An Evaluation of the Ocean and Sea Ice Climate of E3SM Using MPAS and Interannual CORE‐II Forcing
An Evaluation of the Ocean and Sea Ice Climate of E3SM Using MPAS and Interannual CORE‐II Forcing
复制标题
利用 MPAS 和年际 CORE-II 强迫对 E3SM 的海洋和海冰气候进行评估
DOI:
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发表时间:
2019
影响因子:
6.8
通讯作者:
J. Woodring
中科院分区:
文献类型:
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作者:
M. Petersen;X. Asay;A. Berres;Qingshan Chen;N. Feige;M. Hoffman;D. Jacobsen;Philip W. Jones;M. Maltrud;S. Price;T. Ringler;G. Streletz;A. Turner;Luke P. van Roekel;M. Veneziani;J. Wolfe;P. Wolfram;J. Woodring
The Energy Exascale Earth System Model (E3SM) is a new coupled Earth system model sponsored by the U.S Department of Energy. Here we present E3SM global simulations using active ocean and sea ice that are driven by the Coordinated Ocean‐ice Reference Experiments II (CORE‐II) interannual atmospheric forcing data set. The E3SM ocean and sea ice components are MPAS‐Ocean and MPAS‐Seaice, which use the Model for Prediction Across Scales (MPAS) framework and run on unstructured horizontal meshes. For this study, grid cells vary from 30 to 60 km for the low‐resolution mesh and 6 to 18 km at high resolution. The vertical grid is a structured z‐star coordinate and uses 60 and 80 layers for low and high resolution, respectively. The lower‐resolution simulation was run for five CORE cycles (310 years) with little drift in sea surface temperature (SST) or heat content. The meridional heat transport (MHT) is within observational range, while the meridional overturning circulation at 26.5°N is low compared to observations. The largest temperature biases occur in the Labrador Sea and western boundary currents (WBCs), and the mixed layer is deeper than observations at northern high latitudes in the winter months. In the Antarctic, maximum mixed layer depths (MLD) compare well with observations, but the spatial MLD pattern is shifted relative to observations. Sea ice extent, volume, and concentration agree well with observations. At high resolution, the sea surface height compares well with satellite observations in mean and variability.
影响因子:
3.2
作者:
Downes, Stephanie M.;Farneti, Riccardo;Yeager, Stephen G.
通讯作者:
Yeager, Stephen G.