Climate Variability Diagnostics Package (CVDP)

Current CVDP version: 6.0.0 (Jun 9 2024)

The Climate Variability Diagnostics Package (CVDP) developed by NSF-NCAR's Climate Analysis Section is an automated analysis tool and data repository for assessing modes of climate variability and trends in models and observations.  Time series, spatial patterns and power spectra are displayed graphically via webpages and saved as NetCDF files for later use. The package can be applied to individual model simulations ("style 1") or to “initial condition” Large Ensembles (“style 2”).  Both styles provide quantitative metrics comparing models and observations; style 2 also includes ensemble mean (i.e., forced response) and ensemble spread (i.e., internal variability) diagnostics.  Several detrending options are provided, including linear, quadratic, 30-year high-pass filter and removal of the ensemble mean (in the case of Large Ensembles). All diagnostics and metrics are fully documented with references to the peer-reviewed literature.

The CVDP can be applied to any set of model simulations as long as the files meet CMIP output metadata requirements, allowing inter-model comparisons. Multiple observational data sets and analysis periods may be specified by the user.

The CVDP Data Repository contains CVDP output for many CESM and CMIP simulations, as well as the Multi-model Large Ensemble Archive. A few examples are linked below:

• CMIP6 Historical/SSP585 Run Intercomparison 1900-2100
• CSM - CCSM - CESM Control Run Intercomparison
• CESM2 Large Ensemble Intercomparison 1850-2100

To download the CVDP software package please refer to the Code page. 

When presenting results from the CVDP in either oral or written form, please cite at least one of the following:

Phillips, A. S., C. Deser, and J. Fasullo, 2014: A New Tool for Evaluating Modes of Variability in Climate Models. EOS, 95, 453-455, doi: 10.1002/2014EO490002. [Article]

Maher, N., A. S. Phillips, C. Deser, R. C.-J. Wills, F. Lehner, J. Fasullo, J. M. Caron, L. Brunner and U. Beyerle, 2024: The updated Multi-Model Large Ensemble Archive and the Climate Variability Diagnostics Package: New tools for the study of climate variability and change. Geosci. Model Dev., submitted. [Article] [Supplementary Material]