| Summary: | An overarching goal of ATLAS is to investigate the sensitivity of North Atlantic Ocean ecosystems to basin-scale physical processes. This report examines relationships between four pertinent climate indices and key physical variables using both output from a high-resolution ocean model and an observational dataset. After describing long-term mean conditions and determining seasonal cycles, we use a composite approach to create mean conditions for high and low states of each climate index. The Atlantic Meridional Overturning Circulation (AMOC) shows cooler bottom conditions around the boundaries of the western subpolar gyre during a high state, which may be linked to more energetic conditions in this area. The North Atlantic Oscillation (NAO) shows clear anti-correlation between European and North American Shelves: during a high NAO, bottom conditions on the eastern boundary are warmer and more saline, whilst western areas are cooler and fresher. Bottom kinetic energy also shows an east-west disconnect, with less energetic conditions in the eastern overflow currents during a high NAO and a corresponding increase in western overflows. The most striking feature in the Subpolar Gyre (SPG) composites, is a strong area of cooler bottom conditions around the northern and western boundaries of the subpolar North Atlantic during a high SPG. In contrast, during a high Atlantic Multi-decadal Oscillation (AMO), bottom conditions in the same areas are warmer and more saline although areas deeper than around 2000 m in the North Atlantic are cooler and fresher. This is the first study to show that climate indices are associated with spatially-coherent changes in bottom conditions across the North Atlantic region. Although changes are relatively small, due to the multi-annual nature of the climate indices any changes may persist for several years. As such, vulnerable sessile ecosystems may be exposed to sustained changes in mean conditions, with this deviation in the baseline also altering the likelihood of extreme events such as mean heatwaves. Thus, a thorough knowledge of natural variability is essential for the understanding of deep-sea ecosystems, predicting their response to future changes, and evaluation of management frameworks.
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