Integrated Ocean Observing System Research Articles

Multi-AUV dynamic trajectory optimization and collaborative search combined with task urgency and energy consumption scheduling in 3-D underwater environment with random ocean currents and uncertain obstacles

A double layer bio-inspired self-organizing map (DLBSOM) algorithm for multiple autonomous underwater vehicle (multi-AUV) dynamic task planning to search for multi-targets in the 3-D underwater environments affected by random ocean currents and dynamic uncertainty obstacles is proposed. Combined with a task urgency bio-inspired neural network (TUBNN) model that is applied to construct the neuron activity network to complete initial task assignment and path planning with the constraint of energy consumption. The decoupling of the task assignment and path planning in the initial task planning is solved through the corrected redistribution mechanism and end-to-end trajectory optimization method. The unknown obstacles information is fused with the diamond-shaped local neuronal network constructed by the diamond closed curve function. Through the function curve, the local neuronal network can be precisely adjusted according to AUV operation information and equipment performance to achieve the saving of computing resources and quick processing speed. Subsequently, the distance-speed comprehensive evaluation (DSCE) strategy is used to complete dynamic avoidance decision. By the General Bathymetric Chart of the Oceans (GBCO) and the Integrated Ocean Observing System (IOOS), the environment is generated to complete multiple sets of simulations that demonstrate the efficiency and adaptability of the DLBSOM algorithm in multi-AUV collaborative search.

Open Source Workshop to Mobilize Marine Biodiversity Data

The 2022 Marine Biological Data Mobilization Workshop was a collaborative effort between Ocean Biodiversity Information System-USA (OBIS-USA), Marine Biodiversity Observation Network, Hakai Institute, Integrated Ocean Observing System, and Ocean Tracking Network, and hosted to promote open data and software in marine biodiversity assessment. The workshop focused on the application of the Darwin Core data standard (Wieczorek et al. 2012) to extant data and the subsequent publication of data to the open access data infrastructures provided by OBIS and the Global Biodiversity Information Facility. The curriculum for this workshop was modeled using The Carpentries evidence-based best practices of teaching. The materials and website are openly available via GitHub and are free for re-use or adaptation under an MIT license. Some unconventional features of the workshop included: Much of the workshop time was allocated to breakout rooms and individual work. The use of concurrent, topical breakout rooms led by instructors in combination with “floating” specialist volunteers. A 100% open and free virtual workshop leveraging synchronous and asynchronous communications technologies including Slack, Zoom, and GitHub. All instructional steps were offered in both Python and R (dual-programming language materials). Much of the workshop time was allocated to breakout rooms and individual work. The use of concurrent, topical breakout rooms led by instructors in combination with “floating” specialist volunteers. A 100% open and free virtual workshop leveraging synchronous and asynchronous communications technologies including Slack, Zoom, and GitHub. All instructional steps were offered in both Python and R (dual-programming language materials). The workshop was attended internationally by 63 participants, with 48 attendees joining the associated Slack group. These new members have been invited to attend a monthly working group organized to address roadblocks to standardization and promote the mobilization of marine biological data. A pre- versus post-survey analysis showed substantial improvement to self-reported data science skill levels, a multitude of positive feedback was reported, and the workshop scored a perfect 100% standard Net Promoter Score (Reichheld 2003) with 16 “promoters”, 0 “detractors”, and a total of 25 respondents.

Indigenous Traditional Ecological Knowledge and Ocean Observing: A Review of Successful Partnerships

