Global Ocean Observing System Research Articles

The ocean response to climate change guides both adaptation and mitigation efforts

The ocean's thermal inertia is a major contributor to irreversible ocean changes exceeding time scales that matter to human society. This fact is a challenge to societies as they prepare for the consequences of climate change, especially with respect to the ocean. Here the authors review the requirements for human actions from the ocean's perspective. In the near term (∼2030), goals such as the United Nations Sustainable Development Goals (SDGs) will be critical. Over longer times (∼2050–2060 and beyond), global carbon neutrality targets may be met as countries continue to work toward reducing emissions. Both adaptation and mitigation plans need to be fully implemented in the interim, and the Global Ocean Observation System should be sustained so that changes can be continuously monitored. In the longer-term (after ∼2060), slow emerging changes such as deep ocean warming and sea level rise are committed to continue even in the scenario where net zero emissions are reached. Thus, climate actions have to extend to time scales of hundreds of years. At these time scales, preparation for “high impact, low probability” risks — such as an abrupt showdown of Atlantic Meridional Overturning Circulation, ecosystem change, or irreversible ice sheet loss — should be fully integrated into long-term planning.摘要在全球变化背景下, 海洋的很多变化在人类社会发展的时间尺度上 (百年至千年) 具有不可逆转性, 海洋巨大的热惯性是造成该不可逆性的主要原因. 这个特征为人类和生态系统应对海洋变化提出一系列挑战. 本文从海洋变化的角度总结了人类应对气候变化的要求, 提出需要进行多时间尺度的规划和统筹. 在近期 (到2030年) , 实现联合国可持续发展目标至关重要. 在中期 (2050–2060年前后) , 全球需要逐步减排并实现碳中和目标. 同时, 适应和减缓气候变化的行动和措施必须同步施行; 全球海洋观测系统需要得以维持并完善以持续监测海洋变化. 在远期 (在2060年之后) , 即使全球达到净零排放, 包括深海变暖和海平面上升在内的海洋变化都将持续, 因此应对全球变化的行动需持续数百年之久. 在该时间尺度, 应对“低概率, 高影响”气候风险 (即发生的可能性较低, 但一旦发生影响极大的事件带来的风险, 例如: 大西洋经圈反转环流突然减弱, 海洋生态系统跨过临界点, 无可挽回的冰盖质量损失等) 的准备应充分纳入长期规划.

Imaging Technologies Build Capacity and Accessibility in Phytoplankton Species Identification Expertise for Research and Monitoring: Lessons Learned During the COVID-19 Pandemic.

As primary producers, phytoplankton play an integral role in global biogeochemical cycles through their production of oxygen and fixation of carbon. They also provide significant ecosystem services, by supporting secondary production and fisheries. Phytoplankton biomass and diversity have been identified by the Global Ocean Observing System (GOOS) as Essential Ocean Variables (EOVs), properties that need to be monitored to better understand and predict the ocean system. Phytoplankton identification and enumeration relies on the skills and expertise of highly trained taxonomic analysts. The training of new taxonomic analysts is intensive and requires months to years of supervised training before an analyst is able to independently and consistently apply identification skills to a sample. During the COVID-19 pandemic, access to laboratories was greatly restricted and social distancing requirements prevented supervised training. However, access to phytoplankton imaging technologies such as the Imaging FlowCytobot (IFCB), FlowCam, and PlanktoScope, combined with open online taxonomic identification platforms such as EcoTaxa, provided a means to continue monitoring, research, and training activities remotely when in-person activities were restricted. Although such technologies can not entirely replace microscopy, they have a great potential for supporting an expansion in taxonomic training, monitoring, surveillance, and research capacity. In this paper we highlight a set of imaging and collaboration tools and describe how they were leveraged during laboratory lockdowns to advance research and monitoring goals. Anecdotally, we found that the use of imaging tools accelerated the training of new taxonomic analysts in our phytoplankton analysis laboratory. Based on these experiences, we outline how these technologies can be used to increase capacity in taxonomic training and expertise, as well as how they can be used more broadly to expand research opportunities and capacity.

