Ed Blanchard (ed[@]atmos.washington.edu) and Alex Jahn (ajahn[@]ucar.edu).
The scientific question(s) that will be studied:
-Why do different models show large differences in persistence (with each other and observations)?
-Does persistence affect general sea ice predictability/likelihood of RILES in 21C sims?
The process(es) or feedback(s) that will be investigated
-What is the contribution of dynamics vs thermodynamics processes to ice loss and persistence and how do they compare between models?
-Is it mainly a sea ice component issue, or do atmos/ocean play a large role?
The type of analyses that will be conducted (tools)
-Break down contributions to pan-Arctic persistence from regional seas. Perhaps models agree in regional persistence, but each contribute different to total (or conversely they are also different in regional persistence)?
-What is model persistence/variability of Arctic atmos/ocean, and does it help explain inter-model differences in sea ice persistence
-Break down ice thickness variability into dynamic and thermodynamic driven components
-Are RILES dependent on a particular region (i.e., do they always happen in same region)?


• Persistence of Arctic sea ice: Spread in persistence of sea ice in GCMs explains model spread in seasonal sea ice predictability. Furthermore, GCMs are found to show more persistent than observations
Paper: Blanchard-Wrigglesworth E, and Bushuk, M. Robustness of Arctic sea-ice predictability in GCMs, 2019, Climate Dynamics, 52(9-10), pp.5555-5566, https://doi.org/10.1007/s00382-018-4461-3

• Spatial and temporal pattern of sea ice internal variability: Internal variability does not uniformly affects Arctic sea ice in time and space.
Paper: England, M., A. Jahn, and L. Polvani, 2019: Nonuniform Contribution of Internal Variability to Recent Arctic Sea Ice Loss. J. Climate, 32, 4039–4053, https://doi.org/10.1175/JCLI-D-18-0864.1