A Fuzzy-Based Framework for Assessing Uncertainty in Drift Prediction Using Observed Currents and Winds

This paper proposes a fuzzy number—based framework for quantifying and propagating uncertainties through a model for the trajectories of objects drifting at the ocean surface. Various sources of uncertainty that should be considered are discussed. This model is used to explore the effect of parameterizing direct wind drag on the drifting object based on its geometry, and using measured winds to parameterize shear and rotational dynamics in the ocean surface currents along with wave-driven circulation and near-surface wind shear. Parameterizations are formulated in a deterministic manner that avoids the commonly required specification of empirical leeway coefficients. Observations of ocean currents and winds at Ocean Station Papa in the northeast Pacific are used to force the trajectory model in order to focus on uncertainties arising from physical processes, rather than uncertainties introduced by the use of atmospheric and hydrodynamic models. Computed trajectories are compared against observed trajectories from five different types of surface drifters, and optimal combinations of forcing parameterizations are identified for each type of drifter. The model performance is assessed using a novel skill metric that combines traditional assessment of trajectory accuracy with penalties for overestimation of uncertainty. Comparison to the more commonly used leeway method shows similar performance, without requiring the specification of empirical coefficients. When using optimal parameterizations, the model is shown to correctly identify the area in which drifters are expected to be found for the duration of a seven day simulation.

A Scheme for Estimating Time-Varying Wind Stress Drag Coefficient in the Ekman Model with Adjoint Assimilation

In this study, the time-varying wind stress drag coefficient in the Ekman model was inverted by the cubic spline interpolation scheme based on the adjoint method. Twin experiments were carried out to investigate the influences of several factors on inversion results, and the conclusions were (1) the inverted distributions with the cubic spline interpolation scheme were in good agreement with the prescribed distributions of the wind stress drag coefficients, and the cubic spline interpolation scheme was superior to direct inversion by the model scheme and Cressman interpolation scheme; (2) the cubic spline interpolation scheme was more advantageous than the Cressman interpolation scheme even if there is moderate noise in the observations. The cubic spline interpolation scheme was further validated in practical experiments where Ekman currents and wind speed derived from mooring data of ocean station Papa were assimilated. The results demonstrated that the variation of the time-varying wind stress drag coefficient with time was similar to that of wind speed with time, and a more accurate inversion result could be obtained by the cubic spline interpolation scheme employing appropriate independent points. Overall, this study provides a potential way for efficient estimation of time-varying wind stress drag coefficient.

Integrating CVMix into GOTM (v6.0): a consistent framework for testing, comparing, and applying ocean mixing schemes

The General Ocean Turbulence Model (GOTM) is a one-dimensional water column model, including a set of state-of-the-art turbulence closure models, and has widely been used in various applications in the ocean modeling community. Here, we extend GOTM to include a set of newly developed ocean surface vertical mixing parameterizations of Langmuir turbulence via coupling with the Community Vertical Mixing Project (CVMix). A Stokes drift module is also implemented in GOTM to provide the necessary ocean surface waves information to the Langmuir turbulence parameterizations, as well as to facilitate future development and evaluation of new Langmuir turbulence parameterizations. In addition, a streamlined workflow with Python and Jupyter notebooks is also described, enabled by the newly developed and more flexible configuration capability of GOTM. The newly implemented Langmuir turbulence parameterizations are evaluated against theoretical scalings and available observations in four test cases, including an idealized wind-driven entrainment case and three realistic cases at Ocean Station Papa, the northern North Sea, and the central Baltic Sea, and compared with the existing general length scale scheme in GOTM. The results are consistent with previous studies. This development extends the capability of GOTM towards including the effects of ocean surface waves and provides useful toolsets for the ocean modeling community to further study the effects of Langmuir turbulence in a broader scope.

