irreversible with a recurrence to twentieth-century atmospheric forcing and can only be halted through prescribing a return to twentieth-century basal melt rates. This finding might have strong implications for the stability of the Antarctic ice sheet.
We investigate how sea ice decline in summer and warmer ocean and surface temperatures in winter affect sea ice growth in the Arctic. Sea ice volume changes are estimated from satellite observations ...during winter from 2002 to 2019 and are partitioned into thermodynamic growth and dynamic volume change. Both components are compared with validated sea ice–ocean models forced by reanalysis data to extend observations back to 1980 and to understand the mechanisms that cause the observed trends and variability. We find that a negative feedback driven by the increasing sea ice retreat in summer yields increasing thermodynamic ice growth during winter in the Arcticmarginal seas eastward from the Laptev Sea to the Beaufort Sea. However, in the Barents and Kara Seas, this feedback seems to be overpowered by the impact of increasing oceanic heat flux and air temperatures, resulting in negative trends in thermodynamic ice growth of −2 km³ month−1 yr−1 on average over 2002–19 as derived from satellite observations.
The Antarctic ice sheet loses mass at its fringes bordering the Southern Ocean. At this boundary, warm circumpolar water can override the continental slope front, reaching the grounding line through ...submarine glacial troughs and causing high rates of melting at the deep ice-shelf bases. The interplay between ocean currents and continental bathymetry is therefore likely to influence future rates of ice-mass loss. Here we show that a redirection of the coastal current into the Filchner Trough and underneath the Filchner-Ronne Ice Shelf during the second half of the twenty-first century would lead to increased movement of warm waters into the deep southern ice-shelf cavity. Water temperatures in the cavity would increase by more than 2 degrees Celsius and boost average basal melting from 0.2 metres, or 82 billion tonnes, per year to almost 4 metres, or 1,600 billion tonnes, per year. Our results, which are based on the output of a coupled ice-ocean model forced by a range of atmospheric outputs from the HadCM3 climate model, suggest that the changes would be caused primarily by an increase in ocean surface stress in the southeastern Weddell Sea due to thinning of the formerly consolidated sea-ice cover. The projected ice loss at the base of the Filchner-Ronne Ice Shelf represents 80 per cent of the present Antarctic surface mass balance. Thus, the quantification of basal mass loss under changing climate conditions is important for projections regarding the dynamics of Antarctic ice streams and ice shelves, and global sea level rise.
Accurate Arctic sea‐ice forecasting for the melt season is still a major challenge because of the lack of reliable pan‐Arctic summer sea‐ice thickness (SIT) data. A new summer CryoSat‐2 SIT ...observation data set based on an artificial intelligence algorithm may alleviate this situation. We assess the impact of this new data set on the initialization of sea‐ice forecasts in the melt seasons of 2015 and 2016 in a coupled sea ice‐ocean model with data assimilation. We find that the assimilation of the summer CryoSat‐2 SIT observations can reduce the summer ice‐edge forecast error. Further, adding SIT observations to an established forecast system with sea‐ice concentration assimilation leads to more realistic short‐term summer ice‐edge forecasts in the Arctic Pacific sector. The long‐term Arctic‐wide SIT prediction is also improved. In spite of remaining uncertainties, summer CryoSat‐2 SIT observations have the potential to improve Arctic sea‐ice forecast on multiple time scales.
Plain Language Summary
Arctic sea ice is rapidly declining due to global warming, especially in summer. Accurate sea‐ice forecasting is important to understand the potential influence of these changes and devise effective responses. The performance of sea‐ice forecasts highly depends on the accuracy of the initial sea‐ice states. So refining the initial conditions of sea‐ice forecasts with satellite observations is a common way to reduce forecast errors. However, obtaining reliable summer pan‐Arctic satellite sea‐ice thickness (SIT) data is challenging due to complex ice‐surface conditions in summer. A new artificial‐intelligence‐based summer SIT satellite data product may improve initial SIT states. We integrate this data set into a sea‐ice forecast system to evaluate its impact on forecast skill. We find that the new summer satellite SIT data can reduce short‐term ice‐edge location forecast errors and benefit long‐term SIT forecasts.
