The Baseline Evaluation of LASG/IAP Climate System Ocean Model (LICOM) Version 2

The baseline performance of the latest version (version 2) of an intermediate resolution, stand-alone climate oceanic general circulation model, called LASG/IAP (State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics/Institute of Atmospheric Physics) Climate system Ocean Model (LICOM), has been evaluated against the observation by using the main metrics from Griffies et al. in 2009. In general, the errors of LICOM2 in the water properties and in the circulation are comparable with the models of Coordinated Ocean-ice Reference Experiments (COREs). Some common biases are still evident in the present version, such as the cold bias in the eastern Pacific cold tongue, the warm biases off the east coast of the basins, the weak poleward heat transport in the Atlantic, and the relatively large biases in the Arctic Ocean. A unique systematic bias occurs in LICOM2 over the Southern Ocean, compared with CORE models. It seems that this bias may be related to the sea ice process around the Antarctic continent.     

A fast version of LASG/IAP climate system model and its 1000-year control integration

A fast version of the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geo- physical Fluid Dynamics(LASG)/Institute of Atmospheric Physics(IAP)climate system model is briefly documented.The fast coupled model employs a low resolution version of the atmospheric component Grid Atmospheric Model of IAP/LASG(GAMIL),with the other parts of the model,namely an oceanic component LASG/IAP Climate Ocean Model(LICOM),land component Common Land Model(CLM),and sea ice component from National Center for Atmospheric Research Community Climate System Model (NCAR CCSM2),as the same as in the standard version of LASG/IAP Flexible Global Ocean Atmosphere Land System model(FGOALS g).The parameterizations of physical and dynamical processes of the at- mospheric component in the fast version are identical to the standard version,although some parameter values are different.However,by virtue of reduced horizontal resolution and increased time-step of the most time-consuming atmospheric component,it runs faster by a factor of 3 and can serve as a useful tool for long- term and large-ensemble integrations.A 1000-year control simulation of the present-day climate has been completed without flux adjustments.The final 600 years of this simulation has virtually no trends in global mean sea surface temperatures and is recommended for internal variability studies.Several aspects of the control simulation’s mean climate and variability are evaluated against the observational or reanalysis data. The strengths and weaknesses of the control simulation are evaluated.The mean atmospheric circulation is well simulated,except in high latitudes.The Asian-Australian monsoonal meridional cell shows realistic features,however,an artificial rainfall center is located to the eastern periphery of the Tibetan Plateau persists throughout the year.The mean bias of SST resembles that of the standard version,appearing as a"double ITCZ"(Inter-Tropical Convergence Zone)associated with a westward extension of the equatorial eastern Pacific cold tongue.The sea ice extent is acceptable but has a higher concentration.The strength of Atlantic meridional overturning is 27.5 Sv.Evidence from the 600-year simulation suggests a modulation of internal variability on ENSO frequency,since both regular and irregular oscillations of ENSO are found during the different time periods of the long-term simulation.     

Arctic Climate Changes Based on Historical Simulations(1900-2013) with the CAMS-CSM

The Chinese Academy of Meteorological Sciences Climate System Model(CAMS-CSM) is a newly developed global climate model that will participate in the Coupled Model Intercomparison Project phase 6. Based on historical simulations(1900-2013), we evaluate the model performance in simulating the observed characteristics of the Arctic climate system, which includes air temperature, precipitation, the Arctic Oscillation(AO), ocean temperature/salinity,the Atlantic meridional overturning circulation(AMOC), snow cover, and sea ice. The model-data comparisons indicate that the CAMS-CSM reproduces spatial patterns of climatological mean air temperature over the Arctic(60°-90°N) and a rapid warming trend from 1979 to 2013. However, the warming trend is overestimated south of the Arctic Circle, implying a subdued Arctic amplification. The distribution of climatological precipitation in the Arctic is broadly captured in the model, whereas it shows limited skills in depicting the overall increasing trend. The AO can be reproduced by the CAMS-CSM in terms of reasonable patterns and variability. Regarding the ocean simulation, the model underestimates the AMOC and zonally averaged ocean temperatures and salinity above a depth of 500 m, and it fails to reproduce the observed increasing trend in the upper ocean heat content in the Arctic. The largescale distribution of the snow cover extent(SCE) in the Northern Hemisphere and the overall decreasing trend in the spring SCE are captured by the CAMS-CSM, while the biased magnitudes exist. Due to the underestimation of the AMOC and the poor quantification of air–sea interaction, the CAMS-CSM overestimates regional sea ice and underestimates the observed decreasing trend in Arctic sea–ice area in September. Overall, the CAMS-CSM reproduces a climatological distribution of the Arctic climate system and general trends from 1979 to 2013 compared with the observations, but it shows limited skills in modeling local trends and interannual variability.     