Integrating CVMix into GOTM (v6.0): A consistent framework for testing, comparing, and applying ocean mixing schemes

The General Ocean Turbulence Model (GOTM) is a one-dimensional water column model including a set of state-of-the-art turbulence closure models, and has widely been used in various applications in the ocean modeling community. Here we extend GOTM to include a set of newly developed ocean surface vertical mixing parameterizations of Langmuir turbulence via coupling with the Community Vertical Mixing Project (CVMix). A Stokes drift module is also implemented in GOTM to provide the necessary ocean surface waves information to the Langmuir turbulence parameterizations, as well as to facilitate future development and evaluation of new Langmuir turbulence parameterizations. In addition, a streamlined workflow with Python and Jupyter Notebook is also described, enabled by the newly developed and more flexible configuration capability of GOTM. The newly implemented Langmuir turbulence parameterizations are evaluated against theoretical scalings and available observations in four test cases, including an idealized wind-driven entrainment case and three realistic cases at ocean station Papa, the northern North Sea and the central Gotland Sea, and compared with the existing General Length Scale scheme in GOTM. The results are consistent with previous studies. This development extends the capability of GOTM towards including the effects of ocean surface waves and provides useful toolsets for the ocean modeling community to further study the effects of Langmuir turbulence in a broader scope.

An operational overview of the EXport Processes in the Ocean from RemoTe Sensing (EXPORTS) Northeast Pacific field deployment

The goal of the EXport Processes in the Ocean from RemoTe Sensing (EXPORTS) field campaign is to develop a predictive understanding of the export, fate, and carbon cycle impacts of global ocean net primary production. To accomplish this goal, observations of export flux pathways, plankton community composition, food web processes, and optical, physical, and biogeochemical (BGC) properties are needed over a range of ecosystem states. Here we introduce the first EXPORTS field deployment to Ocean Station Papa in the Northeast Pacific Ocean during summer of 2018, providing context for other papers in this special collection. The experiment was conducted with two ships: a Process Ship, focused on ecological rates, BGC fluxes, temporal changes in food web, and BGC and optical properties, that followed an instrumented Lagrangian float; and a Survey Ship that sampled BGC and optical properties in spatial patterns around the Process Ship. An array of autonomous underwater assets provided measurements over a range of spatial and temporal scales, and partnering programs and remote sensing observations provided additional observational context. The oceanographic setting was typical of late-summer conditions at Ocean Station Papa: a shallow mixed layer, strong vertical and weak horizontal gradients in hydrographic properties, sluggish sub-inertial currents, elevated macronutrient concentrations and low phytoplankton abundances. Although nutrient concentrations were consistent with previous observations, mixed layer chlorophyll was lower than typically observed, resulting in a deeper euphotic zone. Analyses of surface layer temperature and salinity found three distinct surface water types, allowing for diagnosis of whether observed changes were spatial or temporal. The 2018 EXPORTS field deployment is among the most comprehensive biological pump studies ever conducted. A second deployment to the North Atlantic Ocean occurred in spring 2021, which will be followed by focused work on data synthesis and modeling using the entire EXPORTS data set.

Concentrations, ratios, and sinking fluxes of major bioelements at Ocean Station Papa

Fluxes of major bioelements associated with sinking particles were quantified in late summer 2018 as part of the EXport Processes in the Ocean from RemoTe Sensing (EXPORTS) field campaign near Ocean Station Papa in the subarctic northeast Pacific. The thorium-234 method was used in conjunction with size-fractionated (1–5, 5–51, and >51 μm) concentrations of particulate nitrogen (PN), total particulate phosphorus (TPP), biogenic silica (bSi), and particulate inorganic carbon (PIC) collected using large volume filtration via in situ pumps. We build upon recent work quantifying POC fluxes during EXPORTS. Similar remineralization length scales were observed for both POC and PN across all particle size classes from depths of 50–500 m. Unlike bSi and PIC, the soft tissue–associated POC, PN, and TPP fluxes strongly attenuated from 50 m to the base of the euphotic zone (approximately 120 m). Cruise-average thorium-234-derived fluxes (mmol m–2 d–1) at 120 m were 1.7 ± 0.6 for POC, 0.22 ± 0.07 for PN, 0.019 ± 0.007 for TPP, 0.69 ± 0.26 for bSi, and 0.055 ± 0.022 for PIC. These bioelement fluxes were similar to previous observations at this site, with the exception of PIC, which was 1 to 2 orders of magnitude lower. Transfer efficiencies within the upper twilight zone (flux 220 m/flux 120 m) were highest for PIC (84%) and bSi (79%), followed by POC (61%), PN (58%), and TPP (49%). These differences indicate preferential remineralization of TPP relative to POC or PN and larger losses of soft tissue relative to biominerals in sinking particles below the euphotic zone. Comprehensive characterization of the particulate bioelement fluxes obtained here will support future efforts linking phytoplankton community composition and food-web dynamics to the composition, magnitude, and attenuation of material that sinks to deeper waters.

