Towards a marginal Arctic sea ice cover

Lead Research Organisation: University of Reading
Department Name: Meteorology

Abstract

Recent observed changes in the Arctic have become a 'poster child' for global climatic changes, particularly because the summer sea ice extent has shrunk rapidly over the past 35 years. This retreat of the sea ice has led to growth of trans-Arctic shipping and plans to extract minerals and fossil fuels from the ocean floor.

The latest assessment of the Intergovernmental Panel on Climate Change (IPCC) concluded that it was likely that the Arctic would become reliably ice-free by 2050 assuming greenhouse gas emissions continue to increase. However, the climate simulations used by the IPCC often fail to realistically capture large scale properties of the Arctic sea ice, such as the extent, variability and recent trends. Therefore, there is a need to improve simulations of Arctic sea ice to provide better understanding of the recent observed changes and credible projections of the future to help assess risks and opportunities and inform important policy decisions about adaptation and mitigation.

Observations of the Arctic have improved in recent years with new satellites measuring sea ice properties from space. These satellites reveal not only that the extent and thickness of the Arctic ice cover is reducing in all seasons but that the Marginal Ice Zone (MIZ), a region of low ice area concentration consisting of a relatively disperse collection of small floes, has grown.

Model projections indicate the MIZ will grow from around 10% to 80% of the summer sea ice cover by 2050, exposing a hitherto relatively quiescent Arctic Ocean to the atmosphere. Nonlinear interactions between the air, ice, and ocean that magnify or diminish change, known as feedbacks, associated with a reduced and marginal sea ice cover will emerge or assume dominance in the coming years. Many of these feedbacks are either entirely absent or inadequately captured in current models. For example, not included is the feedback whereby the creation of smaller floes due to ice melt or breakup under ocean wave stress promotes further lateral melt and propagation of waves deeper into the pack, further enlarging the MIZ. Because existing climate models oversimplify these feedbacks, their utility for understanding and predicting variability and change in the Arctic is compromised. This leads to impairment of climate model accuracy at lower latitudes also, due to errors in meridional atmospheric and oceanic circulations as well as ice export from the Arctic.

We will investigate processes controlling evolution of the MIZ using existing and new observations. We will include physics of wave-ice interaction, ice breakup and melt, and floe collisions into ice, ocean, and climate models. We will use these models, constrained and verified with new observations, to explore feedbacks between the sea ice, ocean, and atmosphere using a series of numerical experiments. We will quantify the impact of the increase in the MIZ on the Arctic physical climate, and explore the processes responsible for the projected loss of Arctic sea ice.

Planned Impact

Arctic sea ice reduction has become a totemic indicator of climate change with impacts on iconic species such as polar bears and the Beluga whale, as well as indigenous human populations. The reduction of Arctic sea ice extent has generated widespread interest with numerous articles in the popular press, radio, television and internet.

Reduction in the sea ice cover is already opening up shipping routes and the potential for oil exploration has generated political statements and actions including, for example, the placement of the Russian flag at the North Pole and Denmark's declaration of sea bed rights up to the North Pole. Lloyd's of London, with Chatham House, published a report called "Arctic Opening" in 2012, with business (including insurance) expansion in mind. In 2014, the PI organised a Royal Society meeting on Arctic sea ice: the evidence, models, and global impacts, which was the Royal Society's most tweeted meeting.

Understanding how and why Arctic sea ice conditions change on decadal timescales is a critical issue facing international governments and business. Improved predictions of Arctic sea ice through scientific research has economic, social and environmental implications. This research brings together broad international expertise in sea ice model development to ensure maximal benefit to sea ice research, modelling and prediction groups.

A major practical impact of this proposal is in the generation of a new sea ice module accounting for marginal ice zone physics in the sea ice component (CICE) of a Global Climate Model (GCM). The CICE sea ice component is used in several GCMs, which include the UK Earth System Model (UKESM), the HadGEM3-GC3 climate model used by the Met Office for contributions to climate projections CMIP6, and the Community Climate System Model (CCSM) at the (US) National Center for Atmospheric Research. The Met Office and Los Alamos National Laboratory are both Project Partners offering in-kind support to help deliver the improvements to sea ice models, and visits are planned for both to ensure maximal usage of the research.

