The material covered here is very similar to that described in introductory materials at Introduction to Marine Data Management II, but it is appropriately reduced in scope according to time constraints and student preferences.

Volunteer instructors:  All Docents, Murray Brown

Required Software (latest versions; Windows and Mac; 32-bit and 64-bit):  Saga, GEBCOLite (if GEBCO not available), Ocean Data View, Integrated Data Viewer (IDV), Google Earth

Please just try to get through this list of articles before you begin the course.  They are not long, nor very technical.  You don't need to follow the many links in the articles, unless you are curious about the subtopic.

2.  Integration of Marine Data Resources - Click on the chart to open a more readable version

Marine data management, quite simply, is a balancing act between the 3 major concepts:  Formats, Software and Data.  You need to become familiar with major resources in all categories, and how they work together.  In years gone past, scientists had to slog through numerous format conversions (including writing necessary code) to make connections.  But in recent years a small family of flexible formats, powerful computer programs and flexible online data sources have brought everything together.

This chart seems terribly complicated at first, but it will be explained during the course.  In this course we'll be using

• Software

  • Ocean Data View (left side)

  • Saga (in the middle)

  • Integrated Data Viewer (right side)

  • Google Earth (right side)

• Data Sources

  • World Ocean Database/WOD (left side)

  • Online data archives/mixed formats (upper middle)

  • Operational data (upper right)

  • Others, as time permits

• Formats - As indicated

You will become hopelessly lost within the short span of this course (1 or 2 weeks) and even in your own personal data collections, unless you adopt good data management practices.  We strongly recommend the constant use of these elements:

• Folder Structure - Basic list of topics developed over 20 years of DM training.  Author has 10 BG and ~4000 files just for Liberia training
• "Long" File Names
  • parameter_
  • date/time_
  • depth/height_
  • location_
  • originator_
  • provider_
  • extras_
• Limited Characters: No spaces, no hyphens, no caps (except T), include format in extras, if zipped

• 1 Computer Basics
• 1.1 Folder Structure

This section deals with setting up an AOI, based on:

• Coastline
• National boundaries
• Relief - bathymetry and topography
• Environmental factors - circulation & ecosystems
• Anything else of concern

Defining the AOI with with signed decimal degree values

• Top latitude (not "north")
• Bottom latitude (not "south")
• Left longitude (not "west")
• Right longitude (not "east")

Making important auxiliary layers

• Graticule - lat/lon lattice
• Line and polygon frames - outer edge of AOI
• Grid templates - to control data gridding

Adding important features

• Political features
• Other coasts

Trimming shapes to the AOI to reduce filesize and speed up mapping

• 2.1 Saga Preliminary Setup
• 2.2 Project Area
• 2.3 Creating a Project Map in Saga

• 2.4 Creating Graticules and Frames in Saga

• 2.5 Creating Grid Templates in Saga
• 2.6 Adding GEBCO Depth Contours to a Project Map in Saga
• 5.3 Resampling Gridded Data to the Project Map Extent with a "Dummy" Grid

• OPTION: 2.8 Adding Administrative Boundaries and Coastline to a Project Map in Saga

• 2.9 Adding Marine Regions to a Project Map in Saga

The WOD is the largest available, online, free ocean database.  It should be the starting point for any personal or organizational database:

• Data range from >200 years old to stations within the past few years
• Constantly updated, includes a synchronizing option
• In-situ only, no remote sensing
• No instrumental time-series - e.g. tide gauge, current meter
• About 30 parameters
• 12 types, depending on measurement methods - ship stations, drifters, diving pinnipeds, etc.
• Uses cruise/station/depth/date/time paradigm for data organization
• Includes quality flags for all measurements

Downloading the data is easy and fast:

• Download zipped collections in a venerable, 80-character "archive format"
• Also download or link to huge collection of metadata for each ocean station

Data can be quickly loaded into Ocean Data View (ODV) to create a "collection"

• Native WOD structure can be used
• Other structures (stored in ODV) can also be used

• 3.1 Obtaining Area-Specific Marine Data from the World Ocean Database
• OFFSITE: Ocean Data View (ODV) Overview - Professor Schlitzer
• 4.1 Creating ODV Collections from World Ocean Database Data

