Publishing Earth Science Data with Python: A Case Study with Regional Climate Model Output

Thursday, 18 December 2014
Gordon M Green1, Marco Tedesco2, Patrick M Alexander3, Xavier Fettweis4 and Rajashree Datta3, (1)CUNY Graduate Center, New York, NY, United States, (2)CUNY City College, Earth and Atmospheric Sciences, New York, NY, United States, (3)CUNY Graduate School and University Center, New York, NY, United States, (4)University of Liège, Geography, Liège, Belgium
As datasets become larger, with the increasing spatial and temporal resolution of both observed and modeled data, the need to provide a service that makes them more accessible to the scientific community is increasing. At the same time, open-source tools are making more options available, but it can be difficult to determine what the viable alternatives are. In this presentation, we discuss a software architecture and data distribution model that was adopted to distribute the outputs of the regional climate model Modèle Atmosphérique Régional (MAR). This involved summarizing a large static dataset for ad-hoc query and data download in a web-based application called "MAR Explorer", and making the application available using a cloud-based Amazon server. The application was built using open-source Python tools, and is available at We discuss the web application development tools and data processing methods used to distribute the above mentioned dataset, with the goal of making these methods more easily accessible to others needing to distribute similar data.