In this study we introduce a pair of idealized tracers to quantify how changes in physical advection and mixing under climate change affect the nutrient supply, new production, and particulate export rates. The low cost and simplicity of these tracers allows us to explore the sensitivity of the model biogeochemistry, and in particular its response to a changing physical environment, to the choice of model parameters. Using CESM2.1 with active ocean and ice only, at nominal one-degree resolution, under initial conditions and forcing representative of 2000 and 2100, our idealized nutrient and particulate are within the spread of nitrate and export from CMIP5 models. The simple form of the tracers allows us to identify the physical controls on the changing rates of supply, production, and export throughout the year, which together form the different seasonal cycles. We find that the ocean basins with the largest changes in the seasonal cycle over the 21st century are the North Atlantic, the Arctic, and the eastern tropical Pacific. We present results comparing the controls across basins, focusing on shifts in the timing of deepening mixed layers and maximum production rate in the northern North Atlantic through the Arctic, and changes in the spatial and temporal patterns of vertical advective exchange in the tropics and subtropics of the Pacific and Indian Oceans. In both cases we discuss how much these changes depend on the biogeochemical model parameter values.

Accurate forecasts of total water level (i.e., a combination of tides, surge, wave and freshwater components) is imperative for stakeholders and federal agencies to adopt strategies for potential flooding hazards in a timely-manner. In that regard, the National Water Center in partnership with several federal agencies have been providing forecast services to the United States since 2017. However, the complex interaction of dynamical forcing conditions among other factors (e.g., anthropogenic activities, land cover change, etc.) reduce the National Water Model’s (NWM) ability to provide accurate Total Water Level (TWL) prediction in Coastal Transition Zones (CTZs). In this study, we use an existing inland to coastal model coupling framework (i.e., NWM, HWRF, Delft3D-FM and ADCIRC) to analyze the influence of dynamical forcing conditions (e.g., local wind, surge and river discharge) on TWL prediction in Delaware Bay, USA. In addition, we quantify the contribution of each component in TWL for Hurricanes Isabel and Sandy based on a systematic set of scenarios generated in Delft3D-FM. It is revealed that in both hurricanes, storm surge-induced water level is the main contributor to TWL followed by astronomical tides. River discharge induced-water level is rather small compared to the other components. Analyses of spatial variation of TWL as well as temporal variation of error in prediction suggest that wind forcing plays a key role in TWL prediction followed by river discharge. Moreover, our results suggest that the wind module of Delft3D-FM greatly improves the model performance at TWL peak when compared to the other forcing.

Seagrasses provide a multitude of ecosystem services: they alter water flow, cycle nutrients, stabilize sediments, support the food web structure, and provide a critical habitat for many animals. However, due to threats to seagrass meadows and their associated ecosystems, these habitats are declining globally. Acoustical methods can be a powerful remote sensing tool to efficiently monitor seagrass meadows, alleviating the problem of space and time aliasing associated with traditional spot measurements. The acoustic field is highly sensitive to the presence of gas bubbles in liquids, which result in acoustic dispersion, absorption, and scattering. The biological processes and physical characteristics associated with seagrass result in trapped gases, which are present in the aerenchyma of seagrass leaves, roots, and rhizomes as well as in freely floating bubbles in the water. To investigate the use of acoustical methods to monitor ecosystem health, an experiment was conducted in the Lower Laguna Madre where the seabed was covered by a dense growth of Thalassia testudinum. During the experiment, a combustive sound source was used to produce broadband signals at ranges of 25 m to 400 m from an array of receivers. The data were collected over a period of one day to assess the diurnal effects of photosynthetic activity on the acoustic measurements. An additional set of measurements were collected in a nearby sparsely vegetated site to provide a baseline data set for comparison. Supporting measurements of irradiance, dissolved oxygen, and water temperature were acquired at the experiment site. The acoustic data were analyzed for the purposes of inferring environmental parameters in the seagrass meadow, including the gas volume present in the environment. An effective medium model for gas bubbles in liquids was used to characterize the frequency-dependency of sound speed and attenuation in the waveguide. [Work sponsored by ARL:UT IR&D and ONR.]

