Overview of the CMIP6 Historical Experiment Datasets with the Climate System Model CAS FGOALS-f3-L

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, https://esgf-node.llnl.gov/projects/cmip6/). 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.     

CAS FGOALS-f3-L Model Datasets for CMIP6 Historical Atmospheric Model Intercomparison Project Simulation

The outputs of the Chinese Academy of Sciences(CAS) Flexible Global Ocean–Atmosphere–Land System(FGOALS-f3-L) model for the baseline experiment of the Atmospheric Model Intercomparison Project simulation in the Diagnostic,Evaluation and Characterization of Klima common experiments of phase 6 of the Coupled Model Intercomparison Project(CMIP6) are described in this paper. The CAS FGOALS-f3-L model, experiment settings, and outputs are all given. In total,there are three ensemble experiments over the period 1979–2014, which are performed with different initial states. The model outputs contain a total of 37 variables and include the required three-hourly mean, six-hourly transient, daily and monthly mean datasets. The baseline performances of the model are validated at different time scales. The preliminary evaluation suggests that the CAS FGOALS-f3-L model can capture the basic patterns of atmospheric circulation and precipitation well, including the propagation of the Madden–Julian Oscillation, activities of tropical cyclones, and the characterization of extreme precipitation. These datasets contribute to the benchmark of current model behaviors for the desired continuity of CMIP.     

Comparative Analysis of the Generalized Omega Equation and Generalized Vertical Motion Equation

Research on vertical motion in mesoscale systems is an extraordinarily challenging effort. Allowing for fewer assumptions, a new form of generalized vertical motion equation and a generalized Omega equation are derived in the Cartesian coordinate system(nonhydrostatic equilibrium) and the isobaric coordinate system(hydrostatic equilibrium),respectively. The terms on the right-hand side of the equations, which comprise the Q vector, are composed of three factors:dynamic, thermodynamic, and mass. ...     

Aerosol-Cloud-Precipitation Interactions in a Closed-cell and Non-homogenous MBL Stratocumulus Cloud

A closed-cell marine stratocumulus case during the Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) aircraft field campaign is selected to examine the heterogeneities of cloud and drizzle microphysical properties and the aerosol-cloud-precipitation interactions. The spatial and vertical variabilities of cloud and drizzle microphysics are found in two different sets of flight legs: Leg-1 and Leg-2, which are parallel and perpendicular to the cloud propagation, respectively. The cloud along Leg-2 was close to adiabatic, where cloud-droplet effective radius and liquid water content linearly increase from cloud base to cloud top with less drizzle. The cloud along Leg-1 was sub-adiabatic with lower cloud-droplet number concentration and larger cloud-droplet effective, but higher drizzle droplet number concentration, larger drizzle droplet median diameter and drizzle liquid water content. The heavier drizzle frequency and intensity on Leg-1 were enhanced by the collision-coalescence processes within cloud due to strong turbulence. The sub-cloud precipitation rate on Leg-1 was significantly higher than that along Leg-2. As a result, the sub-cloud accumulation mode aerosols and CCN on Leg-1 were depleted, but the coarse model aerosols increased. This further leads to a counter-intuitive phenomenon that the CCN is less than cloud-droplet number concentration for Leg-1. The average CCN loss rates are ?3.89 \begin{document}$\mathrm{c}{\mathrm{m}}^{-3}\;{\mathrm{h}}^{-1}$\end{document} and ?0.77 \begin{document}$\mathrm{c}{\mathrm{m}}^{-3}\;{\mathrm{h}}^{-1}$\end{document} on Leg-1 and Leg-2, respectively. The cloud and drizzle heterogeneities inside the same stratocumulus can significantly alter the sub-cloud aerosols and CCN budget. Hence it should be treated with caution in the aircraft assessment of aerosol-cloud-precipitation interactions.     

