AMS Short Course on Using Python in Climate and Meteorology: Advanced Methods

Saturday and Sunday, 21-22 January, Starting at 8:00A.M., Room 239

The AMS Short Course on Using Python in Climate and Meteorology: Advanced Methods will be held on 21-22 January 2012 preceding the 92nd AMS Annual Meeting in New Orleans, LA.

The application of object-oriented programming and other advances in computer science to the atmospheric sciences has in turn led to advances in modeling and analysis tools and methods. The open-source language Python has been at the forefront of the application of such advances, through projects such as PCMDI’s CDAT and ESG’s end-user tools, resulting in a robust computing environment for all kinds of atmospheric science, including (but not limited to): modeling, time series analysis, air quality data analysis, satellite data processing, in-situ data analysis, visualization, gridding, model intercomparison, and very large (petabyte) dataset manipulation and access. This short course is designed in modules covering various areas in which Python is used (I/O, visualization, diagnosis, languages coupling, etc.).

As Python’s reach grows in the Atmospheric community, many users nowadays have some basic knowledge in CDAT, and use it for minimal day-to-day operation. But most still do not feel confortable developing advanced diagnosis with Python-based tools. This course aims at breaking this fear and expose users to richer Python features, leading in turn to the development to new expert diagnosis that can be shared back to the community.

 

The course will span two days and cover mostly features of the new Ultra-scale Visualization Climate Data Analysis Tools (UV-CDAT). UV-CDAT is essentially built n top of CDAT version 6 but is slated to replace CDAT itself. The course will introduce UV-CDAT’s new features especially in the visualization realm. It will also help the users to go past CDAT’s basic use and reach into its full power as a complete analysis tool.

 

Most of the course will be geared around discovering and using data for the Fifth Annual Report of the Intergovernmental Panel on Climate Change (IPCC AR5). The course format consists of two day of lectures mixed with hands-on exercises. Strong user participation will be encouraged that could reshape the flow of the course “on-the-fly”. The main instructor for the course is Charles S. Doutriaux, Program for Climate Model diagnosis and Intercomparison at the Lawrence Livermore National Laboratory, CA.

Users are expected to bring their own laptop. AC and internet access will be available. Note that this class is for users with a good knowledge of CDAT/Python. A sister class, aimed at beginners, is scheduled concurrently with this advanced course; students without experience in Python are encouraged to take the beginner's course.

For more information please contact Charles Doutriaux at PCMDI, 7000 East Avenue, Livermore, CA, 94450, USA. (tel: (925) 422-1487; email: doutriaux1@llnl.gov. (9/11)