Understanding and management of the marine environment requires respect for, and inclusion of, Indigenous knowledge, cultures, and traditional practices. The Aha Honua, an ocean observing declaration from Coastal Indigenous Peoples, calls on the ocean observing community to “formally recognize the traditional knowledge of Indigenous peoples,” and “to learn and respect each other’s ways of knowing.” Ocean observing systems typically adopt open data sharing as a core principle, often requiring that data be Findable, Accessible, Interoperable, and Reusable (FAIR). Without modification, this approach to Traditional Ecological Knowledge (TEK) would mean disregarding historical and ongoing injustices and imbalances in power, and information management principles designed to address these wrongs. Excluding TEK from global ocean observing is not equitable or desirable. Ocean observing systems tend to align with settler geography, but their chosen regions often include Indigenous coastal-dwelling communities that have acted as caretakers and stewards of the land and ocean for thousands of years. Achieving the call of Aha Honua will require building relationships that recognize Indigenous peoples play a special role in the area of ocean stewardship, care, and understanding. This review examines the current understanding of how Indigenous TEK can be successfully coordinated or utilized alongside western scientific systems, specifically the potential coordination of TEK with ocean observing systems. We identify relevant methods and collaborative projects, including cases where TEK has been collected, digitized and the meta(data) has been made open under some or all the FAIR principles. This review also highlights enabling factors that notably contribute to successful outcomes in digitization, and mitigation measures to avoid the decontextualization of TEK. Recommendations are primarily value- and process-based, rather than action-based, and acknowledge the key limitation that this review is based on extant written knowledge. In cases where examples are provided, or local context is necessary to be concrete, we refer to a motivating example of the nascent Atlantic Regional Association of the Canadian Integrated Ocean Observing System and their desire to build relationships with Indigenous communities.

Integrating Biodiversity and Environmental Observations in Support of National Marine Sanctuary and Large Marine Ecosystem Assessments

Species and habitats are the subjects of legislation that mandates reporting of information on ecosystem conditions. Improvements in sensors, sampling platforms, information systems, and collaborations among experts and information users now enables more effective and up-to-date information to meet regional and national needs. Specifically, advances in environmental DNA (eDNA)-based assessments of biodiversity, community science data, various underwater imaging devices, and environmental, behavioral, and physiology observations from animal telemetry provide new opportunities to address multiple requirements for reporting status and trends, including insights into life in the deep ocean. Passive and active acoustic sensors help monitor marine life, boat traffic, and noise pollution. Satellites provide repeated, frequent, and long-term records of many relevant variables from global to local scales and, when combined with numerical computer simulations, allow planning for future scenarios. Metadata standards facilitate the transfer of data from machine to machine, thus streamlining assessments and forecasting and providing knowledge directly to the public. The Marine Biodiversity Observation Network (MBON) facilitates this exchange of information on life in the sea. The collaborative efforts of the Central and Northern California Ocean Observing System (CeNCOOS) of the US Integrated Ocean Observing System and its partners provide an example of a regional MBON process for information delivery. This includes linking policy and management needs, prioritizing observing data from various platforms and methods, streamlining data handling practices, and delivery of information for management such as for the Monterey Bay National Marine Sanctuary and the California Current Large Marine Ecosystem, with iterative process adaptation.

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.

COVERAGE: Next Generation Data Service Infrastructure for a Digitally Integrated Ocean Observing System in Support of Marine Science and Ecosystem-Based Management

Abstract Ocean science and decision support applications increasingly rely on the synergistic, interdisciplinary use of multivariate data from distributed agency repositories. While more available, the growing variety and volume of ocean observing data combined with the heterogeneous modalities of access continue to pose a challenge to broadscale uptake. This limits the effective utilization of costly investments in sustained ocean observation by an increasing diversity of user communities with a need for such environmental information on the oceans for the assessment of climate change and other ecosystem impacts. Leveraging an advanced cloud technology stack and an ongoing multi-agency pilot effort being spearheaded by NASA, the CEOS Ocean Variables Enabling Research and Applications for GEO (COVERAGE) initiative seeks to collaboratively develop the next generation data service infrastructure for a more digitally integrated ocean observing system in support of marine science and ecosystem-based management. In particular, we envisage the implementation of a data services layer atop of existing agency repositories to provide more harmonized access to satellite, in-situ, and model data across a fragmented ocean data landscape with a set of value-added services that include integrated data search, visualization, and analytics. Here we outline the motivation and importance of this effort plus efforts thus far towards the collective realization of this ambitious vision.

