CHELSA V2 is currently only available for a selected number of CMIP6 scenarios. Since the number of models and rcps has increased a lot from CMIP5 to CMIP6, we do not provide a full list of all possible GCM and SSP combinations at 1km resolution anymore. We rather opted for an approach of preselecting GCMs and SSP. The selection follows the models given for the Intersectoral Impact Model Intercomparison Project (ISIMIP). Before downscaling to 1km the models have been bias corrected using a trend-preserving bias correction following (Lange 2019). GCM selection follow that of ISIMIP3b.
As ISIMIP only uses a small selection of all available CMIP6 models, many possible models are excluded here. The amount of possible models, ssps, and possible time frames is large, so we cannot host all the data pre-prepared. In case you need other models, ssps, geographical extents, or timeframes as provided here, you can generate them yourself using the chelsa-cmip6 python package:
https://gitlabext.wsl.ch/karger/chelsa_cmip6/-/tree/master/
or here:
https://pypi.org/project/chelsa-cmip6/
The priority of the model is given following ISIMIP3b. If less than five models are used, GCMs selection should follow the priority with priority=1 equals highest priority, and priority=5 equals lowest priority.
Some of the models show spatial interpolation artifacts from the statistical downscaling employed in ISIMIP3b_BA. These artifacts are an effect of the statistical downscaling algorithm which downscales the original GCM data to a common 0.5° resolution employed in ISIMIP3b_BA.
When using the data, you agree to cite the respective original peer-reviewed publication:
Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E., Linder, P., Kessler, M. (2017): Climatologies at high resolution for the Earth land surface areas. Scientific Data. 4 170122. https://doi.org/10.1038/sdata.2017.122
Additional information is available here: