Melanie Chanona

and 4 more

Quantifying mixing rates in the Arctic Ocean is critical to our ability to predict heat flux, freshwater distribution, and circulation. However, turbulence measurements in the Arctic are sparse, and cannot characterize the high spatiotemporal variability typical of ocean mixing. Using year-round temperature and salinity data from Ice-Tethered Profiler (ITP) instruments between 2004 and 2018, we apply a finescale parameterization to obtain pan-Arctic estimates of turbulent dissipation and mixing rates at unprecedented space-time resolution. Building on previous work that used ITP data to identify double-diffusive staircases and analyze the associated convective mixing, we apply the finescale parameterization only where these step-like thermohaline structures are not present and mixing is expected to be internal wave-dominated. We find that the inferred wave-driven dissipation and mixing rates are generally low, but highly variable in both space and time, displaying significant regional differences between the shelves and central basins, as well as a small seasonal cycle. We detect no statistically significant interannual trend in mixing rate estimates over the period examined, with the exception of a small increase in the Canada Basin immediately below the mixed layer. The joint consideration of turbulent dissipation rates and stratification imply varied Arctic Ocean mixing regimes, which are most often not appropriately characterized as isotropic turbulence. Where justified, we infer turbulent heat fluxes out of the Atlantic Water layer that are mostly small, but also exhibit a distinct regional dependence.

Hayley Dosser

and 3 more

From 2014 to at least 2018, ecosystem health in the eastern boundary upwelling system along the west coast of North America was significantly impacted by a combination of a marine heatwave known as The Blob and an El Niño event, as well as by ongoing climate change. At the northern limit of this upwelling system, in Queen Charlotte Sound on the highly productive central coast of British Columbia, we have demonstrated that changing conditions on the continental shelf and in coastal waters may be skillfully predicted based on observed open-ocean and large-scale atmospheric conditions on seasonal to interannual timescales. In this work, we build on our understanding of this predictability by presenting a statistical model that relates physical and biogeochemical ocean properties in this region to conditions at and beyond the shelf break and large-scale forcing metrics. The model is based on statistical relationships developed using a multi-decadal archive of hydrographic and biogeochemical data in combination with high-temporal-resolution mooring records collected in Queen Charlotte Sound, and is supported by a conceptual understanding of the upwelling and downwelling regimes in this region. We next use the model to examine specifically how the arrival of The Blob and the subsequent El Niño modified ocean conditions on the continental shelf during both upwelling and downwelling, including impacts on nutrient concentrations, dissolved oxygen levels, stratification, and warming. Our results suggest it may be possible to predict changes in this upwelling system caused by future anomalous events and climate change using readily available large-scale data products such as the Argo dataset and NOAA Upwelling Index.