一个灵活的海洋——大气耦合环流模式

Based on the National Center for Atmospheric Research (NCAR) Climate System Model version 1(CSM-1), a Flexible coupled General Circulation Model version 0 (FGCM-0) is developed in this study through replacing CSM-1＇s oceanic component model with IAP L30T63 global oceanic general circulation model and some necessary modifications of the other component models. After the coupled model FGCM--0 is spun up for dozens of years, it has been run for 60 years without flux correction. The model does not only show the reasonable long-term mean climatology, but also reproduce a lot of features of the interannual variability of climate, e.g. the ENSO-like events in the tropical Pacific Ocean and the dipole mode pattern in the tropical Indian Ocean. Comparing FGCM-0 with the NCAR CSM-1, some common features are found, e.g. the overestimation of sea ice in the North Pacific and the simulated double ITCZ etc.The further analyses suggest that they may be attributed to errors in the atmospheric model.     

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.     

Evaluation of Arctic Sea Ice Drift and its Relationship with Near-surface Wind and Ocean Current in Nine CMIP6 Models from China

The simulated Arctic sea ice drift and its relationship with the near-surface wind and surface ocean current during 1979-2014 in nine models from China that participated in the sixth phase of the Coupled Model Intercomparison Project(CMIP6)are examined by comparison with observational and reanalysis datasets.Most of the models reasonably represent the Beaufort Gyre(BG)and Transpolar Drift Stream(TDS)in the spatial patterns of their long-term mean sea ice drift,while the detailed location,extent,and strength of the BG and TDS vary among the models.About two-thirds of the models agree with the observation/reanalysis in the sense that the sea ice drift pattern is consistent with the near-surface wind pattern.About the same proportion of models shows that the sea ice drift pattern is consistent with the surface ocean current pattern.In the observation/reanalysis,however,the sea ice drift pattern does not match well with the surface ocean current pattern.All nine models missed the observational widespread sea ice drift speed acceleration across the Arctic.For the Arctic basin-wide spatial average,five of the nine models overestimate the Arctic long-term(1979-2014)mean sea ice drift speed in all months.Only FGOALS-g3 captures a significant sea ice drift speed increase from 1979 to 2014 both in spring and autumn.The increases are weaker than those in the observation.This evaluation helps assess the performance of the Arctic sea ice drift simulations in these CMIP6 models from China.     

Simulations of Eurasian Winter Temperature Trends in Coupled and Uncoupled CFSv2

Conflicting results have been presented regarding the link between Arctic sea-ice loss and midlatitude cooling, particularly over Eurasia. This study analyzes uncoupled(atmosphere-only) and coupled(ocean–atmosphere) simulations by the Climate Forecast System, version 2(CFSv2), to examine this linkage during the Northern Hemisphere winter, focusing on the simulation of the observed surface cooling trend over Eurasia during the last three decades. The uncoupled simulations are Atmospheric Model Intercomparison Project(AMIP) runs forced with mean seasonal cycles of sea surface temperature(SST)and sea ice, using combinations of SST and sea ice from different time periods to assess the role that each plays individually,and to assess the role of atmospheric internal variability. Coupled runs are used to further investigate the role of internal variability via the analysis of initialized predictions and the evolution of the forecast with lead time.The AMIP simulations show a mean warming response over Eurasia due to SST changes, but little response to changes in sea ice. Individual runs simulate cooler periods over Eurasia, and this is shown to be concurrent with a stronger Siberian high and warming over Greenland. No substantial differences in the variability of Eurasian surface temperatures are found between the different model configurations. In the coupled runs, the region of significant warming over Eurasia is small at short leads, but increases at longer leads. It is concluded that, although the models have some capability in highlighting the temperature variability over Eurasia, the observed cooling may still be a consequence of internal variability.     

