  The rather unique sub-tropical, flat, peninsular region of Florida is subject
to a unique climate with extreme weather events across the year that impacts
agriculture, public health, and management of natural resources. Meteorological
data at high temporal resolutions especially in the tropical latitudes are
essential to understand diurnal and semi-diurnal variations of climate, which
are considered to be the fundamental modes of climate variations of our Earth
system. However, many meteorological datasets contain gaps that limit their use
for validation of models and further detailed observational analysis. The
objective of this paper is to apply a set of data gap filling strategies to
develop a gap-free dataset with 15-minute observations for the sub-tropical
region of Florida. Using data from the Florida Automated Weather Network
(FAWN), methods of linear interpolation, trend continuation, reference to
external sources, and nearest station substitution were applied to fill in the
data gaps depending on the extent of the gap. The outcome of this study
provides continuous, publicly accessible surface meteorological observations
for 30 FAWN stations at 15-minute intervals for the years 2005-2020.