Increasing extent and duration of seasonally ice-free area in the western Arctic Ocean suggests increased air-sea coupling, specifically fluxes of momentum and heat between the lower atmosphere and the upper ocean. The dependence of these fluxes on ice concentration and its dynamical characteristics is still uncertain. As part of the Stratified Ocean Dynamics of the Arctic (SODA) project, year-long time series of upper-ocean velocity profiles were obtained across a range of ice conditions and are used to infer momentum fluxes. We consider the structure of observed current profiles as a function of sea state and ice cover. During the summer and in open water with minimal stratification, the wind forcing is in local equilibrium with surface gravity waves, and there is a direct transfer of momentum from the atmosphere to the upper ocean. The presence of ice modifies the momentum budget through both the inclusion of ice-atmosphere and ice-ocean stresses, and by damping short surface gravity waves and thus changing the surface roughness that the atmosphere acts upon. Ice presence is also associated with increased near-surface stratification, which can act to decouple the sub-surface ocean from atmospheric forcing. Our observations show frequent decoupling of a thin surface layer (<10 m depth), including case studies in which the relatively fresh surface waters formed by “ice puddles” have entirely different motion from the relatively salty water a few meters below. Ice formation in the fall affects both the ocean stratification and the ice characteristics, leading to competing effects affecting momentum transfer. Initial results across the annual cycle are presented.

In this study we introduce a pair of idealized tracers to quantify how changes in physical advection and mixing under climate change affect the nutrient supply, new production, and particulate export rates. The low cost and simplicity of these tracers allows us to explore the sensitivity of the model biogeochemistry, and in particular its response to a changing physical environment, to the choice of model parameters. Using CESM2.1 with active ocean and ice only, at nominal one-degree resolution, under initial conditions and forcing representative of 2000 and 2100, our idealized nutrient and particulate are within the spread of nitrate and export from CMIP5 models. The simple form of the tracers allows us to identify the physical controls on the changing rates of supply, production, and export throughout the year, which together form the different seasonal cycles. We find that the ocean basins with the largest changes in the seasonal cycle over the 21st century are the North Atlantic, the Arctic, and the eastern tropical Pacific. We present results comparing the controls across basins, focusing on shifts in the timing of deepening mixed layers and maximum production rate in the northern North Atlantic through the Arctic, and changes in the spatial and temporal patterns of vertical advective exchange in the tropics and subtropics of the Pacific and Indian Oceans. In both cases we discuss how much these changes depend on the biogeochemical model parameter values.

Journals, funding agencies, and researchers are more frequently expecting manuscripts to include links to shared research data. Effective data sharing requires that data be findable, accessible, interoperable, and reusable (FAIR), and is thus predicated on establishing a common understanding on how to communicate: data exchange standards, common data formats, controlled vocabularies, and a communal data repository. When conducting research, we still communicate in shorthand that is effective for everyone on the team who understands our context, but is lost when data is shared in the absence of that context. “Water temperature” means only one thing to my research team, yet can mean dozens of things outside of that context. Data sharing is thus an exercise in sharing not just the data, which is typically readily available, but also the context of that data, which requires additional effort. This effort is one of the barriers to sharing data. We’ll describe an alternative model for accepting data to a repository: the immediate ingestion of data regardless of its metadata quality, then behavioural nudges and crowd-sourcing features that ensure this data meets appropriate standards prior to publication. We’ll show a work-in-progress prototype software tool that supports this alternative model, capable of accepting and standardizing a research data set to use CF conventions and ISO 8601 dates.