Atmospheric Disturbance Characteristics in the Lower-middle Stratosphere Inferred from Observations by the Round-Trip Intelligent Sounding System (RTISS) in China

Through multi-order structure function analysis and singularity measurement,the Hurst index and intermittent parameter are obtained to quantitatively describe the characteristics of atmospheric disturbance based on the round-trip intelligent sounding system(RTISS)in the lower-middle stratosphere.According to the third-order structure function,small-scale gravity waves are classified into three states:stable,unstable,and accompanied by turbulence.The evolution of gravity waves is reflected by the variation of the third-order structure function over time,and the generation of turbulence is also observed.The atmospheric disturbance intensity parameter RT is defined in this paper and contains both wave disturbance(H₁)and random intermittency(C₁).RT is considered to reflect the characteristics of atmospheric disturbance more reasonably than either of the above two alone.In addition,by obtaining the horizontal wavenumber spectrum from the flat-floating stage and the vertical wavenumber spectrum from the ascending and descending stages at the height range of18-24 km,we found that when the gravity wave activity is significantly enhanced in the horizontal direction,the amplitude of the vertical wavenumber spectrum below is significantly larger,which shows a significant impact of gravity wave activity on the atmospheric environment below.     

Improving Simulations of Vegetation Dynamics over the Tibetan Plateau: Role of Atmospheric Forcing Data and Spatial Resolution

The efficacy of vegetation dynamics simulations in offline land surface models (LSMs) largely depends on the quality and spatial resolution of meteorological forcing data. In this study, the Princeton Global Meteorological Forcing Data (PMFD) and the high spatial resolution and upscaled China Meteorological Forcing Data (CMFD) were used to drive the Simplified Simple Biosphere model version 4/Top-down Representation of Interactive Foliage and Flora Including Dynamics (SSiB4/TRIFFID) and investigate how meteorological forcing datasets with different spatial resolutions affect simulations over the Tibetan Plateau (TP), a region with complex topography and sparse observations. By comparing the monthly Leaf Area Index (LAI) and Gross Primary Production (GPP) against observations, we found that SSiB4/TRIFFID driven by upscaled CMFD improved the performance in simulating the spatial distributions of LAI and GPP over the TP, reducing RMSEs by 24.3% and 20.5%, respectively. The multi-year averaged GPP decreased from 364.68 gC \begin{document}${\mathrm{m}}^{-2}\;{\mathrm{y}\mathrm{r}}^{-1}$\end{document} to 241.21 gC \begin{document}${\mathrm{m}}^{-2}\;{\mathrm{y}\mathrm{r}}^{-1}$\end{document} with the percentage bias dropping from 50.2% to –1.7%. When using the high spatial resolution CMFD, the RMSEs of the spatial distributions of LAI and GPP simulations were further reduced by 7.5% and 9.5%, respectively. This study highlights the importance of more realistic and high-resolution forcing data in simulating vegetation growth and carbon exchange between the atmosphere and biosphere over the TP.     

Climate projections over different climatic regions of Afghanistan under shared socioeconomic scenarios

Theoretical and Applied Climatology - The global climate models (GCMs) of Coupled Model Intercomparison Project phase 6 (CMIP6) were used for spatiotemporal projections of precipitation and...     

Datasets for the CMIP6 Scenario Model Intercomparison Project (ScenarioMIP) Simulations with the Coupled Model CAS FGOALS-f3-L

The datasets for the tier-1 Scenario Model Intercomparison Project(ScenarioMIP)experiments from the Chinese Academy of Sciences(CAS)Flexible Global Ocean-Atmosphere-Land System model,finite-volume version 3(CAS FGOALS-f3-L)are described in this study.ScenarioMIP is one of the core MIP experiments in phase 6 of the Coupled Model Intercomparison Project(CMIP6).Considering future CO2,CH4,N2O and other gases’concentrations,as well as land use,the design of ScenarioMIP involves eight pathways,including two tiers(tier-1 and tier-2)of priority.Tier-1 includes four combined Shared Socioeconomic Pathways(SSPs)with radiative forcing,i.e.,SSP1-2.6,SSP2-4.5,SSP3-7.0 and SSP5-8.5,in which the globally averaged radiative forcing at the top of the atmosphere around the year 2100 is approximately 2.6,4.5,7.0 and 8.5 W m?2,respectively.This study provides an introduction to the ScenarioMIP datasets of this model,such as their storage location,sizes,variables,etc.Preliminary analysis indicates that surface air temperatures will increase by about 1.89℃,3.07℃,4.06℃ and 5.17℃ by around 2100 under these four scenarios,respectively.Meanwhile,some other key climate variables,such as sea-ice extension,precipitation,heat content,and sea level rise,also show significant long-term trends associated with the radiative forcing increases.These datasets will help us understand how the climate will change under different anthropogenic and radiative forcings.     

