Although the ET database was appropriate for numerous applications, no enhancements have been made to either the solar insolation or ET algorithms since 2007. Significant improvements within the database are needed to maintain state-of-the-art methods. Furthermore, extending the database over a 30-year record will allow for more reliable hydrologic model calibration over longer time periods and greater understanding of the historical variability in ET to aid in water-use planning for the future. The Statewide solar insolation and ET maps are not yet prepared for the forthcoming GOES-R satellite that will be available in 2017, offering 500 m resolution visible observations. Additionally, spatiotemporal definition of land surface albedo was not readily available in 2007, necessitating coarse approximations of this parameter which is required to estimate net radiation to land surface; enhanced albedo estimates are now available through satellite methods (i.e., MODIS, VIIRS) and have shown great utility relative to field-scale measurements (Sumner et al., 2011). Lastly, there is a need to replace sparse point data from weather stations with more spatially continuous air temperature (Ta), relative humidity (Rh) and wind speed (Ws) arrays from high-resolution Weather Research and Forecast (WRF) or from the North American Regional Reanalysis (NARR) model simulations.
The presentation will highlight ongoing research and development activities done toward extending the ET database over Florida to 30-years in length, as well as those outlined above. The presentation will describe specific method of processing older GOES-6 and -7 data, as well as Meteosat-3 observations, in the solar insolation model. We will also then outline specific methods being developed to enhance the ET model using WRF/NARR models and MODIS/VIIRS land surface datasets. The main outcome of the project will be applications of a climatological ET dataset for users across Florida, and such examples will be shown as to how the various WMDs are using the ET data, and also how other users benefit from such high-resolution, spatially continuous data (e.g., Florida Statewide Agricultural Irrigation Demand – FSAID).