dataset · Global
Community Earth System Model v2 Large Ensemble (CESM2 LENS)
The US National Center for Atmospheric Research partnered with the IBS Center for Climate Physics in South Korea to generate the CESM2 Large Ensemble which consists of 100 ensemble members at 1 degree spatial resolution covering the period 1850-2100 under CMIP6 historical and SSP370 future radiative forcing scenarios. Data sets from this ensemble were made downloadable via the Climate Data Gateway on June 14th, 2021. NCAR has copied a subset (currently ~500 TB) of CESM2 LENS data to Amazon S3 as
Visit source ↗Source details
Licence: https://www.ucar.edu/terms-of-use/data
Evidence quality: 40.1
Listed in aws-odr public catalogue API on 2026-10-16; relevance/value screened (haiku).
Metadata checked: 2026-10-14T13:20:00.000Z
What's in it
- Data offered docs-verified
- 100-member CESM2 LENS climate model ensemble · physical variables, one Zarr store per variable, run type and frequency · monthly and daily temporal frequency
- Coverage llm-inferred
- Global · 1850-2100
- Resolution docs-verified
- 1 degree spatial; monthly and daily temporal
- Update frequency docs-verified
- Rare
- Formats docs-verified
- Zarr
- Access docs-verified
- Free, open; anonymous S3 access without an AWS account (bucket ncar-cesm2-lens, us-west-2); licence: UCAR terms of use (https://www.ucar.edu/terms-of-use/data)
Useful for
- Use cases llm-inferred
- Assessing internal climate variability versus forced change in SSP3-7.0 projections for water resource planning · Ensemble-based spread of future rainfall extremes as coarse climate context for drainage strategy narratives · Coarse-scale climate change context for FRA or civils options appraisal, with local downscaling applied separately
- Audience llm-inferred
- climate scientists · hydrologists · water resources planners · drainage engineers
Limitations
- Constraints llm-inferred
- 1-degree grid is too coarse for UK catchment or site-scale design without downscaling · Historical and SSP370 scenario only, no other SSPs · Subset of NCAR data (~500 TB), so not every field is available · Requires Python Xarray and Zarr tooling to use efficiently · Rare updates; LENS experiment is complete
Evidence
Check upstream coverage, uncertainty and licence before use. Station observations are not forecasts or design levels.