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Identifying Heat Waves in Florida: Considerations of Missing Weather Data
Emily Leary1, Linda J Young2, Chris DuClos3
1School of Natural Resources and Environment, University of Florida, PO Box 116455, Gainesville, FL, 32611, United States of America.
Plos One
|December 1, 2015
Summary
Missing weather data significantly impacts the identification of extreme heat periods in Florida. Spatio-temporal imputation methods are recommended for accurate heat wave analysis.
Area of Science:
- Climate science
- Environmental monitoring
- Data science
Background:
- Florida faces projected warming and increased high temperature extremes.
- Existing heat wave research often overlooks missing weather data.
- A standardized definition for heat waves is currently lacking.
Purpose of the Study:
- To explore methods for handling and imputing missing weather data.
- To assess the impact of these methods on identifying extreme heat periods in Florida.
Main Methods:
- Utilized temporal, spatial, and spatio-temporal models to impute missing weather data (1973-2012).
- Analyzed data from 43 Florida weather monitors.
- Defined extreme heat periods using calculated thresholds.
Main Results:
- Imputing missing data influences the identification of extreme heat events.
- Observed differences correlate with missing data during peak warm months (June-August).
- The choice of imputation method affects threshold calculations and heat wave identification.
Conclusions:
- Accurate handling of missing data is crucial for defining extreme heat.
- Spatio-temporal data imputation methods are recommended.
- A comprehensive heat wave definition should integrate data from all monitoring stations.
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