OD006
Data Science for Modern Oceanography: Statistics, Machine Learning, Visualization, and More

Session ID#: 85203

Session Description:
Oceanographic research in today's world increasingly relies on analyzing multiple datasets, including ship-based measurements, profiles from autonomous instruments such as floats and gliders, satellite remote sensing data, as well as output from models and state estimates. These datasets are growing larger and more complex every day, and future advances in ocean observing and modeling will add significantly to the quantity and variety of "Big Data" across all disciplines of oceanography. Innovative statistical methods, computational techniques, and data visualizations will be needed in the coming decades to distill these data and to extract maximum scientific understanding. New developments in statistics and data science have the potential to transform our knowledge of the ocean across many spatial and temporal scales and can help address various emerging challenges in oceanographic data analysis. This session solicits studies on using the latest techniques from statistics, machine learning, and visualization to analyze datasets in oceanography and related areas of climate science, both those currently existing as well as those that will be available in the near future. Presentation topics may include computational methods for large datasets; software platforms and tools; model diagnostics, validation, and parameterization; spatio-temporal interpolation; uncertainty quantification; classification and regression techniques; pattern recognition; as well as other advanced data science topics.
Index Terms:

1920 Emerging informatics technologies [INFORMATICS]
1942 Machine learning [INFORMATICS]
1986 Statistical methods: Inferential [INFORMATICS]
1994 Visualization and portrayal [INFORMATICS]

Primary Chair:  Alison R Gray, University of Washington, School of Oceanography, Seattle, WA, United States
Co-chairs:  Mikael Kuusela, Carnegie Mellon University, Department of Statistics and Data Science, Pittsburgh, PA, United States and Donata Giglio, University of Colorado Boulder, Department of Atmospheric and Oceanic Sciences, Boulder, CO, United States
Primary Liaison:  Alison R Gray, University of Washington, School of Oceanography, Seattle, WA, United States
 
The thermohaline modes of the global ocean (635903)
Etienne Pauthenet1, Fabien Roquet2, Gurvan Madec1, Jean-baptiste Sallee1 and David Nerini3, (1)Sorbonne Université, LOCEAN‐IPSL, CNRS/IRD/MNHN, Paris, France, (2)University of Gothenburg, Department of Marine Sciences, Gothenburg, Sweden, (3)Mediterranean Institute of Oceanography, Marseille, France
 
The NOAA/NCEI Data Assembly Center for NOAA/OMAO’s ship and aircraft fleet (636426)
Chris R Paver, NOAA National Environmental Satellite, Data, and Information Service, Silver Spring, MD, United States, Solomon Tadele, NOAA Office of Marine and Aviation Operations, Silver Spring, MD, United States and Fred Katz, NOAA National Environmental Satellite, Data, and Information Service, Silver Spring, United States
 
World Ocean Database and WODSelect: a nexus between aggregation, dissemination, and utilization of ocean profile data (637040)
Tim Boyer, National Centers for Environmental Information, NESDIS/NOAA, Silver Spring, MD, United States
 
Deep Learning Algorithm Forecasts Shellfish Toxicity at Site Scales in Coastal Maine (637972)
Isabella Grasso1, Stephen D Archer2, Craig Burnell3, Kohl Kanwit4, Benjamin Tupper2 and Nicholas Record2,5, (1)Clarkson University, Department of Mathematics, Potsdam, NY, United States, (2)Bigelow Laboratory for Ocean Sciences, East Boothbay, ME, United States, (3)Bigelow Laboratory for Ocean Sciences, United States, (4)Maine Department of Marine Resources, United States, (5)University of Maine, Portland, ME, United States
 
