Using Geographic Information Systems methods with the National Digital Forecast Database

The National Weather Service (NWS) now issues public forecasts for the nation in gridded form at 5 km spatial resolution. These forecasts comprise the National Digital Forecast Database (NDFD). The update frequency is several times per day. Forecasts include 2-meter temperature, dewpoint and relative humidity, wind, precipitation amount, cloud cover, and weather type, across the entire nation. The high-resolution NDFD is a major step forward for the NWS as previously most public forecasts focused only on areas the size of counties or zones, or for specific points of high interest such as city centers. Thus the NDFD allows users to get a forecast for a point within just a few kilometers away, no matter where they live.

The NDFD grids are made available to the public using the World Meteorological Organization (WMO) standard GRIB2 binary format. Only a few applications allow native viewing of GRIB2 format data. Many users of NWS data in the U.S. are not familiar with WMO formats and would prefer the data to be in formats that integrate more easily with Geographic Information Systems (GIS). Indeed, the emergency management community is one of the agency's primary customers and is largely already using GIS software and many of their existing data sets are already in a GIS-ready format.

This paper will explore some applications of using GIS to analyze the NDFD forecast grids. This includes an automated routine for converting the entire national grid into the UNIDATA netCDF format which is commonly used by the atmospheric science community. Through the use of recent enhancements to GIS software, netCDF data will be directly readable, along with other GIS-ready datasets. Providing GIS-ready NDFD in either netCDF or GIS “shapefile” formats will allow more advanced GIS analyses. Examples include verification comparisons of NDFD grids to observational data, short-term (3-12 hours) decisional aids for emergency managers, and increased flexibility for designing forecast graphics for broader dissemination.