Enabling high-performance cloud computing for the Community Multiscale Air Quality Model (CMAQ) version 5.3.3:...

Area of Science:

• Environmental science
• Atmospheric chemistry
• Computational modeling

Background:

• The Community Multiscale Air Quality Model (CMAQ) is a key tool for air quality simulation, used by regulatory agencies and researchers globally.
• CMAQ supports studies on environmental fate, transport, climate, and health impacts.
• High-performance computing (HPC) is crucial for complex air quality simulations.

Purpose of the Study:

• To make CMAQ accessible on cloud platforms for enhanced computational power.
• To provide a tested technology stack for major cloud service providers (CSPs).
• To offer documentation and tutorials for optimizing air quality simulations in the cloud.

Main Methods:

• CMAQ version 5.3.3 configurations were developed for two major CSPs.
• A benchmark application suite was created to test and verify cloud-based simulation components.
• Resources include online documentation, tutorials, and guidelines for scaling and optimization.

Main Results:

• CMAQ is now available as a tested technology stack on leading CSPs.
• Resources facilitate rapid deployment of CMAQ, datasets, and visualization tools on ephemeral HPC clusters.
• Findings from cloud-based CMAQ simulations using vendor resources are presented.

Conclusions:

• Cloud-based CMAQ enables efficient, scalable air quality modeling.
• The developed resources empower the user community to adapt cloud simulations for their needs.
• Identified areas for potential optimization in storage and compute architectures for cloud-based CMAQ.