Investigation of the Dominant Processes controlling Volume, Heat, and Freshwater Transports through the Bering Strait
Investigation of the Dominant Processes controlling Volume, Heat, and Freshwater Transports through the Bering Strait
Abstract:
The 85-km wide Bering Strait serves as the only connection between the Pacific and Arctic oceans. Recent observations have shown increases in northward volume, heat and freshwater fluxes through this narrow and shallow strait, with implications for the prolongation of the ice-free season and enhancement of nutrient supply to the ecosystems in the Chukchi Sea. Further downstream the increased flux influences watermass transformations, heat and freshwater budgets, and stratification in the upper Arctic Ocean. Thus, quantifying the mechanisms that control the mean and variability of the flow through this vital gateway is important for understanding and predicting changes in the Arctic. Here, to identify these key mechanisms, we use 14 years of mooring observations from the Bering Strait and the non-linear inverse-modeling framework of the Arctic Sub-polar gyre sTate Estimate (ASTE). ASTE is a synthesis of the MITgcm coupled ocean-sea ice model with all available satellite and in-situ observations of sea ice and ocean, including hydrographic and mooring data from the Beaufort Sea and the major Arctic gateways (Fram, Bering, and Davis straits), and is developed using the estimation infrastructure of the ECCO consortium. In ASTE’s optimization mode, after 19 iterations, misfits to ITP hydrography and SSM/I ice concentration have reduced by 80% and 50% respectively. With ASTE as the baseline solution, we use the “adjoint” tool to compute the sensitivity of the model transports of volume and water properties at the Bering Strait to a set of control variables including ocean hydrography and atmospheric forcing. The partition of dominant sensitivities is connected to the data in two ways: the data serve as a guide to the interpretation of the controlling process while the model sensitivity can provide insights into processes which can be further tested with additional observations.