Advanced Search

2020 Vol. 37, No. 10

Editorial Notes
Preface to Special Issue on CMIP6 Experiments: Model and Dataset Descriptions
Tianjun Zhou
2020, 37(10): 1033-1033. doi: 10.1007/s00376-020-0008-8
Data Description Article
CAS-FGOALS Datasets for the Two Interglacial Epochs of the Holocene and the Last Interglacial in PMIP4
Weipeng ZHENG, Yongqiang YU, Yihua LUAN, Shuwen ZHAO, Bian HE, Li DONG, Mirong SONG, Pengfei LIN, Hailong LIU
2020, 37(10): 1034-1044. doi: 10.1007/s00376-020-9290-8
Two versions of the Chinese Academy of Sciences Flexible Global Ocean–Atmosphere–Land System model (CAS-FGOALS), version f3-L and g3, are used to simulate the two interglacial epochs of the mid-Holocene and the Last Interglacial in phase 4 of the Paleoclimate Modelling Intercomparison Project (PMIP4), which aims to study the impact of changes in orbital parameters on the Earth’s climate. Following the PMIP4 experimental protocols, four simulations for the mid-Holocene and two simulations for the Last Interglacial have been completed, and all the data, including monthly and daily outputs for the atmospheric, oceanic, land and sea-ice components, have been released on the Earth System Grid Federation (ESGF) node. These datasets contribute to PMIP4 and CMIP6 (phase 6 of the Coupled Model Intercomparison Project) by providing the variables necessary for the two interglacial periods. In this paper, the basic information of the CAS-FGOALS models and the protocols for the two interglacials are briefly described, and the datasets are validated using proxy records. Results suggest that the CAS-FGOALS models capture the large-scale changes in the climate system in response to changes in solar insolation during the interglacial epochs, including warming in mid-to-high latitudes, changes in the hydrological cycle, the seasonal variation in the extent of sea ice, and the damping of interannual variabilities in the tropical Pacific. Meanwhile, disagreements within and between the models and the proxy data are also presented. These datasets will help the modeling and the proxy data communities with a better understanding of model performance and biases in paleoclimate simulations.
FIO-ESM v2.0 Outputs for the CMIP6 Global Monsoons Model Intercomparison Project Experiments
Yajuan SONG, Xinfang LI, Ying BAO, Zhenya SONG, Meng WEI, Qi SHU, Xiaodan YANG
2020, 37(10): 1045-1056. doi: 10.1007/s00376-020-9288-2
Three tiers of experiments in the Global Monsoons Model Intercomparison Project (GMMIP), one of the endorsed model intercomparison projects of phase 6 of the Coupled Model Intercomparison Project (CMIP6), are implemented by the First Institute of Oceanography Earth System Model version 2 (FIO-ESM v2.0), following the GMMIP protocols. Evaluation of global mean surface air temperature from 1870 to 2014 and climatological precipitation (1979–2014) in tier-1 shows that the atmosphere model of FIO-ESM v2.0 can reproduce the basic observed atmospheric features. In tier-2, the internal variability is captured by the coupled model, with the SST restoring to the model climatology plus the observed anomalies in the tropical Pacific and North Atlantic. Simulation of the Northern Hemisphere summer monsoon circulation is significantly improved by the SST restoration in the North Atlantic. In tier-3, five orographic perturbation experiments are conducted covering the period 1979–2014 by modifying the surface elevation or vertical heating in the prescribed region. In particular, the strength of the South Asian summer monsoon is reduced by removing the topography or thermal forcing above 500 m over the Asian continent. Monthly and daily simulated outputs of FIO-ESM v2.0 are provided through the Earth System Grid Federation (ESGF) node to contribute to a better understanding of the global monsoon system.
Overview of the CMIP6 Historical Experiment Datasets with the Climate System Model CAS FGOALS-f3-L
Yuyang GUO, Yongqiang YU, Pengfei LIN, Hailong LIU, Bian HE, Qing BAO, Shuwen ZHAO, Xiaowei WANG
2020, 37(10): 1057-1066. doi: 10.1007/s00376-020-2004-4
The three-member historical simulations by the Chinese Academy of Sciences Flexible Global Ocean–Atmosphere–Land System model, version f3-L (CAS FGOALS-f3-L), which is contributing to phase 6 of the Coupled Model Intercomparison Project (CMIP6), are described in this study. The details of the CAS FGOALS-f3-L model, experiment settings and output datasets are briefly introduced. The datasets include monthly and daily outputs from the atmospheric, oceanic, land and sea-ice component models of CAS FGOALS-f3-L, and all these data have been published online in the Earth System Grid Federation (ESGF, The three ensembles are initialized from the 600th, 650th and 700th model year of the preindustrial experiment (piControl) and forced by the same historical forcing provided by CMIP6 from 1850 to 2014. The performance of the coupled model is validated in comparison with some recent observed atmospheric and oceanic datasets. It is shown that CAS FGOALS-f3-L is able to reproduce the main features of the modern climate, including the climatology of air surface temperature and precipitation, the long-term changes in global mean surface air temperature, ocean heat content and sea surface steric height, and the horizontal and vertical distribution of temperature in the ocean and atmosphere. Meanwhile, like other state-of-the-art coupled GCMs, there are still some obvious biases in the historical simulations, which are also illustrated. This paper can help users to better understand the advantages and biases of the model and the datasets.