The main direct beneficiaries of the knowledge generated by this project will be:

1. The Met Office and other international modelling groups who will be able to utilise an enhanced and improved sea ice component in their global climate models

2. The international climate research community, including the IPCC, through collaborative analysis of the Arctic system to understand the causes of recent changes

3. Policy makers (such as DECC, DEFRA and FCO) who will have an improved understanding of the risks and opportunities presented by a changing Arctic. This work also has the potential to be used to inform mitigation and adaptation decisions under the UNFCCC climate negotiations.

4. This project will supply part of the physical basis for future prediction systems for the Arctic and Northern Hemisphere mid-latitudes, which will have benefits to the stakeholders such as the oil, gas and mineral extraction industry, trans-Arctic shipping, tourism and indigenous communities. The general public and local communities would also benefit from improved forecasts.

Publications

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Ranjan A (2023) Molecule generation toward target protein (SARS-CoV-2) using reinforcement learning-based graph neural network via knowledge graph. in Network modeling and analysis in health informatics and bioinformatics

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Landy J (2019) A Facet-Based Numerical Model for Simulating SAR Altimeter Echoes From Heterogeneous Sea Ice Surfaces in IEEE Transactions on Geoscience and Remote Sensing

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Hwang, B. (2020) Impacts of climate change on Arctic sea ice in MCCIP Science Review 2020

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Hwang B (2022) Multi-scale satellite observations of Arctic sea ice: new insight into the life cycle of the floe size distribution. in Philosophical transactions. Series A, Mathematical, physical, and engineering sciences

 
Description The marginal ice zone is that part of the sea ice cover which is not completely covered in ice. In this region the sea ice floes are interspersed with open water. As the Arctic sea ice cover has reduced in the last several decades, many had assumed that the marginal ice zone would get larger. We performed an analysis of satellite sea ice concentration from 1979 to 2019 and found that the marginal ice zone actually has not got larger over this period, but has migrated northwards and got wider. This work has been published.

We have implemented a floe size distribution model into a climate sea ice model and performed an analysis of its impact on the simulated sea ice mass balance. This work has been published.
Exploitation Route Our findings on the marginal ice zone place an important constraint on models simulating the Arctic climate, which will be uised by researchers and climate modelling institutions.
Sectors Aerospace, Defence and Marine,Environment

 
Description CANARI: Climate change in the Arctic-North Atlantic Region and Impacts on the UK
Amount £9,047,608 (GBP)
Funding ID NE/W004984/1 
Organisation Natural Environment Research Council 
Sector Public
Country United Kingdom
Start 04/2022 
End 03/2027
 
Description Fragmentation and melt of Arctic sea ice
Amount £501,119 (GBP)
Funding ID NE/V011693/1 
Organisation Natural Environment Research Council 
Sector Public
Country United Kingdom
Start 02/2022 
End 01/2025
 