Responses of Marine Phytoplankton Communities to Environmental Changes: New Insights From a Niche Classification Scheme (640080)
Wupeng Xiao1, Edward A. Laws2, Yuyuan Xie3, Lei Wang4, Xin Liu1, Jixin Chen5, Bingzhang Chen6 and Bangqin Huang1, (1)Xiamen University, State Key Laboratory of Marine Environmental Science, Xiamen, China, (2)Louisiana State University, School of the Coast & Environment, Baton Rouge, LA, United States, (3)Xiamen University, China, (4)Xiamen University, State Key Lab of Marine Environmental Science, Xiamen, China, (5)Xiamen University, State Key Laboratory of Marine Environmental Sciences, Xiamen, China, (6)Japan Agency for Marine-Earth Science and Technology, RCGC, Yokohama, Japan
 
A New Bottom Water Climatology Using a Stacked Random Forest and Objective Mapping Approach (641915)
Paige D Lavin, University of Washington, Oceanography, Seattle, WA, United States and Gregory C Johnson, Pacific Marine Environmental Laboratory, Seattle, WA, United States
 
Application of Gaussian mixture distribution model for the pattern recognition of Kuroshio current path (644532)
Kunihiro Aoki, Yasumasa Miyazawa, Tsutomu Hihara and Toru Miyama, JAMSTEC, Application Laboratory, Yokohama, Japan
 
Spatio-temporal changes in upper ocean heat content estimates: an internationally-coordinated intercomparison (644883)
Abhishek Savita, Institute for Marine and Antarctic Studies, University of Tasmania, Antarctic Climate and Ecosystems Cooperative Research Centre, Hobart, TAS, Australia, Catia M Domingues, Institute for Marine and Antarctic Studies, University of Tasmania, Antarctic Climate and Ecosystems Co-operative Research Centre, Hobart, Australia, Tim Boyer, NOAA/National Oceanographic Data Center, Washington, DC, United States, Simon A Good, Met Office, Exeter, United Kingdom, Viktor Vladimir Gouretski, University of Hamburg, Hamburg, Germany, Masayoshi Ishii, Japan Meteorological Agency, Tsukuba, Japan, Gregory C Johnson, Pacific Marine Environmental Laboratory, Seattle, WA, United States, John M Lyman, JIMAR/PMEL, Seattle, WA, United States, Josh K Willis, Jet Propulsion Laboratory, Pasadena, CA, United States, Didier Monselesan, CSIRO Oceans and Atmosphere, Hobart, TAS, Australia, John Antonov, University Corporation for Atmospheric Research, Boulder, CO, United States, Susan Anne Wijffels, Woods Hole Oceanographic Institution, Woods Hole, MA, United States, Rebecca Cowley, CSIRO Marine and Atmospheric Research, Hobart, Australia, Simon James Marsland, CSIRO Ocean and Atmospheric Research Aspendale, Aspendale, VIC, Australia, Peter Dobrohotoff, CSIRO Ocean and Atmospheric Research Aspendale, Ocean and Atmosphere, Melbourne, VIC, Australia, Will R Hobbs, University of Tasmania, Hobart, TAS, Australia and John Church, University of New South Wales, Climate Change Research Centre, Sydney, NSW, Australia
 
A 2DVAR Blending Method for CYGNSS Wind Speed Observations (645092)
Xiaochun Wang1, Zhijin Li2, Yuchan Yi3, C.K. Shum3 and Joel T Johnson4, (1)University of California Los Angeles, Los Angeles, CA, United States, (2)JPL, Pasadena, CA, United States, (3)The Ohio State University, Division of Geodetic Science, School of Earth Sciences, Columbus, OH, United States, (4)Ohio State University Main Campus, Department of Electrical and Computer Enginneering, Columbus, OH, United States
 
A Multi-variables Based Mesoscale Eddy Identification Method by Deep Learning (645267)
Yingjie Liu, Yibin Ren and X. Li, CAS Key Laboratory of Ocean Circulation and Waves, Institute of Oceanology, Chinese Academy of Sciences and Center for Ocean Mega-Science, Chinese Academy of Sciences, Qingdao, China
 
Predicting Shape of Dives of Southern Elephant Seals Using Regression Tree Models (645496)
Morgan Godard, Aix-Marseille University, Mediterranean Institute of Oceanography, Marseille, France, Claude Manté, MIO-AMU CNRS, Marseille, France, Christophe Guinet, Centre d’Etudes Biologiques de Chizé (CEBC), UMR 7372 Université de la Rochelle-CNRS, Villiers en Bois, France and David Nerini, Mediterranean Institute of Oceanography, Marseille, France
 
