The Ocean Observatories Initiative (OOI) includes sensors that measure key biogeochemical properties (pH, pCO2, bio-optics, nitrate, dissolved oxygen) on both moored and mobile autonomous platforms across arrays in the Atlantic, Pacific and Southern Oceans. These sensors provide enormous potential to support the oceanographic community in studying a wide range of important interdisciplinary questions. However, OOI biogeochemical sensor data have thus far been underutilized by the oceanographic community, as the application of these rich data streams to quantify biogeochemical fluxes and answer many questions of scientific interest (e.g., rates of air-sea CO2 flux, productivity, and export; comparison across sites; monitoring of long-term changes) require effective calibration and validation, including post-deployment human-in-the-loop processing. To broaden the use of OOI biogeochemical sensor data and increase community capacity to produce analysis-ready data products, we have acquired NSF support to bring together scientists with expertise in biogeochemical sensor calibration and analysis from both within and beyond the current OOI user community to develop guidelines and best practices for using OOI biogeochemical sensor data. These recommendations will be collated in a published white paper that will be shared with the broader oceanographic community to build data user capacity and enable new scientific applications of OOI biogeochemical sensor data. 

This activity was initially planned as a small workshop in conjunction with the 2021 Ocean Carbon & Biogeochemistry (OCB) summer workshop (June 2021 in Woods Hole, MA). Given the uncertainties related to the pandemic, we would like to identify potentially interested participants early and query their preferred level(s) and mechanism(s) of engagement with this activity to help inform our planning efforts. We anticipate that the development of best practices for different biogeochemical variable sets will require several months of commitment, likely a combination of online engagement and participation in an in-person workshop that will either take place in 2021 or 2022. We envision that members of the oceanographic community may have varied levels of interest in such an activity (e.g., development of detailed OOI sensor data processing guidelines vs. broader scientific applications of OOI biogeochemical data streams). If you have any interest in potentially participating in this activity at any level, please fill out this Google form. Responses received by mid-October are greatly appreciated.

Additional information and questions about this activity can be directed to Hilary Palevsky (palevsky@bc.edu), Sophie Clayton (sclayton@odu.edu), and Heather Benway (hbenway@whoi.edu).

 

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On 16 September at 4 pm Eastern, Ocean Data Labs will kick off it fall webinar series: Ocean Data Labs Plus, a webinar series for Community College and University Professors teaching oceanography or geosciences courses. The series opener will be “New You Can Use,” hosted by the OOI Data Labs Project Team and special guests.

The webinar will explore how the Data Labs Project can support your efforts to introduce big data into your undergraduate courses.  Join the Team to find out about newly-developed interactive online data-focused activities that are grounded in learning science – and consider how to effectively incorporate them into your courses. Check out the Ocean Data Lab’s  online collection of data explorations and data nuggets in advance, and bring your questions and ideas.  Each webinar will last about 60-75 minutes and is meant to be more of an interactive discussion.

Register: https://rutgers.zoom.us/meeting/register/tJApfuGoqjItGtbfEBMLQFf9MNkZTDCVGUdp

 

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To help make OOI data more accessible, useable, and easily integrated into research and classrooms, the OOI data team has spent the last year developing a new tool that will allow users to discover the data required to meet their needs.  The new “Data Explorer” has been undergoing user testing for the past three months and will be ready for broad distribution in early October.

Data Explorer will allow users to search and download cabled, uncabled, and recovered data, compare datasets across regions and disciplines, generate and share custom data views, and download full data sets using ERDDAP.

“We are really excited about the launch of Data Explorer version 1,” explained Jeffrey Glatstein, head of OOI’s cyberinfrastructure, who guided a team of data and visualization experts in developing the tool. “It is an excellent tool that offers a variety of ways for researchers, educators – and others interested in ocean observations—to use OOI data to answer their ocean observation data questions. What we’ve learned over the test period is that additional refinements will be needed, but we first want input from the community, to help identify and prioritize the most important ones.  Subsequent versions will build upon this first release to make the Data Explorer the primary tool to explore OOI data.”

Data Explorer contains physical, chemical, geological, and biological ocean observation data collected in near real time. Glatstein and the OOI Data Team worked with Axiom Data Science to develop a system that is both powerful yet user friendly.

