CESM2 SMYLE

d651065
| DOI: 10.26024/PWMA-RE41
 
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Abstract:

SMYLE (Seasonal-to-MultiYear Large Ensemble) is an initialized prediction system using CESM2. It consists of fully coupled initialized hindcast simulations using CESM2 component models at nominal 1 degree horizontal resolution. Hindcasts are initialized from historical reconstructions (SMYLE-FOSI for ocean and sea-ice; SMYLE-landonly for land; and JRA55 reanalysis for atmosphere) and then integrated forward 24-months. Initialization occurs quarterly (1st of each month of February, May, August, and November) for each year between 1970-2019. The ensemble size is 20 for each start date, with ensemble spread introduced through a random field perturbation applied to the atmospheric initial conditions. The SMYLE data release also includes the historical reconstructions used to initialize the ocean, sea ice, ocean biogeochemistry, and land components (SMYLE-FOSI and SMYLE-landonly).

Temporal Range:
1958 to 2023
Variables:
Latent Heat Flux Rain Sea Level Pressure Specific Humidity
U/V Wind Components Upper Air Temperature Vertical Wind Velocity/Speed
Data Types:
Grid
Data Contributors:
UCAR/NCAR/CGD
Related Resources:
SMYLE simulation additional information
Publications:
Stephen G. Yeager, Nan Rosenbloom, Anne A. Glanville, Xian Wu, Isla Simpson, Hui Li, Maria J. Molina, Kristen Krumhardt, Samuel Mogen, Keith Lindsay, Danica Lombardozzi, Will Wieder, Who M. Kim, Jadwiga H. Richter, Matthew Long, Gokhan Danabasoglu, David Bailey, Marika Holland, Nicole Lovenduski, Warren G. Strand, and Teagan King, 2022: The Seasonal-to-Multiyear Large Ensemble (SMYLE) prediction system using the Community Earth System Model version 2. GMD, 15, 6451-6493 (DOI: 10.5194/gmd-2022-60).
Total Volume:
567.58 TB (Entire dataset) Volume details by dataset product
Data Formats:
netCDF
Metadata Record:
Data License:
Data LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.
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