Downscaling And Aggregation Workflow

Warning

This proof of concept is untested and subject to change. Interpret results as illustrative.

Overview

This workflow estimates carbon pools (SOC and AGB) for California crop fields and aggregates to the county level.

Key components:

• Environmental covariates (ERA5, SoilGrids, TWI)
• Design point selection via k-means
• SIPNET simulations at design points [done externally]
• Random Forest downscaling to all fields
• County-level aggregation

Configuration: see 000-config.R for paths, variables, and parallel settings.

Quick start

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

# Point to the shared CCMMF directory (or set in .Renviron)
export CCMMF_DIR=/projectnb/dietzelab/ccmmf      # or $HOME/ccmmf-dev

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

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

Run Sequence

See full details about how to set up and run the workflows in the Technical Documentation.

# Data prep and clustering
Rscript scripts/010_prepare_covariates.R
Rscript scripts/011_prepare_anchor_sites.R
Rscript scripts/020_cluster_and_select_design_points.R
Rscript scripts/021_clustering_diagnostics.R

# Extract SIPNET outputs and create mixed-PFT scenarios
Rscript scripts/030_extract_sipnet_output.R
Rscript scripts/031_aggregate_sipnet_output.R

# Downscale and aggregate
Rscript scripts/040_downscale.R
Rscript scripts/041_aggregate_to_county.R

# Analysis and figures
Rscript scripts/042_downscale_analysis.R
Rscript scripts/043_county_level_plots.R