Coupling of the Calculated Freezing and Thawing Front Parameterization in the Earth System Model CAS-ESM

The soil freezing and thawing process affects soil physical properties,such as heat conductivity,heat capacity,and hydraulic conductivity in frozen ground regions,and further affects the processes of soil energy,hydrology,and carbon and nitrogen cycles.In this study,the calculation of freezing and thawing front parameterization was implemented into the earth system model of the Chinese Academy of Sciences(CAS-ESM)and its land component,the Common Land Model(CoLM),to investigate the dynamic change of freezing and thawing fronts and their effects.Our results showed that the developed models could reproduce the soil freezing and thawing process and the dynamic change of freezing and thawing fronts.The regionally averaged value of active layer thickness in the permafrost regions was 1.92 m,and the regionally averaged trend value was 0.35 cm yr–1.The regionally averaged value of maximum freezing depth in the seasonally frozen ground regions was 2.15 m,and the regionally averaged trend value was–0.48 cm yr–1.The active layer thickness increased while the maximum freezing depth decreased year by year.These results contribute to a better understanding of the freezing and thawing cycle process.

Investigating the effect of the Tibetan Plateau on the ITCZ using a coupled Earth system model

本文利用耦合地球气候系统模式研究了青藏高原对热带辐合带(ITCZ)的影响.我们研究发现热带大西洋ITCZ的位置对青藏高原存在与否有明显的敏感性.与目前真实情况相比,移除青藏高原会导致北半球海面降温,南半球海面升温.这种海面温度变化在大西洋表现得尤为明显,导致热带大西洋最大海温中心向南移动,从而迫使大气对流中心向南移动,即表现为ITCZ的南移.相应地,夏季热带大气Hadley环流的上升支也发生明显南移.北(南)半球海洋变冷(变暖)这种态势要求增强跨赤道向北的大气经向热量输送,从而维持各个半球的能量平衡,而这需要ITCZ位置的南移才能实现.本文研究表明,青藏高原的存在在现今ITCZ气候态的形成中可能扮演了重要角色.

Major Modes of Short-Term Climate Variability in the Newly Developed NUIST Earth System Model(NESM)

A coupled earth system model（ESM） has been developed at the Nanjing University of Information Science and Technology（NUIST） by using version 5.3 of the European Centre Hamburg Model（ECHAM）, version 3.4 of the Nucleus for European Modelling of the Ocean（NEMO）, and version 4.1 of the Los Alamos sea ice model（CICE）. The model is referred to as NUIST ESM1（NESM1）. Comprehensive and quantitative metrics are used to assess the model＇s major modes of climate variability most relevant to subseasonal-to-interannual climate prediction. The model＇s assessment is placed in a multi-model framework. The model yields a realistic annual mean and annual cycle of equatorial SST, and a reasonably realistic precipitation climatology, but has difficulty in capturing the spring–fall asymmetry and monsoon precipitation domains. The ENSO mode is reproduced well with respect to its spatial structure, power spectrum, phase locking to the annual cycle, and spatial structures of the central Pacific（CP）-ENSO and eastern Pacific（EP）-ENSO; however, the equatorial SST variability,biennial component of ENSO, and the amplitude of CP-ENSO are overestimated. The model captures realistic intraseasonal variability patterns, the vertical-zonal structures of the first two leading predictable modes of Madden–Julian Oscillation（MJO）, and its eastward propagation; but the simulated MJO speed is significantly slower than observed. Compared with the T42 version, the high resolution version（T159） demonstrates improved simulation with respect to the climatology, interannual variance, monsoon–ENSO lead–lag correlation, spatial structures of the leading mode of the Asian–Australian monsoon rainfall variability, and the eastward propagation of the MJO.

Earth System Model FGOALS-s2: Coupling a Dynamic Global Vegetation and Terrestrial Carbon Model with the Physical Climate System Model

Earth System Models （ESMs） are fundamental tools for understanding climate-carbon feedback. An ESM version of the Flexible Global Ocean-Atmosphere-Land System model （FGOALS） was recently developed within the IPCC AR5 Coupled Model Intercomparison Project Phase 5 （CMIP5） modeling framework, and we describe the development of this model through the coupling of a dynamic global vegetation and terrestrial carbon model with FGOALS-s2. The performance of the coupled model is evaluated as follows. The simulated global total terrestrial gross primary production （GPP） is 124.4 PgC yr-I and net pri- mary production （NPP） is 50.9 PgC yr-1. The entire terrestrial carbon pools contain about 2009.9 PgC, comprising 628.2 PgC and 1381.6 PgC in vegetation and soil pools, respectively. Spatially, in the tropics, the seasonal cycle of NPP and net ecosystem production （NEP） exhibits a dipole mode across the equator due to migration of the monsoon rainbelt, while the seasonal cycle is not so significant in Leaf Area Index （LAI）. In the subtropics, especially in the East Asian monsoon region, the seasonal cycle is obvious due to changes in temperature and precipitation from boreal winter to summer. Vegetation productivity in the northern mid-high latitudes is too low, possibly due to low soil moisture there. On the interannual timescale, the terrestrial ecosystem shows a strong response to ENSO. The model- simulated Nifio3.4 index and total terrestrial NEP are both characterized by a broad spectral peak in the range of 2-7 years. Further analysis indicates their correlation coefficient reaches -0.7 when NEP lags the Nifio3.4 index for about 1-2 months.