Stay tuned. The launch is set for the beginning of October 2020.

 

 

 

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The OOI Ocean Data Labs team is looking for instructors of introductory oceanography courses to “test drive” a collection of new online laboratories that focus on important oceanographic themes and topics using OOI data.

They are seeking a pilot implementation team of 14-16 faculty to implement two labs with students this Fall.  They are offering a $750 stipend, which includes a training webinar, detailed feedback and evaluation, and a wrap-up session.  The implementation must be completed by December 2020.

Beginning in January 2020, a team of faculty contributors compiled a sequence of OOI Data Labs into an online laboratory manual.  It includes topics in biological, chemical, physical and geological oceanography for use in typical Introductory Oceanography courses.  The manual is a collection of eight lab exercises, with built-in assessments, and accompanying instructor guides.

Applications are due Sunday 9 August 2020. Apply here.

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[media-caption type="image" path="https://oceanobservatories.org/wp-content/uploads/2020/07/Thank-you2.jpg" link="#"] Sixteen students spent eight intensive weeks during this year’s virtual REU program. Credit: Janice McDonnell.[/media-caption]

Two weeks. That is the amount of time Janice McDonnell and Sage Lichtenwalner, Co-PIs of the OOI Ocean Data Lab Project, had to create an eight-week intensive, hands-on virtual program for Research Experience for Undergraduates (REU) students, who couldn’t attend their original programs due to COVID-19 restrictions. McDonnell and Lichtenwalner jumped in with both feet and successfully pulled together a program for 16 undergrads from 16 institutions that will wrap up on July 31st. Not only did they have to develop a curriculum in short order, they recruited 17 mentors, who provided one-on-one mentoring for each of the REU students.

In 14 days, McDonnell and Lichtenwalner, working with colleagues at the Rutgers RIOS REU, developed a curriculum, which included two two-hour workshop sessions on Zoom every day for the first two weeks. The workshop was followed by six weeks where students focused on a research project using oceanographic data to answer a scientific question. They were helped by REU leaders and mentors along the way.

The initial workshop focused on students using a “baby data set” before working on something as complex as an OOI dataset or other similarly large dataset. “Initially, we gave them mini research projects that could be done in two weeks.  This allowed the students to be collaborative and interactive, while learning Python as a tool using data to answer questions about the ocean,” explained McDonnell.

The key to the program’s success was keeping it engaging.  The curriculum mixed up content, approach, and activities to ensure students stay involved on and off the screen. The team used a tactical approach – starting where students are and building upon their level of understanding. They incorporated a lot of different approaches, including think-pair-shares and an activity from the Right Question Institute, another NSF-funded project, which guides people to ask better research questions.

“We were constantly looking for opportunities to be interactive, reflective, and to give students the opportunity to apply their knowledge,” added McDonnell.

Another technique used were Zoom breakout groups to supplement group interaction. These breakout sessions provided students with opportunities to work together, with mentors, and to get to know each other.

Breakout sessions were also used to meet members of a career panel in virtual personalized sessions.“The career panel for this REU cohort was much more diverse than it is typically.  The virtual nature of the interaction made it possible for people from all over the country to join in and participate,” said Lichtenwalner.  “We facilitated it in a nice round robin sort of way using Zoom’s breakout function. Students chose their top choices, then met with them either individually or with another student.  This gave them an incredible opportunity to meet people in careers that they might not otherwise have access to.”

“I’m really proud of our REU,” said McDonnell. “It’s not easy to teach online but good learning can, and does, happen online and we were able to do that. And the collaboration that took place was really the secret sauce for making this all work. NSF program officer Lisa Rom and Science Assistant Rennie Meyers were committed to and worked really hard to find a solution to make the REU program happen in the middle of a pandemic.  The students were great and so excited about the opportunity that we put together for them. And, the mentors went above and beyond the call of duty to help make this program work for the students.”

Each week, for example, one mentor, Dr. Jessica Carriere-Garwood, of Rutgers University introduced her students to people in her professional circle at lunch time each week, with the opportunity to talk about what the students are doing and their interests. “That doesn’t always happen in a regular REU. There are a lot of pluses and minuses of being virtual and this was certainly one of the pluses,” added McDonnell.

