Abstract
This paper introduces the Flexible Global Ocean-Atmosphere-Land System Model: Grid-Point Version 3 (FGOALS-g3) and evaluates its basic performance based on some of its participation in the sixth phase of the Coupled Model Intercomparison Project (CMIP6) experiments. Our results show that many significant improvements have been achieved by FGOALS-g3 in terms of climatological mean states, variabilities, and long-term trends. For example, FGOALS-g3 has a small (−0.015°C/100 yr) climate drift in 700-yr preindustrial control (piControl) runs and smaller biases in climatological mean variables, such as the land/sea surface temperatures (SSTs) and seasonal soil moisture cycle, compared with its previous version FGOALS-g2 during the historical period. The characteristics of climate variabilities, for example, Madden-Julian oscillation (MJO) eastward/westward propagation ratios, spatial patterns of interannual variability of tropical SST anomalies, and relationship between the East Asian Summer Monsoon and El Niño–Southern Oscillation (ENSO), are well captured by FGOALS-g3. In particular, the cooling trend of globally averaged surface temperature during 1940–1970, which is a challenge for most CMIP3 and CMIP5 models, is well reproduced by FGOALS-g3 in historical runs. In addition to the external forcing factors recommended by CMIP6, anthropogenic groundwater forcing from 1965 to 2014 was incorporated into the FGOALS-g3 historical runs.
| Original language | English |
|---|---|
| Article number | e2019MS002012 |
| Journal | Journal of Advances in Modeling Earth Systems |
| Volume | 12 |
| Issue number | 9 |
| DOIs | |
| State | Published - Sep 1 2020 |
| Externally published | Yes |
Funding
The University of Delaware temperature data were provided by the NOAA/OAR/ESRL PSD, Boulder, Colorado, USA (https://www.esrl.noaa.gov/psd/). This research was jointly funded by the National Natural Science Foundation of China (Grants 41622503, 41775101, 1605061, 41530426, and 91958201) and a National Key Research Project (Grant 2016YFB0200805). We thank Stephen Griffies and three anonymous reviewers for the helpful comments that improved the manuscript. The simulated data sets used in this study are archived at the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG), Institute of Atmospheric Physics, Chinese Academy of Sciences, and are available for research purposes through ESGF-node (https://esgf-node.llnl.gov/projects/cmip6/); for details please contact [email protected] referencing this paper. The coupled model source codes could be obtained after filling out the related memorandum (http://www.lasg.ac.cn/news/202004/t20200425_553389.html), and its atmospheric model codes could be downloaded from the site (https://doi.org/10.5281/zenodo.3774655). The University of Delaware temperature data were provided by the NOAA/OAR/ESRL PSD, Boulder, Colorado, USA ( https://www.esrl.noaa.gov/psd/ ). This research was jointly funded by the National Natural Science Foundation of China (Grants 41622503, 41775101, 1605061, 41530426, and 91958201) and a National Key Research Project (Grant 2016YFB0200805). We thank Stephen Griffies and three anonymous reviewers for the helpful comments that improved the manuscript. The simulated data sets used in this study are archived at the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG), Institute of Atmospheric Physics, Chinese Academy of Sciences, and are available for research purposes through ESGF‐node ( https://esgf‐node.llnl.gov/projects/cmip6/ ); for details please contact [email protected] referencing this paper. The coupled model source codes could be obtained after filling out the related memorandum ( http://www.lasg.ac.cn/news/202004/t20200425_553389.html ), and its atmospheric model codes could be downloaded from the site ( https://doi.org/10.5281/zenodo.3774655 ).