Key Points
Assimilating summer CryoSat‐2 sea‐ice thickness (SIT) observations makes more skillful Arctic ice‐edge forecasts on multiple time scales
The long‐term SIT forecasts improve with the assimilation of summer CryoSat‐2 SIT observations
Further refinement is needed for summer CryoSat‐2 SIT observations
Freezing temperature parameterization significantly impacts the heat balance at sea‐ice bottom and, consequently, the simulated sea‐ice thickness. Here, the single‐column model ICEPACK was used to ...investigate the impact of the freezing temperature parameterization on the simulated sea‐ice thermodynamic growth during the MOSAiC expedition from October 2019 to September 2020. It is shown that large model errors exist with the standard parameterization and that different formulations for calculating the freezing temperature impact the simulated sea‐ice thickness significantly. Considering the winter mixed layer temperature, a modified parameterization of the freezing point temperature based on Mushy scheme was developed. The mean absolute error (ratio) of simulating sea‐ice thickness for all buoys reduces from 7.4 cm (4.9%) with the “Millero” scheme, which performs the best among the existing schemes in the ICEPACK model, to 4.2 cm (2.9%) with the new developed scheme.
Plain Language Summary
The heat transferred from the ocean to the sea‐ice influences the growth and melting of the sea‐ice. Freezing temperature is an essential parameter for calculating the heat transfer. Nevertheless, few studies have attempted to evaluate the impact of different freezing temperature parameterizations on the simulated sea‐ice thermodynamic growth. This study uses observed atmosphere and ocean data to force a single‐column model. Using different methods to calculate the freezing temperature significantly impacts the simulated sea‐ice thickness. After a series of testing and comparisons, we have developed a modified parameterization of freezing temperature that significantly reduces the simulation deviation from the observations.
Key Points
Different parameterizations of the freezing temperature significantly influence the simulated sea‐ice thickness
A modified‐Mushy parameterization method is developed for the freezing temperature, significantly improving ice thickness simulation
Abstract
Improvement and optimization of numerical sea ice models are of great relevance for understanding the role of sea ice in the climate system. They are also a prerequisite for meaningful ...prediction. To improve the simulated sea ice properties, we develop an objective parameter optimization system for a coupled sea ice–ocean model based on a genetic algorithm. To take the interrelation of dynamic and thermodynamic model parameters into account, the system is set up to optimize 15 model parameters simultaneously. The optimization is minimizing a cost function composed of the model–observation misfit of three sea ice quantities (concentration, drift, and thickness). The system is applied for a domain covering the entire Arctic and northern North Atlantic Ocean with an optimization window of about two decades (1990–2012). It successfully improves the simulated sea ice properties not only during the period of optimization but also in a validation period (2013–16). The similarity of the final values of the cost function and the resulting sea ice fields from a set of 11 independent optimizations suggest that the obtained sea ice fields are close to the best possible achievable by the current model setup, which allows us to identify limitations of the model formulation. The optimized parameters are applied for a simulation with a higher-resolution model to examine a portability of the parameters. The result shows good portability, while at the same time, it shows the importance of the oceanic conditions for the portability.
Abstract
Sea ice export through the Fram Strait is crucial in the dynamic evolution of Arctic sea ice and can further modulate Arctic sea ice mass balance as well as the ocean thermohaline ...circulation. In this study, based on outputs from a parameter-optimized and fully physical ocean–sea ice coupled model and sea ice age observation, we estimate sea ice volume (SIV) flux and its age evolution via the Fram Strait. The estimate of mean annual SIV flux is about 1605
±
315 km
3
yr
−1
without a significant trend for 1979–2021. Combining with sea ice age data, the variation of the sea ice age and its corresponding SIV flux are obtained for 1984–2020. The SIV flux of 1st-year ice significantly increases as expected, but it still contributes very little to the total flux in the 2010s with a proportion of 3.5%. SIV fluxes of different ages in multi-year ice present diverse variations. The proportions of 2nd-year ice and 3rd-year ice in the annual SIV flux show an extreme increase from 6.8% and 25.0% in the 1980s to 49.0% and 38.8% in the 2010s, respectively, while the proportions of 4th-year ice and 5th-year and older (5+ year) ice significantly decrease from 22.8% and 45.0% in the 1980s to 7.1% and 1.6% in the 2010s, respectively. Meanwhile, the prevailing age of annual volume export via Fram Strait shifts from 4th-year and 5+ year ice to 2nd-year and 3rd-year ice around 2007/2008. It is worth noticing that the variation in Fram Strait ice export modulates the variation in Arctic SIV prior to 2008, but the reverse is true after 2008, indicating a decreasing influence of Fram Strait SIV export on Artic SIV variability with decreasing sea ice age. The results are beneficial to promote the understanding of the evolution of Fram Strait SIV export under the warming Arctic.
