What is the Grand Ensemble?

The Max Planck Institute for Meteorology (MPI-M) Grand Ensemble (MPI-GE) is the largest ensemble of a single state-of-the-art comprehensive climate model currently available. The Grand Ensemble consists of five Large Ensembles of 100 simulations each, of the Max Planck Institute Earth System Model in the low resolution set up (MPI-ESM1.1), run with varying initial conditions. The five ensembles can be seen in the header image and are:

  • Historical (blue)
  • RCP2.6 (yellow)
  • RCP4.5 (green)
  • RCP8.5 (purple)
  • 1%CO2 (pink)

The Grand Ensemble also has a 2000 year preindustrial control simulation, run with 1850 conditions. 

 

 

How do I access and cite the MPI-GE data?

Atmospheric and ocean data (excluding biogeochemistry) is currently available. The biogeochemistry and land data is anticipated to be available in late February.

Data can be found here: https://esgf-data.dkrz.de/projects/mpi-ge/

To use the data the license must first be accepted and can be found here: https://esgf-data.dkrz.de/ac/subscribe/CC_BY-SA_4.0/ 

Alternatively a direct download of any file will prompt the license agreement to appear. After the license is accepted the wget download will work. Please note that these scripts do not work when the safari browser is used. 

The left hand side of the webpage can be used to search for variables as can the bar at the top. For example to search for precipitation in the RCP8.5 scenario one can put 'pr AND RCP8.5' into the search bar. The most efficient way to download the whole ensemble is to search for the data that you want then click 'Add all displayed results to Data Cart'. From here go into the Data Cart and click 'Select All Datasets' then create a wget script for that download. To run the wget script the following command can be used: $ bash wget-xxx.sh -H 

The data will be available for 10 years from publication (end of 2028).

For scientists who wish to use the data before it is publicly available, we welcome collaboration with scientists based at the Max Planck Institute. 

Please cite the following publication when using the data.

Maher, N., Milinski, S., Suarez-Gutierrez, L., Botzet, M., Dobrynin, M., Kornblueh, L., Kröger, J., Takano, Y., Ghosh, R., Hedemann, C., Li, C., Li, H., Manzini, E., Notz, N., Putrasahan, D., Boysen, L., Claussen, M., Ilyina, T., Olonscheck, D., Raddatz, T., Stevens, B. and Marotzke, J. (2019). The Max Planck Institute Grand Ensemble: Enabling the Exploration of Climate System Variability. Journal of Advances in Modeling Earth Systems, 11, 1-21. doi.org/10.1029/2019MS001639

Please send an email to grandensemble@we dont want spammpimet.mpg.de if you publish a paper using the data, find any errors or bugs in the data or would like to request data that is not currently available. 

The data is currently available on the native grid. We recommend CDO as a tool for regridding, selecting subregions, selecting time periods and much more. It is fast, efficient and can be used in scripting languages (bash, python) to easily loop over ensemble members. CDO can be found here: https://code.mpimet.mpg.de/projects/cdo/.

 

 

Publications

A list of publications using the MPI-GE >>>

 

 

Collaborative projects involving MPI

The SMILE (Single Model Initial-condition Large Ensemble) group was initiated together with colleagues from LMU Munich, University of Reading, and NCAR to provide a forum for exchange and discussion for the large ensemble community.

 

 

A special issue on large ensembles​ based on the EGU session on large ensembles will go ahead in ​Earth System Dynamics​. T​his issue is open to submissions which exploit the new opportunities offered by large ensembles and explore how a combined analysis of the existing large ensembles can advance our knowledge in different fields. The special issue particularly invites submissions that use new methods to investigate these topics. More information can be found at: https://www.earth-system-dynamics.net/special_issues/schedule.html 

Upcoming conference sessions

EGU 2020

Session AS4.2

Large Ensemble Cimate Models Simulations as Tools for Exploring Natural Variability, Change Signals and Impacts

Abstracts due 15 January 2020

Several large ensemble model simulations from General Circulation Models (GCM), Earth System Models (ESM), or Regional Climate Models (RCM), have been generated over the recent years to investigate internal variability and forced changes of the climate system - and to aid the interpretation of the observational record by providing a range of historical climate trajectories that could have been. The increased availability of large ensembles also enables broadening their application to new and inter-disciplinary fields.


This session invites studies using large GCM, ESM, or RCM ensembles looking at the following topics: 1) forced changes in internal variability and reinterpretation of observed record; 2) development of new approaches to attribution of observed events or trends; 3) impacts of natural climate variability; 4) assessment of extreme and compound event occurrence; 5) use of large ensembles for robust decision making; 6) large ensembles as testbeds for method development; and 7) novel methods for efficient analysis and post-processing of large ensembles.

We welcome research across the components of the Earth system and particularly invite studies that apply novel methods or cross-disciplinary approaches to leverage the potential of large ensembles.



AOGS 2020

Session AS61

Large Ensemble Modeling as a Tool for Climate Dynamics and Impacts Research

Abstracts due 21 January 2020

Large ensemble modeling is increasingly being used as a tool in the climate research community. Such ensembles have additionally proven to be valuable for impacts research. Typically, the range of models applied in large ensemble configurations encompasses Earth System Models (ESMs), Coupled General Circulation Models (CGCMs), Atmospheric General Circulation Models (AGCMs), Ocean General Circulation Models (OGCMs), and regional climate models (RCMs). The utility of the method is in identifying not only the emergent forced trend, but also in studying modulations of climate variability and potential changes of extreme event occurrences in response to external forcing. Additionally, large ensembles can provide invaluable insight to the interpretation of climate models in the assessment of climate feedbacks. This session welcomes studies using the full range of large ensemble modeling tools. This includes studies of emergent trends and extreme events, and more generally studies that facilitate interpretation of observations as well as projections of future changes. Abstracts are particularly welcomed that address novel and emergent topics, including but not limited to compound events, terrestrial/oceanic ecosystems and biogeochemistry, and observing system design. Additionally, we encourage the submission of abstracts that use multiple large ensembles, or different types of ensembles combined to provide additional insight into the climate system.