Abstract: This file provides information on how to extract Urban Morphology parameters for the province of British Columbia (BC), Canada. These high-resolution parameters are needed to successfully run the Weather Research and Forecasting (WRF) model coupled with Single Layer (option 1 in WRF urban physics) and Multi-layer (option 2 and 3 in WRF model, urban physics) Urban Canopy Models. This Shapefile dataset has been generated using the Housing dataset from the Canada data warehouse . The shapefiles were collected and combined to serve as input for a Python script. In this file, "domain" refers to the domain the WRF model will be run for (e.g., d01, or d01, d02, d03, etc. if a nested domain is used in the WRF model). "geo_em.{domain}.nc" refers to the output of the geogrid.exe program which is one of the core programs of WPS program. For example, for a 3 nested domain setup, geo_em files will be annotated as follows: 'geo_em.d01.nc', 'geo_em.d02.nc', 'geo_em.d03.nc'. This folder contains all the documents necessary for extracting the Urban Morphology parameters. Refer to Section 1 for a description of the folder structure. You will first need to extract the shapefile of the domain considered using the VERDI program (https://www.cmascenter.org/verdi/). For more details, refer to Section 2. Make sure to save this shapefile under the SHP subfolder described in Section 1. To utilize the dataset, ensure the geo_em files are placed in the 'Main' folder mentioned in Section 1, which should also contain the Python script named 'Canada_UrbanMorphology.py', the folder with the dataset (geo_em.{domain}.nc), and the folder with the shapefiles (Home_BC and domain). The Python script 'Canada_UrbanMorphology.py' necessitates three libraries: NetCDF4, geopandas, and numpy, all of which can be installed via pip or Anaconda. Follow the specific instructions provided in Section 3 to adjust the script, then proceed to running the program using the following command: python3 Canada_UrbanMorphology.py ...
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