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The rather unique sub-tropical, flat, peninsular region of Florida is subjectto a unique climate with extreme weather events across the year that impactsagriculture, public health, and management of natural resources. Meteorologicaldata at high temporal resolutions especially in the tropical latitudes areessential to understand diurnal and semi-diurnal variations of climate, whichare considered to be the fundamental modes of climate variations of our Earthsystem. However, many meteorological datasets contain gaps that limit their usefor validation of models and further detailed observational analysis. Theobjective of this paper is to apply a set of data gap filling strategies todevelop a gap-free dataset with 15-minute observations for the sub-tropicalregion of Florida. Using data from the Florida Automated Weather Network(FAWN), methods of linear interpolation, trend continuation, reference toexternal sources, and nearest station substitution were applied to fill in thedata gaps depending on the extent of the gap. The outcome of this studyprovides continuous, publicly accessible surface meteorological observationsfor 30 FAWN stations at 15-minute intervals for the years 2005-2020.

Gap-free 16-year (2005-2020) sub-diurnal surface meteorological observations across Florida