VIP-SMUR / 24Sp-Microclimate

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Urban Microclimate using the Urban Weather Generator

The Urban Weather Generator models the urban heat island using EnergyPlus (.epw) weather files. The Python model utilizes various parameters to reflect urban canyon conditions.

Introduction

This notebook is a documentation for the urban microclimate sub-team progress and outcomes.

Notebook Summary

This notebook includes steps, process, and issues related to using the Urban Weather Generator (UWG) to have quick urban microclimate results. Below are the summarized steps of the process:

  1. Test run the UWG script using a selected .epw file retrieved from https://climate.onebuilding.org/.
  2. Perform sensitivity analysis test to select the most affective UWG inputs.
  3. Collect the exact values for the selected inputs in the selected .epw file location (Using Grasshopper script).
  4. Run the UWG with the correct inputs.
  5. Compare the UWG .epw results with the initial .epw file.

Usage

The notebook is structured in chronological order, where each heading is a step and below the step are its issues and process.

Key Findings and Observations

Steps

1. Test Run the UWG

Getting Started

  1. Clone repository to local machine:

    git clone https://github.com/ladybug-tools/uwg
  2. Install dependencies:

    cd uwg
    pip install -r dev-requirements.txt
    pip install -r requirements.txt
  3. Run the scripts individually as needed.

Issues

2. Sensitivity Analysis

Process

For the Sobol sensitivity analysis, we define an objective function that takes in our parameters to measure the correlation coefficient and covariance. In this case, we went with measuring the RMSE value to simulated dry bulb temperature to the canyon temperature of the Georgia Tech Campus. Due to the design of the function, the more that the values differ from the actual, the more it would penalize the performance, leading to more accurate outputs. Within our final plotting, we see that our data tends to be normally distributed, which further supports the accuracy of the sensitivity analysis.

Issues

3. Data Collection

Process

Issues/Notes

4. Run Accurate UWG

Process

To run the UWG tool:

  1. Clone this directory and install the required dependencies.
  2. Make sure to have your desired location's EPW file in the directory.
  3. Each of the parameters have a specific range for their values of input, which can be viewed within the Parameters.py file.
  4. Upon running, the UWG will start simulating the desired parameter/conditions onto the location of the EPW file, and will output a new simulated EPW.

5. Useful Tool

GT PACE ICE Cluster

PACE's Instructional Cluster Environment (ICE) offers an educational environment with opportunities to gain scientific computing experience.

To access:

  1. Navigate to terminal and enter: ssh gburdell3@login-ice.pace.gatech.edu
  2. Enter GT password at prompt

References

  1. Mao, J., Norford, L.K. (2021). Urban Weather Generator: Physics-Based Microclimate Simulation for Performance-Oriented Urban Planning. In: Palme, M., Salvati, A. (eds) Urban Microclimate Modelling for Comfort and Energy Studies. Springer, Cham. https://doi.org/10.1007/978-3-030-65421-4_12

  2. Harnessing cooling from urban trees: Interconnecting background climates, urban morphology, and tree traits, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2024-234, 2024.

  3. Bhatt MM, Gupta K, Danodia A, Chakroborty SD, Patel NR. Detailed urban roughness parametrization for anthropogenic heat flux estimation using earth observation data. Heliyon. 2023 Jul 17;9(7):e18361. doi: 10.1016/j.heliyon.2023.e18361. Erratum in: Heliyon. 2023 Sep 10;9(9):e19953. PMID: 37519678; PMCID: PMC10375860


GNI Abstract

https://github.com/kastnerp/Abstract-GNI-Symposium-Microclimate

GNI Data Processing

https://github.com/kastnerp/GNI-Microclimate-Paper