dataset · Other

Hybrid statistical-dynamic downscaling based on multi-model ensembles in Southeast Asia

GCMs under CMIP6 have been widely used to investigate climate change impacts and put forward associated adaptation and mitigation strategies. However, the relatively coarse spatial resolutions (usually 100~300km) preclude their direct applications at regional scales, which are exactly where the analysis (e.g., hydrological model simulation) is performed. To bridge this gap, a typical approach is to ‘refine’ the information from GCMs through regional climate downscaling experiments, which can be

Source details

Licence: All the code in this repository is [MIT](https://choosealicense.com/licenses/mit/) licensed, but we request that you please provide attribution if reusing any of our digital content (graphics, logo, c

Evidence quality: 32.5

Listed in aws-odr public catalogue API on 2026-10-16; relevance/value screened (haiku).

Metadata checked: 2026-10-14T13:20:00.000Z

Evidence

• arn:aws:s3:::cmip6-wrf-southeastasia
• https://registry.opendata.aws/cmip6-era5-hybrid-southeast-asia/

Check upstream coverage, uncertainty and licence before use. Station observations are not forecasts or design levels.