Date of Award

Fall 2023

Document Type

Open Access Thesis

Department

Marine Science

First Advisor

Subrahmanyam Bulusu

Abstract

The Northwest (NW) Atlantic is one of the fastest warming regions in the global ocean and in the recent decade has experienced several extreme temperature events. These extreme anomalous temperature events are known as Marine Heatwaves (MHWs), which are forced by a variety of physical processes that affect the heat source and sink of the water column. These MHWs have been increasing globally in duration and frequency due to anthropogenic warming, and have increased ecological damage seen in mass mortality events of economically viable species. Within the NW Atlantic, several key processes encourage the formation of MHWs, such as the Jet Stream (JS), the North Atlantic Oscillation (NAO), the Gulf Stream (GS), and the GS anticyclonic eddies (AEs) that are shed. Over the past decade, these processes have aided in the formation and intensification of MHW events in the NW Atlantic in four major MHW years: 2012, 2016, 2017, and 2020. These years are characterized as having a large number of days throughout the year experiencing a MHW event and having high MHW temperature intensity. This research aims to increase the understanding of the physical processes and characteristics of the NW Atlantic during these MHW years. Atmospheric parameters such as anomalous JS position, Geopotential height, and NAO are used to understand Sea Surface Temperature (SST) and Sea Surface Salinity (SSS) variability during the aforementioned four major MHW years. Eddy tracking and detection using altimetry identifies AEs during peak MHW months and their interactions with surface processes that modulate MHWs. GLORYS12V1 reanalysis is used to describe the impact of MHWs on subsurface temperature and salinity variability during MHW active years. The interplay between ocean advection and atmospheric-based forcings is found to be unique overall across the four years, despite large-scale similarities regarding JS and GS dynamics. This analysis extends the understanding of MHW drivers and increases our ability to better model and forecast extreme events.

Rights

© 2024, Lydia Rose Duncan Sims

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