Visualizing Spatial and Temporal Variability in Coastal Observatories Walter H. Jimenez Wagner T. Correa Claudio T. Silva Antonio M. Baptista OGI School of Science & Engineering, Oregon Health & Science University Originally Published in the Proceedings of the 14th IEEE Visualization Conference (VIS’03) Bob Armstrong MSIM Feb 2007

Summary of this Paper This paper is about improvements to the Columbia River's environmental observation and forecasting system, called CORIE. Their new tools add 3D and 4D visualization to CORIE. How We'll Proceed  The Problem  The Motivation  Their Approach  Conclusion  Questions

The Big Picture SEATTLE PORTLAND This is the area of CORIE sensors

The Big Picture This is the area of CORIE sensors Take off, you hoser.

The CORIE Sensor Field

Jetty A CORIE Station

The Problem In 2003, there was a mismatch between CORIE's simulation capabilities and generated data  System based on high-resolution time-varying 3D unstructured grids  Also included a visualization component that for the large part only generates 1D or 2D plots  Some 3D information can be inferred from depth plots, which slice the 3D data CORIE is the region's Environmental Observation and Forecasting Systems (EOFS)

Forecast of Velocity Magnitudes

Location of CORIE Stations

Environmental Observation and Forecasting Systems Seek to generate and deliver quantifiably reliable information about the environment Rely heavily on modeling and visualization CORIE  Observation Network Real-Time telemetry from over 20 stations  Advanced Modeling System Models the complex circulation in the river and plume  Information Management System Web Publishing of Processed Data

Why should we care about this problem? Interesting visualizations They desire volume rendering versus isometric surface renderings Very easy to interpret output  Vector treatment is logical  Colorization is logical and very telling Moving towards real-time representation of large- scale fluid fields

Preprocessing of CORIE Output CORIE output data must be converted in order to be visualized Volume rendering of the salinity scalar  Requires an unstructured grid of tetrahedrons  Each vertex is associated with one salinity scalar  Rendering of the bathymetry requires a grid of triangles representing the ground surface Velocity field visualization  Requires an unstructured grid of points  Vector attributes associated with each point

Sample CORIE Data Station : Fort Stevens Wharf (USCG day mark red26) Identifier : red26 Latitude : N Longitude : W Instrument depth : 7.5m Year : 2006 Month : December Time reference : Pacific Standard Time Last revision : 1/29/2007 Data reviewed by : cseaton Expunged temperature measurement : 0 % Expunged salinity measurement : 0 % Expunged depth measurement : 0 % Records removed for time : 0.03 % Comments:Depth data referenced to NGVD29 MSL. See for meanings, formats and quality control procedures yyyy/mm/dd hh:mm:ss saliniy temp depth (PST) (PSU) (C) (m) ######################################### 2006/12/01 00:00: /12/01 00:01: /12/01 00:02: /12/01 00:02:

More CORIE Model Output Unstructured Grid Triangles are elements Verticies are nodes Column of points is variable due to depth Attribute value at each node can be  Scalar -> salinity  Vector -> velocity Volume rendering is performed on tetrahedrons derived from wedges

CORIE Output Data

Bathymetry

Volumetric Rendering Wedges look like slices of pie Wedge is divided into 3 tetrahedrons Polyhedron projection algorithms are used in order to economically volume-render the unstructured grid

Wedges into Three Tetrahedra n1 n2 n3

CORIE and Bathymetry The unstructured grid “stops” on the bottom surface of the river/ocean The grid of triangles that represents the bathymetry is constructed using the vertices at greatest depth Different colors are applied to indicate differing depth

Columbia River Topology and Bathymetry

Columbia River Insertion into Continental Shelf

Representation of Salinity Fields Rely on volume rendering  Allows for study of fine detail between high and low salinity regions Blue = high salinity Yellow = low salinity Red = interface regions

Salinity Intrusion During Flood Tide

Maximum Gradients of Salinity

Freshwater Plume during Ebb Tide

Velocity Field Representation Flow vectors visualized as a set of oriented lines  Lines have the same length  Colors represent vector magnitude  Orientation represents flow direction Easier to view a small subset of the vector field

Velocity Field during Ebb Tide

Use of the Model in Simulation Historical data is used extensively in simulation Simulation can be “validated” by the use of drifters Drifters are floating data and position collection devices Helpful to validate simulation behaviors

Observed & Simulated Trajectories of a Drifter Real Drifter Simulated Drifter

Performance 2.53GHz Pentium 4 Nvidia GeForce 4200 Render 700k to 800k tetrahedrons per second Typical grids include around 6 million cells Sims run in weekly increments One time step is rendered and dumped for each 15 minutes of simulation

Future Work Holy Grail: Real-time frame rates Make the visualization machine independent Reduce the complexity of visualization output production Explore advanced vector visualization techniques

Questions Could this type of visualization be used for atmospheric data? Is 3D volumetric rendering worth the cost? Why is volumetric rendering the right approach here?