DKRZ CMIP Data Pool - Updates Feb 22 📢#
Extensions#
We proudly 🥳 announce that the CDP is extended by new sets of CMIP6 data primarily published at DKRZ.
MPI-ESM1-2-LR ensemble for the historical and ScenarioMIP experiments ⭐#
The ensemble set of simulations from the ESM MPI-ESM1-2-LR is now completed with additional 130 Simulations. For each of the following experiments, 30 Simuluations form an ensemble of different realizations with varying initial conditions:
historical
ssp119
ssp126
ssp245
ssp370
ssp585
The CMIP6 MPI-ESM1-2-LR ensemble can be seen as a successor of the MPI Grand Ensemble (MPI-GE; Maher et. al, 2019). While 100 realizations exist for the MPI-GE, the benefit of the CMIP6 Ensemble is that the full publishable model output was produced: About 650 individual variables can be accessed for each of the runs.
Ensembles are essential to better estimate the internal variability of the climate system and the model itself. From Maher et. al, 2019:
Internal variability and uncertainties in model physics and the future forcing all contribute to uncertainties in climate projections (Hawkins & Sutton, 2009). While multimodel ensembles such as the Coupled Model Intercomparison Project (CMIP; Taylor et al., 2012) can be used to effectively investigate the combined effect of all three in climate projections, it is difficult to separate internal variability from the forced response with a limited number of ensemble members of each single model. […] A large ensemble of a single model can be used to estimate changes in variability in this model, uncertainties due to future forcing, and together with other model ensembles can be used to address uncertainties in model physics.
An example of how to work with the data is provided at the tutorials and use cases repo.
Migration of the CMIP-data-pool pages ⭐#
In the future, the CMIP-data-pool pages will be available under this url. That is because the new DKRZ user portal will contain static content and a minimal sphinx environment for building pages so that maintenance efforts are reduced and consistency is ensured.
The CMIP-data-pool however is evolving. We will link the pool in the official docs when a clear structure has been finalized.
Archival and back Ups 📓#
The DKRZ DM infrastructure team started removing CMIP5 data from disk as CMIP5 data will not be in the CMIP data pool with the upcoming HPC. The consortial disk space will be used for CMIP6 data and other new projects.
Data originals which were published first at DKRZ will still be available on disk under /pool/data/CMIP5. The rest of the data can be accessed via ESGF, WDCC when you search for IPCC-AR5_CMIP5 (IPCC Assessment Report 5 and Coupled Model Intercomparison Project data sets) and/or tape archive. We will provide tutorials and catalogs which will show the data access.
Publications#
Maher, N., Milinski, S., Suarez-Gutierrez, L., Botzet, M., Dobrynin, M., Kornblueh, L., et al. (2019). The Max Planck Institute Grand Ensemble: Enabling the exploration of climate system variability. Journal of Advances in Modeling Earth Systems, 11, 2050– 2069. https://doi.org/10.1029/2019MS001639
Hawkins, E., & Sutton, R. (2009). Decadal predictability of the Atlantic Ocean in a coupled GCM: Forecast skill and optimal perturbations using linear inverse modeling. Journal of Climate, 22(14), 3960–3978. https://doi.org/10.1175/2009JCLI2720.1
Taylor, K. E., Stouffer, R. J., & Meehl, G. A. (2012). An overview of CMIP5 and the experiment design. Bulletin of the American Meteorological Society, 93(4), 485–498. https://doi.org/10.1175/BAMS-D-11-00094.1