24 Low-Level Jets in the Autumnal Marginal Ice Zone: Sensitivity to Ice-Edge Forcings

Monday, 24 July 2017
Kona Coast Ballroom (Crowne Plaza San Diego)
Mimi Hughes, NOAA, Boulder, CO; and P. O. G. Persson, A. Solomon, and J. Intrieri

Low-level jets (LLJs) transport moisture, impact surface fluxes, and ultimately impact sea ice evolution in the marginal ice zone (MIZ) of the Arctic Ocean. We conduct numerical model experiments with the Weather Research and Forecasting (WRF) model to investigate LLJs in the MIZ of the Beaufort Sea north of Alaska for two case studies during the Sea State campaign of October 2015: one very shallow, off-ice LLJ and one slightly deeper along-ice-edge LLJ. Both were associated with significant thermal gradients near the edge of the advancing, thin, first-year ice. We first compare the model control simulations to unique observations taken from the ship Sikuliaq to test WRF’s ability to represent these two different LLJs, including their thermal and kinematic structure. We use the model simulations to help discriminate between spatial and temporal changes in the observations. Then we conduct sensitivity experiments with WRF to test the role(s) different forcing mechanisms play in LLJ evolution. In particular, we eliminate the temperature gradient across the sea ice edge in idealized experiments to test what role shallow baroclinicity due to the temperature gradient induced by the presence of sea ice plays compared to the baroclinicity caused by the passage of transient cyclones and anti-cyclones. Again using idealized experiments, we then explore the sensitivity of the formation and strength of the LLJ to the strength and ice-edge-relative orientation of the synoptic-scale airflow. We also explore the relationship of the LLJ with the mixed layer depth and the sensitivity of its representation to model grid spacing. This study is part of a larger project producing experimental 10-day forecasts during the sea ice freeze up period with a coupled regional atmosphere-ocean-sea ice model, RASM-ESRL, and our results will help inform future developments of the RASM-ESRL forecasting system.
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