[SEO Subhead]
This Guidance shows how to predict the weather over the Continental United States (CONUS) by deploying the Weather Research and Forecasting (WRF) model on AWS. Provided by the National Center for Atmospheric Research (NCAR), the WRF model helps support atmospheric research and operational forecasting applications. By running the WRF model using high performance computing (HPC) clusters on AWS, you can maximize the performance of your weather prediction workloads to accurately and reliably predict, plan, and manage weather forecasts.
Please note: [Disclaimer]
Architecture Diagram

-
HPC Cluster Deployment
-
Prediction Workflow
-
HPC Cluster Deployment
-
This architecture diagram shows how to provision the AWS ParallelCluster user interface (UI) and configure an HPC cluster with compute and storage capabilities. For the numerical weather prediction workflow, open the other tab.
Step 1
Users deploy the Guidance AWS CloudFormation stack to provision networking resources (Amazon Virtual Private Cloud [Amazon VPC] and subnets), storage (Amazon FSx for Lustre), and the AWS ParallelCluster UI. -
Prediction Workflow
-
This architecture diagram shows how to predict the weather for CONUS by deploying the WRF model on AWS and setting up the numerical weather prediction workflow. For the HPC cluster deployment, open the other tab.
Step 1
Users authenticate to the AWS ParallelCluster UI (as detailed in the previous HPC Cluster Deployment architecture diagram).
Well-Architected Pillars

The AWS Well-Architected Framework helps you understand the pros and cons of the decisions you make when building systems in the cloud. The six pillars of the Framework allow you to learn architectural best practices for designing and operating reliable, secure, efficient, cost-effective, and sustainable systems. Using the AWS Well-Architected Tool, available at no charge in the AWS Management Console, you can review your workloads against these best practices by answering a set of questions for each pillar.
The architecture diagram above is an example of a Solution created with Well-Architected best practices in mind. To be fully Well-Architected, you should follow as many Well-Architected best practices as possible.
-
Operational Excellence
This Guidance uses a combination of fully managed services (including API Gateway, Amazon Cognito, and Lambda) and self-managed services (including FSx for Lustre and Amazon EC2). The latter services are deployed to a configurable HPC cluster by means of a template and can be reconfigured or updated if cluster performance requirements change. You can use Amazon CloudWatch to monitor all these services through event logging.
-
Security
Amazon Cognito and API Gateway provide secure authentication and authorization and secure API access management. You can then log in to the HPC cluster’s head node for application deployment and management, using the AWS Systems Manager Session Manager secure shell—which provides greater security—or by using NICE DCV. Additionally, FSx for Lustre provides data encryption both in transit and at rest. By scoping AWS Identity and Access Management (IAM) policies to the minimum permissions required, you can limit unauthorized access to resources.
-
Reliability
AWS ParallelCluster uses HPC cluster job scheduling to enable parallel computational task implementation, using Slurm Workload Manager, which optimally allocates resources based on job requirements, priorities, and user-defined policies. This reduces the chance of application failure so that you can run weather simulations and avoid downtime errors. Additionally, this Guidance deploys EC2 instances in different Availability Zones for increased reliability, and FSx for Lustre provides highly reliable storage for your HPC clusters.
-
Performance Efficiency
This Guidance lets you efficiently manage and provision HPC clusters using AWS ParallelCluster and a YAML-based configuration. AWS ParallelCluster efficiently scales its CPU and RAM footprint and the instance number both horizontally and vertically to handle increased workloads. This Guidance also uses Message Passing Interface to provide efficient parallel processing and distributed data processing capabilities. Additionally, FSx for Lustre provides a high-performance storage layer for the HPC clusters.
-
Cost Optimization
As a managed service, Amazon Cognito provides cost-effective user authentication and authorization. Additionally, Amazon EC2 Auto Scaling scales cluster node instances horizontally or vertically based on workload demand, so that you won’t have to provision and pay for unused resources. FSx for Lustre also provides a cost-efficient storage layer that makes it easy to launch, run, and scale storage for your HPC tasks.
-
Sustainability
This Guidance uses specialized Amazon EC2 instances (including Hpc6a instances powered by third-generation AMD Epyc processors) that offer high performance for compute-intensive HPC workloads. This performance, combined with the elasticity and scalability of serverless of AWS services, helps you achieve optimal resource utilization, helping you avoid overprovisioning resources. Additionally, FSx for Lustre supports concurrent access to the same files and directories from thousands of compute instances, further helping you minimize your workloads’ environmental impact.
Implementation Resources

A detailed guide is provided to experiment and use within your AWS account. Each stage of building the Guidance, including deployment, usage, and cleanup, is examined to prepare it for deployment.
The sample code is a starting point. It is industry validated, prescriptive but not definitive, and a peek under the hood to help you begin.
Related Content

[Title]
Disclaimer
The sample code; software libraries; command line tools; proofs of concept; templates; or other related technology (including any of the foregoing that are provided by our personnel) is provided to you as AWS Content under the AWS Customer Agreement, or the relevant written agreement between you and AWS (whichever applies). You should not use this AWS Content in your production accounts, or on production or other critical data. You are responsible for testing, securing, and optimizing the AWS Content, such as sample code, as appropriate for production grade use based on your specific quality control practices and standards. Deploying AWS Content may incur AWS charges for creating or using AWS chargeable resources, such as running Amazon EC2 instances or using Amazon S3 storage.
References to third-party services or organizations in this Guidance do not imply an endorsement, sponsorship, or affiliation between Amazon or AWS and the third party. Guidance from AWS is a technical starting point, and you can customize your integration with third-party services when you deploy the architecture.