Ed Dever, one of the mentors from Oregon State University, had this to say about his mentoring experience: “Janice and Sage did a remarkable job spinning this REU up on short notice. They mentored not just the students, but the mentors (well, at least this mentor!). Janice, Sage, and Christine Bean did an amazing job of building a virtual community of students and mentors on the fly. This virtual community provided a unique experience to the students in that the community was much broader than an in-person REU at a single institution. It took all of us out of our comfort zones and helped us grow. Throughout the whole process, Sage patiently guided REU students in technical aspects of using Python to access and analyze data.”

The REU cohort will finish their research projects and present on 30-31 July.  Of the 16 students, eight are using data from the OOI.

Citing the success of this first virtual REU, the team’s National Science Foundation (NSF) program officer Rom pondered “Why don’t we do this all the time, even if there isn’t a pandemic?“

Based on the successful experience this summer, NSF’s Division of Ocean Sciences is encouraging REU proposals for virtual REU’s, and especially those that use OOI data. The deadline is August 26th this year. Apply here.

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A new website of curated OOI datasets, called Data Nuggets, has launched.  It contains valuable resources ready for integration into educational activities. The nuggets explore various concepts common in upper-level high school and introductory college courses and are designed and packaged to be readily accessible to educators to integrate into their existing curricula.  Datasets were selected based on their quality and alignment with a broader OOI Science Theme.

The nuggets were created as part of the National Science Foundation-funded OOI Synthesis & Education project, Ocean Data Lab,  conducted by Rutgers University and led by the Consortium for Ocean Leadership.

For now, four data nuggets are available:

  • 2015 Axial Seamount Eruption
  • Seasonal Phytoplankton Blooms at High Latitudes
  • Flux of CO2 Between Ocean and Atmosphere
  • Seasonal Mixing of the Irminger Sea Water Column

The material provided in each nugget ranges from a description of scientific relevance to high resolution graphs to how use Python to pull and use OOI data in the classroom.  The nuggets are designed to support educators as they design their own activities using OOI data.

More nuggets will be continually added so check the website often.

 

 

 

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A team from Woods Hole Oceanographic Institution (WHOI) was onboard the R/V Neil Armstrong at the Pioneer Array, about 75 nautical miles south of Martha’s Vineyard in the Atlantic, deploying equipment and collecting data. Due to COVID-19 restrictions, the number of the science party onboard was limited. These limits prevented participation by the Northeast U.S. Shelf Long-Term Ecological Research (NES-LTER) team, whose members would have been onboard under normal circumstances.

But through an innovative use of onboard technology, WHOI’s Shipboard Scientific Services Group made it possible for the NES-LTER team to receive data and images of phytoplankton and microzooplankton in near-real-time along the cruise track. The data were collected by Imaging FlowCytobots (IFCBs), which provide long term, high-resolution measurements of phytoplankton abundance and their cell properties. The data can be viewed here.

Said WHOI researcher Taylor Crockford from her research laboratory on land, who beta-tested the data transmission with the WHOI onboard team, “In this challenging time of the Coronavirus, we are thankful for this opportunity to continue long-term research into the productivity and food web on the Northeast U.S. Shelf while the cruise was underway.”

The Ocean Observatories Initiative is funded by the National Science Foundation.

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Given the significant importance of understanding and modeling levels of carbon dioxide in our atmosphere (and its potential sources and sinks), Ocean-Atmosphere Exchange and Global Biogeochemistry and Carbon Cycling are two of the OOI’s primary science themes. We address these themes in part through measurements of the air and surface water partial pressure of carbon dioxide (pCO2).  Chris Wingard, the OOI Endurance Array Data Lead, recently completed an in-depth assessment of pCO2 data returned during the first four years of Endurance Array operations. These measurements were made using the Pro-Oceanus CO2-ProTM Atmosphere pCO2 sensor. By measuring the partial pressure of CO2 gas in both the air and surface water, researchers can estimate estimate surface flux of CO2 using data from this instrument. 

Wingard developed a protocol based on cross-comparisons of overlapping deployments of this sensor, comparing these with independent shipboard pCO2 measurements (including CTD samples and samples taken underway using flow-thru systems), and externally sourced air and surface water pCO2 measurements (e.g. from the LDEO Underway Database).  This array of sampling techniques served to confirm the quality and scientific applicability of the Endurance Array pCO2 measurements.