Doppio – a ROMS (v3.6)-based circulation model for the Mid-Atlantic Bight and Gulf of Maine: configuration and comparison to integrated coastal observing network observations

Abstract. We describe “Doppio”, a ROMS-based (Regional Ocean Modeling System) model of the Mid-Atlantic Bight and Gulf of Maine regions of the northwestern North Atlantic developed in anticipation of future applications to biogeochemical cycling, ecosystems, estuarine downscaling, and near-real-time forecasting. This free-running regional model is introduced with circulation simulations covering 2007–2017. The ROMS configuration choices for the model are detailed, and the forcing and boundary data choices are described and explained. A comprehensive observational data set is compiled for skill assessment from satellites and in situ observations from regional associations of the U.S. Integrated Ocean Observing Systems, including moorings, autonomous gliders, profiling floats, surface-current-measuring coastal radar, and fishing fleet sensors. Doppio's performance is evaluated with respect to these observations by representation of subregional temperature and salinity error statistics, as well as velocity and sea level coherence spectra. Model circulation for the Mid-Atlantic Bight and Gulf of Maine is visualized alongside the mean dynamic topography to convey the model's capabilities.

The Evolution and Outcomes of a Collaborative Testbed for Predicting Coastal Threats

Beginning in 2003, the Southeastern Universities Research Association (SURA) enabled an open-access network of distributed sensors and linked computer models through the SURA Coastal Ocean Observing and Predicting (SCOOP) program. The goal was to support collaborations among universities, government, and industry to advance integrated observation and modeling systems. SCOOP improved the path to operational real-time data-guided predictions and forecasts of coastal ocean processes. This was critical to the maritime infrastructure of the U.S. and to the well-being of coastal communities. SCOOP integrated and expanded observations from the Gulf of Mexico, the South Atlantic Bight, the Middle Atlantic Bight, and the Chesapeake Bay. From these successes, a Coastal and Ocean Modeling Testbed (COMT) evolved with National Oceanic and Atmospheric Administration (NOAA) funding via the Integrated Ocean Observing System (IOOS) to facilitate the transition of key models from research to operations. Since 2010, COMT has been a conduit between the research community and the federal government for sharing and improving models and software tools. SCOOP and COMT have been based on strong partnerships among universities and U.S. agencies that have missions in ocean and coastal environmental prediction. During SURA’s COMT project, which ended September 2018, significant progress was made in evaluating the performance of models that are progressively becoming operational. COMT successes are ongoing.

Implementation of the U.S. Integrated Ocean Observing System (DOC)

Implementation of the U.S. Integrated Ocean Observing System (DOC)

Implementation of the U.S. Integrated Ocean Observing System (DOC)

Implementation of the U.S. Integrated Ocean Observing System (DOC)

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.

The impact of remote sensing observations on cross-shelf transport estimates from 4D-Var analyses of the Mid-Atlantic Bight

This paper explores the impact of the individual components of a coastal ocean observing system on estimates of the circulation derived from a state-of-the-art analysis and forecast system for the Mid-Atlantic Bight and Gulf of Maine. The foundation of these activities is the Regional Ocean Modeling System 4-dimensional variational (4D-Var) data assimilation platform, which is run in support of the Mid-Atlantic Regional Association Coastal Ocean Observing System as part of the U.S. Integrated Ocean Observing System. The specific focus of this study is on the impact of remote sensing observations from both space- and land-based platforms on estimates of cross-shelf transport in the vicinity of the National Science Foundation Ocean Observatories Initiative Pioneer array. Sea surface temperature (SST) and sea surface height (SSH) were found to have, on average, a similar impact on the transport estimates. However, during a typical 3-day 4D-Var assimilation cycle, approximately two orders of magnitude more observations of SST than SSH are used in the model, and closer analysis shows that each altimeter measurement has approximately 50 times more impact on the transport estimates than an individual SST observation. This highlights the value of altimetry data for ocean state estimation, and the significance of expanding the altimeter constellation. The observations that are most impactful of all are in situ measurements of temperature and salinity, which have typically 3–4 times more impact than an individual SSH datum. A robust geographical distribution of the observation impacts emerges across a range of transport metrics which results from the combined influence of space-time dynamical interpolation and error covariance information within the 4D-Var system. The observation impact calculations suggest that High Frequency (HF) radar estimates of surface currents have relatively little direct influence on cross-shelf transport estimates. However, quantification of the sensitivity of these same estimates to changes in the observing system indicate that HF radar observations indirectly provide important information. This is understood in the current system by appealing to the idea of borrowing strength from the field of statistics in which some observations (satellite remote sensing in the case considered here) can borrow strength from other, seemingly less important observations.

