## About

### Introduction

This platform enables free and easy access to the **urban** climate simulations provided by [National Center for Atmospheric Research](https://ncar.ucar.edu/) and [Amazon Web Services (AWS)](https://aws.amazon.com/) via Cloud Computing. By providing the necessary information as the input (e.g., time, latitude, longitude, climate scenarios, etc.), users can explore and utilize urban climate data. Specifically, users can:

- **visualize/analyze** urban climate of a particular city/cities under different climate change scenarios and different version model simulations (e.g., urban heat waves analysis)
- **train** fast machine learning emulators of the urban climate (e.g., mapping from radiation to urban temperature) using a Automated Machine Learning tool ([FLAML](https://microsoft.github.io/FLAML/))
- **apply** the machine learning emulators to users' own data to create customized urban climate projections for their own needs

### Relevant Publications

- Zheng, Z., Zhao, L. & Oleson, K.W. Large model structural uncertainty in global projections of urban heat waves. *Nat Commun* **12,** 3736 (2021). https://doi.org/10.1038/s41467-021-24113-9
- Zhao, L., Oleson, K., Bou-Zeid, E. *et al.* Global multi-model projections of local urban climates. *Nat. Clim. Chang.* **11,** 152–157 (2021). https://doi.org/10.1038/s41558-020-00958-8

### Concept

![concept](../pages/figures/concept.png)

### Technical Workflow

![workflow](../pages/figures/workflow.png)