3b. Process Forcings (case.process_forcings)

The final part of the CrocoDash workflow is extracting and processing all the forcing data your simulation needs. This includes initial conditions, boundary conditions, tidal forcings, biogeochemistry data, and more. You process all of this data through the case.process_forcings call. case.process_forcings wraps a submodule of CrocoDash called extract_forcings. Extract_forcings is a set of scripts to process each forcing, like initial/boundary conditions, tides, etc… You trigger this from Python via case.process_forcings(), or from the shell via crocodash process.

Workflow Overview

1. case.configure_forcings(...) — writes inputdir/extract_forcings/config.json with your case-specific forcing setup

2. case.process_forcings(...) — reads that config and runs the extraction pipeline

3. Outputs land in inputdir/ocnice/

The key insight: you don’t have to run this from a Jupyter notebook. After configure_forcings completes you can submit the extraction as a batch job using the CLI:

crocodash process --caseroot ~/croc_cases/mycase --all

Directory Structure

inputdir/
├── extract_forcings/
│   └── config.json        # Written by case.configure_forcings
└── ocnice/                # Output goes here
    ├── init_eta_filled.nc
    ├── init_vel_filled.nc
    ├── init_tracers_filled.nc
    ├── forcing_obc_segment_001.nc
    └── ...

Command-Line Interface

See CLI reference for full flag documentation.

# Run all forcing extractions
crocodash process --caseroot ~/croc_cases/mycase --all

# Run only specific forcings
crocodash process  --tides
crocodash process  --runoff
crocodash process  --bgc

# Run multiple forcings
crocodash process  --tides --runoff --bgc

# Run all except certain forcings
crocodash process  --all --skip bgcic
crocodash process  --all --skip conditions bgcic

# Skip entire processing phases
crocodash process  --all --skip conditions

This flexibility lets you:

• Test individual components without running everything

• Re-run one forcing type if your source data changed

• Submit to a batch queue and re-run from the CLI after a failure

• Resume a partially-completed run

Python API

You can also call the driver directly from Python:

from CrocoDash.extract_forcings.driver import run_workflow

run_workflow(
    config_path="~/scratch/croc_input/mycase/extract_forcings/config.json",
    ic=True,
    bc=True,
    tides=True,
)

The Processing Pipeline

config.json + _crocodash_state.json
    ↓
get_dataset_piecewise     (download raw OBC/IC data in time-stepped chunks)
    ↓
regrid_dataset_piecewise  (regrid to model grid, fill missing data)
    ↓
merge_piecewise_dataset   (concatenate chunks into final OBC files)
    ↓
[tides / bgc / runoff / chl modules run independently]
    ↓
inputdir/ocnice/

Design Philosophy

CrocoDash delegates heavy lifting to specialist packages:

Task	Tool	Module
OBC regridding	regional-mom6	obc.py
Initial condition regridding	regional-mom6	initial_condition.py
IC land-fill	mom6_forge	initial_condition.py
Chlorophyll, fill, mapping	mom6_forge	Various modules
Data formatting	netCDF4, xarray	Throughout

For more detail on OBC regridding, see the regional-mom6 documentation.

See also

• 3a. Configure Forcings — the step that writes the config.json this driver consumes

• Datasets — the raw data sources the driver downloads from

• Architecture — where extract_forcings lives in the code and how to extend it

• Submodule API Usage — exact regional-mom6 / mom6_forge functions called during processing