Machine Learning (ML) enabled forecasts derived from Carbon, Silicate, and Nitrogen Ecosystem (CoSiNE) model generated climatology (646326)
Christopher Wood1, Richard W Gould Jr2, Bradley Penta3, Sergio deRada3, Sean McCarthy2 and Gregory P Behm4, (1)United States, (2)US Naval Research Laboratory, Stennis Space Center, MS, United States, (3)Naval Research Laboratory, Stennis Space Center, MS, United States, (4)High Performance Computing Modernization Program, Productivity Enhancement, Technology Transfer, and Training (PETTT), Vicksburg, MS, United States
 
Characterization of Physical and Biogeochemical Variability around the Kerguelen Plateau and across the Southern Ocean Frontal Zones: A Machine Learning Approach (646784)
Isabella Rosso1, Matthew R Mazloff1, Lynne D Talley2, Sarah G Purkey3, Natalie M Freeman4 and Guillaume Maze5, (1)Scripps Institution of Oceanography, UC San Diego, La Jolla, CA, United States, (2)Scripps Institution of Oceanography, UC San Diego, UC San Diego, La Jolla, CA, United States, (3)Scripps Institution of Oceanography, University of California San Diego, San Diego, CA, United States, (4)Scripps Institution of Oceanography, University of California San Diego, La Jolla, CA, United States, (5)IFREMER, Laboratory for Ocean Physics and Satellite remote sensing, Plouzané, France
 
A Synthetic Ensemble of Global Ocean Chlorophyll Concentration (647946)
Geneviève Elsworth, University of Colorado at Boulder, Department of Geological Sciences, Boulder, United States, Nicole S Lovenduski, University of Colorado, Department of Atmospheric and Oceanic Sciences, Boulder, CO, United States, Karen A McKinnon, University of California Los Angeles, Departments of Statistics, Institute of the Environment and Sustainability, Los Angeles, CA, United States and Riley Xavier Brady, University of Colorado at Boulder, Department of Atmospheric and Oceanic Sciences, Boulder, CO, United States
 
PyEcholab: Processing Water Column Echosounder Data in the Cloud (648084)
Veronica Martinez, United States, Charles Anderson, Cooperative Institute for Research in Environmental Sciences, Boulder, CO, United States, Carrie Wall, University of Colorado at Boulder, Cooperative Institute for Research in Environmental Sciences, Boulder, CO, United States, Rick Towler, NOAA Alaska Fisheries Science Center, Seattle, WA, United States, George Cutter, NOAA Southwest Fisheries Science Center, Antarctic Ecosystem Research Division, La Jolla, CA, United States and Josef Michael Jech, NOAA Northeast Fisheries Science Center, Woods Hole, MA, United States
 
Using machine learning to improve operational wave forecasts (648627)
Jeff Hansen1, Chen Wu2, Phil Watson2 and Diana Jane Greenslade3,4, (1)University of Western Australia, Crawley, WA, Australia, (2)The University of Western Australia, Perth, WA, Australia, (3)Bureau of Meteorology, Melbourne, Australia, (4)Bureau of Meteorology, Melbourne, VIC, Australia
 
Statistics for Mapping Ocean Heat Content with Argo Floats: Modeling and Uncertainty Quantification (648701)
Mikael Kuusela, Carnegie Mellon University, Department of Statistics and Data Science, Pittsburgh, PA, United States, Donata Giglio, University of Colorado Boulder, Department of Atmospheric and Oceanic Sciences, Boulder, CO, United States, Anirban Mondal, Case Western Reserve University, Department of Mathematics, Applied Mathematics and Statistics, Cleveland, OH, United States and Michael Stein, University of Chicago, Department of Statistics, Chicago, IL, United States; Rutgers University, Department of Statistics, Piscataway, NJ, United States
 
