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Abstract The spatiotemporal evolution of marine heatwaves (MHWs) is explored using a tracking algorithm called Ocetrac that provides the objective characterization of MHW spatiotemporal evolution. Candidate MHW grid points are defined in detrended gridded sea temperature data using a seasonally varying temperature threshold. Identified MHW points are collected into spatially distinct objects using edge detection with weak sensitivity to edge detection and size percentile threshold criteria at each time step. Ocetrac then uses 3D connectivity to determine if these objects are part of the same event, but Ocetrac only defines the full MHW event after all time steps have been processed, limiting its use in predictability studies. Here, Ocetrac is applied to monthly satellite sea surface temperature data from September 1981 through January 2021. The resulting MHWs are characterized by their intensity, duration, and total area covered. The global analysis shows that MHWs in the Gulf of Maine and Mediterranean Sea are spatially isolated, while major MHWs in the Pacific and Indian Oceans are connected in space and time. The largest and most long-lasting MHW using this method lasts for 60 months from November 2013 to October 2018, encompassing previously identified MHW events including those in the northeast Pacific (2014–15), the Tasman Sea (2015–16, 2017–18), and the Great Barrier Reef (2016). Significance StatementThis study introduces Ocetrac, a method to track the spatiotemporal evolution of marine heatwaves (MHWs). It is applied to satellite sea surface temperature data from 1981 to 2021. The method objectively identifies and tracks MHWs in space and time while allowing for splitting and merging. The resulting MHWs are characterized by intensity, duration, and total area covered. Marine heatwaves can have significant ecological consequences, including biodiversity loss and mortality, geographical shifts, and range reductions in marine species and community structure changes when physiological thresholds are exceeded. This results in both ecological and economic impacts. Ocetrac provides a method of tracking the space and time evolution of MHWs that can provide a visualization that demonstrates the global impact of these events. 

Abstract Microstructure observations in the Pacific cold tongue reveal that turbulence often penetrates into the thermocline, producing hundreds of watts per square meter of downward heat transport during nighttime and early morning. However, virtually all observations of this deep-cycle turbulence (DCT) are from 0°, 140°W. Here, a hierarchy of ocean process simulations, including submesoscale-permitting regional models and turbulence-permitting large-eddy simulations (LES) embedded in a regional model, provide insight into mixing and DCT at and beyond 0°, 140°W. A regional hindcast quantifies the spatiotemporal variability of subsurface turbulent heat fluxes throughout the cold tongue from 1999 to 2016. Mean subsurface turbulent fluxes are strongest (∼100 W m −2 ) within 2° of the equator, slightly (∼10 W m −2 ) stronger in the northern than Southern Hemisphere throughout the cold tongue, and correlated with surface heat fluxes ( r 2 = 0.7). The seasonal cycle of the subsurface heat flux, which does not covary with the surface heat flux, ranges from 150 W m −2 near the equator to 30 and 10 W m −2 at 4°N and 4°S, respectively. Aseasonal variability of the subsurface heat flux is logarithmically distributed, covaries spatially with the time-mean flux, and is highlighted in 34-day LES of boreal autumn at 0° and 3°N, 140°W. Intense DCT occurs frequently above the undercurrent at 0° and intermittently at 3°N. Daily mean heat fluxes scale with the bulk vertical shear and the wind stress, which together explain ∼90% of the daily variance across both LES. Observational validation of the scaling at 0°, 140°W is encouraging, but observations beyond 0°, 140°W are needed to facilitate refinement of mixing parameterization in ocean models. Significance Statement This work is a fundamental contribution to a broad community effort to improve global long-range weather and climate forecast models used for seasonal to longer-term prediction. Much of the predictability on seasonal time scales is derived from the slow evolution of the upper eastern equatorial Pacific Ocean as it varies between El Niño and La Niña conditions. This study presents state-of-the-art high-resolution regional numerical simulations of ocean turbulence and mixing in the eastern equatorial Pacific. The results inform future planning for field work as well as future efforts to refine the representation of ocean mixing in global forecast models. 

In nutrient-limited conditions, phytoplankton growth at fronts is enhanced by winds, which drive upward nutrient fluxes via enhanced turbulent mixing and upwelling. Hence, depth-integrated phytoplankton biomass can be 10 times greater at isolated fronts. Using theory and two-dimensional simulations with a coupled physical-biogeochemical ocean model, this paper builds conceptual understanding of the physical processes driving upward nutrient fluxes at fronts forced by unsteady winds with timescales of 4–16 days. The largest vertical nutrient fluxes occur when the surface mixing layer penetrates the nutricline, which fuels phytoplankton in the mixed layer. At a front, mixed layer deepening depends on the magnitude and direction of the wind stress, cross-front variations in buoyancy and velocity at the surface, and potential vorticity at the base of the mixed layer, which itself depends on past wind events. Consequently, mixing layers are deeper and more intermittent in time at fronts than outside fronts. Moreover, mixing can decouple in time from the wind stress, even without other sources of physical variability. Wind-driven upwelling also enhances depth-integrated phytoplankton biomass at fronts; when the mixed layer remains shallower than the nutricline, this results in enhanced subsurface phytoplankton. Oscillatory along-front winds induce both oscillatory and mean upwelling. The mean effect of oscillatory vertical motion is to transiently increase subsurface phytoplankton over days to weeks, whereas slower mean upwelling sustains this increase over weeks to months. Taken together, these results emphasize that wind-driven phytoplankton growth is both spatially and temporally intermittent and depends on a diverse combination of physical processes. 

