SIMIP is an endorsed diagnostic MIP for CMIP6 that defines a list of variables to understand the evolution of sea ice in any experiment using the sea ice model as part of CMIP6.
The work of SIMIP is broadly divided into two phases:
1. In the run-up to CMIP6, we have defined a list of sea-ice related variables to be stored from CMIP6 model simulations. These variables allow researchers to analyze the three budgets that govern the evolution of sea ice and its impact on the Earth’s climate system, namely conservation of heat, the momentum balance and tracer conservation. In addition, variables are included that allow for the high frequency analysis of the sea-ice state itself. This list is now part of the official CMIP6 data request.
2. Now that CMIP6 model output has become available, SIMIP has coordinated an overview paper documenting the Arctic sea ice simulation in CMIP6 models, published as SIMIP Community 2020. An overview paper documenting Antarctic sea ice in CMIP6 has also been published as Roach et al. 2020.
SIMIP continues to coordinate analysis using the new SIMIP requested variables through a number of dedicated sub-groups. These include:
– Establish best practices for regridding sea ice model output (Nikolay Koldunov & Daniel Senftleben)
– Develop a long time-series sea ice reanalysis dataset (Axel Schweiger)
– Sea-ice dynamics, in particular analysis of velocity fields, strain variance and maximum shear strength (Bruno Tremblay)
– Spatio-temporal characteristics of sea ice (Ed Blanchard and Alex Jahn).
– Sea ice advance and retreat (Julienne Stroeve and Abigail Smith).
– Radiative feedbacks (Cecilia Bitz and Kyle Armour)
– Non-radiative feedbacks (François Massonnet and Martin Vancoppenolle) .
– Machine learning methods for sea ice analysis, prediction and projection (Neven S. Fuckar)
– Understanding/constraining sea ice volume and surface energy budgets (Ed Blockley)
– Snow on sea ice (Alek Petty)
– Quantifying influence of sea ice internal variability in CMIP5 models (Dirk Olonscheck)
– Use large ensembles to quantify the limitations and opportunities of using short observational sea ice timeseries (Alexandra Jahn)
– Developing sea-ice satellite simulators to provide a new perspective on simulated and observed sea ice (Abigail Smith & Clara Burgard)
If you are interested in joining any of these projects, please get in touch with the leaders of the sub groups as indicated in the brackets.
Note that the deadline for papers to be included in the AR6 report has been extended due to COVID-19. Papers now need to be accepted by January 31 2021. However, the AR6 report authors will need to know about your paper before then to incorporate it into the report if relevant. So please email Dirk a copy of any submitted AR6 relevant sea ice results you expect to be published by the January 31 2021 deadline, so he can make space for those results while revising the sea ice section. Please email all your accepted papers of possible relevance to AR6 to email@example.com as soon as possible, with copy to Dirk to let him now they are now accepted. Confidentiality is ensured.
- List of reported issues related to SIMIP-CMIP6 data
Observation for sea ice model evaluation
SIMIP also works towards a common standard for sea-ice model evaluation. For the time being, we refer to the following to data sources:
• The National Snow and Ice Data Center (NSIDC) maintains a list of sea-ice related observational records that can be used to analyse the performance of sea-ice model simulations: http://nsidc.org/data/sipn/data-sets.html
• The NCAR ClimateDataGuide also features some sea ice products (in particular sea ice concentrations), with expert guidance on their properties for some of these data records: https://climatedataguide.ucar.edu/
SIMIP Mailing List
To subscribe to the SIMIP mailing list, please send an email to the CliC Office (firstname.lastname@example.org).
SIMIP co-chairs: Dirk Notz (MPI Hamburg) and Alexandra Jahn (University of Colorado at Boulder )
SIMIP SSG: Marika Holland, Elizabeth Hunke, François Massonnet, Julienne Stroeve, Bruno Tremblay, Martin Vancoppenolle