The advocacy activities necessary to sustain healthy watersheds and improve impaired ones ultimately rely on the democratic process, and therefore depend on a public that values our coastal resources and understands the role that water quality plays in maintaining that value. We contend that an opportunity exists to improve the temporal and spatial density of monitoring by reducing the cost of collecting measurements, while simultaneously fostering an informed and invested public. We envision a distributed water quality monitoring sensor network, composed of low-cost ($1000-$2000) profiling devices we call TideRiders, built and operated by private citizens and local educational organizations and supported by an institution-hosted centralized data and control portal. The TideRider concept engages the public not just in the collection of data but also in the building, deployment, operation, and recovery of these robot sensors. TideRiders will carry a suite of basic water quality instrumentation (temperature, conductivity, and dissolved oxygen), transmit data and accept commands over the cellular network, and can sample surface and bottom waters by surfacing and submerging on a programmable schedule. Operators will harness tidal currents to move their TideRiders deliberately around an embayment, essentially by surfacing in a favorable tide and anchoring on the bottom in an adverse tide. A network of TideRiders deployed in tidally-dominated estuaries like Buzzards Bay and Narragansett Bay could provide basic water quality data at several-hour intervals for weeks at a time by “virtually mooring” in center-bay locations that are otherwise only accessible by boat and therefore typically sampled less frequently than shore stations. We present preliminary field results from a series of prototypes designed and built by students. The prototype devices utilize a novel low-cost semi-passive shallow-water buoyancy engine and were constructed for less than $1000 in parts.

In high-latitude environments such as the Arctic Ocean, phytoplankton growth is strongly constrained by light availability. Because light penetration into the upper ocean is attenuated by snow and ice cover, it was generally believed until recently that phytoplankton growth was limited to areas of open water, with negligible growth under the ice. However, under-ice phytoplankton blooms have been reported multiple times over the past several decades [e.g. Fukuchi et al. (1989); Legendre, Ingram, and Poulin (1989)]. In July 2011, Arrigo et al. (2012) observed a massive phytoplankton bloom beneath sea ice in the Chukchi Sea. Observational evidence suggests that this bloom was not an isolated case, and that under-ice blooms maybe widespread on Arctic continental shelves (Arrigo et al., 2014; Lowry, van Dijken, & Arrigo, 2014). Arrigo and van Dijken (2011) estimate the total primary production north of the Arctic Circle to be 438 +/- 21.5 Tg C yr -1. However, due to observational limitations, this estimate did not include under sea ice production. Therefore, an open question remains: How important are under-ice phytoplankton blooms to the total Arctic primary production? RASM is a high-resolution, fully-coupled, regional model with a domain encompassing the entire marine cryosphere of the Northern Hemisphere, including the major inflow and outflow pathways, with extensions into North Pacific and Atlantic oceans. The components of RASM include: atmosphere, sea ice, ocean, biogeochemical, and land hydrology (Maslowski et al. 2012, Roberts et al. 2015, DuVivier et al. 2016, Hamman et al. 2016, Hamman et al. 2017, Cassano et al. 2017). The ocean BGC component in RASM is a medium-complexity Nutrients-Phytoplankton-Zoo-plankton-Detritus (NPZD) model (Jin et al. 2018). The model has three phytoplankton categories: diatoms, small phytoplankton and diazotrophs. RASM results show that under-ice pelagic chl-a and primary production values can at times be very high, particularly during the spring and early summer. Our numerical model results produce a mean of 495 Tg C yr -1 north of the Arctic Circle during 1980-1998 (and 507 Tg C yr -1 during 1980-2018). We also see an increase in primary production over the last several decades. This increase is attributed to the reduced sea ice cover, which increases light availability to the upper ocean. We conclude that under-sea-ice pelagic primary production makes up a large fraction of the total production and cannot be considered negligible.

Ocean primary production constitutes approximately half of global biospheric production, affecting both fisheries productivity and biogeochemical cycling. Although climate change is predicted to affect the ocean's biological productivity, the extent of the global impact is poorly quantified. Assessing changes in the ocean biosphere using remote sensing data is challenged by the relatively short length of the observational record, restricting our ability to disentangle fluctuations in internal variability from forced anthropogenic trends. Additionally, the majority of ocean circulation models with embedded biogeochemistry do not skillfully predict observational records of ocean chlorophyll at ocean time series locations. To overcome these limitations, we have constructed a synthetic ensemble of global ocean chlorophyll concentration. By employing statistical resampling methods to the SeaWiFS and MODIS ocean color datasets and creating surrogate climate modes of ENSO and PDO, we quantify the range of internal climate variability in the 20 year observational record and create multiple alternate realities for the possible evolution of the ocean biosphere over time. Our synthetic ensemble can be used for a variety of purposes, including diagnosing patterns of internal variability and emergence of anthropogenic trends in observed chlorophyll, and validating Earth system model representation of such variability.

