Downscaling Workflow

Overview

The downscaling workflow predicts carbon pools (SOC and AGB) for California crop fields and aggregates predictions to the county level. It uses ensemble-based uncertainty propagation via SIPNET model runs and Random Forest downscaling.

Key components:

• Environmental covariate extraction from multiple sources (ERA5, SoilGrids, TWI)
• Design point selection using k-means clustering
• SIPNET model runs at design points
• Random Forest models to downscale from design points to all fields
• County-level aggregation of carbon estimates

Concepts

• Anchor sites: Fields with ground truth validation data (e.g., Ameriflux sites)
• Design points: Representative fields selected for SIPNET simulation based on environmental clustering
• Downscaling: Process of extending predictions from design points to all California crop fields

Documentation

• Detailed Workflow Documentation - Step-by-step description of methods
• Results and Analysis - Visualizations and interpretation

Environment and Setup

Key Configuration Files

• .future.R - Sets up parallel processing
• 000-config.R - Configuration file for the workflow (called in each workflow script)

Quick start

# Load modules (geo cluster example)
module load R/4.4.0 gdal proj geos sqlite udunits quarto

# Decide where the shared CCMMF area lives (or set in .Renviron)
export CCMMF_DATA_DIR=/projectnb/dietzelab/ccmmf      # or $HOME/ccmmf-dev

git clone https://github.com/ccmmf/downscale.git
cd downscale

# Restore exact packages for this workflow
R -e 'if (!requireNamespace("renv", quietly = TRUE)) install.packages("renv"); renv::restore()'

# Run the pipeline [Not implemented]
# R -e 'targets::tar_make()'

Running the Workflow

The workflow consists of these main scripts:

# 1. Prepare environmental covariates
Rscript scripts/010_prepare_covariates.R

# 2. Assign anchor sites to fields
Rscript scripts/011_prepare_anchor_sites.R

# 3. Select design points via clustering
Rscript scripts/020_cluster_and_select_design_points.R

# 4. Cluster diagnostics and visualization
Rscript scripts/021_clustering_diagnostics.R

# 5. Extract SIPNET output from model runs
Rscript scripts/030_extract_sipnet_output.R  

# 6. Downscale and aggregate to county level
Rscript scripts/040_downscale_and_aggregate.R

# 7. Downscale analysis and interpretation
Rscript scripts/041_downscale_analysis.R

# 8. Generate results documentation
quarto render reports/downscaling_results.qmd

Advanced Setup and Use

Interactive Session on BU Cluster

# On geo.bu.edu:
qrsh -l h_rt=3:00:00 -pe omp 16 -l buyin

Job Submission

This is an example of how a script can be run on an HPC

qsub \
  -l h_rt=1:00:00 \
  -pe omp 8 \
  -o logs/03.out \
  -e logs/03.err \
  -b y Rscript downscale/999_workflow_step.R