He reported the results of this assessment at a poster session at the recent Ocean Sciences 2020 meeting held this past February in San Diego, CA. The protocol is largely applicable to the same suite of measurements made using the Pro-Oceanus sensor on moorings deployed in the OOI Pioneer, Irminger Sea, Southern Ocean, and Argentine Basin Global Arrays. The MATLAB code and data used to download, process, merge, and cross-compare the data used in this assessment are available online for use.

Both the air and surface water measurements and the flux estimates used in this assessment are available through the OOI Data Portal. Endurance Array air and surface water pCO2 measurements are made at four locations distributed across the Oregon and Washington shelf and slope within the northern California Current Marine Ecosystem.

Other sources of Endurance Array-specific data include the most recent 60 days of the Endurance Array’s air and surface water pCO2 data are available on the NANOOS Visualization System (NVS) and the Global Ocean Acidification Observing System Data Portal (GOA-ON).

Figure 1: Surface water () and air pCO2 (, observed and , array average) measurements from 2015-04-01 through 2019-12-31 for the four moorings. The plots also show the distribution of discrete sample (*) and LDEO V2018 (O) data that coincide with each mooring. The data plotted have had human-in-the-loop (HITL) QC flags applied to remove points marked as suspect or failed. Beyond smoothing the data records and the estimation of an array averaged air pCO2 (), no further corrections were applied to the data. Note the high degree of variability during the summer months in the surface water pCO2 measurements for CE02SHSM, which are similar to other observations made on the Oregon Shelf (Evans et al., 2011).

Figure 2: Focused view (upper panel) of the Spring 2017 deployment (#5) of CE02SHSM showing the observed offsets between the surface water pCO2 measurements () and the discrete samples (*) and LDEO V2018 (O). Detailed views in the lower two panels, provide a better picture of the observed offsets during the periods of over-lapping deployments; between deployments 4 and 5 (lower left) and deployments 5 and 6 (lower right). Prior to using the OOI pCO2A data, users are strongly encouraged to conduct such cross-comparisons. The independent measurements obtained by the separate systems, and the close agreement between them, provide measures of confidence in the accuracy and applicability of the data.

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[video width="670" height="384" m4v="/wp-content/uploads/2020/04/OOI-F6.mp4"][/video]

OOI data team members have  developed a new toolbox for downloading data from the Machine-to-Machine (M2M) interface using MATLAB, making data access as easy as 1, 2, 3. The work expands on the existing tools available on OOI. This new toolbox covers data from moorings, gliders, and profilers in the OOI Coastal Arrays and can easily be extended to other research platforms. A video tutorial on how to use this new tool is provided above. (A pdf of the tutorial is provided below).

In three short steps – define the mooring, node, and instrument – users can easily and quickly access relevant OOI data. “This new approach eliminates some steps and makes it easy for anyone to find and access data they are looking for, “said Jonathan Fram, OOI Endurance Array Project Manager at Oregon State University (OSU). “We found this new approach really streamlined data access using the M2M interface and we are certain other OOI data users will find it similarly helpful.”

Developed by OOI OSU team members, Craig Risien and Russ Desiderio, these new tools are part of our ongoing effort to simplify access to OOI data to encourage its broader integration into scientific research and classroom content. A tutorial showing how to use MATLAB to access OOI data can be viewed here.

Other members of the OOI OSU team, Chris Wingard and Ian Black, are testing Python and R tools to explore OOI data, as well. Once the tools have been tested and vetted, they will be available along with other community-generated tools here.

This new tutorial adds to others that have been developed to help users integrate OOI data into their science.

OOI Video Tutorial PDF

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“Just like lightning,” in one-minute presentations, 15 scientists shared amazing ways they are using OOI data in scientific investigations and in the classroom. This round of lightning talks capped the Ocean Observatories Initiative Facility Board’s (OOIFB) Town Hall at the 2020 Ocean Sciences Meeting on 20 February, demonstrating the multiple and creative ways OOI data are being used to answer key science questions in a changing environment.

The presentations ranged from how students are using real-life and real-time OOI data to advance their understanding of scientific principles to how researchers are using OOI data to identify the presence of marine life by sound to how modelers are making OOI data more accessible and useable.