Title ARC36 stand-alone SI3 Arctic configuration 
Description SI3 regional configuration of the Arctic This is a configuration of the NEMO community ocean model based on the ORCA2_SAS_ICE reference configuration. The NEMO code is available from https://forge.nemo-ocean.eu/nemo/nemo. This configuration has a resolution of 1/36 degree and is a cut-out of the global 1/36 configuration: https://github.com/immerse-project/ORCA36-demonstrator. The code base is a pre-4.2.0 NEMO version, the model source code can be found in the file src_tar. Model setup Follow the instructions on https://sites.nemo-ocean.io/user-guide/index.html to download and install the NEMO model version 4.2.0. Swap the src directory for the one in the tar file src_tar. Compile the ORCA2_SAS_ICE reference configuration. Put the rest of the files in this zenodo archive in the EXP00 directory, except the namelist_cfg_for_DOMAINcfg file which goes into tools/DOMAINcfg along with the grid files to be downloaded later. The files provided include example configuration namelist files namelist_cfg and namelist_ice_cfg. The atmospheric forcing used is the Drakkar forcing set (DFS) version 5.2, year 2008. The atmospheric forcing is interpolated on-the-fly, using the weights files. The weights were calculated using the nemo WEIGHTS tool. For the ocean (bottom) boundary the World Ocean Atlas 2018 multidecadal monthly averages are used. The data is already interpolated onto the ARC36 grid. Interpolation was done using the SOSIE tool. Files provided are monthly averages of sea surface salinity and temperature. Finally, the model grid domain_cfg.nc needs to be created. Download the ORCA36 files from ftp://ftp.mercator-ocean.fr/download/users/cbricaud/BENCH-ORCA36-INPUT.tar.gz, see the ORCA36 demonstrator github page. The necessary files are the coordinates and bathymetry files. To cut out the Arctic domain use ncks -F -d y,7000,,1 in.nc out.nc. Put in tools/DOMAINcfg and use the DOMAINcfg NEMO tool to create the domain_cfg.nc file using the file namelist_cfg_for_DOMAINcfg as namelist_cfg. The resulting file is large (122GB) therefore executing in parallel mode is required. The individual processor files need to be merged into one, use the REBUILD_NEMO tool. Put the resulting domain_cfg.nc file into EXP00 and run NEMO following the instructions. The ARC36 configuration was set up and run on ARCHER2 using 594 NEMO processors and 12 XIOS processors. Animation The animation has been created from daily average of sea ice fraction from the 1/36° Arctic NEMO-SI3 model integrations with the EAP rheology. The animation has started on the 00:00 of the 1st January 2008 and carried out through the January. It shows a limited area of the model domain north of Fram Strait. The lower concentrations correspond to the opening leads, with "blurred" leads and some multiple signatures due to ice displacement and data averaging over 1-day periods. Acknowledgements: EU IMMERSE (Grant agreement ID: 821926), NERC APEAR project (NE/R012865/1, NE/R012865/2, #03V01461), part of the Changing Arctic Ocean programme; EU H2020 COMFORT (no. 820989); NERC PRE-MELT (NE/T000546/1), and LTS-S CLASS (NE/R015953/1). ARCHER UK National Supercomputing and JASMIN facilities. 
Type Of Material Database/Collection of data 
Year Produced 2022 
Provided To Others? Yes  
Impact Improved air to ocean momentum coupling in presence of sea ice cover. 
URL https://zenodo.org/record/6327870
 
Title MEDEA Floe size data 
Description High-resolution MEDEA satellite data have been collected at three sites in the Arctic. This data set spans from 1999 to 2014. Some of the data have been preliminary analysed to derive sea ice floe size (mostly pre-ponding season). Sample floe size data made available to investigators within the project. 
Type Of Material Database/Collection of data 
Year Produced 2019 
Provided To Others? Yes  
Impact Initial data set has been shared, but any notable impact still remains to see in the future. 
 
Title Multi-satellite floe size distribution of Arctic sea ice 2000-2020 
Description This dataset contains the floe size distribution (FSD) data derived from multi-satellite imagery data acquired across the Arctic Ocean. Satellite imagery data includes high-resolution visible images from the USGS Global Fiducials Library (MEDEA), TerraSAR-X/TanDEM-X and Worldview-3 (WV3). The derived data contain floe size (calliper diameter), shape factor, minor/major axis, perimeter and area of the floes. This data set has been used to investigate the characteristics of the FSD during major seasonal evaluation stages of Arctic sea ice floes. The retrieval of the FSD data was done by the University of Huddersfield team. 
Type Of Material Database/Collection of data 
Year Produced 2022 
Provided To Others? Yes  
Impact Used in academic studies in research project. 
URL https://data.bas.ac.uk/full-record.php?id=GB/NERC/BAS/PDC/01650
 
