A Suite of Perturbed Parameter Ensembles using CESM2.2 CAM6 under a Wide Range of Temperatures

This dataset originates from a new CESM2 CAM6 perturbed parameter ensemble (PPE) designed to explore climate and hydroclimate dynamics under a wide range of sea surface temperature (SST) conditions. The SST varies from 4 degrees Celsius colder to 16 degrees Celsius warmer than preindustrial levels, encompassing a broad spectrum of mean temperatures spanning the past 65 million years. This dataset offers valuable insights into climate and hydroclimate responses, as well as weather and climate extremes under diverse conditions.

The dataset includes results from nine PPE simulations with different SST scenarios: preindustrial (PREI), 4K cooler (M04K), and 4K, 8K, 12K, and 16K warmer (P04K to P16K). For SSTs exceeding 8K warming, sea ice was removed to improve numerical stability. Each PPE set consists of 250 ensemble members, with 45 parameters related to microphysics, convection, turbulence, and aerosols perturbed using Latin Hypercube Sampling. An additional simulation with default parameter settings brings the total to 251 simulations, each running for five years using CAM6.3 (https://github.com/ESCOMP/CAM/tree/cam6_3_026; with additional paleo modifications).

Post-processing converted the data into compressed NetCDF-4 format. All 251 runs were concatenated using ncecat to minimize the number of files. For example, the following file contains monthly surface temperature data from the preindustrial PPE: f.c6.F1850.f19_f19.paleo_ppe.sst_prei.ens251/atm/proc/tseries/month_1/f.c6.F1850.f19_f19.paleo_ppe.sst_prei.ens251.cam.h0.TS.000101-000512.nc

A detailed variable list [https://rda.ucar.edu/OS/web/datasets/d651038/docs/detailed_vars.txt] can be found in the Documentation Tab.

Parameter values are provided in the PPE Parameter File. More details can be found in the paper: Zhu et al. (2025). Investigating the State Dependence of Cloud Feedback Using a Suite of Perturbed Parameter Ensembles, Journal of Climate.

To Access Resource:

Questions? Email Resource Support Contact:

  • Teagan King
    tking@ucar.edu
    UCAR/NCAR - Research Data Archive

Temporal Range

  • Begin:  0001-01
    End:  0005-12

Keywords

Resource Type dataset
Temporal Range Begin 0001-01
Temporal Range End 0005-12
Temporal Resolution N/A
Bounding Box North Lat N/A
Bounding Box South Lat N/A
Bounding Box West Long N/A
Bounding Box East Long N/A
Spatial Representation N/A
Spatial Resolution N/A
Related Links

Related Resource #1 : Model Source Code

Related Resource #2 : Note additional paleoclimate-calibrated fixes need to be added to the code above
Additional Information N/A
Resource Format NetCDF (Binary)
Standardized Resource Format NetCDF
Asset Size 0.00 MB
Legal Constraints

Creative Commons Attribution 4.0 International License
Access Constraints None
Software Implementation Language N/A

Resource Support Name Teagan King
Resource Support Email tking@ucar.edu
Resource Support Organization UCAR/NCAR - Research Data Archive
Distributor NCAR Research Data Archive
Metadata Contact Name N/A
Metadata Contact Email rdahelp@ucar.edu
Metadata Contact Organization NCAR Research Data Archive

Author Zhu, Jiang
Otto-Bliesner, Bette L.
Brady, Esther C.
Eidhammer, Trude
Gettelman, Andrew
Feng, Ran
McCluskey, Christina
Publisher Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory
Publication Date 2025-03-19
Digital Object Identifier (DOI) Not Assigned
Alternate Identifier d651038
Resource Version N/A
Topic Category climatologyMeteorologyAtmosphere
Progress completed
Metadata Date 2025-04-04T19:05:01Z
Metadata Record Identifier edu.ucar.rda::d651038
Metadata Language eng; USA
Suggested Citation Zhu, Jiang, Otto-Bliesner, Bette L., Brady, Esther C., Eidhammer, Trude, Gettelman, Andrew, Feng, Ran, McCluskey, Christina. (2025). A Suite of Perturbed Parameter Ensembles using CESM2.2 CAM6 under a Wide Range of Temperatures. Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory. https://rda.ucar.edu/datasets/d651038/. Accessed 07 April 2025.

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