“We were simply thrilled by the depth, breadth, and range of applications of OOI data shown during this lightning round,” Kendra Daly, chair of the OOIFB.  “We were pleased so many presenters were willing to accept the challenge. This enthusiastic response clearly shows that OOI data are being used to help answer important science questions.”

Brief summaries of the talks are presented below.

Advancing science

Isabela Le Bras, Scripps Institution of Oceanography, reported on a recent article in Geophysical Research Letters, where she and her colleagues describe how they used data from the Irminger Sea Array moorings (2014–2016) to identify two water masses formed by convection and showing that they have different rates of export in the western boundary current. Upper Irminger Sea Intermediate Water appears to form near the boundary current and is exported rapidly within three months of its formation. Deep Irminger Sea Intermediate Water forms in the basin interior and is exported on longer time scales. The subduction of these waters into the boundary current is consistent with an eddy transport mechanism. The eddy transport process is more effective for the waters cooled near the boundary current, implying that cooling near boundary currents may be more important for the climate than has been appreciated to date.

Since 2017, Clare Reimers and Kristen Fogaren, Oregon State University, have been working to assess seasonal variability in benthic oxygen consumption and the contribution of benthic respiration to the development of hypoxic conditions in the northern California Current, using time series data from the OOI Endurance Array. Reimers and Fogaren measured benthic oxygen consumption rates using in situ eddy covariation techniques and ex situ core incubations, during a series of ten cruises that allowed sampling near the Endurance Oregon Shelf and Inshore stations, in all seasons. During these cruises, the researchers used real-time data provided by the Endurance Array to optimize the settings for their eddy covariance deployments. They are now examining property-relationships in discrete bottom water samples collected during the cruises and using data from OOI assets to help separate influences of mixing and biochemical processes in the water column and sediments. The researchers are also synthesizing benthic flux measurements and placing these rates in the context of cross-shelf glider measurements and benthic node time series.

Adrienne Silver, University of Massachusetts Dartmouth provided details about how she is using Pioneer Array data to learn more about the influence of warm core rings on Shelf break circulation.  Results from a 40-year Warm Core Ring census show a regime shift in warm core ring formation at 2000, with the number of rings doubling from an average of 18 rings per year (during 1980-1999) to 33 rings per year (during 2000-2019). This regime shift creates a large increase in the amount of warm salty water being transported northward toward the shelf from the Gulf Stream. The preferred pathway of these rings, or the Ring Corridor seem to indicate their proximity to the shelf break and the Pioneer array during their lifetime. The goal of Silver’s project is to understand how these warm core rings affect the shelf break exchange while traveling along the shelf. A large focus of the study will be on the salinity intrusion events which might be sourced from these warm core rings.

Liz Ferguson, CEO and founder of Ocean Science Analytics, is using data from OOI’s Coastal Endurance and Regional Cabled Arrays to determine the variables that are most useful for assessing the ecosystem of this region and obtaining baseline information on marine mammal acoustic presence for use in monitoring.   Using long term physical and biological data provided by these arrays, Ferguson is assessing long-standing shifts in the ecology of this coastal and offshore environment by associating physical oceanographic variables with the vocal presence of marine mammals using the broadband hydrophone data. Temporal changes in the occurrence of marine mammal species such as killer whales, sperm whales and dolphins can be used as an indicator of ecosystem shifts over time. She is analyzing passive acoustic data provided by the OOI arrays to determine the presence of vocally active marine mammal species, identify their spatial and temporal use of these sites, and combining this information with the physical oceanographic variables to assess the ecological characteristics associated with marine mammal occurrence.

Sam Urmy of the Monterey Bay Aquarium Research Institute (MBARI) also is using OOI acoustical data in his research.  Using an upward-looking echosounder and a high-frequency hydrophone at MBARI’s Monterey Accelerated Research System, Urmy showed how small animals in the epipelagic and mesopelagic altered their behavior in response to predators.  These responses included abrupt dives during bouts of foraging by dolphins, changes in depth to avoid predatory fish schools, and dramatic alterations to daily vertical migratory behavior. Continual observations of the mesopelagic with active and passive acoustics are revealing several dynamic predator-prey interactions in an ecosystem that is typically thought of as relatively slow and static.