Diurnal tidal currents are the dominate contributors to diapycnal mixing in many regions along the pathways for warm Atlantic Water (AW) circulating within the Arctic Ocean along the continental slope. This mixing diffuses AW heat and salt into the cooler and fresher surroundings, including the upper ocean where ocean heat fluxes play a role in the stability of the ice pack. The strongest diurnal currents are associated with topographically-trapped vorticity waves, which are sensitive to stratification and mean flow. In models, these waves are also sensitive to choices for forcing and geometry. Sensitivity to background conditions implies that tidal currents and mixing will change as the Arctic evolves towards a new climate state. Here, as a first step towards understanding how diurnal tidal currents might change in a future Arctic Ocean, we describe results from a suite of high-resolution (dx=2 km) 2-D and 3-D models for Arctic diurnal tides, focusing on their currents at locations along the AW pathways. We first demonstrate that accurate representation of barotropic diurnal tides requires forcing with both open boundary conditions and the direct potential tide. Next, we use 3-D models with realistic, ocean background stratification and mean flow to describe the annual cycle of depth-averaged diurnal tidal currents. Finally, we investigate the baroclinic structure of diurnally forced waves including the generation of harmonics (semidiurnal and higher) that can contribute to mixing within the water column. Our results show that tides should be explicitly included in ocean and coupled predictive models for the Arctic to represent the feedbacks between tidal energetics and ocean mean state via mixing.

Zooplankton and micronekton are key links in tropical Pacific food webs, which include tuna as top-level predators. Zooplankton and micronekton vertically migrate to deeper depths to avoid visual predators, including tuna, during the day and then return to shallower depths to feed at night. Vertical migration depths vary spatially in the tropical Pacific and are correlated with oxygen, light, and temperature. El Niño-Southern Oscillation (ENSO) causes vertical shifts in the thermocline and oxycline. The accessibility of prey during the day should therefore vary interannually depending on the ENSO phase. We use available acoustic doppler current profiler (ADCP) data from cruises within the tropical Pacific between 1990 and 2019 to investigate the timescales and potential drivers of variability in zooplankton and micronekton vertical distributions in this region. Preliminary results suggest that ENSO-associated variations in vertical migration depths differ across the Exclusive Economic Zones (EEZs) of small island nations in the tropical Pacific. These variations are compared to temperature and oxygen-driven tuna vertical habitat variability to assess potential impacts on tuna.

Since its formation in 2015, the National Centers for Environmental Information (NCEI) has used disparate, legacy systems spread across several IT networks of the National Environmental Satellite, Data, and Information Service (NESDIS) to fulfill its data-stewardship functions. As part of its modernization and consolidation of these functions, NCEI implemented Common Ingest as the functional component that ingests approximately 200 data streams every month into its enterprise archival information system. In parallel, NESDIS completed the Secure Ingest Gateway Project (SIGP), a pilot project to establish standard-enterprise secure methods for NESDIS and the rest of the National Oceanic and Atmospheric Administration (NOAA) to receive data in a cloud environment from their external partners. SIGP is now transitioning to operations as the Operational Secure Ingest Service (OSIS), which will be the on-ramp to NCEI’s “Common Ingest” functionality when it too moves to the cloud. In addition, this ingest function will populate and use a cloud-based metadata catalog, which will be the beating heart of the NESDIS and NCEI information systems in the cloud environment. The vision is to scale their ingest of environmental data to keep pace with its ever increasing volume, veracity, variety, and velocity. In this presentation to the ocean data community, the authors describe NESDIS and NCEI’s challenges and successes with the implementation of the ingest function of their archival information system in a cloud environment.