Variations of sea ice temperature from CHINARE 2003 and its application on sea ice model evaluation

Variation of vertical profiles of sea ice temperature and adjacent atmosphere and ocean temperatures were measured by ice drifting buoys deployed in the northeast Chukchi Sea as part of the 2003 Chinese Arctic Research Expedition.The buoy observations (September 2003 to February 2005) show that the cooling of the ice began in late September,propagated down through the ice,reaching the bottom of the ice in December,and continued throughout the winter.In winter 2003/04,some obvious warmings were observed in the upper portion of the ice in response to major warmings in the overlying atmosphere associated with the periodicity of storms in the northeast Chukchi Sea.It is found that the melt season at the buoy site in 2004 was about 15% longer than normal.The buoy observed vertical ice temperature profiles were used as a diagnostic for sea ice model evaluation.The results show that the simulated ice temperature profiles have large discrepancies as compared with the observations.     

Numerical Simulation of Atmosphere-Ocean-Sea Ice Interaction During Interannual Cycle in High Northern Latitudes

The interannual atmosphere-ocean-sea ice interaction （AOSI） in high northern latitudes is studied with a global atmosphere-ocean-sea ice coupled model system, in which the model components of atmosphere and land surface are from China National Climate Center and that of ocean and sea ice are from LASG, Institute of Atmospheric Physics, Chinese Academy of Sciences. A daily flux anomaly correction scheme is employed to couple the atmosphere model and the ocean model with the effect of inhomogenity of sea ice in high latitudes is considered. The coupled model system has been run for 50 yr and the results of the last 30 years are analyzed. After the sea level pressure （SLP）, surface air temperature （SAT）, sea surface temperature （SST）, sea ice concentration （SIC）, and sea surface sensible heat flux （SHF） are filtered with a digital filter firstly, their normalized anomalies are used to perform the decomposition of combined complex empirical orthogonal function （CCEOF） and then they are reconstructed with the leading mode. The atmosphere-ocean-sea ice interactions in high northern latitudes during a periodical cycle （approximately 4 yr） are analyzed. It is shown that： （1） When the North Atlantic Oscillation （NAO） is in its positive phase, the southerly anomaly appears in the Greenland Sea, SAT increases, the sea loses less SHF, SST increases and SIC decreases accordingly; when the NAO is in its negative phase, the northerly anomaly appears in the Greenland Sea, SAT decreases, the sea loses more SHF, SST decreases and SIC increases accordingly. There are similar features in the Barents Sea, but the phase of evolution in the Barents Sea is different from that in the Greenland Sea. （2） For an average of multi-years, there is a cold center in the inner part of the Arctic Ocean near the North Pole. When there is an anomaly of low pressure, which is closer to the Pacific Ocean, in the inner part of the Arctic Ocean, anomalies of warm advection appear in the region near the Pacif     

NUMERICAL SIMULATIONS ON INFLUENCES OF VARIATION OF SEA ICE THICKNESS AND EXTENT ON ATMOSPHERIC CIRCULATION

By using a 2-layer AGCM designed by Institute of Atmospheric Physics,Chinese Academy ofSciences.this paper investigates influences of thickness and extent variations in Arctic sea ice onthe atmosphere circulation,particularly on climate variations in East Asia.The simulation resuhshave indicated that sea ice thickness variation in the Arctic exhibits significant influences onsimulation results,particularly on East Asian monsoon.A nearly reasonable distribution of sea icethickness in the model leads directly to stronger winter and summer monsoon over East Asia.andimproves the model's simulation results for Siberia high and Icelandic low in winter.On the otherhand,sea ice thickness variation can excite a teleconnection wave train across Asian Continent,andin low latitudes,the wave propagates from the western Pacific across the equator to the easternPacific.In addition,the variation of sea ice thickness also influences summer convective activitiesover the low latitudes including South China Sea and around the Philippines.Effects of winter sea ice extents in the Barents Sea on atmospheric circulation in the followingspring and summer are also significant.The simulation result shows that when winter sea iceextent in the target region is larger (smaller) than normal.(1)in the following spring (averagedfrom April to June).positive (negative) SLP anomalies occupy the northern central Pacific.whichleads directly to weakened (deepened)Aleutian low.and further favors the light (heavy) sea icecondition in the Bering Sea:(2)in the following summer,thermal depression in Asian Continent isdeepened (weakened).and the subtropical high in the northwestern Pacific shifts northward(southward) from its normal position and to be strengthened (weakened).     

BCC_CSM北极海冰模拟性能的改进对东亚冬季气候模拟的影响

国家气候中心气候系统模式(BCC_CSM)将美国Los Alamos国家实验室发展的海冰模式CICE5.0替代原有的海冰模式SIS,形成一个新版本耦合模式,很好地提高了模式对北极海冰和北极气候的模拟能力.在此基础上,本文评估新耦合模式对1985-2014年东亚冬季气候的模拟性能,检验北极海冰模拟性能的改进对东亚冬季气候...     

