# 11th Symposium on Advances in Modeling and Analysis Using Python

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> **[11th Symposium on Advances in Modeling and Analysis Using Python](https://annual.ametsoc.org/index.cfm/2021/program-events/conferences-and-symposia/11th-symposium-on-advances-in-modeling-and-analysis-using-python/)**
>
> The AMS is a global community committed to advancing weather, water, and climate science and service.

Abstracts are due by **8 September 2020 at 11:59 PM EST**

### **Topics Covered**

This symposium is soliciting papers on the use of Python in research, operational, and educational contexts. Please submit work relating to methodologies, applications, and package development in the following topics:

- Working with large data sets using Python
- Visualization and data discovery using Python
- Teaching, training, outreach and building communities around Python
- Python in operations and research to operations
- New Python tools in the atmospheric and oceanographic sciences New

In addition there will be joint sessions on: Workflows for cloud-based data analysis in Python with a focus on CMIP6 (Python and the 34th Conference on Climate Variability & Change), Python frameworks for reproducible communicable Artificial Intelligence workflows (Python and Conference on AI) Exploring the Scalability and Parallel Performance of Python on High Performance Computing Systems (HPC and Python).

### Joint Sessions

- The Earth Prediction Innovation Center – Enabling a community-based approach to advance NWP (Joint with HPC, EIPT, AI, and R2O)

### Conference Contacts

The Eleventh Symposium on Advances in Modeling and Analysis Using Python is organized by the [AMS Committee on Environmental Information Processing Technologies](https://annual.ametsoc.org/stac/index.cfm/boards/board-on-environmental-information-processing-technologies/).

For updates follow the Python Symposiums on Twitter [@amspython](https://twitter.com/amspython?lang=en)

For additional information, please contact the program chair, Scott Collis (email: [scollis@anl.gov](mailto:scollis@anl.gov)). We gratefully acknowledge the work of the Python program committee: Hannah Aizenman, Sheri Mickelson, Daniel Rothenberg, Ryan May and Jingyin Tang.
