MPAS-Atmosphere and MPAS-JEDI Tutorials

Summer 2026

Overview

The Mesoscale and Microscale Meteorology (MMM) Laboratory of the NSF National Center for Atmospheric Research (NSF NCAR) will be hosting an in-person tutorial on the Model for Prediction Across Scales – Atmosphere (MPAS-A), followed by a tutorial covering the use of MPAS-A with the Joint Effort for Data assimilation Integration (JEDI) system. The tutorials will take place at the NSF NCAR Foothills campus, in Boulder, Colorado August 10 - 14, 2026.

MPAS-A tutorial on 10 – 12 August (Monday – Wednesday)

MPAS-JEDI tutorial on 13 – 14 August (Thursday – Friday)

The portion of the tutorial covering MPAS-JEDI is planned and conducted together with the Joint Center for Satellite Data Assimilation, the lead developers of JEDI.

The tutorials will consist of lectures, and practical sessions where participants will gain experience building, configuring and running the MPAS-Atmosphere model and MPAS-JEDI code. There will be no online/virtual component for these tutorials.

The primary audience for these tutorials is new or beginning users of MPAS-Atmosphere and/or MPAS-JEDI. Basic knowledge of atmospheric science and numerical modeling, as well as experience working within a Unix computing environment, is required for these tutorials.

MPAS-Atmosphere

The MPAS-A tutorial will cover the basics of how to set-up, run, and post-process stand-alone MPAS-A simulations. Topics that will be covered will include:

Horizontal (uniform and variable resolution) mesh configuration

Global and regional configurations

Real-data and idealized case initialization

MPAS-A dynamical solver and numerical methods

MPAS-A physics

Software framework and MPAS infrastructure

Post-processing tools

MPAS-JEDI

MPAS-JEDI is the global-/regional-unified data assimilation system for MPAS-A based upon the Joint Effort for Data assimilation Integration. The MPAS-JEDI tutorial will cover the following topics with instructional lectures and hands-on practicals:

MPAS-JEDI data assimilation software build and test

Deterministic and ensemble data assimilation algorithms and configurations

Preprocessing and assimilation settings of observations

Global and regional applications