CAMS-CSM模式及其参与CMIP6的方案

世界气候研究计划(WCRP)组织开展的耦合模式比较计划已实施到第六阶段（CMIP6),中国气象科学研究院发展的气候系统模式CAMS-CSM是注册参加CMIP6的模式之一。除CMIP6要求的气候诊断、评估和描述试验（DECK）以及历史气候模拟试验（Historical）外,CAMS-CSM还计划参加情景模式比较计划（ScenarioMIP)、云反馈模式比较计划（CFMIP)、全球季风模式比较计划（GMMIP）和高分辨率模式比较计划（HighResMIP)这4个模式比较子计划（MIPs)。文中通过介绍CAMS-CSM的基本情况和模拟性能,以及计划参加的CMIP6试验及MIPs,为模式试验数据使用者提供参考。     

关于CAS FGOALS-f3-L模式中青藏高原地表温度偏差的归因分析

中国科学院全球海洋-大气-陆地耦合模式(FGOALS-f3-L)参加了耦合模式比较计划的第六阶段(CMIP6)试验,但是其对关键气候敏感地区青藏高原的地表温度的再现能力还不清楚.这项研究用再分析资料CFSR评估了FGOALS-f3-L模式对青藏高原地表温度的再现能力.结果表明,FGOALS-f3-L可以合理模拟整个高原上年平均地表温度的空间分布,但低估了整个高原上年平均地表温度.模拟的地表温度在整个高原上冬春季表现为冷偏差,夏秋季表现为暖偏差.基于地表能量平衡方程的进一步定量分析表明,地表反照率反馈(SAF)项极大地贡献了高原西部年平均,冬春季平均地表温度的冷偏差,而对高原东部是暖偏差贡献.与SAF项相比,地表感热项对地表温度偏差的贡献几乎相反,这大大抵消了SAF项引起的偏差.云辐射强迫项对高原东部的年平均和季节平均弱冷偏差有很大贡献.与高估的水蒸气含量有关的长波辐射项造成了夏秋季整个高原上大部分的暖偏差.该研究表明,提高FGOALS-f3-L中的陆面和云过程对降低高原上地表温度偏差至关重要.     

CAS-ESM2.0 Model Datasets for the CMIP6 Ocean Model Intercomparison Project Phase 1(OMIP1)

As a member of the Chinese modeling groups,the coupled ocean-ice component of the Chinese Academy of Sciences’Earth System Model,version 2.0(CAS-ESM2.0),is taking part in the Ocean Model Intercomparison Project Phase 1(OMIP1)experiment of phase 6 of the Coupled Model Intercomparison Project(CMIP6).The simulation was conducted,and monthly outputs have been published on the ESGF(Earth System Grid Federation)data server.In this paper,the experimental dataset is introduced,and the preliminary performances of the ocean model in simulating the global ocean temperature,salinity,sea surface temperature,sea surface salinity,sea surface height,sea ice,and Atlantic Meridional Overturning Circulation(AMOC)are evaluated.The results show that the model is at quasi-equilibrium during the integration of 372 years,and performances of the model are reasonable compared with observations.This dataset is ready to be downloaded and used by the community in related research,e.g.,multi-ocean-sea-ice model performance evaluation and interannual variation in oceans driven by prescribed atmospheric forcing.     

Simulation and Improvements of Oceanic Circulation and Sea Ice by the Coupled Climate System Model FGOALS-f3-L

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.     

