Conda-forge (CURRENT, recommended):
PCMDI Conda Channel (old, deprecated):
The PCMDI Metrics Package (PMP) is used to provide "quick-look" objective comparisons of Earth System Models (ESMs) with one another and available observations. Results are produced in the context of all model simulations contributed to CMIP6 and earlier CMIP phases. Among other purposes, this enables modeling groups to evaluate changes during the development cycle in the context of the structural error distribution of the multi-model ensemble. Currently, the comparisons emphasize metrics of large- to global-scale annual cycle, tropical and extra-tropical modes of variability, ENSO, MJO, regional monsoons, high frequency characteristics of simulated precipitation, and cloud feedback.
PCMDI uses the PMP to produce quick-look simulation summaries across generations of CMIP.
The metrics package consists of the following parts:
- Analysis software
- Observation-based reference database of global (or near global, land or ocean) time series and climatologies
- Package documentation and interactive jupyter notebook demos
- Database of performance metrics computed for CMIP models
The package expects model data to be CF-compliant. To successfully use the package some input data "conditioning" may be required. We provide several demo scripts within the package.
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Installation requirements and instructions are available on the Install page
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Users will need to contact the PMP developers (pcmdi-metrics@llnl.gov) to obtain supporting datasets and get started using the package.
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An overview for using the package and template scripts are detailed on the Using-the-package page
Latest:
- Lee, J., Gleckler, P. J., Ahn, M.-S., Ordonez, A., Ullrich, P. A., Sperber, K. R., Taylor, K. E., Planton, Y. Y., Guilyardi, E., Durack, P., Bonfils, C., Zelinka, M. D., Chao, L.-W., Dong, B., Doutriaux, C., Zhang, C., Vo, T., Boutte, J., Wehner, M. F., Pendergrass, A. G., Kim, D., Xue, Z., Wittenberg, A. T., and Krasting, J.: Systematic and objective evaluation of Earth system models: PCMDI Metrics Package (PMP) version 3, Geosci. Model Dev., 17, 3919–3948, https://doi.org/10.5194/gmd-17-3919-2024, 2024.
Earlier versions:
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Gleckler, P. J., Doutriaux, C., Durack, P. J., Taylor, K. E., Zhang, Y., Williams, D. N., Mason, E., and Servonnat, J.: A more powerful reality test for climate models, Eos T. Am. Geophys. Un., 97, https://doi.org/10.1029/2016eo051663, 2016.
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Gleckler, P. J., Taylor, K. E., and Doutriaux, C.: Performance metrics for climate models, J. Geophys. Res., 113, D06104, https://doi.org/10.1029/2007jd008972, 2008.
Some installation support for CMIP participating modeling groups is available: pcmdi-metrics@llnl.gov
Content in this repository is developed by climate and computer scientists from the Program for Climate Model Diagnosis and Intercomparison (PCMDI) at Lawrence Livermore National Laboratory (LLNL). This work is sponsored by the Regional and Global Model Analysis (RGMA) program, of the Earth and Environmental Systems Sciences Division (EESSD) in the Office of Biological and Environmental Research (BER) within the Department of Energy's Office of Science. The work is performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.
Distributed under the BSD 3-Clause License. See LICENSE for more information.
| Update summary | |
|---|---|
| v3.8 | New capability (figure generation for ENSO, xCDAT migration completed for Monsoon Wang with figure generation), major dependency update (numpy >= 2.0) |
| v3.7.2 | Technical update |
| v3.7.1 | Technical update with documentation improvements |
| v3.7 | New capability (figure generation for mean climate) and technical update |
| v3.6.1 | Technical update, additional QC repair functions |
| v3.6 | New capability (regional application of precip variability) and technical update |
| v3.5.2 | New capability (QC, new modes for modes of variability metrics: PSA1, PSA2) and technical update |
| v3.5.1 | Technical update |
| v3.5 | Technical update: MJO and Monsoon Sperber xCDAT conversion |
| v3.4.1 | Technical update |
| v3.4 | Technical update: Modes of variability xCDAT conversion |
| v3.3.4 | Technical update |
| v3.3.3 | Technical update |
| v3.3.2 | Technical update |
| v3.3.1 | Technical update |
| v3.3 | New metric added: Sea-Ice |
| v3.2 | New metric added: Extremes |
| v3.1.2 | Technical update |
| v3.1.1 | Technical and documentation update |
| v3.1 | New metric added: Precipitation Benchmarking -- distribution bimodality |
| v3.0.2 | Minor patch and more documentation added |
| v3.0.1 | Minor technical patch |
| v3.0.0 | New metric added: Cloud feedback metric by @mzelinka. xCDAT implemented for mean climate metrics |
Click here for older versions
| Update summary | |
|---|---|
| v2.5.1 | Technical update |
| v2.5.0 | New metric added: Precipitation Benchmarking -- distribution. Graphics updated |
| v2.4.0 | New metric added: AMO in variability modes |
| v2.3.2 | CMEC interface updates |
| v2.3.1 | Technical update |
| v2.3 | New graphics using archived PMP results |
| v2.2.2 | Technical update |
| v2.2.1 | Minor update |
| v2.2 | New metric implemented: precipitation variability across time scale |
| v2.1.2 | Minor update |
| v2.1.1 | Simplified dependent libraries and CI process |
| v2.1.0 | CMEC driver interfaced added. |
| v2.0 | New capabilities: ENSO metrics, demos, and documentations. |
| v1.2 | Tied to CDAT 8.0. Extensive regression testing added. New metrics: Diurnal cycle and intermittency of precipitation, sample monsoon metrics. |
| v1.1.2 | Now managed through Anaconda, and tied to UV-CDAT 2.10. Weights on bias statistic added. Extensive provenance information incorporated into json files. |
| v1.1 | First public release, emphasizing climatological statistics, with development branches for ENSO and regional monsoon precipitation indices |
| v1.0 | Prototype version of the PMP |
- Jiwoo Lee
- Ana Ordonez
- Peter Gleckler
- Paul Ullrich
- Bo Dong
- Kristin Chang
Thanks goes to these wonderful people (emoji key):
This project follows the all-contributors specification.
This document was prepared as an account of work sponsored by an agency of the United States government. Neither the United States government nor Lawrence Livermore National Security, LLC, nor any of their employees makes any warranty, expressed or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States government or Lawrence Livermore National Security, LLC. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States government or Lawrence Livermore National Security, LLC, and shall not be used for advertising or product endorsement purposes.