The trajectory of Arctic climate system change has exhibited highly nonlinear behavior, as manifested by the increased frequency of occurrence of extreme events superimposed on a long‐term trend towards a warmer mean state. The most recent, striking extreme events include occurrences of record minima of sea ice extent in the summers of 2007, 2012, and 2016, and record maxima of surface air temperatures in the winters of 2015/16 and 2017/18. However, Arctic climate change studies have predominantly focused on the long‐term changes or trends using monthly, seasonal, or annual mean data. But extreme events generally occur intermittently for periods from days to several months as outliers of the long‐term trends. Even for the extreme events that occur across longer time periods, monthly or seasonal mean data may not be able to resolve the underlying physics supporting their rapid development. It therefore still remains unclear why these extreme events occur, what their multi-scale driving mechanisms are, and where the source of their predictability exists. The time is now right to address outstanding questions about the fundamental physical processes underlying extreme events in the Arctic and their prediction and predictability.
Recently two comprehensive field campaigns have been either completed or launched to measure physical and biogeochemical processes of the coupled Arctic climate system: The Year of Polar Prediction (YOPP) field observations, and the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) field campaign. Also, the Coupled Model Intercomparison Project Phase 6 (CMIP6) and the Polar Amplification Model Intercomparison Project (PAMIP) modeling experiment results have become available. PAMIP was proposed and designed by the U.S. CLIVAR Arctic‐midlatitude working group and extensively developed at an AGCI workshop in 2017. All of these provide systematic and comprehensive new data sets for conducting new research and advancing progress on the topic.
Workshop Topic (s):
- Climate Variability and Change (including Climate Modeling)
- Human Contributions & Responses