Biogenic sinking particle fluxes and sediment trap collection efficiency at Ocean Station Papa

Comprehensive field observations characterizing the biological carbon pump (BCP) provide the foundation needed to constrain mechanistic models of downward particulate organic carbon (POC) flux in the ocean. Sediment traps were deployed three times during the EXport Processes in the Ocean from RemoTe Sensing campaign at Ocean Station Papa in August–September 2018. We propose a new method to correct sediment trap sample contamination by zooplankton “swimmers.” We consider the advantages of polyacrylamide gel collectors to constrain swimmer influence and estimate the magnitude of possible trap biases. Measured sediment trap fluxes of thorium-234 are compared to water column measurements to assess trap performance and estimate the possible magnitude of fluxes by vertically migrating zooplankton that bypassed traps. We found generally low fluxes of sinking POC (1.38 ± 0.77 mmol C m–2 d–1 at 100 m, n = 9) that included high and variable contributions by rare, large particles. Sinking particle sizes generally decreased between 100 and 335 m. Measured 234Th fluxes were smaller than water column 234Th fluxes by a factor of approximately 3. Much of this difference was consistent with trap undersampling of both small (<32 μm) and rare, large particles (>1 mm) and with zooplankton active migrant fluxes. The fraction of net primary production exported below the euphotic zone (0.1% light level; Ez-ratio = 0.10 ± 0.06; ratio uncertainties are propagated from measurements with n = 7–9) was consistent with prior, late summer studies at Station P, as was the fraction of material exported to 100 m below the base of the euphotic zone (T100, 0.55 ± 0.35). While both the Ez-ratio and T100 parameters varied weekly, their product, which we interpret as overall BCP efficiency, was remarkably stable (0.055 ± 0.010), suggesting a tight coupling between production and recycling at Station P.

Organic Matter Composition at Ocean Station Papa Affects Its Bioavailability, Bacterioplankton Growth Efficiency and the Responding Taxa

The bioavailability of organic matter (OM) to marine heterotrophic bacterioplankton is determined by both the chemical composition of OM and the microbial community composition. In the current study, changes in OM bioavailability were identified at Ocean Station Papa as part of the 2018 Export Processes in the Ocean from Remote Sensing (EXPORTS) field study. Removal rates of carbon (C) in controlled experiments were significantly correlated with the initial composition of total hydrolyzable amino acids, and C removal rates were high when the amino acid degradation index suggested a more labile composition. Carbon remineralization rates averaged 0.19 ± 0.08 μmol C L–1 d–1 over 6–10 days while bacterial growth efficiencies averaged 31 ± 7%. Amino acid composition and tandem mass spectrometry analysis of compound classes also revealed transformations to a more degraded OM composition during experiments. There was a log2-fold increase in the relative abundances of 16S rDNA-resolved bacterioplankton taxa in most experiments by members of the Methylophilaceae family (OM43 genus) and KI89A order. Additionally, when OM was more bioavailable, relative abundances increased by at least threefold for the classes Bacteroidetes (Flavobacteriaceae NS2b genus), Alphaproteobacteria (Rhodobacteraceae Sulfitobacter genus), and Gammaproteobacteria (Alteromonadales and Ectothiorhodospiraceae orders). Our data suggest that a diverse group of bacterioplankton was responsible for removing organic carbon and altering the OM composition to a more degraded state. Elevated community diversity, as inferred from the Shannon–Wiener H index, may have contributed to relatively high growth efficiencies by the bacterioplankton. The data presented here shed light on the interconnections between OM bioavailability and key bacterioplankton taxa for the degradation of marine OM.