  The sea breeze is a phenomenon frequently impacting Long Island, New York,
especially during the spring and early summer, when land surface temperatures
can exceed ocean temperatures considerably. The sea breeze influences daily
weather conditions by causing a shift in wind direction and speed, limiting the
maximum temperature, and occasionally serving as a trigger for precipitation
and thunderstorms. Advance prediction of the presence or absence of the sea
breeze for a certain location on a given day would therefore be beneficial to
weather forecasters. To forecast sea breeze occurrence based on the previous
night's weather conditions, we used a novel algorithm called the $D$-Basis. We
analyzed sea breeze data from a recent four year period (2017-2020) at a single
weather station several miles inland from the coast. High or constant station
pressure, high or constant dew point, and onshore wind from the previous night
were found to be strong predictors of sea breeze formation the following day.
The accuracy of the prediction was around 74\% for June 2020. Unlike other
prediction methods which involve the comparison of sea surface and land surface
temperatures in near real time, our prediction method is based on the
parameters from the prior night, allowing it to potentially aid in advanced
forecasting of the sea breeze.