大气环流模式（SAMIL）海气耦合前后性能的比较

基于耦合器框架，中国科学院大气物理研究所大气科学和地球流体力学数值模拟国家重点实验室大气环流谱模式 （SAMIL）最近成功地实现了与海洋、海冰等气候分量模式的耦合，形成了“非通量调整”的海－陆－气－冰直接耦合的气候模式系统（FGOALS-s）。在耦合系统中，由于海温、海冰等的分布由预报模式驱动，大气与海洋、海冰之间引入了相互作用过程，这样大气环流的模拟特征与耦合前会有不同。为分析耦合系统的性能，作者对耦合前后的模拟结果进行了分析比较，重点是大气模拟特征的差异。结果表明，耦合前、后大气环流的基本特征相似，都能成功地模拟出主要的环流系统分布及季节变化，但是由于海温和海冰的模拟存在系统性的偏差，使得耦合后的大气环流受到明显影响。例如耦合后热带海温偏冷，南大洋、北太平洋和北大西洋等中纬度地区的海温偏高，导致海温等值线向高纬海域的伸展较弱，海温经向梯度减小。耦合后海冰在北极区域范围偏大，在南极周边地区则偏小。海温、海冰分布模拟的偏差影响到中、高纬低层大气的温度。热带海温偏低，使得赤道地区降水偏弱，凝结潜热减少，热带对流层中高层温度比耦合前要低，大气温度的经向梯度减小。经向温度梯度的改变，直接影响到对平均经圈环流及西风急流强度的模拟。尽管耦合系统中海温、海冰的模拟存在偏差，但在亚洲季风区，耦合后季风环流及降水等的分布都比耦合前单独大气模式的结果合理，表明通过海[CD*2]气相互作用可减少耦合前季风区的模拟误差，改善季风模拟效果。比较发现，海温、海冰模拟的偏差，除与海洋模式中经向热输送偏弱、海冰模式中海冰处理等有关外，也与大气模式中总云量模拟偏低有关。大气模式本身的误差，特别是云、辐射过程带来的误差，对耦合结果具有极为重要的影响。完全耦合后，这些误差通过与海洋、海冰的反馈作用而放大。因此，对于FGOALS-s而言，要提高耦合系统的整体性能，除改进各气候分量模式的模拟性能外，需要重点改进大气模式中的云、辐射过程。     

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.     

任意正交曲线坐标系下的海洋模式动力框架的发展与评估

本文发展了一个可以适用于任意水平正交曲线坐标系的海洋模式动力框架,并将其应用于中国科学院大气物理研究所大气科学和地球流体力学数值模拟国家重点实验室发展的气候系统海洋模式LICOM2.0（LASG/IAP Climate system Ocean Model,version2.0）。在经纬网格坐标系下,新的动力框架与LICOM2.0原有的动力框架模拟结果完全一致。基于新的动力框架,海洋模式可采用能够准确描述北冰洋地形的三极网格,克服了LICOM2.0经纬网格版本必须将北极点处理为孤岛的缺陷,从而显著改进了模式对于北冰洋环流和北大西洋经圈翻转流函数（AMOC）的模拟能力。此外,引进三极网格还可以避免模式网格距随纬度增加而急剧减小带来的计算不稳定,在LICOM2.0的三极网格版本中,模式不需要采用任何空间滤波方案仍然能够保证计算的稳定性,从而与LICOM2.0的经纬网格版本相比,极大地提高了模式的并行效率,这一点在当水平分辨率提高到0.1度时表现得尤为明显,海洋模式的并行加速比可以从经纬网格版本的5.8左右提高到三极网格版本的15.0左右。     

CICE海冰模式中反照率相关参数对北极海冰模拟的影响

国家气候中心气候系统模式BCC_CSM2.0最新耦合了美国Los Alamos国家实验室发展的海冰模式CICE5.0,为试验模式中与反照率相关参数的敏感性及其对模拟结果的影响,提高模式对北极海冰的模拟能力,选取海冰模式中3个主要参数进行了敏感性试验。利用以BCC_CSM2.0耦合框架为基础建立的海冰-海洋耦合模式,选取CORE资料为大气强迫场开展试验,试验的3个参数分别为冰/雪表面反射率、雪粒半径和雪粒半径参考温度。结果表明,参数取值的不同对北极海冰的模拟有显著的影响,优化后的取值组合极大提高了模式的模拟能力,主要表现在:（1）改善了对北极冬季海冰厚度的模拟,海冰厚度增大,与观测资料更为吻合;（2）显著提高了对北极夏季海冰密集度的模拟能力,从而模拟的北极海冰范围年际循环与观测更为一致。参数取值的优化改进了模式对海冰反照率的模拟,进而影响了冰面短波辐射的吸收和海冰表层的融化,最终提高了模式对海冰密集度和厚度的模拟效果。      

