Tuesday, 8 January 2019: 11:45 AM
North 132ABC (Phoenix Convention Center - West and North Buildings)
Jung-Sun Im, NWS, Silver Spring, MD; and M. E. Churma, S. B. Smith, G. Dusek, P. Santos, A. J. Van der Westhuysen, R. Padilla-Hernandez, J. Kuhn, and D. Atkinson
Handout
(1.2 MB)
The National Weather Service (NWS) and the National Ocean Service (NOS) are collaboratively transitioning the NOAA probabilistic rip current forecast model into NWS operations. This model predicts the statistical likelihood of hazardous rip currents using a logistic regression technique with predictor inputs of significant wave height, mean wave direction, water level, and a bathymetry proxy. In a staged implementation along the US coasts, the model is running experimentally as a component of the National Center for Environmental Prediction (NCEP)’s Nearshore Wave Prediction System (NWPS).
As the rip current probability forecasts have been generated, rip current observation reports have been collected from lifeguards in coordination with local NWS Weather Forecast Offices (WFOs). The NWS Meteorological Development Laboratory (MDL) is using these rip current observations to evaluate the model performance at WFO pilot beaches across the US. This presentation will summarize the NOAA probabilistic rip current forecast model, quality controls for the observation data, and verification results. In addition, we will compare performance scores of this model to the traditional, deterministic index-based guidance used by WFOs. We will discuss the model’s strengths and weaknesses, and also the benefits of using MDL’s Model Output Statistics (MOS) method to improve the performance scores. The presentation will conclude with future research plans with a focus on operational implementation.
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