The Development of a Canadian Integrated Ocean Observing System (CIOOS)

Ocean observation is fundamental to Canada’s ocean science community. The federal government, academia, small businesses, not-for-profit organizations, and other research partners, collect and synthesize physical, chemical and biological observations for research purposes, to model ocean changes, to support resource management decision-making, and to establish baseline data for long-term monitoring. Aside from building comprehensive ocean observatories (Fisheries and Oceans Canada (DFO) et al. 2010), there is no easy mechanism to integrate the large amounts of data from the various sources or to explore interrelationships among variables, and no coordination and collaboration mechanism for the ocean community as a whole to generate an efficient system (Ocean Science and Technology Partnership (OSTP), for Fisheries and Oceans Canada (DFO) 2011). Consequently, we observe fragmented and isolated data that is only discoverable by a limited range of end users. Canada’s ocean science community (Wallace et al. 2014), led and supported by Fisheries and Oceans Canada (DFO), is developing a Canadian Integrated Ocean Observation System (CIOOS) that brings together and leverages existing Canadian and international ocean observation data into a federated data system. This system (Wilson et al. 2016) will improve coordination and collaboration among diverse data producers, improve access to information for decision making, and enable discovery and access to data to support a wide variety of applied and theoretical research efforts to better understand, monitor, and manage activities in Canada’s oceans. Canada is implementing a CIOOS test-phase, which will eventually lead to the development of a robust and integrated observing system, improving connections between end users and providers of ocean observations. The improved coordination of regional and national efforts within CIOOS will contribute to global ocean observing, maximizing the overall benefit of integrated observing.

Evaluation of Alternative Direction-of-Arrival Methods for Oceanographic HF Radars

The majority of ocean current measuring HF radars obtain the direction of arrival (DOA) of signals backscattered from the ocean with the multiple signal classification (MUSIC) algorithm. These radars often operate under conditions including low signal-to-noise ratio (SNR), low numbers of data samples (aka snapshots), and with the number of signal sources approaching or exceeding the number of receive antenna elements. Improving the accuracy and coverage of the radar data in these situations would improve data produced by radar networks such as the U.S. Integrated Ocean Observing System, revealing new understanding of coastal ocean dynamics. This paper presents an evaluation of DOA techniques developed over the last 10–20 years, for application to oceanographic HF radars using a simulation-based approach. Simulations performed using three commonly used receive arrays suggest that the use of maximum-likelihood estimation by alternating projection (MLE-AP) leads to similar accuracy, with improvement in coverage due to the higher number of DOA solutions obtained when compared to MUSIC. These advances come at a higher computational cost, though the difference is manageable. The analysis also illustrates the need to identify and evaluate signal detection methods (i.e., methods to identify the number of simultaneous source bearings) to work in conjunction with MLE-AP. Overall, these results suggest improvements in the data coverage of ocean current maps produced by HF radars, and thus in the many practical applications employing them such as spill response, and search and rescue.

