Quickstart guide

This guide provides a brief introduction to using the BLDFM framework through example scripts. It covers running a minimal example and extending it to compare with the Kormann-Meixner (FKM) footprint model.

Minimal Example

The runs.minimal_example script demonstrates the basic usage of the BLDFM framework. It calculates concentration and flux fields for a neutrally stratified boundary layer with default settings.

To run the script, execute the following command in the terminal:

$ python3 -m runs.minimal_example

This will generate three plots saved in the plots/ directory:

  • Concentration at z0: The concentration field at the surface.

  • Concentration at zm: The concentration field at the measurement height.

  • Vertical kinematic flux at zm: The flux field at the measurement height.

The script uses the following steps:

  1. Defines the domain, grid resolution, and atmospheric parameters (e.g., wind speed, roughness length).

  2. Generates a synthetic surface flux field using src.utils.ideal_source().

  3. Computes vertical profiles of wind and diffusivity using src.pbl_model.vertical_profiles().

  4. Solves the steady-state transport equation using src.solver.steady_state_transport_solver().

This example provides a foundation for understanding the core components of BLDFM.

Comparison with the FKM Model

The runs.comparison_footprint script extends the minimal example by comparing the BLDFM model with the Kormann-Meixner (FKM) footprint model. This script demonstrates how to evaluate the performance of BLDFM against an established analytical model.

To run the script, execute the following command in the terminal:

$ python3 -m runs.comparison_footprint
This will generate a plot saved in the plots/ directory:

  • Comparison of BLDFM and FKM footprints: A side-by-side visualization of the flux footprints from both models.

The script follows these steps:

  1. Sets up the domain, grid resolution, and atmospheric parameters, similar to the minimal example.

  2. Computes the BLDFM footprint using src.solver.steady_state_transport_solver().

  3. Computes the FKM footprint using estimateFootprint from the Kormann Meixner model.

  4. Plots the results for visual comparison.

This example demonstrates how BLDFM can be used for model validation and comparison with analytical solutions.