Infilling of Rain Gage Records Using Radar (NEXRAD) Data: Influence of Spatial and Temporal Variability of Rainfall Processes

Deterministic and stochastic weighting methods are the most frequently used methods for infilling rainfall values at a gage based on values recorded at all other available recording gages or other sources. Radar (NEXRAD) data is also commonly used for infilling of rainfall data. Several issues that affect the infilling methods include: the historical rain gage and radar data, spatial and temporal variability of rainfall, radar-rain gage relationships, selection of spatial extent of radar data. The current study evaluates the influence of spatial and temporal variability of rainfall processes on the performance of spatial interpolation algorithms. Seasonal variation of rainfall, rainfall areas that are delineated based on physical processes affecting the genesis and morphology of rainfall processes, and other factors may affect the performance of infilling methods. All these issues are important for south Florida which experiences wide variability in rainfall in space and time. In the current study, data from several rain gages and radar (NEXRAD) data in the south Florida region are used to evaluate the influence of spatial and temporal variability of rainfall processes on the performance of methods used for infilling rain gage data.