Impacts of the Lagrangian Data Assimilation of Surface Drifters on Estimating Ocean Circulation during the Gulf of Mexico Grand Lagrangian Deployment

Abstract Satellite-tracked in situ surface drifters, providing measurements of near-surface ocean quantities, have become increasingly prevalent in the global ocean observation system. However, the position data from these instruments are typically not leveraged in operational ocean data assimilation (DA) systems. In this work, the impact of an augmented-state Lagrangian data assimilation (LaDA) method using the local ensemble Kalman transform filter is investigated within a realistic regional ocean DA system. Direct positioning data of surface drifters released by the Consortium for Advanced Research on Transport of Hydrocarbon in the Environment during the summer 2012 Grand Lagrangian Deployment Experiment are assimilated using a Gulf of Mexico (GoM) configuration of the Modular Ocean Model, version 6, of the Geophysical Fluid Dynamics Laboratory. Multiple cases are tested using both 1/4° eddy-permitting and 1/12° eddy-resolving model resolutions: 1) a free running model simulation, 2) a conventional assimilation of temperature and salinity profile observations, 3) an assimilation of profiles and Lagrangian surface drifter positions, and 4) an assimilation of the profiles and derived Eulerian velocities. LaDA generally produces more accurate estimates of all fields compared to the assimilation of derived Eulerian velocities, with estimates of surface currents notably improving, when transitioning to 1/12° model resolution. In particular, LaDA produces the most accurate estimates of sea surface velocities under tropical cyclone conditions when Hurricane Isaac (2012) impacted the GoM. Further experiments applying a vertical localization while assimilating surface drifter positions improve the estimates of temperature and salinity below the mixed layer depth. Cases including the surface drifter positions in the DA show better Lagrangian predictability than the conventional DA.

Thermocline Model for Estimating Argo Sea Surface Temperature

Argo has become an important constituent of the global ocean observation system. However, due to the lack of sea surface measurements from most Argo profiles, the application of Argo data is still limited. In this study, a thermocline model was constructed based on three key thermocline parameters, i.e, thermocline upper depth, the thermocline bottom depth, and thermocline temperature gradient. Following the model, we estimated the sea surface temperature of Argo profiles by providing the relationship between sea surface and subsurface temperature. We tested the effectiveness of our proposed model using statistical analysis and by comparing the sea surface temperature with the results obtained from traditional methods and in situ observations in the Pacific Ocean. The root mean square errors of results obtained from thermocline model were found to be significantly reduced compared to the extrapolation results and satellite retrieved temperature results. The correlation coefficient between the estimation result and in situ observation was 0.967. Argo surface temperature, estimated by the thermocline model, has been theoretically proved to be reliable. Thus, our model generates theoretically feasible data present the mesoscale phenomenon in more detail. Overall, this study compensates for the lack surface observation of Argo, and provides a new tool to establish complete Argo data sets.

Hospital Effluents and Wastewater Treatment Plants: A Source of Oxytetracycline and Antimicrobial-Resistant Bacteria in Seafood

The present study employs a data review on the presence and aggregation of oxytetracycline (OTC) and resistance (AMR) bacteria in wastewater treatment plants (WWTPs), and the distribution of the contaminated effluent with the aid of shallow and deep ocean currents. The study aims to determine the fate of OTC and AMR bacteria in seafood, and demonstrate a relationship between AMR levels and human health. This review includes (1) OTC, (2) AMR bacteria, (3) heavy metals in aquatic environments, and their relationship. Few publications describe OCT in surface waters. Although OTC and other tetracyclines were found in 10 countries in relatively low concentrations, the continuous water mass movement poses a contamination risk for mariculture and aquaculture. There are 10 locations showing AMR bacteria in treated and untreated hospital effluent. Special effort was made to define the geography distribution of OTC, AMR bacteria, and heavy metals detected in WWTPs to show the likely dissemination in an aquatic environment. The presence of OTC in surface waters in Asia, USA, and Europe can potentially impact seafood globally with the aid of ocean currents. Moreover, low concentrations of heavy metals exert environmental pressure and contribute to AMR dissemination. Recommended solutions are (1) quantitative analysis of OTC, heavy metals, and AMR bacteria to define their main sources; (2) employing effective technologies in urban and industrial wastewater treatment; and (3) selecting appropriate modelling from Global Ocean Observing System to predict the OTC, heavy metals, and AMR bacteria distribution.