Title Sea ice concentration data produced from a simulation with the sea ice model CICE-CPOM-2019, including a prognostic floe size distribution model to study the Marginal Ice Zone 
Description Monthly mean sea ice concentration output from CICE-CPOM-2019, a stand-alone (fully forced) dynamic-thermodynamic sea ice model, based on CICE model version 5.1.2, but with an added prognostic floe-size distribution, prognostic melt pond model, elastic anisotropic plastic rheology, and a prognostic ocean mixed layer. Details on the forcing and full references concerning the modifications made to the original CICE model can be found in the Readme file. 
Type Of Material Database/Collection of data 
Year Produced 2020 
Provided To Others? Yes  
URL https://researchdata.reading.ac.uk/id/eprint/253
 
Title Sea ice floe size distribution data GFL 
Description Hwang, B. (2020). Sea-ice floe size distribution data derived from USGS GFL high-resolution satellite imagery for the pre-ponding period of 2000-2014 [Data set]. UK Polar Data Centre, Natural Environment Research Council, UK Research & Innovation. https://doi.org/10.5285/FCA1C981-98DC-4F4F-BBDF-822062DF87AC 
Type Of Material Database/Collection of data 
Year Produced 2020 
Provided To Others? Yes  
Impact The sea ice floe size data will be used in this project and provides an important resource for future understanding of the sea ice cover and model development. 
URL https://doi.org/10.5285/FCA1C981-98DC-4F4F-BBDF-822062DF87AC
 
Title UCL CPOM CryoSat2 Polar Ocean Significant Wave Height 2011-2019 
Description We present the significant ocean surface wave heights in the Arctic and Southern Oceans from CryoSat-2 data. We use a semi-analytical model for an idealised synthetic aperture satellite radar or pulse-limited radar altimeter echo power. We develop a processing methodology that specifically considers both the Synthetic Aperture and Pulse Limited modes of the radar that change close to the sea ice edge within the Arctic Ocean. All CryoSat-2 echoes to date were matched by our idealised echo revealing wave heights over the period 2011-2019. Our retrieved data were contrasted to existing processing of CryoSat-2 data and wave model data, showing the improved fidelity and accuracy of the semi-analytical echo power model and the newly developed processing methods. We contrasted our data to in situ wave buoy measurements, showing improved data retrievals in seasonal sea ice covered seas. We have shown the importance of directly considering the correct satellite mode of operation in the Arctic Ocean where SAR is the dominant operating mode. Our new data are of specific use for wave model validation close to the sea ice edge and is available at the link in the data availability statement. NERC NE/R000654/1 Towards a marginal Arctic sea ice cover. 
Type Of Material Database/Collection of data 
Year Produced 2022 
Provided To Others? Yes  
URL https://data.bas.ac.uk/full-record.php?id=GB/NERC/BAS/PDC/01643
 
Title UCL CPOM CryoSat2 derived Dynamic Ocean Topography 2011-2021 
Description The ocean surface height is constantly varying under the effects of gravity, density and the Earth's rotation. Information on the Ocean surface elevation in polar regions is available from the CryoSat2 Radar instrument. We compare ocean surface elevation to a static geoid product (GOCO03s) to give the part of the ocean surface elevation accountable due to surface currents, the Dynamic Ocean Topography (DOT). This measurement is smoothed over 100 km and gives monthly surface currents. NERC NE/R000654/1 Towards a marginal Arctic sea ice cover. 
Type Of Material Database/Collection of data 
Year Produced 2022 
Provided To Others? Yes  
URL https://data.bas.ac.uk/full-record.php?id=GB/NERC/BAS/PDC/01642
 
Description INterview for national press 
Form Of Engagement Activity A press release, press conference or response to a media enquiry/interview
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Media (as a channel to the public)
Results and Impact Aksenov and Luneva gave interview on the topic "When will the ice of the Arctic Ocean melt? Scientists Prediction" to the TASS correspondent Irina Skalina at the ASSW-2019 in Archangelsk. https://tass.ru/v-strane/6925897
Year(s) Of Engagement Activity 2019
URL https://tass.ru/v-strane/6925897