PhD Thesis - Thermohaline staircases in the Arctic Ocean: Detection, evolution, and interaction

Abstract: Thermohaline staircases consist of a series of horizontal, well-mixed layers, each on the order of a meter thick, separated by thin interfaces, across which temperature and salinity make abrupt jumps. While they have been consistently observed several hundred meters below the surface of the Arctic Ocean for over fifty years, little is known about their long-term evolution. Such stratification structures affect the propagation of internal waves and, because of an effect called internal gravity wave tunnelling, interactions between internal waves and staircases can be complex. This thesis presents a novel method of detecting thermohaline staircase layers in observations, analyzes their evolution on a decadal scale, and examines their interactions with internal waves.

Inspired by the patterns made by observations of thermohaline staircases in temperature-salinity space, I develop a novel detection method. Using the Hierarchical Density-Based Spatial Clustering of Applications with Noise algorithm, I find I can detect and connect staircase layers across datasets of hydrographic profiles from the Canada Basin in the Arctic Ocean. This offers an advantage over previous detection methods which treat each profile individually as, here, the sprawling horizontal nature of the layers can be analyzed.

Using this clustering method, I identify layers in the Beaufort Gyre Region which span over 1000 km horizontally and persist for nearly two decades. In addition to reproducing many results from previous studies, I find the layers to be evolving in time. The layers are sinking at approximately the same rate as the overall downwelling in the region. I also find that layers in the upper staircase are warming while layers near the bottom are cooling.

I develop a set of numerical experiments to examine the interactions between internal waves and idealized staircase stratification structures. For structures with one layer, I find the transmission of waves decreases monotonically as the layer thickness gets larger relative to the wavelength. With multiple layers present, I find peaks in transmission for particular ratios of thickness to wavelength, the patterns of which become more complex as more layers are added. I also reproduce the results of a laboratory experiment, finding the same pattern of reflection and transmission of waves.

Schee, M.G. (2024) “Thermohaline staircases in the Arctic Ocean: Detection, evolution, and interaction,” University of Toronto Doctoral Thesis, URI: hdl.handle.net/1807/140974

Unsupervised clustering identifies thermohaline staircases in the Canada Basin of the Arctic Ocean

Abstract: Thermohaline staircases are a widespread stratification feature that impacts the vertical transport of heat and nutrients and are consistently observed throughout the Canada Basin of the Arctic Ocean. Observations of staircases from the same time period and geographic region form clusters in temperature-salinity (T-S) space. Here, for the first time, we use an automated clustering algorithm called the Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN), to detect and connect individual well-mixed staircase layers across profiles from Ice-Tethered Profilers (ITPs). Our application only requires an estimate of the typical layer thickness and expected salinity range of staircases. We compare this method to two previous studies that used different approaches to detect layers and reproduce several results, including the mean lateral density ratio 𝑅𝐿 and that the difference in salinity between neighboring layers is a magnitude larger than the salinity variance within a layer. We find that we can accurately and automatically track individual layers in coherent staircases across time and space between different profiles. In evaluating the algorithm's performance, we find evidence of different physical features, namely splitting or merging layers and remnant intrusions. Further, we find a dependence of 𝑅𝐿 on pressure, whereas previous studies have reported constant 𝑅𝐿. Our results demonstrate that clustering algorithms are an effective and parsimonious method of identifying staircases in ocean profile data.

Schee, M.G., E. Rosenblum, J.M. Lilly, and N. Grisouard (2024) “Unsupervised clustering identifies thermohaline staircases in the Canada Basin of the Arctic Ocean,” Environmental Data Science, 3:e13, 1-19, DOI: 10.1017/eds.2024.13

Two-dimensional Numerical Simulations of Mixing under Ice Keels

Starting in 2021, I assisted Rosalie M. Cormier and Sam De Abreu in developing simulations in Dedalus to analyze mixing under ice keels, eventually resulting in the following article.

Abstract: Changes in sea ice conditions directly impact the way the wind transfers energy to the Arctic Ocean. The thinning and increasing mobility of sea ice is expected to change the size and speed of ridges on the underside of ice floes, called ice keels, which cause turbulence and impact upper-ocean stratification. However, the effects of changing ice keel characteristics on below-ice mixing are difficult to determine from sparse observations and have not been directly investigated in numerical or laboratory experiments. Here, for the first time, we examine how the size and speed of an ice keel affect the mixing of various upper-ocean stratifications using 16 two-dimensional numerical simulations of a keel moving through a two-layer flow. We find that the irreversible ocean mixing and the characteristic depth over which mixing occurs each vary significantly across a realistic parameter space of keel sizes, keel speeds, and ocean stratifications. Furthermore, we find that mixing does not increase monotonically with ice keel depth and speed, but instead depends on the emergence and propagation of vortices and turbulence. These results suggest that changes to ice keel speed and depth may have a significant impact on below-ice mixing across the Arctic Ocean, and highlight the need for more realistic numerical simulations and observational estimates of ice keel characteristics.

De Abreu, S., R.M. Cormier, M.G. Schee, V.E. Zemskova, E. Rosenblum, and N. Grisouard (2024) Two-dimensional Numerical Simulations of Mixing under Ice Keels, The Cryosphere, 18, 3159–3176, DOI: 10.5194/tc-18-3159-2024

Poster at Ocean Sciences Meeting 2020 - San Diego

In February 2020, I presented my poster entitled “Idealized Numerical Modeling of Internal Wave Propagation Through Density Staircases” at the 2020 Ocean Sciences Meeting. The poster explained the project described in my Master’s Report along with some extensions. I show a side-by-side comparison of the experimental results of Ghaemsaidi et al. 2016 and my direct numerical simulation in Dedalus for internal waves propagating through one or two well-mixed layers. I also explain the technique of complex demodulation which allows the separation of upward and downward propagating waves. Using this technique, I will be able to compare the properties of the incident, reflected, and transmitted waves.