Running the Model

The `run_model()` function

run_model() is the single entry point for all forward model simulations. It accepts keyword overrides for any parameter, runs the full pipeline, and returns an Outputs object.

from biosnicar import run_model
 
# Default configuration
outputs = run_model()
print(outputs.BBA)
 
# Override specific parameters
outputs = run_model(solzen=50, rds=1000, black_carbon=500)
print(outputs.albedo)  # 480-element spectral albedo

Supported override keys

solzen, direct, incoming, rds, rho, dz, lwc, layer_type, shp, grain_ar, cdom, water, hex_side, hex_length, shp_fctr, and impurity names (black_carbon, snow_algae, glacier_algae, dust).

Working with outputs

import numpy as np
 
outputs = run_model(solzen=50, rds=500)
albedo = np.array(outputs.albedo)
wavelengths = np.arange(0.205, 4.999, 0.01)
 
print(f"Albedo at 0.5 µm:  {albedo[29]:.4f}")
print(f"Albedo at 1.0 µm:  {albedo[79]:.4f}")
print(f"Albedo at 1.5 µm:  {albedo[129]:.4f}")
print(f"Broadband albedo:  {outputs.BBA:.4f}")
print(f"Visible BBA:       {outputs.BBAVIS:.4f}")
print(f"NIR BBA:           {outputs.BBANIR:.4f}")

Chaining to satellite bands

run_model() returns an Outputs object that supports .to_platform():

s2 = run_model(solzen=50, rds=1000).to_platform("sentinel2")
print(s2.B3, s2.NDSI)

See Remote Sensing for details.

Running from the command line

For a quick test, run from the repository root:

python main.py

This runs with all default settings and prints results to the console.

Custom input files

For batch configuration or non-standard settings, edit inputs.yaml or point to a custom file:

outputs = run_model(input_file="path/to/custom_inputs.yaml")

You can maintain multiple YAML files for different configurations and loop through them:

for config in ["config_clean.yaml", "config_dusty.yaml", "config_algal.yaml"]:
    outputs = run_model(input_file=config)
    print(f"{config}: BBA = {outputs.BBA:.4f}")

Input Parameters Working with Impurities