IAP第四代大气环流模式的耦合气候系统模式模拟性能评估

本文首先扼要介绍了基于中国科学院大气物理研究所(简称IAP)第四代大气环流模式的新气候系统模式-CAS-ESM-C(中国科学院地球系统模式气候系统模式分量)的发展和结构,之后主要对该模式在模拟大气、海洋、陆面和海冰的气候平均态、季节循环以及主要的年际变率等方面的能力做一个初步的评估.结果表明:模式没有明显的气候漂移,各...     

Simulation of sea ice in FGOALS-g2: Climatology and late 20th century changes

Sea ice is an important component in the Earth’s climate system. Coupled climate system models are indispensable tools for the study of sea ice, its internal processes, interaction with other components, and projection of future changes. This paper evaluates the simulation of sea ice by the Flexible Global Ocean-Atmosphere-Land System model Grid-point Version 2 (FGOALS-g2), in the fifth phase of the Coupled Model Inter-comparison Project (CMIP5), with a focus on historical experiments and late 20th century simulation. Through analysis, we find that FGOALS-g2 produces reasonable Arctic and Antarctic sea ice climatology and variability. Sea ice spatial distribution and seasonal change characteristics are well captured. The decrease of Arctic sea ice extent in the late 20th century is reproduced in simulations, although the decrease trend is lower compared with observations. Simulated Antarctic sea ice shows a reasonable distribution and seasonal cycle with high accordance to the amplitude of winter-summer changes. Large improvement is achieved as compared with FGOALS-g1.0 in CMIP3. Diagnosis of atmospheric and oceanic forcing on sea ice reveals several shortcomings and major aspects to improve upon in the future: (1) ocean model improvements to remove the artificial island at the North Pole; (2) higher resolution of the atmosphere model for better simulation of important features such as, among others, the Icelandic Low and westerly wind over the Southern Ocean; and (3) ocean model improvements to accurately receive freshwater input from land, and higher resolution for resolving major water channels in the Canadian Arctic Archipelago.     

Arctic Climate Changes Based on Historical Simulations (1900‒2013) with the CAMS-CSM

The Chinese Academy of Meteorological Sciences Climate System Model (CAMS-CSM) is a newly developed global climate model that will participate in the Coupled Model Intercomparison Project phase 6. Based on historical simulations (1900?2013), we evaluate the model performance in simulating the observed characteristics of the Arctic climate system, which includes air temperature, precipitation, the Arctic Oscillation (AO), ocean temperature/salinity, the Atlantic meridional overturning circulation (AMOC), snow cover, and sea ice. The model?data comparisons indicate that the CAMS-CSM reproduces spatial patterns of climatological mean air temperature over the Arctic (60°?90°N) and a rapid warming trend from 1979 to 2013. However, the warming trend is overestimated south of the Arctic Circle, implying a subdued Arctic amplification. The distribution of climatological precipitation in the Arctic is broadly captured in the model, whereas it shows limited skills in depicting the overall increasing trend. The AO can be reproduced by the CAMS-CSM in terms of reasonable patterns and variability. Regarding the ocean simulation, the model underestimates the AMOC and zonally averaged ocean temperatures and salinity above a depth of 500 m, and it fails to reproduce the observed increasing trend in the upper ocean heat content in the Arctic. The large-scale distribution of the snow cover extent (SCE) in the Northern Hemisphere and the overall decreasing trend in the spring SCE are captured by the CAMS-CSM, while the biased magnitudes exist. Due to the underestimation of the AMOC and the poor quantification of air–sea interaction, the CAMS-CSM overestimates regional sea ice and underestimates the observed decreasing trend in Arctic sea–ice area in September. Overall, the CAMS-CSM reproduces a climatological distribution of the Arctic climate system and general trends from 1979 to 2013 compared with the observations, but it shows limited skills in modeling local trends and interannual variability.