This repository provides the processing pipeline and metadata for computing 250 m bioclimatic variables (BIO1–BIO19) for Bhutan from CMIP6 climate projections.
It does not host the climate data. Source data must be downloaded from the original CSIRO dataset (see below).
Download the required climate grids from:
Dorji, S., Stewart, S., Bajwa, A., Aziz, A., Shabbir, A., & Adkins, S. (2025). High-resolution (250 m) historical and projected (CMIP6) air temperature and precipitation grids for Bhutan (v1). CSIRO. Data Collection. DOI: https://doi.org/10.25919/pec2-hs50
- Download source climate grids from https://doi.org/10.25919/pec2-hs50
- Place raw monthly rasters into
01_raw_cmip6_data/01_cmip6_monthly/ - Run the pipeline:
Rscript 10_scripts/r/bioclim_master.R \
--input_root ./01_raw_cmip6_data/01_cmip6_monthly \
--output_root ./03_bioclim_variables/01_bioclim_by_gcmOr using PowerShell (full pipeline):
pwsh -File ./10_scripts/ps/run_all.ps1 -ProjectRoot . -Overwrite -CleanOutputscmip6_bioclim_bhutan_v1_0/
├── 00_project_metadata/ ← Citation, provenance, variable dictionaries
├── 01_raw_cmip6_data/ ← Place source data here (not tracked in git)
├── 02_bias_corrected_data/ ← Intermediate bias-corrected grids
├── 03_bioclim_variables/ ← Per-GCM BIO1–BIO19 rasters
├── 04_ensemble_products/ ← Multi-model ensemble mean/SD/min/max/uncertainty
├── 05_multicollinearity_analysis/ ← VIF/correlation screening outputs
├── 06_quality_control/ ← QC and alignment reports
├── 07_logs/ ← Processing logs
├── 08_model_ready_layers/ ← Final SDM-ready predictor rasters
└── 10_scripts/ ← All R and PowerShell scripts
- Historical baseline: BIO1–BIO19 for 1986–2015
- Future projections: BIO1–BIO19 for 10 GCMs × 4 SSPs × 3 time periods (2021–2050, 2051–2080, 2071–2100)
- Ensemble products: mean, standard deviation, minimum, maximum, uncertainty maps
- Predictor sets: multicollinearity-screened subsets for SDM use
See 00_project_metadata/ for:
| File | Contents |
|---|---|
citation.cff / citation.txt |
How to cite this pipeline |
data_provenance.md |
Processing lineage |
variable_dictionary.csv |
BIO variable definitions and units |
gcm_inventory.csv |
GCM inventory |
ssp_inventory.csv |
SSP/scenario inventory |
temporal_coverage.csv |
Time period inventory |
modeling_guide.html |
Detailed guide for downstream SDM workflows |
Bioclimatic variables (BIO1–BIO19) follow the standard definitions of O'Donnell & Ignizio (2012) and Nix (1986), computed from monthly tasmin, tasmax, and pr rasters using the R terra package. Source climate grids (Dorji et al., 2025) are pre-bias-corrected and downscaled to 250 m by the CSIRO team using a delta-change approach; no additional bias correction is applied in this pipeline. See METHODS.md for full methodological detail.
If you use this pipeline or its outputs, please cite both this repository and the source dataset:
This pipeline:
See 00_project_metadata/citation.cff
Source data (required):
Dorji, S., Stewart, S., Bajwa, A., Aziz, A., Shabbir, A., & Adkins, S. (2025). High-resolution (250 m) historical and projected (CMIP6) air temperature and precipitation grids for Bhutan (v1). CSIRO. Data Collection. https://doi.org/10.25919/pec2-hs50
- GitHub: https://github.com/wangdiues/BhutanBioClims-High-resolution-250-m-historical-and-projected-CMIP6-bioclimatic-variables-for-Bhutan
- Release v1.0.0: https://github.com/wangdiues/BhutanBioClims-High-resolution-250-m-historical-and-projected-CMIP6-bioclimatic-variables-for-Bhutan/releases/tag/v1.0.0