Amélie Bouchat

and 17 more

As the sea-ice modeling community is shifting to advanced numerical frameworks, developing new sea-ice rheologies, and increasing model spatial resolution, ubiquitous deformation features in the Arctic sea ice are now being resolved by sea-ice models. Initiated at the Forum for Arctic Modelling and Observational Synthesis (FAMOS), the Sea Ice Rheology Experiment (SIREx) aims at evaluating current state-of-the-art sea-ice models using existing and new metrics to understand how the simulated deformation fields are affected by different representations of sea-ice physics (rheology) and by model configuration. Part I of the SIREx analysis is concerned with evaluation of the statistical distribution and scaling properties of sea-ice deformation fields from 35 different simulations against those from the RADARSAT Geophysical Processor System (RGPS). For the first time, the Viscous-Plastic (and the Elastic-Viscous-Plastic variant), Elastic-Anisotropic-Plastic, and Maxwell-Elasto-Brittle rheologies are compared in a single study. We find that both plastic and brittle sea-ice rheologies have the potential to reproduce the observed RGPS deformation statistics, including multi-fractality. Model configuration (e.g. numerical convergence, atmospheric forcing, spatial resolution) and physical parameterizations (e.g. ice strength parameters and ice thickness distribution) both have effects as important as the choice of sea-ice rheology on the deformation statistics. It is therefore not straightforward to attribute model performance to a specific rheological framework using current deformation metrics. In light of these results, we further evaluate the statistical properties of simulated Linear Kinematic Features (LKFs) in a SIREx Part II companion paper.

Nils Christian Hutter

and 16 more

Michael Steele

and 2 more

The Forum for Arctic Modeling and Observational Synthesis (FAMOS) is a project funded by the U.S. National Science Foundation to advance the science of Arctic physical, chemical, and biological marine modeling. It is further designed to foster collaboration with marine observationalists and those who wish to work with Arctic marine modelers, e.g., atmospheric scientists, glaciologists, hydrologists, terrestrial ecologists. FAMOS holds an annual workshop of ~120 people and spawns numerous collaborative projects that have filled three special JGR collections and more. Attendance at FAMOS workshops is a mix of senior researchers and early-career scientists. The final three days of the 4-day workshop consist of AGU-style short talks, break-out sessions, and panel discussions. But the first day is devoted to the FAMOS School, wherein ~ 40 graduate students, postdocs, and early career polar scientists attend 5 longer-format (~ 35 minute) lectures. Discussion sessions are especially highlighted, and senior scientists in attendance are not allowed to speak. A “wild card” after-lunch session is devoted to various topics, e.g., outreach, alternate career choices, and geoengineering. The day ends with a working dinner in which further discussions and networking occur. School attendees are typically gender-balanced and have included students from non-traditional Arctic countries (e.g., Iran, Brazil, Egypt). The FAMOS School has been very successful, as measured by participant feedback and by the number of applications received (i.e., more than we can accommodate each year). A key outcome has been to bolster confidence in the early-career students, so that they are more willing to actively participate in the following days’ activities. This is also enhanced by naming them as session and discussion chairs, and by suppressing the tendency of senior scientists to “hog the microphone.” Discussion at FAMOS workshops has significantly influenced the focus of many PhD projects and spawned a number of student-led research papers. A main lesson learned from the FAMOS School is that just inviting students to a workshop or into a research community is not enough: One must also take active steps to foster confidence and give them a voice. The good news is that this really works.