A Statistical Nowcast System for Galveston Bay




Schmalz RA

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American Society of Civil Engineers


The National Ocean Service (NOS) installed a Physical Oceanographic Real Time System (PORTS) in June 1996 in Galveston Bay, Texas. The PORTS water surface elevation, currents at National Ocean Service prediction depth (-4.6m below MLLW) as well as near-surface and near-bottom temperature and salinity, and meteorological information are scheduled to be made available at six-minute intervals. Due to biofouling, cable snagging, and an assortment of maintenance issues, these data are either not available or degraded part of the time. A Continuous Operational Real-time Monitoring System (CORMS) has been implemented to quality control the PORTS data. Under the present operational scheme, if data are suspect, data dissemination is suppressed. This paper investigates the possibility of statistically nowcasting these missing data to at least provide an estimate to the mariner for missing data values. A computer program is developed to acquire the PORTS screen data every six-minutes and to statistically nowcast missing water level, current, near-surface salinity and temperature, as well as wind and atmospheric pressure. A proof of concept is demonstrated for two PORTS screen datasets, each with missing data. The statistical nowcast procedures involving linear regression of subtidal water level and along channel axis currents are evaluated for a typical dry season month (July 2001) and a typical wet season month (January 2002). The evaluation results are discussed and demonstrate the utility of the statistical nowcast for both water levels and currents when contrasted to harmonic analysis. Water level and current statistical nowcasts are compared with nowcasts produced by the NOS Experimental Nowcast/Forecast System, which is based on a three-dimensional hydrodynamic model for Galveston Bay and a one-way coupled fine resolution Houston Ship Channel model (Schmalz, 1998). Next, the role of statistical nowcasting within an operational nowcast/forecast system for Galveston Bay is considered. Finally, conclusions are drawn and additional statistical nowcast enhancements are discussed




Atmospheric pressure, Hydrodynamics, Mathematical models, Meteorology, Monitoring, Neural networks, Oceanography, Quality control, Real time systems, Regression analysis, Three dimensional, Weather forecasting