1. Division of Nearshore Research TCOON
Dr. Gary Jeffress Dr. Patrick Michaud
February 3, 2003

2. Division of Nearshore Research Projects
Texas Coastal Ocean Observation Network
NOAA/NOS Natl Water Level Obs Network
Houston/Galveston PORTS
National/Global Ocean Observing System
TWDB Intensive Surveys
Nueces Bay Salinity Project
Corpus Christi Real-Time Navigation System
CMP - Neural-Network Forecasting
CMP - Waves

3. TCOON Overview Started 1988 Over 50 stations Primary Sponsors
General Land Office
Water Devel. Board
US Corps of Eng
Nat'l Ocean Service
Gulf of
Mexico

4. TCOON Overview Measurements Follows NOAA/NOS standards
Precise Water Levels
Wind
Temperature
Barometric Pressure
Follows NOAA/NOS standards
Real-time, online database

5. Typical TCOON Station Wind anemometer Radio Antenna
Satellite Transmitter
Solar Panels
Data Collector
Water Level Sensor
Water Quality Sensor
Current Meter
These are the typical sensors associated with a TCOON station.

6. Once the data are collected at the Blucher Institute, they are available via our web site. This slide shows an example of one of our “overview” pages describing the current conditions at a nearby platform. The top of the page identifies the platform (“Naval Air Station”), its location and other parameters. The latest observations are displayed next in both metric and English units. For many stations we are able to display the information in “real-time” (not older than 15 minutes).

7. Because of the importance of the data for boundary determination and navigation, we have an extensive quality control system in place. Every morning, an analyst reviews all of the data collected by all stations. This slide shows what an analyst would be looking at. Since 1996, all TCOON data processing has taken place via the World Wide Web; that is, not only do we publish data via the web, but we also use the web as the primary internal interface for updating and maintaining the network itself. Thus, the analyst visits a web page showing recently collected data.
In this slide, the top graph represents the water elevations, the next graph displays wave activity, and the bottom graph shows air and water temperatures.

8. Moving further down the web page, you can see the interface the analyst uses to monitor the system. If any problems are observed in the operation of the station, the analyst enters a note using the form at the bottom of the web page. When all of the stations have been reviewed, the outstanding notes are then organized and sent via electronic mail to the entire staff. These notes then form the basis for repair and maintenance operations for the next few days.

9. Nueces Bay Salinity Project
Started 1991
Informs data management officials of opportunities to avoid water releases
Water quality data collected every 30 minutes

10. Other Real-Time Systems
Real-time Navigation
Port of Corpus Christi
Port Freeport
NOAA PORTS
Offshore Weather

11. Data Collection Paths
Data are transmitted from the stations to the Conrad Blucher Institute in a variety of paths, including satellite transmissions,
packet radio, and telephone connections.

12. Data Management Automated Acquisition, Archive, Processing, Retrieval
10-year Historical Database
Most processing takes place via Internet
Infrastructure for other observation systems

13. Uses of DNR/TCOON Data Tidal Datums Littoral Boundaries
Oil-Spill Response
Navigation
Storm Preparation/ Response
Water Quality Studies
Research

14. Tidal Datums Used for Coastal property boundaries Nautical charts
Bridge and engineering structures

15. Tidal Datum Schematic

16. New Data Collection Hardware
PC-104 based computer
Linux operating system
Solid-state Flash memory
10 serial ports, 16 A/D channels
Low power consumption
Rugged for harsh environments
Because of difficulties in finding flexible data collection systems, the Blucher Institute has been designing its own data collectors using commercially available components. We are now using PC-104 based computer components to provide the sensor control and data collection for our individual stations. PC-104 provides a good, stable platform for software development and long-term availability of components.

17. Research Real-time Automated Data Processing Tidal Datum Processing
Web-based Visualization and Manipulation of Coastal Data
Neural-Network-based forecasts from real-time observations
Specialized sensor and data acquisition system development
Support for other research efforts

18. Water level forecasting
Isidore begins to (re-)enter the Gulf…
…what will happen next?

19. Tide predictions
tide: The periodic rise and fall of a body of water resulting from gravitational interactions between Sun, Moon, and Earth.
Tide and Current Glossary, National Ocean Service, 2000
According to NOS, changes in water level from non-gravitational forces are not “tides”.

20. Harmonic analysis Standard method for tide predictions
Represented by constituent cosine waves with known frequencies based on gravitational (periodic) forces
Elevation of water is modeled as
h(t) = H0 +  Hc fy,c cos(act + ey,c – kc)
h(t) = elevation of water at time t
H0 = datum offset
ac = frequency (speed) of constituent t
fy,c ey,c = node factors/equilibrium args
Hc = amplitude of constituent c
kc = phase offset for constituent c

21. Prediction vs. observation
It’s nice when it works…

22. Prediction vs. observation
…but it often doesn’t work in Texas

23. Water level != tide
In Texas, meteorological factors have a significant effect on water elevations

24. Uses of harmonic predictions
However, harmonic predictions can still be useful! Consider…
Isidore begins to (re-)enter the Gulf…
…what will happen next?

25. Uses of harmonic predictions
If we add harmonic prediction…
…what will happen next?

26. Uses of harmonic prediction
landfall

27. Harmonic WL prediction - present capabilities
Automated system for computing harmonic constituent values from observations database
Harmonic predictions available via query page for many TCOON stations

28. Water-level prediction – (near) future capabilities
Persistent model forecast
Apply difference between latest observation and harmonic prediction to future predictions
Forecasts page on DNR web site
Obtain forecasts from different models
Harmonic predictions
Persistent model
Neural-network model
Linear-regression/statistical model
Hybrid models
Information about water-level forecasting methods
Statistics on previous forecasts

29. Neural Network Forecasting
Use neural network to model non-tidal component of water level
Reliable short-term predictions
CCNAS ANN 24-hour Forecasts for 1997 (ANN trained over 2001 Data Set)

30. Forecasts in storm events
CCNAS ANN 12-hour Forecasts During 1998 Tropical Storm Frances
(ANN trained over 2001 Data Set)

31. Conclusions Long-term, data-rich observation network
Web-based infrastructure for automated collection and processing of marine data
Research in datum computation and coastal forecasting