Prediction of Sea Surface Temperature in the South China Sea by Artificial Neural Networks (649087)
Lei Guan, Li Wei and Liqin Qu, Ocean University of China, Qingdao, China
 
Echopype: Interoperable and Scalable Processing of Ocean Sonar Data (649395)
Wu-Jung Lee, University of Washington, Applied Physics Laboratory, Seattle, WA, United States, Valentina Staneva, University of Washington, eScience Institute, Seattle, WA, United States and Kavin Nguyen, University of Washington, Department of Physics, United States
 
GOANA, a Global Ocean Atlas, Neutrally Averaged (649707)
Paul M Barker, University of New South Wales, School of Mathematics and Statistics, Sydney, NSW, Australia and Trevor J McDougall, University of New South Wales, Sydney, NSW, Australia
 
The CIGOM Data Management portal (650044)
Favio Medrano and Argelia Ronquillo, Center for Scientific Research and Higher Education at Ensenada, Ensenada, BJ, Mexico
 
Non-Gaussian Process Modeling of Argo Float Data (650308)
Jonas Wallin, Lund University, Department of statistics, Lund, Sweden
 
Long-term trends in ocean chlorophyll: update from a Bayesian hierarchical space-time model (650393)
Matthew Hammond, National Oceangraphy Centre, Southampton, United Kingdom, Claudie Beaulieu, University of California Santa Cruz, Santa Cruz, CA, United States, Stephanie Henson, National Oceanography Centre, Southampton, United Kingdom and Sujit K Sahu, University of Southampton, Mathematical Sciences, Southampton, United Kingdom
 
Near real-time data management of multiplatform autonomous vehicles fleet and integration with multi-source heterogeneous data in a web-based visualization tool for data-sharing, dissemination, and operational purposes (650837)
Rubén Marrero1, Tania Morales1, Rayco Moran1, Eduardo Caudet1, Carlos Barrera2, Octavio Llinas1 and Patricia Rivera1, (1)Oceanic Platform of the Canary Islands, Telde, Spain, (2)Oceanic Platform of the Canary Islands, Underwater Vehicles, Telde, Spain
 
Novel characterization and correction of ocean model biases using sparse observations: application to surface ocean radiocarbon (650931)
Heather D Graven1, Gerald Lim1, Kei Yeung1, Joanna Lester1 and Peer Johannes Nowack2, (1)Imperial College London, Physics, London, United Kingdom, (2)Imperial College London, Faculty of Natural Sciences, Department of Physics, Grantham Institute and the Data Science Institute, London, United Kingdom
 
Data Science and Signal Processing for Drifter Data (651389)
Adam Sykulski, Lancaster University, Lancaster, United Kingdom, Jeffrey J Early, NorthWest Research Associates, Redmond, WA, United States, Jonathan M Lilly, Theiss Research, La Jolla, CA, United States, Sofia Olhede, Ecole polytechnique fédérale de Lausanne (EPFL), Switzerland and Arthur P. Guillaumin, University College London, London, United Kingdom
 
When data arrive as curves: an overview of Functional Data Analysis methods in oceanography (651523)
David Nerini, Aix-Marseille University, Mediterranean Institute of Oceanography, Marseille, France, Etienne Pauthenet, Sorbonne Université, LOCEAN‐IPSL, CNRS/IRD/MNHN, Paris, France, Pascal Monestiez, INRA Institut National de la Recherche Agronomique, Avignon, France, Christophe Guinet, Centre d’Etudes Biologiques de Chizé (CEBC), UMR 7372 Université de la Rochelle-CNRS, Villiers en Bois, France, Fabien Roquet, University of Gothenburg, Department of Marine Sciences, Gothenburg, Sweden, Madec Gurvan, Sorbonne Universités (UPMC, Univ Paris 06)-CNRS-IRD-MNHN, LOCEAN Laboratory, IPSL, Paris, France, Frédéric Ménard, IRD, France, Christophe Menkes, IRD/LOCEAN, Nouméa, New Caledonia and Arnaud Bertrand, Institut de Recherche pour le Développement (IRD), France
 