Tropical cyclones (TCs) are perhaps the most powerful example of air-sea interaction. Although TC-induced energy exchange has been hypothesized to be a signicant agent of ocean heat transport under past and current climates, the margin of uncertainty in both observation and TC-permitting conventional climate models confounds these evaluations. In this study, we introduce a novel approach using simpler climate models, where land geometry is represented by a single strip of pole-to-pole continent, known as the Ridge conguration in previous work. This idealized design is known to represent the large-scale features of atmosphere-ocean general circulation and energy transport, serving to facilitate the physical interpretation of TC-induced energy exchange in the ocean, and its potential role in ocean heat transport. Under the framework of the Community Earth System Model, we congure an idealized, fully coupled Ridge model using Community Atmosphere Model version 4 (CAM4) and Modular Ocean Model version 6 (MOM6) at low horizontal resolutions. After obtaining a quasi-equilibrium climate, we then use the climatological sea surface temperature for forcing a CAM4-only, decadal simulation at TC-permitting resolution. Preliminary results indicate that the formation of a warm pool on the western side of the bounded ocean basin creates a more favorable environment for TC genesis than the cooler eastern side, analogous to observed TC climatology in the Pacic. By comparing ocean-only simulations with and without TCs in the atmospheric forcing, we evaluate the signicance of ocean heat transport attributable to TCs in the idealized atmosphere-ocean climate system. The insights gained through the process- based investigation of TC-induced air-sea interaction in this simpler model framework contribute to an improved understanding of the energetics of TCs, and their role in the climate system.

Ocean processes in the Southwest North Atlantic (SWNA) play an important role in long-term earth and ocean climate change. This region is also a resource-rich coastal zone with abundant fisheries and other material assets. Combined, the previously released NCEI Northwest Atlantic (NWA) regional climatology (RC) and newly developed SWNA RC provide complete coverage of the Gulf Stream system, which is the critical element of northward heat transport and the Atlantic Meridional Overturning Circulation. The SWNA RC is a collection of high-resolution quality-controlled temperature and salinity fields on standard depth levels from the sea surface to 4,900 m depth. This RC is based on temperature and salinity observations from the 2018 release of the World Ocean Database. The coverage includes the years 1955 to 2017 by annual, seasonal, and monthly fields for the entire period, as well as for each of the six decades. All fields computed on three horizontal grids: 1°x1°, 1/4°x1/4°, and 1/10°x1/10° degree. The SWNA RC is instrumental for assessing ocean climate changes in this region of the North Atlantic Ocean over the 1955-2017 time period and can be used in various climate studies, environmental research projects, and related applications.

The Amazon River discharges more than 200,000 m3 s-1 into the Western Tropical Atlantic Ocean from May to June. The low salinity surface plume extends more than 1800 km from the mouth and covers an area greater than 1 million square kilometers. We hypothesize that the plume exhibits distinct microbial community assemblages driven by plume age, nutrient supply, and light availability. We collected samples for nutrients and flow-cytometry measurements to investigate the spatial variability of the cyanobacteria Prochlorococcus spp. and Synechococcus spp., picoeukaryotes, and heterotrophic bacteria. Overall the surface salinity of the water we sampled ranged from 15.5 ppt at the southernmost station to 36.3 ppt in the open ocean station. The surface nitrate and soluble reactive phosphorus concentrations ranged from below detection limit to 3.3 µM and 2 µM, respectively. Generally, in the freshest surface plume waters (15-28 ppt) we found the highest abundances of Synechococcus spp., picoeukaryotes, and hetrotrophic bacteria with little or no Prochlorococcus spp. In the transition of surface salinities from 28 ppt to 32 ppt, a population of Prochlorococcus spp. began to form below the surface plume while Synechococcus spp. abundances at the surface remained unchanged and picoeukaryotes, and heterotrophic bacteria abundances decreased. As the surface salinity climbed over 32 ppt, the Prochlorococcus spp. abundance was uniformly high throughout the euphotic zone. On the other hand, as surface salinities increased over 32 ppt Synechococcus spp. abundances at the surface gradually decreased, while picoeukaryote and hetrotrophic bacterial abundances remained constant. We will discuss changes in the microbial community composition as a function of nutrient and light availability, as well as plume age in the Amazon Plume-Ocean continuum in both surface and deep chlorophyll maximum assemblages.