Animal Borne Ocean Sensors – AniBOS – An Essential Component of the Global Ocean Observing System

Marine animals equipped with biological and physical electronic sensors have produced long-term data streams on key marine environmental variables, hydrography, animal behavior and ecology. These data are an essential component of the Global Ocean Observing System (GOOS). The Animal Borne Ocean Sensors (AniBOS) network aims to coordinate the long-term collection and delivery of marine data streams, providing a complementary capability to other GOOS networks that monitor Essential Ocean Variables (EOVs), essential climate variables (ECVs) and essential biodiversity variables (EBVs). AniBOS augments observations of temperature and salinity within the upper ocean, in areas that are under-sampled, providing information that is urgently needed for an improved understanding of climate and ocean variability and for forecasting. Additionally, measurements of chlorophyll fluorescence and dissolved oxygen concentrations are emerging. The observations AniBOS provides are used widely across the research, modeling and operational oceanographic communities. High latitude, shallow coastal shelves and tropical seas have historically been sampled poorly with traditional observing platforms for many reasons including sea ice presence, limited satellite coverage and logistical costs. Animal-borne sensors are helping to fill that gap by collecting and transmitting in near real time an average of 500 temperature-salinity-depth profiles per animal annually and, when instruments are recovered (∼30% of instruments deployed annually, n = 103 ± 34), up to 1,000 profiles per month in these regions. Increased observations from under-sampled regions greatly improve the accuracy and confidence in estimates of ocean state and improve studies of climate variability by delivering data that refine climate prediction estimates at regional and global scales. The GOOS Observations Coordination Group (OCG) reviews, advises on and coordinates activities across the global ocean observing networks to strengthen the effective implementation of the system. AniBOS was formally recognized in 2020 as a GOOS network. This improves our ability to observe the ocean’s structure and animals that live in them more comprehensively, concomitantly improving our understanding of global ocean and climate processes for societal benefit consistent with the UN Sustainability Goals 13 and 14: Climate and Life below Water. Working within the GOOS OCG framework ensures that AniBOS is an essential component of an integrated Global Ocean Observing System.

Data Management and Interactive Visualizations for the Evolving Marine Biodiversity Observation Network

Assessing the current state of and predicting change in the ocean’s biological and ecosystem resources requires observations and research to safeguard these valuable public assets. The Marine Biodiversity Observation Network (MBON) partnered with the Global Ocean Observing System Biology and Ecosystems Panel and the Ocean Biodiversity Information System to address these needs through collaboration, data standardization, and data sharing. Here, we describe the generalized MBON data processing flow, which includes several steps to ensure that data are findable, accessible, interoperable, and reusable. By following this flow, data collected and managed by MBON have contributed to our understanding of the Global Ocean Observing System Essential Ocean Variables and demonstrated the value of web-based, interactive tools to explore and better understand environmental change. Although the MBON’s generalized data processing flow is already in practice, work remains in building ontologies for biological concepts, improving processing scripts for data standardization, and speeding up the data collection-to-sharing timeframe.

Technological Trends and Significance of the Essential Ocean Variables by the Indian Moored Observatories: Relevance to UN Decade of Ocean Sciences

Abstract The ocean plays a key role in regulating the climate as well as supporting diverse ecosystems. Technology is the key for the sustained and precise in-situ spatio-temporal measurements of the physical, biological, biogeochemical, and near-atmospheric meteorological parameters essential for carrying out effective assessments of the status, variability, and change in the ocean ecosystems and for creating policies at the right time. The United Nations Decade of Ocean Science for Sustainable Development 2021‐2030 provides a timeframe to build a comprehensive, sustainable, and data-based informed decision-making global ocean observing system. This demands global-scale investigations, trans-disciplinary science, and mechanisms to integrate and distribute data that otherwise would appear to be disparate. The essential ocean variables (EOVs) conceptualized by the Global Ocean Observing System (GOOS) of UNESCO's Intergovernmental Oceanographic Commission guide observation of the ocean. In order to achieve the goal of UN Decade envisaged and to have an Earth System approach under the World Meteorological Organization reforms, it is imperative to address globally and nationally relevant indicators and assessments, which require increased sharing of data and analytical methods, sustained long-term and large-scale observations, and resources dedicated to these tasks. Technology for observing the ocean is important, which is not addressed in detail in the recent past. In this paper we provide a comprehensive overview of Sensor versus Essential Ocean Variable from our experience in sustained 25 years of moored ocean observation network and collaborating with institutions and experts in the United States and GOOS. An attempt has been made to furnish an overview for any group or nation to start or sustain an observation network using EOVs with guiding principles of Findable, Accessible, Interoperable, Reusable data that is targeted to deliver essential information needed for sustainable development and protecting ocean health.