Eddy-resolving Simulation of CAS-LICOM3 for Phase 2 of the Ocean Model Intercomparison Project
Yiwen LI, Hailong LIU, Mengrong DING, Pengfei LIN, Zipeng YU, Yongqiang YU, Yao MENG, Yunlong LI, Xiaodong JIAN, Jinrong JIANG, Kangjun CHEN, Qian YANG, Yaqi WANG, Bowen ZHAO, Jilin WEI, Jinfeng MA, Weipeng ZHENG, Pengfei WANG
2020, 37(10): 1067-1080. doi: 10.1007/s00376-020-0057-z
A 61-year (1958–2018) global eddy-resolving dataset for phase 2 of the Ocean Model Intercomparison Project has been produced by the version 3 of Chinese Academy of Science, the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics/Institute of Atmospheric Physics (LASG/IAP) Climate system Ocean Model (CAS-LICOM3). The monthly and a part of the surface daily data in this study can be accessed on the Earth System Grid Federation (ESGF) node. Besides the details of the model and experiments, the evolutions and spatial patterns of large-scale and mesoscale features are also presented. The mesoscale features are reproduced well in the high-resolution simulation, as the mesoscale activities can contribute up to 50% of the total SST variability in eddy-rich regions. Also, the large-scale circulations are remarkably improved compared with the low-resolution simulation, such as the climatological annual mean SST (the RMSE is reduced from 0.59°C to 0.47°C, globally) and the evolution of Atlantic Meridional Overturning Circulation. The preliminary evaluation also indicates that there are systematic biases in the salinity, the separation location of the western boundary currents, and the magnitude of eddy kinetic energy. All these biases are worthy of further investigation.
CAS FGOALS-g3 Model Datasets for the CMIP6 Scenario Model Intercomparison Project (ScenarioMIP)
Ye PU, Hongbo LIU, Ruojing YAN, Hao YANG, Kun XIA, Yiyuan LI, Li DONG, Lijuan LI, He WANG, Yan NIE, Mirong SONG, Jinbo XIE, Shuwen ZHAO, Kangjun CHEN, Bin WANG, Jianghao LI, Ling ZUO
2020, 37(10): 1081-1092. doi: 10.1007/s00376-020-2032-0
This paper describes the datasets from the Scenario Model Intercomparison Project (ScenarioMIP) simulation experiments run with the Chinese Academy of Sciences Flexible Global Ocean–Atmosphere–Land System Model, GridPoint version 3 (CAS FGOALS-g3). FGOALS-g3 is driven by eight shared socioeconomic pathways (SSPs) with different sets of future emission, concentration, and land-use scenarios. All Tier 1 and 2 experiments were carried out and were initialized using historical runs. A branch run method was used for the ensemble simulations. Model outputs were three-hourly, six-hourly, daily, and/or monthly mean values for the primary variables of the four component models. An evaluation and analysis of the simulations is also presented. The present results are expected to aid research into future climate change and socio-economic development.
FGOALS-g3 Model Datasets for CMIP6 Flux-Anomaly-Forced Model Intercomparison Project
Yaqi WANG, Zipeng YU, Pengfei LIN, Hailong LIU, Jiangbo JIN, Lijuan LI, Yanli TANG, Li DONG, Kangjun CHEN, Yiwen LI, Qian YANG, Mengrong DING, Yao MENG, Bowen ZHAO, Jilin WEI, Jinfeng MA, Zhikuo SUN
2020, 37(10): 1093-1101. doi: 10.1007/s00376-020-2045-8
The Flux-Anomaly-Forced Model Intercomparison Project (FAFMIP) is an endorsed Model Intercomparison Project in phase 6 of the Coupled Model Intercomparison Project (CMIP6). The goal of FAFMIP is to investigate the spread in the atmosphere–ocean general circulation model projections of ocean climate change forced by increased CO2, including the uncertainties in the simulations of ocean heat uptake, global mean sea level rise due to ocean thermal expansion and dynamic sea level change due to ocean circulation and density changes. The FAFMIP experiments have already been conducted with the Flexible Global Ocean–Atmosphere–Land System Model, gridpoint version 3.0 (FGOALS-g3). The model datasets have been submitted to the Earth System Grid Federation (ESGF) node. Here, the details of the experiments, the output variables and some baseline results are presented. Compared with the preliminary results of other models, the evolutions of global mean variables can be reproduced well by FGOALS-g3. The simulations of spatial patterns are also consistent with those of other models in most regions except the North Atlantic and the Southern Ocean, indicating large uncertainties in the regional sea level projections of these two regions.