Extracting Regional and Seasonal Trends of Multiscale Energetics in the Global Ocean (651533)
Benjamin Aaron Storer, University of Waterloo, Burlington, Canada and Hussein Aluie, Los Alamos National Laboratory, Los Alamos, NM, United States
 
How to save 95% of computational load of numerical modeling in examining the coastal protection decision scenarios (651626)
Ruo-Qian Wang, Rutgers University New Brunswick, Piscataway, United Kingdom and Gaofeng Jia, Colorado State University, Civil and Environmental Engineering, Fort Collins, United States
 
Extracting nutrient - ocean state relationships from oceanic biogeochemistry simulations for macroalgae mariculture (651867)
Zhendong Cao1, Phillip J. Wolfram Jr1, Mathew E Maltrud1 and Riley Xavier Brady2, (1)Los Alamos National Laboratory, Los Alamos, NM, United States, (2)University of Colorado at Boulder, Department of Atmospheric and Oceanic Sciences, Boulder, CO, United States
 
Detecting rainfall through prediction of precipitation forcing in the salinity balance equation (651985)
Oksana Chkrebtii, United States and Frederick Bingham, University of North Carolina at Wilmington, Wilmington, NC, United States
 
Semi-Automated 3D Analysis as a Tool for Monitoring and Environmental Assessment for Large Volume Image and Video Data (652001)
Linda Gwen Waters1, Igor C S Cruz2, Nayara F Carvalho1, Guarani Cavalcanti3, Alexander Turra Sr4 and Paulo Y G Sumida1, (1)Universidade de São Paulo, Instituto Oceanografico, São Paulo, Brazil, (2)Universidade Federal da Bahia, Departamento de Oceanografia, Salvador, Brazil, (3)PETROBRAS, Research and Development Center Leopoldo Américo Miguez de Mello, Rio De Janeiro, Brazil, (4)Oceanographic Institute - University of São Paulo, Brazil
 
EchoFish - Visualizing water column sonar data (652191)
Carrie Wall, Chris Slater, Rudy Klucik, Charles Anderson and Veronica Martinez, Cooperative Institute for Research in Environmental Sciences, Boulder, CO, United States
 
CruisePack: A Tool to Facilitate Submission and Archiving of Cruise-Based Data (652568)
Charles Anderson, Cooperative Institute for Research in Environmental Sciences, Boulder, CO, United States and Brian Meyer, CIRES, Boulder, CO, United States
 
Resolving the Short-term Persistence of Oceanographic Measurements from an Autonomous Underwater Vehicle in the Central Red Sea, October 2017 (653281)
Michael Fredrick Campbell Jr and Burton H Jones, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
 
Improve Hydrodynamic Modeling for the Laurentian Great Lakes Using a Combination of Deep Learning and Data Assimilation (653458)
Pengfei Xue, Michigan Technological University, Civil and Environmental Engineering, Houghton, MI, United States, Chenfu Huang, Michigan Technological University, Houghton, MI, United States and Yilin Wang, Michigan Technological University, Houghton, United States
 
A Functional Data Approach to the Argo Project (654385)
Drew Yarger, Tailen Hsing and Stilian Stoev, University of Michigan, Statistics, Ann Arbor, United States
 
Metrics and Citations for Data and Software (654979)
Jessica Hausman1, Lewis John McGibbney2, Suresh Vannan1, Sara Bond3 and Dudee Chiang3, (1)Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States, (2)NASA Jet Propulsion Laboratory, Pasadena, CA, United States, (3)Jet Propulsion Laboratory, United States
 
On the use of the Ocean Virtual Laboratory open tools to prepare training sets for AI deep learning of ocean surface signatures (655019)
Fabrice Collard1, Lucile Gaultier2, Benjamin Holt3, Sylvain Herlédan4, Ziad El Khoury Hanna4 and Gilles Guitton5, (1)OceanDataLab, Locmaria-Plouzané, France, (2)OceanDataLab, Brest, France, (3)NASA Jet Propulsion Laboratory, Pasadena, CA, United States, (4)Oceandatalab, France, (5)OceanDataLab, Plouzané, France
 