Meeting Regional, Coastal and Ocean User Needs With Tailored Data Products: A Stakeholder-Driven Process

New coastal and ocean observing stations and instruments deployed across the globe are providing increasing amounts of meteorological, biological, and oceanographic data. While these developments are essential for the development of various data products to inform decision-making among coastal communities, more data does not automatically translate into more benefits to society. Rather, decision-makers and other potential end-users must be included in an ongoing stakeholder-driven process to determine what information to collect and how to best streamline access to information. We present a three-step approach to develop effective tailored data products: (1) tailor stakeholder engagement to identify specific user needs; (2) design and refine data products to meet specific requirements and styles of interaction; and (3) iterate engagement with users to ensure data products remain relevant. Any of the three steps could be implemented alone or with more emphasis than others, but in order to successfully address stakeholders’ needs, they should be viewed as a continuum—as steps in a process to arrive at effective translation of coastal and ocean data to those who need it. Examples from the Regional Associations of the U.S. Integrated Ocean Observing System (IOOS®), the Texas General Land Office, and the Vanuatu Meteorology and Geo-hazards Department are woven throughout the discussion. These vignettes illustrate the value of this stakeholder-driven approach and provide a sample of the breadth of flexibility and customizability it affords. We hope this community white paper inspires others to evaluate how they connect their stakeholders to coastal and ocean observing data and provides managers of observing systems with a guide on how to evolve in a manner that addresses societal needs.

The U.S. Integrated Ocean Observing System: Governance Milestones and Lessons From Two Decades of Growth

Reflecting on two decades of the U.S. Integrated Ocean Observing System (IOOS) is particularly timely during the OceanObs’19 meeting. Over the past twenty years since the first OceanObs meeting was convened, U.S. IOOS has advanced from regional proofs of concept to a national, sustained enterprise. U.S. IOOS has grown to include 17 Federal partners and 11 Regional Associations (RAs) that implement regional observing systems covering all U.S. coasts and Great Lakes with activities spanning from head of tide to the U.S. exclusive economic zone (EEZ). The National Oceanographic and Atmospheric Administration (NOAA), as lead agency, provides guidance and national-level coordination. An interagency body, the Integrated Ocean Observation Committee (IOOC), communicates across federal agencies and ensures IOOS maintains strong connections to the Global Ocean Observing System (GOOS). Additionally, a federal advisory committee, non-federal association, and various informal partnerships further inform and advance the IOOS enterprise. This governance structure fosters both national consistency, regional flexibility, and global contributions addressing the diverse needs of U.S. coastal and Great Lakes stakeholders.

U.S. IOOS Coastal and Ocean Modeling Testbed: Hurricane‐Induced Winds, Waves, and Surge for Deep Ocean, Reef‐Fringed Islands in the Caribbean

AbstractAs part of a U.S. Integrated Ocean Observing System (IOOS) funded Coastal and Ocean Modeling Testbed (COMT), hindcasts of waves and storm surge for 2017 Hurricanes Irma and Maria are examined and compared to wave and water level gauge data in the vicinity of Puerto Rico and the U.S. Virgin Islands. The region is characterized by adjacent deep ocean water, narrow shelves, and coral reef systems providing coastal protection. The storm physics are analyzed using an unstructured grid third‐generation wave circulation coupled modeling system (ADCIRC+SWAN) with respect to tides, winds, atmospheric pressure, waves, and wave radiation stress‐induced setup. The water level response is generally dominated by the pressure deficit of the hurricanes. Wind‐driven surge is important over the shallow shelf to the east of Puerto Rico and wave‐induced setup becomes significant at locations in close proximity to the coastline. Contrary to conditions along the Gulf of Mexico shelf, geostrophically induced setup is negligible. Characteristics from a range of meteorological forcing models are assessed, and the associated errors in the hydrodynamic response are quantified. A data‐assimilated tropical planetary boundary model leads to the smallest atmospheric pressure, water level and wave property errors across both storms. Through comparisons between ADCIRC+SWAN and SLOSH‐FW (a structured grid first‐generation wave circulation coupled model), it is shown that the response to atmospheric forcing is similar; however, nearshore wave setup is smaller in SLOSH‐FW due to its coarser resolution here. Further, in addition to erroneous wind‐driven surge through depth limiting over the open ocean, numerical oscillations in the water level time series develop in SLOSH‐FW likely due to its small domain size.