Original Paper
Differences between CMIP6 and CMIP5 Models in Simulating Climate over China and the East Asian Monsoon
Dabang JIANG, Dan HU, Zhiping TIAN, Xianmei LANG
2020, 37(10): 1102-1118. doi: 10.1007/s00376-020-2034-y
We compare the ability of coupled global climate models from the phases 5 and 6 of the Coupled Model Intercomparison Project (CMIP5 and CMIP6, respectively) in simulating the temperature and precipitation climatology and interannual variability over China for the period 1961–2005 and the climatological East Asian monsoon for the period 1979–2005. All 92 models are able to simulate the geographical distribution of the above variables reasonably well. Compared with earlier CMIP5 models, current CMIP6 models have nationally weaker cold biases, a similar nationwide overestimation of precipitation and a weaker underestimation of the southeast–northwest precipitation gradient, a comparable overestimation of the spatial variability of the interannual variability, and a similar underestimation of the strength of winter monsoon over northern Asia. Pairwise comparison indicates that models have improved from CMIP5 to CMIP6 for climatological temperature and precipitation and winter monsoon but display little improvement for the interannual temperature and precipitation variability and summer monsoon. The ability of models relates to their horizontal resolutions in certain aspects. Both the multi-model arithmetic mean and median display similar skills and outperform most of the individual models in all considered aspects.
Does CMIP6 Inspire More Confidence in Simulating Climate Extremes over China?
Huanhuan ZHU, Zhihong JIANG, Juan LI, Wei LI, Cenxiao SUN, Laurent LI
2020, 37(10): 1119-1132. doi: 10.1007/s00376-020-9289-1
Based on climate extreme indices calculated from a high-resolution daily observational dataset in China during 1961–2005, the performance of 12 climate models from phase 6 of the Coupled Model Intercomparison Project (CMIP6), and 30 models from phase 5 of CMIP (CMIP5), are assessed in terms of spatial distribution and interannual variability. The CMIP6 multi-model ensemble mean (CMIP6-MME) can simulate well the spatial pattern of annual mean temperature, maximum daily maximum temperature, and minimum daily minimum temperature. However, CMIP6-MME has difficulties in reproducing cold nights and warm days, and has large cold biases over the Tibetan Plateau. Its performance in simulating extreme precipitation indices is generally lower than in simulating temperature indices. Compared to CMIP5, CMIP6 models show improvements in the simulation of climate indices over China. This is particularly true for precipitation indices for both the climatological pattern and the interannual variation, except for the consecutive dry days. The areal-mean bias for total precipitation has been reduced from 127% (CMIP5-MME) to 79% (CMIP6-MME). The most striking feature is that the dry biases in southern China, very persistent and general in CMIP5-MME, are largely reduced in CMIP6-MME. Stronger ascent together with more abundant moisture can explain this reduction in dry biases. Wet biases for total precipitation, heavy precipitation, and precipitation intensity in the eastern Tibetan Plateau are still present in CMIP6-MME, but smaller, compared to CMIP5-MME.
Simulation and Improvements of Oceanic Circulation and Sea Ice by the Coupled Climate System Model FGOALS-f3-L
Yuyang GUO, Yongqiang YU, Pengfei LIN, Hailong LIU, Bian HE, Qing BAO, Bo AN, Shuwen ZHAO, Lijuan HUA
2020, 37(10): 1133-1148. doi: 10.1007/s00376-020-0006-x
This study documents simulated oceanic circulations and sea ice by the coupled climate system model FGOALS-f3-L developed at the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, under historical forcing from phase 6 of the Coupled Model Intercomparison Project (CMIP6). FGOALS-f3-L reproduces the fundamental features of global oceanic circulations, such as sea surface temperature (SST), sea surface salinity (SSS), mixed layer depth (MLD), vertical temperature and salinity, and meridional overturning circulations. There are notable improvements compared with the previous version, FGOALS-s2, such as a reduction in warm SST biases near the western and eastern boundaries of oceans and salty SSS biases in the tropical western Atlantic and eastern boundaries, and a mitigation of deep MLD biases at high latitudes. However, several obvious biases remain. The most significant biases include cold SST biases in the northwestern Pacific (over 4°C), freshwater SSS biases and deep MLD biases in the subtropics, and temperature and salinity biases in deep ocean at high latitudes. The simulated sea ice shows a reasonable distribution but stronger seasonal cycle than observed. The spatial patterns of sea ice are more realistic in FGOALS-f3-L than its previous version because the latitude–longitude grid is replaced with a tripolar grid in the ocean and sea ice model. The most significant biases are the overestimated sea ice and underestimated SSS in the Labrador Sea and Barents Sea, which are related to the shallower MLD and weaker vertical mixing.