An Algorithm for Detecting the Chesapeake Bay Breeze from Mesoscale NWP Model Output

Abstract

A novel algorithm is developed for detecting and classifying the Chesapeake Bay breeze and similar water-body breezes in output from mesoscale numerical weather prediction (NWP) models. To assess the generality of the new model-based detection algorithm (MBDA), it is tested on simulations from the Weather Research and Forecasting (WRF) Model and on analyses and forecasts from the High-Resolution Rapid Refresh (HRRR) model. The MBDA outperforms three observation-based detection algorithms (OBDAs) when applied to the same model output. In addition, by defining the onshore wind directions on the basis of model land-use data and not on the actual geography of the region of interest, performance of the OBDAs with model output can be improved. Although simulations by the WRF Model were used to develop the new MBDA, it performed best when applied to HRRR analyses. The generality of the MBDA is promising, and additional tuning of its parameters might improve it further.