Boundary Ocean Observation Network for the Global South

Abstract The UN Decade of Ocean Science for Sustainable Development should establish a Boundary Ocean Observing Network (BOON) for the Global South (GS). The BOON is part of the OceanGlider Program, which is part of the Global Ocean Observing System (GOOS). The BOON is a network of established timeseries transects collecting long-term data sets. Timeseries are critical for making immediate operational decisions and for identifying long-term trends of anthropogenic global environmental change. The network has proven important enough to continue observations and expand them. Due to resource and expertise limitations, expanded locations are in similar locations. The UN should build on this success and establish a BOON for the Global South. The same benefits will be garnered by countries and regions that have been missing out. Increased observation coverage will benefit humanity, improving understanding of the Ocean-Climate System, e.g. leading to improved climate prediction models. The UN will facilitate activities to realize a BOON for the Global South including: coordinating local scientists, partnering scientific and technical experts with local scientists, identifying new affordable and easy-to-operate technologies, channeling funds for initial and ongoing costs, and building a framework to continue the BOON-GS long after the Ocean Science Decade.

Envisioning a Global Multi-Purpose Ocean Acoustic Network

Abstract Due to the efficient propagation of sound in water, sound in the deep ocean propagates such great distances that soundscapes are influenced not only by local conditions but also by distant sound sources. Ocean Sound is now an Essential Ocean Variable within the Global Ocean Observing System making passive acoustic monitoring routine. Active acoustic probing of the environment informs us about ocean topography, currents and temperature, and abundance and type of marine life vital to fisheries and biodiversity related interests.Efficient sound propagation is the foundation of a proposed multipurpose acoustic network. Judiciously placed low-frequency acoustic sources transmitting to globally distributed passive acoustic systems provide: (1) high temporal resolution measurements of large-scale ocean temperature/heat content variability using tomography; and (2) underwater geo-positioning (UW-GPS) and communication services enabling basin-scale underwater operation of floats, gliders, and AUVs. Every platform (fixed or moving) equipped with a hydrophone becomes a “GPS” receiver, while listening to the ocean soundscape. The combined active and passive acoustic technology will lead to multi-disciplinary discovery and improved understanding of ocean ecosystem health and biodiversity, climate variability and change, marine hazards, and maritime safety. The same system will improve the operation of gliders, floats and AUVs.

Ecological Forecasts for a Rapidly Changing Coastal Ocean

Abstract The U.S. Integrated Ocean Observing System (IOOS) has a vision to provide ecological forecasts that inform response to multiple stressors in the face of rapid changes in our ocean and Great Lakes. IOOS supports 11 nationally distributed Regional Associations, each with established ties to local decision makers and regional coastal scientists. IOOS also supports thematic networks of platforms and observations to characterize and monitor marine ecosystems and living resources throughout the nation. IOOS serves as the U.S. contribution to the Global Ocean Observing System. This infrastructure, stakeholder engagement, and local-to-global reach uniquely positions IOOS to advance development of an ecological forecast system, across sectors and disciplines, that is responsive and effective.