Cluster-based ocean model evaluation on the Antarctic continental shelf (655055)
Qiang Sun1, Christopher M Little1 and Alice M Barthel2, (1)Atmospheric and Environmental Research Lexington, Lexington, MA, United States, (2)Los Alamos National Laboratory, Los Alamos, NM, United States
 
CF Conventions for netCDF: Support for Data Access, Analysis, and Visualization (655315)
Ethan Davis, University Corporation for Atmospheric Research, Boulder, CO, United States, Guilherme P Castelao, Scripps Institution of Oceanography, La Jolla, United States, David Hassell, University of Reading, Reading, United Kingdom, Jessica Hausman, Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States, Aleksandar Jelenak, HDF Group, Champaign, IL, United States, Daniel Lee, EUMETSAT, Darmstadt, Germany and Kevin O'Brien, NOAA/PMEL UW Joint Institute for the Study of the Atmosphere and Ocean, Seattle, WA, United States
 
Data-driven stochastic parameterization of multi-scale flow interactions in ocean models (655541)
Dmitri A Kondrashov, University of California Los Angeles, Atmos. Sci, Los Angeles, CA, United States, Eugene Ryzhov, Imperial College London, Mathematics, United Kingdom, Pavel S Berloff, Imperial College London, London, SW7, United Kingdom and Agarwai Niraj, Imperial College London, United Kingdom
 
A Machine Learning Approach to Quality Control Oceanographic Data (Invited) (655672)
Guilherme P Castelao, Scripps Institution of Oceanography, La Jolla, United States
 
Disentangling Complex Flows by Blurring the Data (656135)
Hussein Aluie, University of Rochester, Rochester, NY, United States, Matthew W Hecht, Los Alamos Nat'l Lab, Los Alamos, NM, United States, Mathew E Maltrud, Los Alamos National Laboratory, Los Alamos, NM, United States, Shikhar Rai, United States, Mahmoud Sadek, University of Rochester, Mechanical Engineering, Rochester, NY, United States, Benjamin Aaron Storer, University of Waterloo, Applied Mathematics, Waterloo, ON, Canada and Geoffery Vallis, University of Exeter, Exeter, United Kingdom
 
Reconstructing Subsurface Ocean Temperature and Salinity by the Reduced Space Objective Analysis With Dynamical Constraints (656720)
Alexey Kaplan, Lamont Doherty Earth Observatory, Palisades, NY, United States, Yochanan Kushnir, Columbia Univ, Palisades, NY, United States and Mark A Cane, Lamont-Doherty Earth Obs, Palisades, NY, United States
 
Reconstruction of incomplete spatial data with feature preserving information transport (656772)
Siavash Ameli, University of California, Berkeley, CA, United States and Shawn Shadden, University of California, Berkeley, Berkeley, CA, United States
 
Machine learning for inference and parametrization of ocean turbulence (657279)
Laure Zanna, University of Oxford, Dept of Physics, Oxford, United Kingdom and Thomas Bolton, University of Oxford, Department of Physics, Oxford, United Kingdom
 
Rethinking Prior Approaches – Bayesian Neural Networks for Information Retrieval from Ocean Color (657309)
Susanne Elizabeth Craig1, Erdem Karakoylu1 and Deric Gray2, (1)NASA Goddard Space Flight Center, Greenbelt, MD, United States, (2)US Naval Research Laboratory, Washington, DC, United States
 
Visualizing oceanic and atmospheric fields on a tile based web map: a new gridded product comparison tool in the Argovis web application (657737)
Tyler Tucker, University of Colorado, Department of Atmospheric and Oceanic sciences, Boulder, CO, United States, Donata Giglio, University of Colorado, Department of Atmospheric and Oceanic Sciences, Boulder, CO, United States and Megan Scanderbeg, Scripps Institution of Oceanography, La Jolla, CA, United States
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