Zooplankton is a key ecological component of aquatic ecosystems. Studying and monitoring the spatial distribution and temporal variability of zooplankton is vital to understanding their community composition and its relation to climate change. Manual methods for analysis are time-consuming and have limitations on the ecological studies of these organisms. Real-time, fast and accurate in situ zooplankton detection and classification remains a challenge. Currently, research focuses on automating zooplankton image classification using handcrafted computer vision techniques and neural network based approaches [1,2]. Most recent approaches adopt deep learning techniques for identification and classification [3,4]. In this paper, we propose the use of Fast Region-based Convolutional Neural Network (Faster R-CNN) for fast and accurate in situ detection and classification of zooplankton groups in underwater images. Faster R-CNN is a region-based object detection framework which combines region proposal and classification in a unified network [5]. Indeed, end-to-end learning reduces overall training time and increases the accuracy of the network. Faster R-CNN has shown state-of-the-art performance on benchmarks such as ImageNet and VOC [6,7]. We perform the experiments over ZooScan, Kaggle, WHOI-Plankton datasets [8,9,10]. We evaluate the performance of our proposed approach of in situ zooplankton identification and classification in terms of detection speed and mean Average Precision (mAP). In addition, we compare the performance of the proposed method with popular detectors such as Single Shot Multibox Detector (SSD) and You Only Look Once (YOLOv3) to demonstrate its efficacy at processing noisy underwater images [11,12]. Results of our evaluation recommend the use of Faster R-CNN for real-time zooplankton image analysis. The ultimate goal of this work is to automate the current manual process exerted in the lab while improving the accuracy and processing speed of an otherwise time-consuming task for marine biologists.

Eddies have two distinct properties known as eddy advection (K_GM ) and eddy diffusion (K_iso). These are parameterized by Gent-McWilliams [1990] (K_GM ) and Redi [1982] (K_iso), respectively, in low to moderate resolution global ocean models. Both processes play an active part in the uptake of tracers such as CO_2 and CFCs. The advective role of eddies is associated with slumping of isopycnals, whereas the diffusive role is associated with the down-gradient diffusion [Lee et al., 2007]. In this work we investigate, for the first-time, which eddy process plays a dominant role in controlling tracer distribution in models. The model (pyOM2) used in this work is a coarse-resolution (2°x 2°) global ocean model [Eden et al., 2014]. We use a suite of nine different experiments, each with different K_GM and K_iso values. An idealised passive tracer is introduced at the surface of the ocean after the model is well equilibrated and it evolves for 100 years. We found on decadal time scales eddy diffusion and eddy advection both play equally important roles in controlling tracer distribution. However, on the time scale of hundred years or more eddy advection dominates over eddy diffusion. Small K_GM values set the isopycnal slopes to be steep, which allows the tracer to easily penetrate the deep ocean along isopycnals. On the contrary, large K_GM values flatten the isopycnals and therefore tracer only weakly penetrates the deep ocean. Near Antarctica, large values of K_iso exert strong control over the tracer distribution and brings tracer rich water to depth.

Potential habitat models have become an increasingly used method for characterizing fish larval habitat. Describing the potential habitat of fish larvae can yield insight into distribution patterns over temporal and spatial scales that cannot be easily characterized w discrete ichthyoplankton surveys, as well as setting a reference against which to assess the impact of anthropogenic and natural disturbances. Potential habitats are defined based on larval distribution and the environmental conditions that are suitable for development and survival. In the central Gulf of México (GoM), mesoscale circulation is dominated by the Loop Current (LC), LC-derived anticyclonic eddies that are transported westward and cyclonic eddies; these features influence productivity and water column characteristics and hence larval habitat. A semi-permanent cyclonic eddy in the Bay of Campeche (southern GoM) and other processes such as regional upwelling and offshore transport can also influence larval potential habitat. Between 2011-2017 nine oceanographic cruises covering the Mexican EEZ were conducted and fish larvae were collected using a bongo net sampler. Five taxa with different life history strategies, abundance and distribution patterns, spawning seasonality, and of varying economic importance were selected for the characterization of their potential habitat (Auxis spp., Benthosema suborbitale, Bregmaceros atlanticus, Caranx crysos and Cubiceps pauciradiatus). Their potential habitat will be characterized using generalized additive models correlating larval distribution with environmental parameters derived from in situ CTD and satellite-based measurements. The results of this study will yield insight into the potential larval habitat of representative fish species throughout the central and southern Gulf of Mexico.