One pathway of the biological pump that remains largely unquantified in many export models is the active transport of carbon from the surface ocean to the mesopelagic by zooplankton diel vertical migration (DVM). Here, we develop a simple representation of zooplankton DVM and implement it in a global export model as a thought experiment to illustrate the effects of DVM on carbon export and mesopelagic biogeochemistry. The model is driven by diagnostic satellite measurements of net primary production, algal biomass, and phytoplankton size structure. Due to constraints on available satellite data, the results are restricted to the latitude range from 60°N to 60°S. The modeled global export flux from the base of the euphotic zone was 6.5 PgC/year, which represents a 14% increase over the export flux in model runs without DVM. The mean (± standard deviation, SD) proportional contribution of the DVM‐mediated export flux to total carbon export, averaged over the global domain and the climatological seasonal cycle, was 0.16 ± 0.04 and the proportional contribution of DVM activity to total respiration within the twilight zone was 0.16 ± 0.06. Adding DVM activity to the model also resulted in a deep local maximum in the oxygen utilization profile. The model results were most sensitive to the assumptions for the fraction of individuals participating in DVM, the fraction of fecal pellets produced in the euphotic zone, and the fraction of grazed carbon that is metabolized.

The Mid‐Atlantic Bight (MAB) hosts a large and productive marine ecosystem supported by high phytoplankton concentrations. Enhanced surface chlorophyll concentrations at the MAB shelf‐break front have been detected in synoptic measurements, yet this feature is not present in seasonal means. To understand why, we assess the conditions associated with enhanced surface chlorophyll at the shelf break. We employ in‐situ and remote sensing data, and a 2‐dimensional model to show that Ekman restratification driven by upfront winds drives ephemerally enhanced chlorophyll concentrations at the shelf‐break front in spring. Using 8‐day composite satellite‐measured surface chlorophyll concentration data from 2003–2020, we constructed a daily running mean (DRM) climatology of the cross‐shelf chlorophyll distribution for the northern MAB region. While the frontal enhancement of chlorophyll is apparent in the DRM climatology, it is not captured in the seasonal climatology due to its short duration of less than a week. In‐situ measurements of the frontal chlorophyll enhancement reveal that chlorophyll is highest in spring when the shelf‐break front slumps offshore from its steep wintertime position causing restratification in the upper part of the water column. Several restratification mechanisms are possible, but the first day of enhanced chlorophyll at the shelf break corresponds to increasing upfront winds, suggesting that the frontal restratification is driven by offshore Ekman transport of the shelf water over the denser slope water. The 2‐dimensional model shows that upfront winds can indeed drive Ekman restratification and alleviate light limitation of phytoplankton growth at the shelf‐break front.

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Over the past century, global average sea surface temperature (SST) has increased by 0.7°C (Bindoff et al., 2007). This surface warming has been accompanied by a steady increase in the heat content of the upper 2,000 m of the water column since at least the 1950s, with accelerating trends since 1991 (Cheng et al., 2019). Earth system model (ESM) projections predict additional increases in SST in the 21st century under all Representative Concentration Pathways (Bopp et al., 2013). In addition to increasing mean conditions, anthropogenic warming has caused unprecedented marine heatwaves in recent years, which are predicted to increase in both intensity and frequency (Frölicher et al., 2018;Laufkötter et al., 2020).Rising ocean temperatures are expected to have significant impacts on pelagic plankton communities, which form the basis of marine food webs (Benedetti et al., 2021). The relatively short time scale of large spatial scale (e.g., satellite) observations makes it difficult to test this prediction because of challenges distinguishing between