Investigating Sea Breeze Climatology In Tampa, Florida Using Reanalysis Data

The sea breeze forms due to temperature differences between the air over land and the ocean, which affects coastal areas. Within and around Florida, the sea breeze can exhibit complex behavior based on interactions and influences of other phenomena such as El Nino and La Nina, where El Nino and La Nina can shift low-level jet streams, causing years of El Nino to have colder and wetter winters and years of La Nina to have an increase in frequency and intensity of tropical storms in this region. One of the places affected by these mechanisms is Tampa, Florida which is a coastal city in the western central peninsula of Florida. This investigation is centered at the Tampa International Airport (TPA), due to its proximity to the National Weather Service and has the most available data. The methodology and data used for this work were surface observations downloaded from Iowa Environmental Mesonet ASOS from 1990 to 2020, and reanalysis data was downloaded from the ECMWF ERA-5 single-level data set from 1990 to 2020. The variables downloaded from both sources were the two-meter max wind speed and precipitation. To use the entirety of the reanalysis data set, the surface observations and reanalysis data from 2020 were compared along the same time scale to verify the accuracy of the reanalysis data. As a result of that comparison, the correlations of the variables from the reanalysis data downloaded were calculated. NOAA's Oceanic Nino Index (ONI) data was downloaded to compare patterns from 1990-2020. The monthly average variables showed an inversely proportional correlation of 0.482. A focus on the peak wet season was done using the months of July and August from 1990-2020, and the variables' correlation was 0.042. The correlations among the variables proved to be unexpected. However, compared to the ONI patterns, maximums and minimums of wind speed and precipitation seem to match ONI patterns. Years of peak wind speed maximums and peak precipitation maximums were identified, and a possible correlation was found between the years of El Nino and La Nina, respectively. In conclusion, due to the unexpected correlation results, more analysis of the variables involved with the sea breeze, such as temperature and moisture, should be done to create a proper understanding of sea breeze climatology. Future recommendations include adjusting the time scale for daily or hourly data. However, this is only possible if resolutions to the reanalysis data sets can be obtained to combat missing data.