Building an open-source GIS pipeline for meteorological analysis

Meteorological data is, by its very nature, geospatial. Therefore, a robust geographic information system is necessary in order to analyze, manipulate, visualize, and disseminate data. Fortunately, there are several open-source projects available which, when combined, can create a powerful GIS pipeline. These projects offer a no-cost alternative to commercial products without sacrificing performance or support. Most of these projects are simple to set up and are supported by excellent documentation. A large development and user base, along with permissive licensing and the ability to completely customize each solution to specific needs make these projects a highly valuable resource for the meteorological community.

This paper/presentation will discuss the application of an open-source GIS solution stack incorporating GDAL, MapSever, OpenLayers, and PostGIS. This stack was selected because it provides a wide range of analytical and visualization functionality - attributes highly desired by the meteorological community. While this pipeline can be adapted for practically any geospatial data, our focus will be on meteorological datasets and the pipeline will be designed to accommodate the most common meteorological data formats including GRIB, NetCDF, KML, GeoJSON, shapefiles, and geo-referenced images.