The climate-projection dataset landscape
What this page covers
The major climate-projection and climate-baseline datasets you’ll encounter doing African adaptation work. For each: what it is, what it’s best for, what its limitations are, and where to get it. The headline comparison table; then per-dataset write-ups for the most-likely-relevant ones.
At-a-glance comparison
To be written. A single table with columns:
| Dataset | Type | Resolution | Coverage | Bias-corrected | Africa-suited | Best for |
|---|
Populated from datasets_inventory.md.
Datasets you’ll meet most often
Per-dataset write-ups (1-2 paragraphs each) for:
NEX-GDDP-CMIP6
The Atlas default. 18 models, 0.25°, BCSD bias correction.
CORDEX-Africa
Dynamical downscaling. CMIP5-era mature, CMIP6-era in progress.
ISIMIP3b
Impact-sector default. 5 models, 0.5°, ISIMIP3BASD bias adjustment.
CHELSA-CMIP6
Very-high-resolution (1 km) for ecology / agroecology.
ERA5 / ERA5-Land
The dominant historical-reanalysis baseline for Africa.
CHIRPS / CHIRTS-ERA5
UCSB observational gridded rainfall + temperature.
AR6 Interactive Atlas
IPCC’s pre-processed CMIP6 + CORDEX organised by AR6 regions.
World Bank Climate Knowledge Portal
The most-likely alternative tool the Atlas’s audience already uses.
Mentioned briefly
One-line each on: CMIP6 raw (ESGF), CMIP5 raw, CIL-GDPCIR, WorldClim Future, MERRA-2, JRA-55, GMFD, W5E5.
How to choose for your use case
To be written. Decision-tree framing:
- National / admin-1 adaptation work with multiple variables → NEX-GDDP-CMIP6
- Impact-sector modelling (crops / water / health) → ISIMIP3b
- Very-fine-resolution ecological work → CHELSA-CMIP6
- Physical-consistency-critical extreme events → CORDEX-Africa
- Historical baseline + observed-change analysis → ERA5 + CHIRPS/CHIRTS
- Operational reporting + government policy framing → AR6 Interactive Atlas + CCKP
Why the Atlas chose NEX-GDDP-CMIP6
To be written. Brief justification cross-linking to Atlas approach.