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. ARISE-SAI-1.5K simulates stratospheric aerosol injection at ~ 21 km altitude starting in 2035. The underlying emission scenario is the middle-of-the-road SSP2-4.5 scenario. SAI is used to keep global mean surface air temperature near 1.5°C above the pre-industrial.

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 or git clone https://github.com/ReflectiveCloud/Book.git

  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#