Users of ODV can immediately make very professional graphical analyses, using several very common "layouts"

• Station plots - plot of any variable(s) versus depth for one or a few stations; usually joined lines
• Scatter plots - plot of any two variables versus each other, usually for large numbers of samples
  • T-S plot is a famous plot of temperature and salinity; often used to characterize water masses
• Section plots - plot of any variable along a specified line and versus depth, like a fence; usually gridded for clarity
• Surface plots - plot of any variable on a surface defined by another variable; easier to make and use than to describe

• 4.2 Creating Marine Data Station Plots in ODV

• 4.3 Creating Marine Data Scatter Plots in ODV

• 4.4 Creating Marine Data Section Plots in ODV

• 4.5 Creating Marine Data Surface Plots in ODV

ODV collections are ideal mechanisms to make data products and graphical analysis products for use elsewhere:

• Original data - exported according to various selection criteria
  • Export as tabular spreadsheet
  • Export as smaller ODV collection for fast use
• Interpolated data - exported for a defined "surface" from surface mode
  • Variable at Depth = X is often the method used, but can be Variable_1 at Variable_2 = X, etc.
• Images of data - as points or gridded analyses (usual graphics formats)

• 4.8 Exporting Marine Data from ODV:  Data Subsets

Gridding and contouring data are linked methods used to visualize and understand data points that are scattered in space.  Before computers were set up to contour data, scientists had to do it by hand after all cruises. This exercise should give you some respect for how much work contouring was.

• Gridding - Process of creating a regular lattice ("grid") of regularly spaced values. Each value is the result of calculations ("algorithms") based on nearby original data value.  Gridding is a science all its own, and needs careful study.  Algorithms range from simple averaging of all values in a defined box around a central point, to extremely complex methods involving much more complex mathematics and operational parameters.
• Smoothing - Gridding smooths out rough areas, and fills in gaps
• Grid - May be rectilinear (horizontal and vertical lattice lines), or may conform to any curvilinear shape.  Rectilinear grids may be equilateral (i.e. x intervals = y intervals) or not.  Necessary information to describe rectilinear grids would include:
  1. Data are Big Endian or Little Endian?
  2. ASCII or binary?
  3. Number types if binary?
  4. Data line terminators if ASCII:  UNIX or DOS?
  5. Lat/lon of first point in grid array?
  6. Location of first point in the grid, lower-left or upper-left?
  7. Read the grid by rows or by columns?
  8. Number of grid cells in E-W direction?
  9. Columns spacing (delta-X)?
  10. Number of grid cells in N-S direction?
  11. Row spacing (delta-Y)?
  12. Have the grid values been multiplied by some factor, and what is that factor?
  13. For nested multiple grids, what is the reading order of the variables? 
• Self-Describing Formats - Some formats are self-describing, so they take care of these questions for you, e.g. HDF, NetCDF, ESRI ASC
• Contours - Contours can be drawn (manually or digitally) through a grid, to depict the loci of points where a parameter has a specific value, e.g. 18-degree temperature contour
  • General term for all contours:  ISOPLETHS
  • Various types of isopleths:
    • Isotherms
    • Isohales
    • Isobars
    • Etc.

The method to grid data in Saga is very general and applies to most GIS systems:

• The data are first loaded into Saga as a data table
  • TXT, tab-separated is best
• Convert the table in the GIS to a "point shape"
  • Other shapes you should know are "line shapes" and "polygon shapes"
• Use any one of many available algorithms in Saga
  • Make tests to see which work best with your data, and also experiment with the gridding parameters for each algorithm
• Once you have the grid, you can make any of several very important "standard" products for use in publications, theses and websites

• 5.1 Converting a Data Table to a Point Shape in Saga
• 5.2 Gridding Point Shapes in Saga
• OPTION: 5.5 Creating "Standard" Grid Products with Saga

• 2.31 Importing Satellite SST and Sea Ice Climatologies into Marine GIS: NODC LAS -  Use only the SST method; if your own country or personal project is near-polar, then also use the sea ice method

