WRF-SUEWS Coupling

7.1.1.1. WRF-SUEWS Coupling#

The WRF-SUEWS coupling project integrates the Weather Research and Forecasting (WRF) atmospheric model with SUEWS to provide detailed urban climate simulations at the mesoscale.

Warning

Version Compatibility: WRF-SUEWS is currently based on an older version of SUEWS. Integration with modern SuPy workflows requires additional development work.

7.1.1.1.1. Overview#

Purpose: WRF-SUEWS combines the strengths of both models:

WRF: Mesoscale atmospheric dynamics, 3D meteorological fields
SUEWS: Detailed urban surface energy and water balance processes

Key Benefits: - Two-way coupling: SUEWS provides surface fluxes to WRF, WRF provides meteorological forcing to SUEWS - Urban-specific physics: Detailed representation of urban surface processes within mesoscale simulations - High-resolution urban climate: Better representation of urban heat islands and urban meteorology - Research applications: Urban climate change studies, heat wave analysis, urban planning support

7.1.1.1.2. Technical Architecture#

Coupling Strategy: The integration replaces WRF’s default urban canopy model with SUEWS:

Initialisation: SUEWS surface parameters integrated into WRF land use data
Runtime coupling: At each timestep, WRF calls SUEWS for surface flux calculations
Data exchange: Meteorological variables and surface fluxes exchanged between models
Output: Combined WRF atmospheric fields with SUEWS surface diagnostics

Supported Features: - Seven surface types: Buildings, paved surfaces, vegetation, water bodies - Energy balance: Complete surface energy balance including storage heat flux - Water balance: Urban hydrology including runoff and evapotranspiration - Anthropogenic effects: Human activities and building energy consumption

7.1.1.1.3. Installation and Setup#

Note

High-Performance Computing: WRF-SUEWS is typically deployed on HPC systems due to computational requirements. The installation process requires significant technical expertise.

System Requirements:

Compilers: Intel Fortran compiler (recommended), GCC support available
Libraries: NetCDF, HDF5, MPI libraries
Platform: Linux/Unix systems, tested on JASMIN HPC and Apple M1

Installation Steps:

Clone Repository:

git clone --recurse-submodules https://github.com/Urban-Meteorology-Reading/WRF-SUEWS.git
cd WRF-SUEWS

Environment Setup:

# Create conda environment
conda env create --file=wrf_suews.yml
conda activate wrf_suews

Compilation:

Follow platform-specific compilation instructions in the repository documentation.

7.1.1.1.4. Usage Workflow#

1. Preprocessing (WPS):

# Process meteorological data
./geogrid.exe    # Define domain and terrain
./ungrib.exe     # Extract meteorological data
./metgrid.exe    # Interpolate met data to domain

2. SUEWS Configuration:

Prepare urban surface parameters:

Land use classification: Map urban areas to SUEWS surface types
Surface parameters: Building heights, vegetation fractions, surface properties
Anthropogenic forcing: Population density, energy consumption patterns

3. WRF-SUEWS Execution:

# Real data preprocessing
./real.exe

# WRF-SUEWS simulation
mpirun -np <cores> ./wrf.exe

4. Output Analysis:

WRF-SUEWS produces standard WRF output files with additional SUEWS diagnostics:

Atmospheric variables: Temperature, humidity, wind fields
Surface fluxes: Sensible heat, latent heat, momentum flux
Urban diagnostics: Storage heat flux, runoff, building energy use

7.1.1.1.5. Integration with Modern SUEWS#

Current Limitations:

Legacy SUEWS version: Based on older SUEWS physics and interface
No SuPy integration: Cannot leverage modern Python workflows
Manual configuration: Requires extensive manual parameter setup

Future Development Opportunities:

SuPy Integration:

# Conceptual future workflow
import supy as sp
import wrfsuews

# Configure SUEWS sites from WRF grid
sites = wrfsuews.generate_suews_sites(wrf_domain, landuse_data)

# Run coupled simulation
wrf_output = wrfsuews.run_coupled(
    wrf_config="namelist.input",
    suews_sites=sites,
    start_date="2020-06-01",
    end_date="2020-08-31"
)

Automated Parameter Generation: - Use modern GIS tools to derive SUEWS parameters from spatial data - Integration with UMEP spatial analysis capabilities - Automated urban morphology characterisation
Enhanced Output Processing: - Native pandas/xarray integration for analysis - Automated visualisation tools - Direct integration with climate impact assessment workflows

7.1.1.1.6. Research Applications#

Urban Heat Island Studies:

# Example analysis (conceptual)
# Extract urban temperature from WRF-SUEWS output
urban_temp = wrf_output.sel(landuse='urban')['T2']
rural_temp = wrf_output.sel(landuse='rural')['T2']

# Calculate UHI intensity
uhi_intensity = urban_temp - rural_temp

Climate Change Assessment:

Scenario analysis: Compare current vs future climate scenarios
Heat wave analysis: Detailed urban temperature during extreme events
Adaptation strategies: Evaluate green infrastructure impacts

Urban Planning Support:

Development scenarios: Test different urban development patterns
Green infrastructure: Quantify cooling effects of urban vegetation
Building energy: Assess urban-scale energy consumption patterns

7.1.1.1.7. Getting Started#

For Researchers New to WRF-SUEWS:

Background Knowledge: Familiarity with WRF and urban climate modelling essential
Start Simple: Begin with existing test cases before custom domains
Computational Resources: Ensure adequate HPC access for meaningful simulations
Community Support: Engage with WRF and SUEWS user communities

Resources:

WRF-SUEWS GitHub Repository
WRF User Guide
SUEWS documentation
JASMIN Computing Platform (for UK researchers)

Contributing:

The WRF-SUEWS project welcomes contributions:

Bug reports: Issue tracking on GitHub
Platform support: Help with compilation on new systems
Documentation: Improve installation and usage guides
Integration: Work on modern SuPy integration

Note

Development Status: WRF-SUEWS represents a sophisticated but complex integration. Future development should focus on simplifying the workflow and integrating with modern SUEWS/SuPy capabilities for broader adoption in the urban climate modelling community.