For the first time, the Mercator Ocean Forecasting Center in Toulouse and the ICE-ARC as well as IICWG projects publish together a special issue of the newsletter dedicated to sea ice modelling and data assimilation.
The EU FP7 ICE-ARC Project and the International Ice Charting Working Group (IICWG) held a workshop on Sea-Ice Modelling and Data Assimilation in Toulouse (France) on September 15-16 2014. It was also a key-event for the MyOcean2 project. This special issue reports on a representative selection of works presented at this workshop. The two-day workshop was hosted by Mercator Ocean, one of the ICE-ARC partners, and 38 people from 9 countries all over Europe and Canada attended. The focus was put on research and development related to numerical sea ice analysis and prediction. General topics included:
Sea ice observations and uncertainties
Sea ice data assimilation (methods and results)
Sea ice model parameterizations and coupling to ocean and atmosphere models
Verification approaches for sea-ice analyses and forecasts
The four first papers present the ICE-ARC, ACCESS, PPP/YOPP and IAOOS projects.
ICE-ARC (Ice, Climate, Economics – Arctic Research on Change) is a four year (2014-2018) EU-funded project which brings together physicists, chemists, biologists, economists, and sociologists from 21 institutes from 11 countries across Europe. With a budget of €11.5M, it aims at understanding and quantifying the multiple stresses involved in the change in the Arctic marine environment.
ACCESS is a European Project (2011-2015) supported by the Ocean of Tomorrow call of the European Commission Seventh Framework Programme. Its main objective is to assess climatic change impacts on marine transportation (including tourism), fisheries, marine mammals and the extraction of oil and gas in the Arctic Ocean. ACCESS is also focusing on Arctic governance and strategic policy options.
One of the key elements of the WWRP (WORLD WEATHER RESEARCH PROGRAMME from the WORLD METEOROLOGICAL ORGANIZATION, i.e. WMO) Polar Prediction Project is The Year of Polar Prediction (YOPP) which will consider both the Arctic and Antarctic, and is scheduled to take place from mid 2017 to mid 2019. The intention is to have an extended period of coordinated intensive observational and modelling activities in order to improve polar prediction capabilities on a wide range of time scales. YOPP is a contribution to the hourly to seasonal research component of the WMO Global Integrated Polar Prediction System (GIPPS).
IAOOS (Ice Atmosphere Ocean Observing System, http://www.iaoos-equipex.upmc.fr, http://iaoos.ipev.fr/ ) is a nine-year French-funded project (2011-2019), developed by LOCEAN and LATMOS, which objective is to provide and maintain an integrated observing system over the Arctic Ocean that collects synoptic and near real time information related to the state of the atmosphere, the snow, the sea-ice and the ocean. The IAOOS system involves 15 autonomous platforms operating at any given time in the Arctic Ocean for a total period of 5 years (2015-2019) and collecting synoptic and near real time information related to the state of the lower atmosphere, the sea-ice and the upper ocean.
Then, aspects about operational sea ice forecasting are displayed in the three next papers by Peterson, Buehner et al. and finally in Garric et al. :
Peterson presents the UK Metoffice GloSea5 Coupled Seasonal Forecast System which has sea ice fields initialized with the FOAM ocean and sea ice system with assimilation of SSM/I satellite sea ice concentration observations along with ocean surface and sub-surface observations. He presents the seasonal forecast of September sea ice extent emphasizing the problems associated with too thin initial ice thickness conditions.
Then Buehner et al. display the progress in sea ice data assimilation at Environment Canada. They describe the current configuration of the analysis component of the Environment Canada Regional Ice Prediction System and recent research results from the assimilation of high resolution visible/infrared satellite data.
Finally, Garric et al. describe the recent developments impacting the sea ice in the Mercator Océan French Operational Oceanography Center global ¼° configuration. Two main developments in the NEMO-based model component are tested: (i) the multi-category LIM3 sea ice model and (ii) the comprehensive representation of the freshwater flux from polar ice sheets. The two last papers by Lupkes et al. and Dansereau et al. display specific parameterization aspects:
Lupkes et al. describe a new parameterization of drag coefficients accounting for the impact of edges at ice floes, leads, and melt ponds on momentum transport. The parameterization is evaluated for idealized meteorological forcing in the Siberian and Central Arctic. The distributions of drag coefficients obtained from traditional parameterizations and from the new one show large differences in their test scenario especially in the region south of 80°N.
Dansereau et al. present a new dynamical model built on the elasto-brittle (EB) rheology and which is developed in the context of the operational modeling of sea ice conditions over the Arctic. The EB model is modified and tested in early idealized simulations. Results show that the model is able to reproduce the strong heterogeneity and intermittency and the anisotropy that characterize the deformation of sea ice.
We wish you a pleasant reading,
Laurence Crosnier and Gilles Garric, Editors.
ASSESSING CLIMATE CHANGE IMPACTS ON MARINE ECOSYSTEMS AND HUMAN ACTIVITIES
IN THE ARCTIC OCEAN: THE EUROPEAN ACCESS PROGRAMME (2011-2015)
THE YEAR OF POLAR PREDICTION (YOPP): CHALLENGES AND OPPORTUNITIES
IN ICE-OCEAN FORECASTING
IAOOS (ICE – ATMOSPHERE – ARCTIC OCEAN OBSERVING SYSTEM, 2011-2019)
SEA ICE ANALYSIS AND FORECASTING WITH GLOSEA5
RECENT PROGRESS IN SEA ICE DATA ASSIMILATION AT ENVIRONMENT CANADA
RECENT DEVELOPMENTS IMPACTING THE SEA ICE IN THE MERCATOR OCÉAN GLOBAL ¼° CONFIGURATION
PARAMETERIZATION OF DRAG COEFFICIENTS OVER POLAR SEA ICE FOR CLIMATE MODELS
A MAXWELL-ELASTO-BRITTLE RHEOLOGY FOR SEA ICE MODELING