A standardisation framework for bio‐logging data to advance ecological research and conservation

Abstract Bio‐logging data obtained by tagging animals are key to addressing global conservation challenges. However, the many thousands of existing bio‐logging datasets are not easily discoverable, universally comparable, nor readily accessible through existing repositories and across platforms, slowing down ecological research and effective management. A set of universal standards is needed to ensure discoverability, interoperability and effective translation of bio‐logging data into research and management recommendations. We propose a standardisation framework adhering to existing data principles (FAIR: Findable, Accessible, Interoperable and Reusable; and TRUST: Transparency, Responsibility, User focus, Sustainability and Technology) and involving the use of simple templates to create a data flow from manufacturers and researchers to compliant repositories, where automated procedures should be in place to prepare data availability into four standardised levels: (a) decoded raw data, (b) curated data, (c) interpolated data and (d) gridded data. Our framework allows for integration of simple tabular arrays (e.g. csv files) and creation of sharable and interoperable network Common Data Form (netCDF) files containing all the needed information for accuracy‐of‐use, rightful attribution (ensuring data providers keep ownership through the entire process) and data preservation security. We show the standardisation benefits for all stakeholders involved, and illustrate the application of our framework by focusing on marine animals and by providing examples of the workflow across all data levels, including filled templates and code to process data between levels, as well as templates to prepare netCDF files ready for sharing. Adoption of our framework will facilitate collection of Essential Ocean Variables (EOVs) in support of the Global Ocean Observing System (GOOS) and inter‐governmental assessments (e.g. the World Ocean Assessment), and will provide a starting point for broader efforts to establish interoperable bio‐logging data formats across all fields in animal ecology.

Enhance Ocean Carbon Observations: Successful Implementation of a Novel Autonomous Total Alkalinity Analyzer on a Ship of Opportunity

Over recent decades, observations based on merchant vessels (Ships of Opportunity—SOOP) equipped with sensors measuring the CO2 partial pressure (pCO2) in the surface seawater formed the backbone of the global ocean carbon observation system. However, the restriction to pCO2 measurements alone is one severe shortcoming of the current SOOP observatory. Full insight into the marine inorganic carbon system requires the measurement of at least two of the four measurable variables which are pCO2, total alkalinity (TA), dissolved inorganic carbon (DIC), and pH. One workaround is to estimate TA values based on established temperature-salinity parameterizations, but this leads to higher uncertainties and the possibility of regional and/or seasonal biases. Therefore, autonomous SOOP-based TA measurements are of great interest. Our study describes the implementation of a novel autonomous analyzer for seawater TA, the CONTROS HydroFIAⓇ TA system (-4H-JENA engineering GmbH, Germany) for unattended routine TA measurements on a SOOP line operating in the North Atlantic. We present the installation in detail and address major issues encountered with autonomous measurements using this analyzer, e.g., automated cleaning and stabilization routines, and waste handling. Another issue during long-term deployments is the provision of reference seawater in large-volume containers for quality assurance measurements and drift correction. Hence, a stable large-volume seawater storage had to be found. We tested several container types with respect to their suitability to store seawater over a time period of 30 days without significant changes in TA. Only one gas sampling bag made of polyvinylidene fluoride (PVDF) satisfied the high stability requirement. In order to prove the performance of the entire setup, we compared the autonomous TA measurements with TA from discrete samples taken during the first two trans-Atlantic crossings. Although the measurement accuracy in unattended mode (about ± 5 μmol kg^-1) slightly deteriorated compared to our previous system characterization, its overall uncertainty fulfilled requirements for autonomous TA measurements on SOOP lines. A comparison with predicted TA values based on an established and often used parameterization pointed at regional and seasonal limitations of such TA predictions. Consequently, TA observations with better coverage of spatiotemporal variability are needed, which is now possible with the method described here.

New Cost-Effective Technologies Applied to the Study of the Glacier Melting Influence on Physical and Biological Processes in Kongsfjorden Area (Svalbard)

The Arctic region is greatly affected by climate change, with evident alterations in both physical and biological processes: temperatures are changing at a rate that is twice the global average and phytoplankton productivity is directly affected by ice melting. Continuous monitoring of this ecosystem is fundamental to gain greater understanding of the impact of changes on the natural environment, but the Global Ocean Observing System only provides partial coverage in these extreme areas, which are particularly difficult to reach. Technological progress in oceanographic measurement capabilities is indispensable for the implementation of marine observatories, especially in these remote regions. In recent years, autonomous systems and cost-effective technologies have proved to be valuable for increasing spatial and temporal coverage of data. This is the case with the innovative ArLoC (Arctic Low-Cost) probe, which was designed and developed for easy integration into various types of platforms, enabling continuous measurement of temperature, pressure and fluorescence of chlorophyll a. This work reports on the results of two scientific campaigns carried out in Kongsfjorden (Svalbard Islands) in 2018 in the framework of the UVASS (Unmanned Vehicles for Autonomous Sensing and Sampling) research project. The ArLoC probe was integrated onboard the PROTEUS (Portable RObotic TEchnology for Unmanned Surveys) unmanned semi-submersible vehicle and this allowed us to collect important data in the stretches of sea near tidewater glacier fronts. The acquired data showed several significant effects of glacier melting such as: high temperature and salinity gradients, which cause considerable variations in water mass stratification, and an increase in turbidity and the chlorophyll a concentration, which directly affects primary productivity and the trophic chain. During the surveys, ArLoC proved to be an easy-to-integrate, very reliable instrument, which permitted high spatial resolution investigation of ecological processes during glacier melting as never studied before.

