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1. Dynamics of simulated Atlantic upwelling annual cycle in CMIP5 models: UPWELLING ANNUAL CYCLE

   https://doi.org/10.1002/2017JC012781  

   Wang, Li-Chiao ; Jin, Fei-Fei ; Wu, Chau-Ron ( July 2017 , Journal of Geophysical Research: Oceans)
2. Southern Ocean Upwelling and the Marine Iron Cycle

   https://doi.org/10.1029/2020GL090737  

   Weber, Thomas ( October 2020 , Geophysical Research Letters)

   The iron (Fe) supply to phytoplankton communities in the Southern Ocean surface exerts a strong control on oceanic carbon storage and global climate. Hydrothermal vents are one potential Fe source to this region, but it is not known whether hydrothermal Fe persists in seawater long enough to reach the surface before it is removed by particle scavenging. A new study (Jenkins, 2020,https://doi.org/10.1029/2020GL087266) fills an important gap in this puzzle: a helium‐3 mass balance model is used to show that it takes ~100 yr for deep hydrothermally influenced waters to upwell to the surface around Antarctica. However, estimates of Fe scavenging time scales range from tens to hundreds of years and must be more narrowly constrained to fully resolve the role of hydrothermal Fe in the ocean's biological pump.

    

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3. The Annual Salinity Cycle of the Denmark Strait Overflow

   https://doi.org/10.1029/2021JC018139  

   Opher, J. G. ; Brearley, J. A. ; Dye, S. R. ; Pickart, R. S. ; Renfrew, I. A. ; Harden, B. E. ; Meredith, M. P. ( April 2022 , Journal of Geophysical Research: Oceans)
4. The annual salinity cycle of the Denmark Strait Overflow

   Opher, J.G. ( January 2021 , Journal of geophysical research)
5. Modeling the annual cycle of daily Antarctic sea ice extent

   https://doi.org/10.5194/tc-14-2159-2020  

   Handcock, Mark S. ; Raphael, Marilyn N. ( January 2020 , The Cryosphere)

   Abstract. The total Antarctic sea ice extent (SIE) experiences a distinct annual cycle, peaking in September and reaching its minimum in February. In thispaper we propose a mathematical and statistical decomposition of this temporal variation inSIE. Each component is interpretable and, when combined,gives a complete picture of the variation in the sea ice. We consider timescales varying from the instantaneous and not previously defined to themulti-decadal curvilinear trend, the longest. Because our representation is daily, these timescales of variability give precise information about thetiming and rates of advance and retreat of the ice and may be used to diagnose physical contributors to variability in the sea ice. We definea number of annual cycles each capturing different components of variation, especially the yearly amplitude and phase that are major contributors toSIE variation. Using daily sea ice concentration data, we show that our proposed invariant annual cycle explains 29 % more of the variation indaily SIE than the traditional method. The proposed annual cycle that incorporates amplitude and phase variation explains 77 % more variation thanthe traditional method. The variation in phase explains more of the variability in SIE than the amplitude. Using our methodology, we show that theanomalous decay of sea ice in 2016 was associated largely with a change of phase rather than amplitude. We show that the long term trend inAntarctic sea ice extent is strongly curvilinear and the reported positive linear trend is small and dependent strongly on a positive trend thatbegan around 2011 and continued until 2016. 

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