Urban Climate Explorer

Explore and Emulate Urban Climate on AWS Cloud.

Author: Dr. Zhonghua Zheng

Overview

• About
  • Introduction
  • Relevant Publications
  • Concept
  • Technical Workflow
• Install and Run
  • Install
  • Run

Tutorial

• Setup
• Example for CESM1
  • Step 1: data analysis
  • Step 2: automated machine learning
• Example for CESM2
  • Step 1: data analysis
  • Step 2: automated machine learning
• Example for CMIP6
  • Step 1: load CESM2 data
  • Step 2: load CMIP6 data
  • Step 3: compare CESM2 training and CMIP6 data
  • Step 4: automated machine learning
  • Step 5: visualization
• Example for CESM2 Climate Change
  • Step 1: load future data (2066-01-02 to 2085-12-31)
  • Step 2: load present data (2016-01-02 to 2035-12-31)
  • Step 3: compare future and present training data
  • Step 4: automated machine learning

Reference

• How to create a JSON file?
• How to create a mask for CESM1’s “urban areas”?
• How to create a subgrid info file for CESM2’s CLM processing?

How to ask for help?

The GitHub issue tracker is the primary place for bug reports.

Acknowledgments

We thank AWS for providing AWS Cloud Credits for Research.

We would like to acknowledge high-performance computing support from Cheyenne (doi:10.5065/D6RX99HX) provided by NCAR’s Computational and Information Systems Laboratory, sponsored by the National Science Foundation.