Research on the Operational Stability and Energy Consumption of the Profiling Float

Liu, Y.; Guo, F.; Zhai, X.; Li, Z.; Zhao, H., and Xue, G., 2020. Research on the operational stability and energy consumption of the profiling float. In: Zheng, C.W.; Wang, Q.; Zhan, C., and Yang, S.B. (eds.), Air-Sea Interaction and Coastal Environments of the Maritime and Polar Silk Roads. Journal of Coastal Research, Special Issue No. 99, pp. 21-30. Coconut Creek (Florida), ISSN 0749-0208.The profiling float is the crucial component of global ocean observation system. Considering the excessive change rate of motion speed and energy consumption issues during the ascending process of the float, this paper proposes two sets of the piecewise oil-pumping control strategies based on speed closed-loop (SCL) and speed-acceleration double closed-loop (SADCL) respectively. The kinematic model and energy consumption model of the 4000-meter profiling float during the ascending process are established, then the simulation and analysis were made to study the operational stability and energy consumption of the float. By comparing the influence of SCL and SADCL control strategies with that of traditional control strategy for pumping (TCS) on the performance of the float, the results are as follows: SCL and SADCL control strategies can effectively improve the float operational stability and lessen the energy consumption. The amplitude of velocity fluctuation decreased by 65.44% compared with the traditional strategy. When the setting value of feedback speed uset is 1m/s, the SCL control strategy is more efficient, saving 18% energy than TCS. However, optimized control strategies will no longer have the advantage of energy saving at the speed uset below 0.050 m/s. The conclusion drawn in this paper is beneficial for the further study of the profiling float oil-pumping control strategy.

Energy recovery and conservation utilizing seawater pressure in the working process of Deep-Argo profiling float

Argo profiling float is the key equipment of global ocean observation system. Energy supply issues have limited the working time and the exploring depth of Deep-Argo. In this paper, the scheme of energy recovery and conservation utilizing seawater pressure is put forward innovatively. The hydraulic motor is used to recover and conserve energy when seawater drives hydraulic oil moving from buoyancy bladder to storage bladder in the descending process of Deep-Argo. The working environment of Deep-Argo is defined by the data from sea trials and the simulation model based on AMESim-Simulink is verified by the experiment. Several cases are conducted to analyze the effect of energy recovery and conservation. It shows that the larger fluid drag coefficient of Deep-Argo will lead to the smaller motion speed and the larger energy consumption. The input pressure of hydraulic motor is related with its working time and working frequency. Under the condition that Deep-Argo could reach the target depth, the less volume of hydraulic oil driven by hydraulic pump and the higher input pressure of hydraulic motor will lead to better results of energy recovery and conservation. The recovered energy by the hydraulic motor can be 11.35% of the consumed energy by the hydraulic pump and the conserved energy can be 2.77% of the consumed energy by the hydraulic pump. This paper verifies the feasibility of the scheme for energy recovery and conservation utilizing seawater pressure for Deep-Argo profiling float, and provides the basis for further applied research.

Impacts of Temperature Measurements From Sea Turtles on Seasonal Prediction Around the Arafura Sea

In this work, we added the assimilation of subsurface temperature measurements obtained from sea turtles around the Arafura Sea from June to October 2017 into an operational seasonal prediction system. The impact of these measurements was explored by conducting the so-called ocean observing system experiments. It was found that the prediction of regional sea surface temperatures around the Arafura Sea is significantly improved at 3-4 months lead-time. The results also showed that the addition of temperature measurements from sea turtles into the existing Global Ocean Observing System (including satellites, mooring buoys, ships, and profiling floats) may open a new door to improving regional seasonal prediction through better representation of the initial state of the upper ocean.

