Air-sea forcing of coastal ocean sea surface temperature

Abstract

Nearshore sea surface temperatures show both strong seasonal trends and rapid changes associated with local weather events. As a result, commercial fishing operations search and rescue services, and recreational users have a very limited capability to predict expected sea surface temperatures for any given day. We use empirical and neural net modeling techniques to describe the seasonal relationships between wind velocity, offshore sea surface temperature, air temperature, wave energy and nearshore sea surface temperature along the Outer Banks of North Carolina. In the winter months, nearshore sea surface temperature is influenced by both offshore sea surface temperatures and air temperature, both of which reflect solar input. During the summer months, the ocean is stratified. Consequently, winds influence nearshore sea surface temperatures by inducing upwelling and downwelling phenomena, resulting in decreases and increases in nearshore SSTs respectively. The spring and fall seasons exhibit trends from both the summer and the winter, but these trends are weaker. We also look at how the greater prevalence of winds and waves during various seasons also influences nearshore sea surface temperatures. The resulting neural net model can predict nearshore sea surface temperature with a reasonable amount of accuracy.