The weather and climate modeling communities have developed data storage formats, as well as analysis and visualization tools, that are appropriate for the large volumes of spatial and temporal data required to model the earth's atmosphere. However, these specialized formats and tools may limit accessibility to members who are outside of the established community, such as new graduate students or curious members of the general public. One way of expanding the number of potential users is to make the datasets accessible in Google Earth, a freely-available virtual globe browser. According to Google engineers, Google Earth is available in 13 languages and has been downloaded over 350 million times. Because of it's popularity, using Google Earth to display your weather and climate data may increase your potential user base. Just a bit.

While Google Earth comes by default with a rich set of satellite imagery and data layers, custom user data can be formatted for viewing in Google Earth using KML, an XML-based language used to display and annotate geographic data. The KML language was originally developed by Keyhole/Google and is now an open standard managed by the Open Geospatial Consortium (OGC), an international standards organization for geographic content and location services. While KML documents that display a few geographic entities are fairly easy to create, creating KML files for displaying large, complex datasets or documents that utilize the advanced features of the KML language (such as animation, touring, overlays, etc.) are often difficult and/or cumbersome to create.

This talk will present pyKML, an open source Python package for creating, parsing, and manipulating KML. pyKML is designed to make creating KML documents easier for those who are familiar with the Python programming language. Major features of the pyKML library will be described, and examples of using pyKML to display current weather data will be shown.

http://packages.python.org/pykml/