NEX-GDDP和CMIP5对青藏高原地区近地面气象场历史和未来模拟的评估与偏差校正

青藏高原是全球变化研究的热点区域,气候模式模拟是研究该区域气候变化的重要数据来源。本文使用基于中国地面台站的插值格点数据集(CN05.1),对国际气候耦合模式第5次比较计划(CMIP5)及其高分辨率统计降尺度数据集(NEX-GDDP)中15个模式1966-2005年间的逐日最高/最低气温、降水和平均风速在青藏高原区域的模拟能力进行了评估。使用多领域间影响模型比较计划(ISI-MIP)的偏差校正方法对上述数据进行了训练和验证,并对未来时期模式数据进行了校正。研究表明:(1)训练时期(1986-2005年),NEX-GDDP高估了日最高气温(1.04℃)和日最低气温(0.23℃),低估了日降水量(-0.11 mm),CMIP5低估了日平均风速(-0.11 m·s^-1)。年/季平均值/总量和极端值存在较大偏差。(2)校正后,验证时期(1966-1985年)各变量逐日数据的相关系数提高(除气温外),均方根误差下降,平均偏差幅度减小。各变量的年/季平均值/总量和极端值的偏差大幅减小。(3)对于未来时期(2006-2095年),校正过程保留了原有数据年/季平均值/总量和极端值的变化趋势,调整了各要素平均值/总量和极端值的基准值和空间分布特征,以更准确地衔接历史时期的规律,可为该地区未来气候变化及其影响研究提供重要参考。     

Developing climate change scenarios for Tamil Nadu, India using MAGICC/SCENGEN

This paper describes the projection of climate change scenarios under increased greenhouse gas emissions, using the results of atmospheric-ocean general circulation models in the Coupled Model Intercomparison Project phase 3 dataset. A score is given to every model based on global and regional performance. Four out of 20 general circulation models (GCMs) were selected based on skill in predicting observed annual temperature and precipitation conditions. The ensemble of these four models shows superiority over the individual model scores. These models were subjected to increases in future anthropogenic radiative forcings for constructing climate change scenarios. Future climate scenarios for Tamil Nadu were developed with MAGICC/SCENGEN software. Model results show both temperature and precipitation increases under increased greenhouse gas scenarios. Northeast and northwest parts of Tamil Nadu show a greater increase in temperature and precipitation. Seasonally, the maximum rise in temperature occurred during the MAM season, followed by DJF, JJA, and SON. Decreasing trends of precipitation were observed during DJF and MAM.     

通用地球系统模式对亚洲夏季风降水的模拟能力评估

通过与观测/再分析资料和参加第五次耦合模式比较计划(CMIP5)的模式模拟结果进行对比,评估了通用地球系统模式(CESM,1.0.3版本)对亚洲夏季风降水的模拟能力。结果表明:CESM能够合理地模拟出亚洲夏季风降水的气候平均态,但与其他CMIP5模式模拟结果类似,对中国东南地区降水模拟偏少,而对中国西部高原地区降水模拟偏多;CESM可以再现亚洲季风区降水冬弱夏强、雨带北进南退的季节变化特征,其模拟偏差具有区域性和季节性差异;从EOF分析结果来看,CESM能够模拟出亚洲夏季风降水的时空变化特征,且能较好地抓住亚洲夏季风降水与厄尔尼诺-南方涛动(El Ni?o-Southern Oscillation,简称ENSO)的相关关系。总的说来,CESM对亚洲夏季风降水的模拟是合理的,模拟水平与4个最好的CMIP5模式相当。     

Influence of the circumglobal wave-train on European summer precipitation

We investigate European summer (July–August) precipitation variability and its global teleconnections using the NCEP/NCAR reanalysis data (1950–2010) and a historical Coupled Model Intercomparison Project climate simulation (1901–2005) carried out using the ECHAM6/MPIOM climate model. A wavelike pattern is found in the upper tropospheric levels (200 hPa) similar to the summer circumglobal wave train (CGT) extending from the North Pacific to the Eurasian region. The positive phase of the CGT is associated with upper level anomalous low (high) pressure over western (eastern) Europe. It is further associated with a dipole-like precipitation pattern over Europe entailing significantly enhanced (reduced) precipitation over the western (eastern) region. The anomalous circulation features and associated summer precipitation pattern over Europe inverts for the negative CGT phase. Accordingly, the global teleconnection pattern of a precipitation index summarizing summer precipitation over Western Europe entails an upper level signature which consists of a CGT-like wave pattern extending from the North Pacific to Eurasia. The imprint of the CGT on European summer precipitation is distinct from that of the summer North Atlantic Oscillation, despite the two modes of variability bear strong similarities in their upper level atmospheric pattern over Western Europe. The analysis of simulated CGT features and of its climatic implications for the European region substantiates the existence of the CGT-European summer precipitation connection. The summer CGT in the mid-latitude therefore adds to the list of the modes of large-scale atmospheric variability significantly influencing European summer precipitation variability.     

