wrfup: WRF Urban Parameters Toolkit

Welcome to the wrfup documentation! A python tool to integrate high-resolution, real-world urban data into WRF (Weather Research and Forcast). It automatically downloads, calculates, and ingests the needed urban fields directly into WRF geo_em files. Using wrfup, users can enhance urban weather simulations with any of the WRF’s urban canopy parameterizations, including SLUCM, BEP, and BEP+BEM.

Overview

wrfup is a Python tool designed to streamline the urban data preparation of urban climate simulations. It automatically:

• Downloads urban morphology data like building heights and urban fraction from the state of the art global sources.

• Calculates the necessary urban fields for WRF, such as URB_PARAM and FRC_URB2D.

• Ingests these fields directly into WRF’s geo_em files, ensuring a fine representation of urban areas in your simulations.

Workflow Diagram

The following diagram shows how wrfup integrates into the WRF preprocessing workflow:

Sections:

• Installation
  • System Requirements
• Usage
  • Basic Command Structure
  • Example Use Case
  • Workflow Diagram
• Features
  • Example Data Sources:
• wrfup package
  • main()
  • download_and_extract_zip()
  • download_tiles()
  • get_tile_names_in_aoi()
  • get_total_download_size()
  • lat_lon_to_tile_indices()
  • merge_tiles()
  • add_frc_urb2d_field_if_not_exists()
  • add_urb_param_fields_if_not_exists()
  • calculate_frc_urb2d()
  • calculate_urb_param()
  • crop_opened_tiff_by_lat_lon_bounds_and_return_mosaic()
  • check_geo_em_file()
  • clean_up()
  • get_lat_lon_extent()
  • Info

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Indices and tables

• Index

• Module Index

• Search Page