Observations of sea-ice concentration are available from satellites year-round and almost weather-independently using passive microwave radiometers at resolutions down to 5 km. Thermal infrared ...radiometers provide data with a resolution of 1 km but only under cloud-free conditions. We use the best of the two satellite measurements and merge thermal infrared and passive microwave sea-ice concentrations. This yields a merged sea-ice concentration product combining the gap-free spatial coverage of the passive microwave sea-ice concentration and the 1 km resolution of the thermal infrared sea-ice concentration. The benefit of the merged product is demonstrated by observations of a polynya which opened north of Greenland in February 2018. We find that the merged sea-ice concentration product resolves leads at sea-ice concentrations between 60 % and 90 %. They are not resolved by the coarser passive microwave sea-ice concentration product. The benefit of the merged product is most pronounced during the formation of the polynya. Next, the environmental conditions during the polynya event are analysed. The polynya was caused by unusual southerly winds during which the sea ice drifted northward instead of southward as usual. The daily displacement was 50 % stronger than normal. The polynya was associated with a warm-air intrusion caused by a high-pressure system over the Eurasian Arctic. Surface air temperatures were slightly below 0 ∘C and thus more than 20 ∘C higher than normal. Two estimates of thermodynamic sea-ice growth yield sea-ice thicknesses of 60 and 65 cm at the end of March in the area opened by the polynya. This differed from airborne sea-ice thickness measurements, indicating that sea-ice growth processes in the polynya are complicated by rafting and ridging. A sea-ice volume of 33 km3 was produced thermodynamically.
Anthropogenic radionuclides released into European coastal waters from nuclear fuel reprocessing plants at Sellafield (UK) and La Hague (France) flow northward through the Nordic Seas and label ...Atlantic Water (AW) entering the Arctic Ocean. Transport of the soluble radionuclide 129I through the Arctic Ocean has been simulated using a numerical model for the period from 1970 to 2010. The simulated tracer distributions closely conform to 129I measurements made across the Arctic Ocean during the mid‐1990s and 2000s and clearly illustrate the dramatic changes in oceanic circulation which occurred during this time. The largest changes in surface circulation were associated with the transition from a negative to a positive phase of the Arctic Oscillation in the early 1990s and the subsequent return to a weak positive phase in the late 1990s and early 2000s. Model and experimental results indicate that a new circulation regime evolved after 2004 when a period of intense, anti‐cyclonic surface stress led to a strengthening of the Beaufort Gyre. We submit that this resulted in a suppression of the cyclonic boundary current of mid‐depth Atlantic Water (AW) below the Beaufort Gyre, with upper AW in the Canada Basin showing signs of a reversal from cyclonic to anti‐cyclonic flow. These results are consistent with the development of a new AW circulation scheme involving a separation between flow at intermediate depths in the Eurasian and Canada Basins which could eventually result in modification of the Arctic intermediate water which feeds the overflows.
Key Points
Model simulates dispersion of tracer 129 I in the Arctic Ocean
Tracer 129 I outlines changes in Arctic Ocean circulation over last decades
Middepth Atlantic Water circulation in Canadian Basin breaks down after 2004
Reliable and detailed measurements of atmospheric and snow conditions in the Arctic are limited. While modern atmospheric reanalyses could potentially replace the former, the latter can be ...principally simulated by dedicated snow modelling. However, because the uncertainties of reanalyses and modelling are still exceptionally large at high latitudes, a thorough analysis of the performance of atmospheric reanalyses and the snow model simulations are required. Specifically, we aim to answer the following questions for Villum Research Station (VRS), northeast Greenland: (1) What are the predominant snow and meteorological conditions? (2) What are systematic differences between the modern atmospheric reanalysis ERA5 and
in situ
measurements? (3) Can the snow model Crocus simulate reliably snow depth and stratigraphy? We systematically compare atmospheric
in situ
measurements and ERA5 reanalysis (November 2015–August 2018) and evaluate simulated and measured snow depth (October 2014–September 2018). Moreover, modelled and measured vertical profiles of snow density and snow specific surface area (SSA) are analysed for two days where a survey had taken place. We found good agreement between
in situ
and ERA5 atmospheric variables with correlation coefficients >0.84 except for precipitation, wind speed, and wind direction. ERA5’s resolution is too coarse to resolve the topography in the study area adequately, leading presumably to the detected biases. Crocus can simulate satisfactorily the evolution of snow depth, but simulations of SSA and density profiles, whether driven by ERA5 or
in situ
measurements are biased compared to measurements. Unexpectedly, measured snow depth agrees better with ERA5 driven simulation than with simulation forced with
in situ
measurements (explained variance: 0.73
versus
0.23). This is due to differences in snowfall, humidity and air temperature between both forcing datasets. In conclusion, ERA5 has great potential to force snow models but the use of Crocus in the Arctic is affected by limitations such as inappropriate parametrisations for Arctic snowpack evolution, but also by lack of process formulations such as vertical water vapour transport. These limitations strongly affect the accuracy of the vertical profiles of physical snow properties.
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