Relief (= depths + heights) - always a critical concern for scientists, explorers and builders, fishermen, etc.  An entire vocabulary and technology has grown up around management of relief data:

• Relief can be expressed as grids or as contour lines.  Contour maps are immediately understood by most persons, but grids are required to make them.
• Dozens of formats exist to hold relief data, including special formats designed just for relief.
  • Digital Elevation Models (DEM)
  • ETOPO series of global products - various resolutions
  • GEBCO global grids - 0.5 and 1.0 degree resolutions
• Contours can be held in a small family of vector formats
• GIS programs usually can make/save contour lines from grids, according to user specifications
• Contour lines still hand-drawn to satisfy some official purposes (e.g. GEBCO) or for special situations (e.g. expert knowledge of an area)

Relief product examples:

• Contour maps
• Grids using value-color mapping ("palettes")
• Elevation "tracks" created by moving a cursor over a relief grid

• 7.1 Working with the GEBCO 08 Global Relief Grids
• 7.2 Creating Vector Contours from Grids: GEBCO 08 Shelf Estimations

There are basically 2 types of natural data:

• SCALARS - Values of a parameter that can be complete expressed as a numerical value and its units (when existing).  For example temperature in degrees Kelvin, or salinity (no units).
• VECTORS - Values of a parameter that 2 numerical values to be expressed, for example winds and currents:
  • COMPONENT VECTORS:  Most common method requires vector components in the east-west direction (commonly called the U component), and the vector component in the north-south direction (commonly called the V component).
  • DIRECTION VECTOR AND SPEED:  Less commonly used method (nowadays) requires a scalar quantity expressing simple speed, and a vector of unit length that expresses direction.

There are 3 ways to express vector directions:

• COMPONENT VECTORS - direction already uniquely defined by components; use geographic direction to describe the result
• GEOGRAPHIC DIRECTION - clockwise "rose"
  • North = 0º or 360º according to user's conventions
  • East = 90º
  • South = 180º
  • West = 270º
• MATHEMATICAL DIRECTION - counter-clockwise "rose":
  • East = 0º or 360º according to user's conventions
  • North = 90º
  • West = 180º
  • South = 270º

Meteorology versus Oceanography

• Met data often display "direction from which" for wind vectors
• Oc data often display "direction toward which" for current vectors
• You need to look after this on a case-by-case basis to make sure you have the right data and the right display method

• 6.2 Plotting Vector Arrows from U and V Component Grids with Saga
• OPTION: 6,3 Plotting Vector Arrows from the Global Drifter Program 0.5-Degree Climatology

Definition - "Operational Oceanography can be defined as the activity of systematic and long-term routine measurements of the seas and oceans and atmosphere, and their rapid interpretation and dissemination." - EuroGOOS Definition.

Strategy - Operational Oceanography is attempting to develop along the same highly successful lines as the global weather systems of the World Meteorological Organization (WMO).  A bridge agency between the IOC and the WMO has been created, named JCOMM.

• Making measurements/sampling
  • In-situ
  • Remote/satellite
• Transmitting data to centers
• QC and processing
• Integration between technical systems
• Modeling
• Distribution of products from all elements

Formats - Complex data formats that integrate data and metadata, for example:

• GRIB - met or OO grids
• BUFR - met obs
• HDF - satellite grids
• NetCDF - met or OO obs or grids
• Etc.

Standards and Software - Also developed, for example:

• OPeNDAP - protocol for client-server actions for earth science data
• LAS - very widely used online program for visualizing/obtaining data, uses OPeNDAP
• THREDDS - umbrella concept that combines client-server functions of several approaches, including metadata catalogs, OPeNDAP, FTP to allow easy community access to data

• 9.1 Integrated Data Viewer (IDV) Preliminary Setup
• 9.2 Visualizing Satellite-Measured Surface Temperature Fields in IDV: GHRSST, G1SST (Method 2 only)

• 9.10 Visualizing Ocean Model Simulations (Rasters or Vectors) in IDV: HYCOM

• 9.22 Visualizing Satellite-Measured Sea Surface Salinity in IDV: AQUARIUS (NetCDF)