Making Lake Erie Smart by Driving Innovations in Technology and Networking

Tomorrow’s smart lake will able to predict what could happen and to identify actions that affect the trajectory of the lakes. Smart Lake Erie – the proof of concept – will integrate data from distributed sensors using resilient networks to feed adaptive, predictive analytics that define and perhaps even perform necessary management actions. This paper describes Smart Lake Erie pilot as a series of steps including convening innovation challenges, engaging stakeholders, securing the core observation system, and designing and operationalizing a sustainable Harmful Algae Bloom Early-Warning System. The technology platform of the pilot will be a window into what is needed to serve new contributors, new service providers, new stakeholders and consumers of the data and information service paradigm. Lessons learned are drawn from the early implementation of the pilot which are applicable to the larger Great Lakes region, other Region Associations within the U.S. Integrated Ocean Observing System, and the Global Ocean Observing System.

How Deep Argo Will Improve the Deep Ocean in an Ocean Reanalysis

AbstractGlobal ocean sampling with autonomous floats going to 4000–6000 m, known as the deep Argo array, constitutes one of the next challenges for tracking climate change. The question here is how such a global deep array will impact ocean reanalyses. Based on the different behavior of four ocean reanalyses, we first identified that large uncertainty exists in current reanalyses in representing local heat and freshwater fluxes in the deep ocean (1 W m−2 and 10 cm yr−1 regionally). Additionally, temperature and salinity comparison with deep Argo observations demonstrates that reanalysis errors in the deep ocean are of the same size as, or even stronger than, the deep ocean signal. An experimental approach, using the 1/4° GLORYS2V4 (Global Ocean Reanalysis and Simulation) system, is then presented to anticipate how the evolution of the global ocean observing system (GOOS), with the advent of deep Argo, would contribute to ocean reanalyses. Based on observing system simulation experiments (OSSE), which consist in extracting observing system datasets from a realistic simulation to be subsequently assimilated in an experimental system, this study suggests that a global deep Argo array of 1200 floats will significantly constrain the deep ocean by reducing temperature and salinity errors by around 50%. Our results also show that such a deep global array will help ocean reanalyses to reduce error in temperature changes below 2000 m, equivalent to global ocean heat fluxes from 0.15 to 0.07 W m−2, and from 0.26 to 0.19 W m−2 for the entire water column. This work exploits the capabilities of operational systems to provide comprehensive information for the evolution of the GOOS.

Chlorophyll fluorescence as measured in situ by animal-borne instruments in the northeastern Pacific Ocean

Abstract Chlorophyll concentration in the ocean is a metric for phytoplankton biomass, which forms the base of most pelagic food webs and is a critical component of the planet's carbon cycle. Phytoplankton biomass has been designated an Essential Ocean Variable (EOV), but in situ chlorophyll measurements are challenging and expensive to obtain, especially in remote regions. We deployed 11 Conductivity-Temperature-Depth-Fluorescence (CTDF) instruments on 15 northern elephant seals (Mirounga angustirostris) during 2014, 2018, and 2019 collecting 2532 temperature, salinity, and chlorophyll fluorescence profiles that exceeded 180 m depth and extended over 2000 km from the nearest landmass. The tags' fluorometers were calibrated in a laboratory and a controlled field setting approximating northeastern Pacific phytoplankton assemblages and conditions, resulting in adjustments to manufacturer calibration curves ranging from −4% to 81%. Subsurface chlorophyll maxima were observed below the first optical depth in 69.2% of the casts, of which 24.9% were deep chlorophyll maxima below the mixed layer. Established fluorescence quenching correction methods were not applicable to this dataset; however, time of day did not introduce a consistent bias to our results. In situ chlorophyll measurements were on average 5.24 times higher than coincident satellite measurements. This in situ chlorophyll dataset measures an EOV in high resolution in remote regions at low cost, a valuable contribution to the Global Ocean Observing System (GOOS). Regional index terms: North Pacific Ocean [35–50°N, 120–180°W].