Why the Mixed Layer Depth Matters When Diagnosing Marine Heatwave Drivers Using a Heat Budget Approach - Elzahaby, Youstina; Schaeffer, Amandine; Roughan, Moninya; Delaux, Sébastien (Frontiers in Climate, 2022)
Marine heatwaves (MHWs) are extreme warming events that can have damaging consequences for marine ecosystems and local economies. The primary drivers of these events have been frequently studied using an upper ocean heat budget. However, various surface mixed layer (SML) depths have been used with little attention paid to the impact of SML depth on heat budget term estimates. We analyse MHW drivers in two dynamically contrasting regions off the east coast of Australia (East Australian Current extension) and the west coast of New Zealand over a 30-year period (1985-2014, inclusive). We compare the magnitude of the air-sea heatflux and advection terms in a volume-averaged heat budget using three different SML depth estimates. We show that the depth of the SML over which the heat budget is calculated has direct consequences for the identification of the dominant drivers of marine heatwaves. The air-sea heatflux term is amplified when the SML depth is underestimated and dampened when overestimated. The magnitude of the advection term in various SML depth estimates is dependent on the barotropic or baroclinic structure of the currents. We show that the impact on MHW driver classification is both temporally and regionally dependent. Generally, a deep SML estimate results in more MHWs being classified as advection and less classified as air-sea heatflux driven. However, during the cooler months, a shallow estimate produces the opposite pattern and to varying degrees depending on the region's dynamics. Use of daily and spatially variable SML depth in a heat budget calculation allows comparisons between regions with different dynamics influencing the mixed layer depth. These results show that when using a heat budget approach to explore marine heatwaves over extended time and space (e.g. regions and seasons), it is imperative to consider the temporal and spatial variability in the SML depth.