ALBERT

Description: An ocean iodine cycling model is presented, which predicts upper ocean iodine speciation. The model comprises a three-layer advective and diffusive ocean circulation model of the upper ocean, and an iodine cycling model embedded within this circulation. The two primary reservoirs of iodine are represented, iodide and iodate. Iodate is reduced to iodide in the mixed layer in association with primary production, linked by an iodine to carbon (I:C) ratio. A satisfactory model fit with observations cannot be obtained with a globally constant I:C ratio, and the best fit is obtained when the I:C ratio is dependent on sea surface temperature, increasing at low temperatures. Comparisons with observed iodide distributions show that the best model fit is obtained when oxidation of iodide back to iodate is associated with mixed layer nitrification. Sensitivity tests, where model parameters and processes are perturbed, reveal that primary productivity, mixed layer depth, oxidation, advection, surface fresh water flux and the I:C ratio all have a role in determining surface iodide concentrations, and the timescale of iodide in the mixed layer is sufficiently long for non-local processes to be important. Comparisons of the modelled iodide surface field with parameterisations by other authors shows good agreement in regions where observations exist, but significant differences in regions without observations. This raises the question of whether the existing parameterisations are capturing the full range of processes involved in determining surface iodide, and shows the urgent need for observations in regions where there are currently none.

Description: Phytoplankton primary productivity (PP) varies significantly over environmental gradients, particularly in physically‐dynamic systems such as estuaries and coastal seas. During summer, runoff peaks in the Changjiang River driving large environmental gradients in both the Changjiang estuary and adjacent East China Sea (ECS), likely driving significant variability in PP. As satellite models of PP often underperform in coastal waters, we aimed to develop a novel approach for assessing net PP variability in such a dynamic environment. Parallel in situ measurements of Fast Repetition Rate (FRR) fluorometry and carbon (C) uptake rates were conducted for the first time in this region during two summer cruises in 2019 and 2021. A series of 13 C‐incubations ( n = 31) were performed, with measured PP ranging from ∼6 to 1,700 mgC m −3 d −1 . Net PP values were significantly correlated with salinity ( r = 0.45), phytoplankton chlorophyll a (Chl‐ a , r = 0.88), Photosystem II (PSII) functional absorption cross‐section ( σ PSII , r = −0.76) and maximum PSII quantum yield ( F v / F m , r = 0.59). Stepwise regression analysis showed that Chl‐ a and σ PSII were the strongest predictors of net PP. A generalized additive model (GAM) was also used to estimate net PP considering nonlinear effects of Chl‐ a and σ PSII . We demonstrate that GAM outperforms linear modeling approaches in estimating net PP in this study, as evidenced by a lower root mean square error (∼140 vs. 250 mgC m −3 d −1 ). Our novel approach provides a valuable tool to examine carbon cycling dynamics in this important region. Plain Language Summary The East China Sea has a complex current system that creates a highly dynamic physical environment for phytoplankton, particularly during the summer months. Net primary productivity (PP) is highly variable in this region, yet characterizing these spatial patterns in PP is difficult due to the lack of a high‐resolution data collecting method. Therefore, a strong need exists for a quick and easily implemented method for monitoring PP in this dynamic system. Based on parallel measurements of phytoplankton biomass and photophysiology, we present a novel approach that allows us to rapidly and easily assess regional PP at a high resolution. The high data volume potentially afforded by our net PP estimation method could not only contribute to a better understanding of PP variations in such a dynamic environment, but also help fill the large gaps in field data needed for validating satellite‐based PP models. Key Points Parallel in situ measurements of net primary productivity (PP) and Fast Repetition Rate fluorometry were conducted in the Changjiang estuary Productivity was highest at stations with high Chl and low σ PSII , typically located along the Chiangjiang river plume front A generalized additive model was developed to estimate net PP, providing an approach for assessing regional C‐cycling dynamics

Description: Multiyear turbulence measurements from oceanographic moorings in equatorial Atlantic and Pacific cold tongues reveal similarities in deep cycle turbulence (DCT) beneath the mixed layer (ML) and above the Equatorial Undercurrent (EUC) core. Diurnal composites of turbulence kinetic energy dissipation rate, ϵ, clearly show the diurnal cycles of turbulence beneath the ML in both cold tongues. Despite differences in surface forcing, EUC strength and core depth DCT occurs, and is consistent in amplitude and timing, at all three sites. Time-mean values of ϵ at 30 m depth are nearly identical at all three sites. Variations of averaged values of ϵ in the deep cycle layer below 30 m range to a factor of 10 between sites. A proposed scaling in depth that isolates the deep cycle layers and of ϵ by the product of wind stress and current shear collapses vertical profiles at all sites to within a factor of 2.