Importance of overnight parameters to predict Sea Breeze on Long Island

TL;DR

This study introduces a novel algorithm using overnight weather parameters to predict sea breeze occurrence on Long Island, achieving around 74% accuracy and aiding in advanced weather forecasting.

Contribution

The paper presents a new prediction method based on previous night's data, improving early sea breeze forecasts compared to existing temperature-based approaches.

Findings

High or constant station pressure predicts sea breeze.

Onshore wind from previous night indicates next-day sea breeze.

Prediction accuracy was approximately 74% in June 2020.

Abstract

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.