CBI Coastal Predictions

Summary: TCOON as well as other observation networks, provide an increasing amount of real-time data. CBI takes advantage of this information to develop and implement real-time predictive models in order to help decision makers and the general public. We have focused on using machine learning techniques such as artificial neural networks. These techniques are well suited for the modeling of non-linear processes when large data sets are available and also provide predictions virtually instantly once the models are trained.

The models are developed in collaboration with faculty members of Texas A&M University-Corpus Christi, the Center for Water Supply Studies and the Corpus Christi Weather Forecasting Office. If you have suggestions about existing or new models, please e-mail us or pass by our offices—we thoroughly enjoy the research and the related discussions!

WATER LEVEL PREDICTIONS FOR THE COASTAL BEND

If you would like water level predictions for the Coastal Bend for the Gulf, Bay and Laguna in one chart, this is your link. The predictions include the effect of wind and the design of the graph is in large part due to the feedback for the Corpus Christi Caller Times (Thanks!).

ADDITIONAL INFORMATION

Predictive Model Performance

Frequently Asked Questions

ACCESS TO SELECTED ATMOSPHERIC PREDICTIONS FROM THE NORTH AMERICAN MODEL (NAM)

Since early 2002, NAM and GFS atmospheric predictions are being stored for about 50 locations along the Texas Coast, in the Gulf of Mexico and inland Texas in a joint project between DNR and the Corpus Christi Weather Forecasting Office. Most DNR/TCOON stations are covered. Real-time and archived predictions are available for these models:
NSM Data Retrieval.