BCC-ESM1 Model Datasets for the CMIP6 Aerosol Chemistry Model Intercomparison Project(AerChemMIP)

BCC-ESM1 is the first version of the Beijing Climate Center’s Earth System Model,and is participating in phase 6 of the Coupled Model Intercomparison Project(CMIP6).The Aerosol Chemistry Model Intercomparison Project(AerChemMIP)is the only CMIP6-endorsed MIP in which BCC-ESM1 is involved.All AerChemMIP experiments in priority 1 and seven experiments in priorities 2 and 3 have been conducted.The DECK(Diagnostic,Evaluation and Characterization of Klima)and CMIP historical simulations have also been run as the entry card of CMIP6.The AerChemMIP outputs from BCC-ESM1 have been widely used in recent atmospheric chemistry studies.To facilitate the use of the BCC-ESM1 datasets,this study describes the experiment settings and summarizes the model outputs in detail.Preliminary evaluations of BCC-ESM1 are also presented,revealing that:the climate sensitivities of BCC-ESM1 are well within the likely ranges suggested by IPCC AR5;the spatial structures of annual mean surface air temperature and precipitation can be reasonably captured,despite some common precipitation biases as in CMIP5 and CMIP6 models;a spurious cooling bias from the 1960s to 1990s is evident in BCC-ESM1,as in most other ESMs;and the mean states of surface sulfate concentrations can also be reasonably reproduced,as well as their temporal evolution at regional scales.These datasets have been archived on the Earth System Grid Federation(ESGF)node for atmospheric chemistry studies.     

Dynamical Downscaling of Temperature and Precipitation Extremes in China under Current and Future Climates

Climate changes over China from the present (1996–2005) to the future (2046–2055) under Representative Concentration Pathways 4.5 (RCP4.5) and Representative Concentration Pathways 8.5 (RCP8.5) scenarios are projected using the Weather Research and Forecasting (WRF) model, version 3.7.1. The WRF model was driven by the Global 6-Hourly Bias-corrected Coupled Model Intercomparison Project, Phase 5 (CMIP5), Community Earth System Model dataset over China with a resolution of 30?km. The results demonstrate that WRF downscaling generally simulates more reliable spatial distributions of surface air temperature and precipitation in China with higher spatial pattern correlations and closer in magnitude to the Community Climate System Model, version 4.0, simulation results, especially near mountain ranges. The WRF projections for temperature and precipitation for the future under the two emission scenarios are compared with the present simulation. Generally stronger warming, both in mean temperature and extreme statistics, is produced by WRF-RCP8.5 than by WRF-RCP4.5. The projections for precipitation changes are more varied with season and region for both scenarios.     

CAS FGOALS-f3-L Large-ensemble Simulations for the CMIP6 Polar Amplification Model Intercomparison Project

Large-ensemble simulations of the atmosphere-only time-slice experiments for the Polar Amplification Model Intercomparison Project (PAMIP) were carried out by the model group of the Chinese Academy of Sciences (CAS) Flexible Global Ocean-Atmosphere-Land System (FGOALS-f3-L). Eight groups of experiments forced by different combinations of the sea surface temperature (SST) and sea ice concentration (SIC) for pre-industrial, present-day, and future conditions were performed and published. The time-lag method was used to generate the 100 ensemble members, with each member integrating from 1 April 2000 to 30 June 2001 and the first two months as the spin-up period. The basic model responses of the surface air temperature (SAT) and precipitation were documented. The results indicate that Arctic amplification is mainly caused by Arctic SIC forcing changes. The SAT responses to the Arctic SIC decrease alone show an obvious increase over high latitudes, which is similar to the results from the combined forcing of SST and SIC. However, the change in global precipitation is dominated by the changes in the global SST rather than SIC, partly because tropical precipitation is mainly driven by local SST changes. The uncertainty of the model responses was also investigated through the analysis of the large-ensemble members. The relative roles of SST and SIC, together with their combined influence on Arctic amplification, are also discussed. All of these model datasets will contribute to PAMIP multi-model analysis and improve the understanding of polar amplification.