Developing an Integrated Ocean Observing System for New Zealand

New Zealand (NZ) is an island nation with stewardship of an ocean twenty times larger than its land area. While the challenges facing NZ’s ocean are similar to other maritime countries, no coherent national plan exists that meets the needs of scientists, stakeholders or kaitiakitanga (guardianship) of NZ’s ocean in a changing climate. The NZ marine science community will use the OceanObs’19 white paper to establish a framework and implementation plan for a collaborative NZ ocean observing system (NZ-OOS). Co-production of ocean knowledge with Māori will be embedded in this national strategy for growing a sustainable, blue economy for NZ. The strengths of an observing system for a relatively small nation come from direct connections between the science impetus through to users and stakeholders of an NZ-OOS. The community will leverage off existing ocean observations to optimise effort and resources in a system that has historically made limited investment in ocean observing. The goal of the community paper will be achieved by bringing together oceanographers, data scientists and marine stakeholders to develop an NZ-OOS that provides best knowledge and tools to the sectors of society that use or are influenced by the ocean.

The Ocean Enterprise – understanding and quantifying business activity in support of observing, measuring and forecasting the ocean

ABSTRACTSustained ocean observations, measurements and models provide a wide range of societal benefits underpinning the safety, operational and compliance needs of beneficiaries that operate around, on and under the ocean (In the context of this paper, the term ‘ocean’ is defined as encompassing the global ocean, enclosed seas and the US Great Lakes.) They also provide an essential input to ocean scientific research and the effective protection of the marine environment. Delivering the means to collect and use ocean data and information on a sustained basis constitutes a significant business undertaking. The companies that enable sustained ocean observation, measurement and forecasting, and deliver its benefits as commercial services, combine to create a unique and growing industry cluster; the Ocean Enterprise. Ocean Enterprise businesses underpin the ability to provide societal benefit from sustained ocean observations, measurements and models, as well as delivering significant economic and employment benefits in their own right. In this paper, we describe a systematic evaluation of the scale, scope and characteristics of the Ocean Enterprise in the United States. We explore the ways in which this industry cluster interacts with the US Integrated Ocean Observing System and how the United States Ocean Enterprise compares to that of the United Kingdom.

Predicting outcomes in patients with advanced non-small cell lung cancer enrolled in early phase immunotherapy trials

ObjectivesImmunotherapy (IO) has altered the non-small cell lung cancer (NSCLC) therapeutic landscape. However, the majority of patients do not respond to immune-checkpoint blockade, and subsequently either receive further chemotherapy or are referred for clinical trials. Here we examined the outcomes and predictors of response to IO in early phase clinical trials. Materials and methodsWe analyzed the records of 74 patients with metastatic NSCLC that were enrolled on phase 1 IO trials within MD Anderson Cancer Center from 1/2010 to 7/2017. ResultsThe median age was 68, with a median follow-up of 12.3 months. The median lines of prior therapy was three. There were 53 patients who did not receive any IO as a prior line of treatment with a mOS of 8.2 months and mPFS of 3.4 months. There were 21 patients who progressed on a prior IO agent and subsequently went on an IO study with a mOS of 10.5 months and mPFS of 4.3 months, which was similar to patients who did not receive IO OS HR 0.81 (P = .51) and PFS HR 0.85 (P = .59). Royal Marsden Hospital (RMH) prognostic score >1 was predictive of decreased OS HR 3.59 (P = .014) although PFS was not statistically different. MDACC prognostic score was predictive of both OS HR 3.39 (P = .0002) and PFS HR 1.9 (P = .030). ANC/ALC ratio (NLR) of >6 was predictive of decreased survival mOS 3.2 months compared to NLR <6 mOS 11 months; HR 3.0 (P = .0023). ConclusionsIn our heavily pretreated patient population with NSCLC, early phase clinical trials with IO demonstrated similar outcomes to those seen in larger clinical studies that also used immune checkpoint inhibitors. The addition of NLR to RMH and MDACC prognostic scores can identify patients with poor overall outcomes treated with early phase IO studies.