When phytoplankton growth is limited by low nutrient concentrations, full-depth-integrated phytoplankton biomass increases in response to intermittent mixing events that bring nutrient-rich waters into the sunlit surface layer. Here it is shown how oscillatory winds can induce intermittent nutrient entrainment events and thereby sustain more phytoplankton at fronts in nutrient-limited oceans. Low-frequency (i.e., synoptic to planetary scale) along-front wind drives oscillatory cross-front Ekman transport, which induces intermittent deeper mixing layers on the less dense side of fronts. High-frequency wind with variance near the Coriolis frequency resonantly excites inertial oscillations, which also induce deeper mixing layers on the less dense side of fronts. Moreover, we show that low-frequency and high-frequency winds have a synergistic effect and larger impact on the deepest mixing layers, nutrient entrainment, and phytoplankton growth on the less dense side of fronts than either high-frequency winds or low-frequency winds acting alone. These theoretical results are supported by two-dimensional numerical simulations of fronts in an idealized nutrient-limited open-ocean region forced by low-frequency and high-frequency along-front winds. In these model experiments, higher-amplitude low-frequency wind strongly modulates and enhances the impact of the lower-amplitude high-frequency wind on phytoplankton at a front. Moreover, sensitivity studies emphasize that the synergistic phytoplankton response to low-frequency and high-frequency wind relies on the high-frequency wind just below the Coriolis frequency. 

Abstract Storms deepen the mixed layer, entrain nutrients from the pycnocline, and fuel phytoplankton blooms in midlatitude oceans. However, the effects of oceanic submesoscale (0.1–10 km horizontal scale) physical heterogeneity on the physical‐biogeochemical response to a storm are not well understood. Here, we explore these effects numerically in a Biogeochemical Large Eddy Simulation (BLES), where a four‐component biogeochemical model is coupled with a physical model that resolves some submesoscales and some smaller turbulent scales (2 km to 2 m) in an idealized storm forcing scenario. Results are obtained via comparisons to BLES in smaller domains that do not resolve submesoscales and to one‐dimensional column simulations with the same biogeochemical model, initial conditions, and boundary conditions but parameterized turbulence and submesoscales. These comparisons show different behaviors during and shortly after the storm. During the storm, resolved submesoscales double the vertical nutrient flux. The vertical diffusivity is increased by a factor of 10 near the mixed layer base, and the mixing‐induced increase in potential energy is double. Resolved submesoscales also enhance horizontal nutrient and phytoplankton variance by a factor of 10. After the storm, resolved submesoscales maintain higher nutrient and phytoplankton variance within the mixed layer. However, submesoscales reduce net vertical nutrient fluxes by 50% and nearly shut off the turbulent diffusivity. Over the whole scenario, resolved submesoscales double storm‐driven biological production. Current parameterizations of submesoscales and turbulence fail to capture both the enhanced nutrient flux during the storm and the enhanced biological production. 

Abstract Global warming may modify submesoscale activity in the ocean through changes in the mixed layer depth (MLD) and lateral buoyancy gradients. As a case study we consider a region in the NE Atlantic under present and future climate conditions, using a time‐slice method and global and nested regional ocean models. The high resolution regional model reproduces the strong seasonal cycle in submesoscale activity observed under present‐day conditions. Focusing on the well‐resolved winter months, in the future, with a reduction in the MLD, there is a substantial reduction in submesoscale activity, an associated decrease in kinetic energy (KE) at the mesoscale, and the vertical buoyancy flux induced by submesoscale activity is reduced by a factor of 2. When submesoscale activity is suppressed, by increasing the parameterized lateral mixing in the model, the climate change induces a larger reduction in winter MLDs while there is less of a change in KE at the mesoscale. A scaling for the vertical buoyancy flux proposed by (Fox‐Kemper et al., 2008; doi:10.1175/2007JPO3792.1) based on the properties of mixed layer instability (MLI), is found to capture much of the seasonal and future changes to the flux in terms of regional averages as well as the spatial structure, although it over predicts the reduction in the flux in the winter months. The vertical buoyancy flux when the mixed layer is relatively shallow is significantly greater than that given by the scaling based on MLI, suggesting during these times other processes (besides MLI) may dominate submesoscale buoyancy fluxes.