Veronica Tamsitt of the University of New South Wales used the OOI’s Southern Ocean mooring and the Southern Ocean Flux Site (SOFS, in the Southeast Indian) to study the Sub Antarctic Mode water (SAMW) formation. Tamsitt’s and her colleagues findings were reported in the Journal of Climate in March 2020. Using data from the two mooring locations, the researchers were able to compare and contrast characteristics and variability of air-sea heat fluxes, mixed-layer depths, and SAMW formation. The researchers found that inter mixed-layer depth anomalies tended to be intermittent at the two moorings, where anomalously deep mixed layers were associated with anomalous advection of cold air from the south, and conversely shallow mixed layers correspond to warm air from the north. Both the winter heat flux and mixed-layer depth anomalies, however, showed a complex spatial pattern, with both positive and negative anomalies in both the Indian and Pacific basins that Tasmitt and colleagues relate to the leading modes of climate variability in the Southern Ocean.

Editor’s note: The Southern Ocean Array was decommissioned in January 2020.  Its data, however, are still available for use by researchers, students, and the public.

Bringing OOI data into the classroom

Sage Lichtenwalner, Department of Marine and Coastal Sciences at Rutgers, The State University of New Jersey reported on the progress of the Ocean Data Labs Project. This project is a Rutgers-led effort to build a “Community of Practice” to tap into the firehose of OOI ocean data to support undergraduate education. To date, the project has hosted four “development” workshops that introduced participants to the OOI, conducted data processing with Python notebooks, and shared effective teaching strategies, in addition to a series of introductory workshops and webinars.  As part of the development workshops, 56 university, college, and community college faculty designed 19 new “Data Explorations,” featuring web-based interactive “widgets” that allow students to interact with pre-selected data from the OOI. The project also sponsors a series of webinars, a fellowship program, and is compiling a library of resources (including coding notebooks, datasets, and case studies in teaching) to help the community.

Cheryl Greengrove, University of Washington Tacoma, summarized an article in the March issue of Oceanography that she and colleagues from across the United States wrote detailing ways to integrate OOI data into the undergraduate curriculum. The wealth of freely-accessible data provided by OOI platforms, many of which can be viewed in real or near-real time, provides an opportunity to bring these authentic data into undergraduate classrooms. The TOS article highlights existing educational resources derived from OOI data that are ready for other educators to incorporate into their own classrooms, as well as presents opportunities for new resources to be developed by the community. Examples of undergraduate introductory oceanography OOI data-based lessons using existing interactive online data widgets with curated OOI data on primary productivity, salinity, and tectonics and seamounts are presented, as well as ways to use OOI data to engage students in undergraduate research. The authors provide a synthesis of existing tools and resources as a practical how-to guide to support new resource development and invite other educators to develop and implement new educational resources based on OOI data.

Matthew Iacchei, Hawaiʻi Pacific University, presented how he has been integrating OOI data explorations to supplement his upper division oceanography lecture and labs with real data from around the world. Last semester, he had students explore patterns of dissolved oxygen and impacts of anoxia at the coastal endurance array in Oregon and compare that data to dissolved oxygen data the students collected in Kāneʻohe Bay, Hawaiʻi. This semester, students are working through two exercises with OOI data as part of their primary productivity lab (perfect, as it is now online!). Students will compare vertical profiles from Hawaiʻi with seasonal variations across the world, and will compare latitudinal drivers of primary production using data from a time-series from the Southern Ocean Array.

Strengthening OOI data usability

Wu-Jung Lee, a senior oceanographer at the Applied Physics Laboratory, University of Washington, is using data collected by the OOI to develop new methodologies for analyzing long-term ocean sonar time series. In a project funded by the National Science Foundation, she and her colleagues show that unsupervised matrix decomposition techniques are effective in discovering dominant patterns from large volumes of data, which can be used to describe changes in the sonar observation. Their preliminary analysis also show that the summaries provided by these methods facilitate direct comparison and interpretation with other ocean environmental parameters concurrently recorded by the OOI. A parallel effort that spun out of this project is an open-source software package echopype, which was created to enable interoperable and scalable processing of biological information from ocean sonar data.

As part of the Rutgers Ocean Modeling Group, in conjunction with University of California Santa Cruz, John Wilkin and Elias Hunter are delivering a high-resolution data assimilative ocean model analysis of the environs of the Pioneer Coastal Array, including a systematic evaluation of the information content of different elements of the observing network. The project uses the Regional Ocean Modeling System with 4-Dimensional Variational data assimilation. To produce a comprehensive multi-year (2014-2018) analysis required them to assimilate all available Pioneer CTD data, with quality checks, in a rolling sequence of data assimilation analysis intervals. They used three days of data in each analysis, which required queries to with a time range constraint and relevant platform (i.e. glider, profiler, fixed sensor), migrating  all Pioneer CTD data (wire following profilers, gliders, fixed sensors, plus ADCP velocity) to an ERDDAP server. The simple graphing capabilities in ERDDAP allow quick browsing of the data to trace quality control or availability issues, and ERDDAP provides a robust back-end to other web services to create more sophisticated graphical views, or time series analysis. Using the ERDDAP Slide Sorter tool, they operate a quick look Control Panel to monitor the data availability and quality.

Mitchell Scott and colleagues Aaron Marburg and Bhuvan Malladihalli Shashidhara at the University of Washington, are studying how to segment macrofauna from the background environment using OOI data from the Regional Cabled Axial Seamount Array. Their long-term goal is to use an automated approach to study species variation over time, and against other environmental factors. Their initial step focuses specifically on scale worms, which are very camouflaged, making them difficult to detect. To address this, the researchers initially used a deep learning model, called U-Net, to detect and localize the scale worm locations within an image. To address the high rate of false positives using this model, they added an additional classifier (a VGG-16 model) to verify the presence of scaleworms.  This combined, applied approach proved feasible for scale worm detection and localization. Yet because the environment of the Axial Seamount is so dynamic due to the growth and decay of chimneys at the site and resulting changes in bacteria and macrofauna present, they found the performance of the model decreased over time.

Weifeng (Gordon) Zhang of Woods Hole Oceanographic Institution has been using Pioneer Array data to understand the physical processes occurring at the Mid-Atlantic Bight shelf break, including the intrusion of Gulf Stream warm-core ring water onto the shelf and the ring-induced subduction of the biologically productive shelf water into the slope sea. His findings were reported in a Geophysical Research Letters paper where data from the Pioneer Array moorings and gliders demonstrated the anomalous intrusion of the warm and salty ring water onto the shelf and revealed the subsurface structure of the intrusion. Zhang also shared findings reported in the Journal of Geophysical Research: Oceans where data from the Pioneer Array showed a distinct pattern of relatively cold and fresh shelf water going underneath the intruding ring water. These results show the subduction of the shelf water into the slope sea and a pathway of shelf water exiting the shelf. In both instances, Zhang and his colleagues used computer modeling to study the dynamics of these water masses. These two studies together suggest that shelf break processes are complex and require more studies in the region.

Hilary Palevsky of Boston College presented results from an ongoing project funded by the National Science Foundation’s Chemical Oceanography program, using biogeochemical data from the OOI Irminger Sea Array. Analysis of dissolved oxygen data on OOI Irminger Sea gliders and moorings from 2014-2016 showed the importance of biogeochemical data collected over the full seasonal cycle and throughout the entire water column, due to the influence of subsurface respiration and deep winter convection on biological carbon sequestration. The OOI Irminger Sea array is the first source of such full-depth year-round data in the subpolar North Atlantic. To quantitatively evaluate the annual rate of carbon sequestration by the biological pump and the role of deep winter convection, Palevsky and colleague David Nicholson of the Woods Hole Oceanographic Institution collaborated with OOI to improve the calibration of oxygen data at the Irminger Sea array by modifying the configuration of glider oxygen sensors to enable calibration in air each time the glider surfaces, which improves the accuracy and utility of the data collected both from gliders and from moorings. Palevsky presented preliminary results demonstrating successful glider air calibration at the Irminger array in 2018-2019 as well as work by student Lucy Wanzer, Wellesley College, demonstrating the importance of well-calibrated oxygen time series data to determine interannual variability in rates of subsurface respiration and deep winter ventilation in the Irminger Sea.

 

 

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