21st Conf. on Severe Local Storms and 19th Conf. on Weather Analysis and Forecasting/15th Conf. on Numerical Weather Prediction

Tuesday, 13 August 2002
Comparison of Meso Eta Wind Forecasts with TCOON Measurements along the Coast of Texas
Jeremy Alan Stearns, Texas A&M University, Conrad Blucher Institute, Corpus Christi, TX; and P. Tissot, A. R. Patrick, P. Michaud, and W. G. Collins
Poster PDF (218.8 kB)

Comparison of Meso Eta Wind Forecasts with TCOON Measurements along the Coast of Texas

Jeremy A. Stearns

Dr. Philippe Tissot

Andrew Patrick

Dr. Patrick Michaud

The Texas Coastal Ocean Observation Network (TCOON), operated by the Conrad Blucher Institute (CBI) of Texas A&M University-Corpus Christi, has a series of observation platforms covering the coast of Texas from Brownsville, TX to Louisiana. The data collected by TCOON, also published on the World Wide Web, includes water levels, wind speeds, wind directions, barometric pressures and air and water temperatures. Based on these parameters, a Neural Network (NN) is presently developed to predict short-term water levels. An additional component of NN input, forecasts from the NCEP Meso Eta model provide wind speeds, wind directions, barometric pressures and air temperatures for several locations up to 48 hours into the future. As part of a collaborative effort between the National Weather Service (NWS) Corpus Christi office, CBI, and Texas A&M University, data from the NCEP Meso Eta model is transferred every three hours from NWS to complete the data set for NN model input.

Close agreement between Meso Eta forecasts and observed measurements is expected for most inland and gulf locations. However, significant temperature differences between Gulf waters and the land lead to strong sea breezes. The sea breeze can occur on a smaller scale than the resolution of the NCEP Meso Eta model and may cause differences between the forecasted and measured winds. The objective of this study is to compare the Meso Eta wind forecasts with TCOON measurements for several stations along and across the coast of Texas. The predictions and measurements are compared for the spring of 2002. An assessment of the differences and their potential impact on the NN model is made. The development of the NN based model to forecast water levels along the coast of Texas is supported by a grant from the Coastal Management Program (CMP) of the Texas General Land Office (TGLO).

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