Using the AWS ARISE-SAI-1.5 Simulations Cloud Archive

Using the AWS ARISE-SAI-1.5 Simulations Cloud Archive#

Overview#

This repository contains Python notebooks demonstrating simple usage examples of the AWS ARISE-SAI-1.5k simulations cloud archive.

Repository Information#

About ARISE-SAI-1.5k Simulations#

The ARISE-SAI-1.5k simulations (Richter et al., 2022) are available on Amazon Web Services (AWS). These simulations are part of the CESM Community Projects and provide valuable data for Solar Radiation Management research.

Available Notebooks#

1. Basic Example#

AWS_ARISE_basic_example.ipynb

Shows how to use the S3 file system to read in the data and perform basic analysis tasks.

What you’ll learn:

  • Accessing data from AWS S3

  • Basic data reading and manipulation

  • Simple analysis workflows

2. Kerchunk Example#

kerchunk_example/AWS_ARISE_kerchunk_test.ipynb

Demonstrates how to use the kerchunk package to save metadata and create virtual zarr files, significantly speeding up read-in and processing steps for ARISE simulation analysis.

What you’ll learn:

  • Using kerchunk for metadata management

  • Creating virtual zarr files

  • Optimizing data access and processing

  • Advanced analysis workflows

Use Cases#

These notebooks are designed for researchers who want to:

  • Access ARISE-SAI-1.5k simulations from AWS cloud storage

  • Learn cloud-native data analysis techniques

  • Optimize data processing workflows using kerchunk

  • Perform reproducible research with cloud-based climate data

Getting Started#

  1. Clone the repository: git clone https://github.com/alistairduffey/AWS_ARISE

  2. Choose your notebook: Start with the basic example for fundamental concepts

  3. Explore kerchunk: Move to the advanced example for optimization techniques

  4. Adapt for your research: Modify the examples for your specific analysis needs

Additional Resources#