Global air-sea CO_(2) exchange fl ux since 1980s: results from CMIP6 Earth System Models

The ocean could profoundly modulate the ever-increasing atmospheric CO_(2) by air-sea CO_(2) exchange process,which is also able to cause signifi cant changes of physical and biogeochemical properties in return.In this study,we assessed the long-term average and spatial-temporal variability of global air-sea CO_(2) exchange fl ux(F CO_(2))since 1980s basing on the results of 18 Coupled Model Intercomparison Project Phase 6(CMIP6)Earth System Models(ESMs).Our fi ndings indicate that the CMIP6 ESMs simulated global CO_(2) sink in recent three decades ranges from 1.80 to 2.24 Pg C/a,which is coincidence with the results of cotemporaneous observations.What’s more,the CMIP6 ESMs consistently show that the global oceanic CO_(2) sink has gradually intensifi ed since 1980s as well as the observations.This study confi rms the simulated F CO_(2) could reach agreements with the observations in the aspect of primary climatological characteristics,however,the simulation skills of CIMP6 ESMs in diverse open-sea biomes are unevenness.None of the 18 CMIP6 ESMs could reproduce the observed F CO_(2) increasement in the central-eastern tropical Pacifi c and the midlatitude Southern Ocean.Defi ciencies of some CMIP6 ESMs in reproducing the atmospheric pressure systems of the Southern Hemisphere and the El Niño-Southern Oscillation(ENSO)mode of the tropical Pacifi c are probably the major causes.

Simulations of dissolved oxygen concentration in CMIP5 Earth system models

The climatologies of dissolved oxygen concentration in the ocean simulated by nine Earth system models(ESMs) from the historical emission driven experiment of CMIP5(Phase 5 of the Climate Model Intercomparison Project) are quantitatively evaluated by comparing the simulated oxygen to the WOA09 observation based on common statistical metrics. At the sea surface, distribution of dissolved oxygen is well simulated by all nine ESMs due to well-simulated sea surface temperature(SST), with both globally-averaged error and root mean square error(RMSE) close to zero, and both correlation coefficients and normalized standard deviation close to 1. However, the model performance differs from each other at the intermediate depth and deep ocean where important water masses exist. At the depth of 500 to 1 000 m where the oxygen minimum zones(OMZs) exist, all ESMs show a maximum of globally-averaged error and RMSE, and a minimum of the spatial correlation coefficient. In the ocean interior, the reason for model biases is complicated, and both the meridional overturning circulation(MOC) and the particulate organic carbon flux contribute to the biases of dissolved oxygen distribution. Analysis results show the physical bias contributes more. Simulation bias of important water masses such as North Atlantic Deep Water(NADW), Antarctic Bottom Water(AABW) and North Pacific Intermediate Water(NPIW) indicated by distributions of MOCs greatly affects the distributions of oxygen in north Atlantic, Southern Ocean and north Pacific, respectively.Although the model simulations of oxygen differ greatly from each other in the ocean interior, the multi-model mean shows a better agreement with the observation.

Global Climate Internal Variability in a 2000-year Control Simulation with Community Earth System Model(CESM)

Using the low-resolution(T31, equivalent to 3.75°× 3.75°) version of the Community Earth System Model(CESM) from the National Center for Atmospheric Research(NCAR), a global climate simulation was carried out with fixed external forcing factors(1850 Common Era.(C.E.) conditions) for the past 2000 years. Based on the simulated results, spatio-temporal structures of surface air temperature, precipitation and internal variability, such as the El Nio-Southern Oscillation(ENSO), the Atlantic Multi-decadal Oscillation(AMO), the Pacific Decadal Oscillation(PDO), and the North Atlantic Oscillation(NAO), were compared with reanalysis datasets to evaluate the model performance. The results are as follows: 1) CESM showed a good performance in the long-term simulation and no significant climate drift over the past 2000 years; 2) climatological patterns of global and regional climate changes simulated by the CESM were reasonable compared with the reanalysis datasets; and 3) the CESM simulated internal natural variability of the climate system performs very well. The model not only reproduced the periodicity of ENSO, AMO and PDO events but also the 3–8 years variability of the ENSO. The spatial distribution of the CESM-simulated NAO was also similar to the observed. However, because of weaker total irradiation and greenhouse gas concentration forcing in the simulation than the present, the model performances had some differences from the observations. Generally, the CESM showed a good performance in simulating the global climate and internal natural variability of the climate system. This paves the way for other forced climate simulations for the past 2000 years by using the CESM.

Regional earth system modeling：review and future directions

耦合区域地球系统模式(RESM)现在仍处于早期的发展阶段,在本文中,我们对其近期相关进展进行了回顾。到目前为止,已经开发出了耦合的区域大气–海洋–海冰、大气–气溶胶和大气–生物圈模式,但总体它们仅在有限的区域得到应用,需要更多的工作来评估其在更多区域的可移植性。我们认为RESM发展中的未来挑战,是在大气、海洋、冰冻圈、生物圈、化学圈以外,同时将人类及其活动成分以完全相互作用的方式引入进来。

Evaluating the performance of CMIP6 Earth system models in simulating global vegetation structure and distribution

Evaluation of vegetation structure and distribution simulations in Earth system models(ESMs)is the basis for understanding historical reconstruction and future projection of changes in terrestrial ecosystems,carbon cycle,and climate based on these ESMs.Such assessments can also provide important information of models'merits and shortcomings or systematic biases,and so clues for model development.Vegetation structure and distribution in ESMs are primarily characterized by three variables:leaf area index(LAI),tree height,and fractional coverage of plant functional type(PFT).However,for the ongoing Coupled Model Intercomparison Project Phase 6(CMIP6),only temporal variabilities of global-averaged LAI time series were evaluated,others remain largely uninvestigated.This study systematically investigates the spatial and/or temporal variability of the three critical variables from 27 ESMs in CMIP6 using satellite observations.Our results show that all models and the multi-model ensemble mean(MME)can generally reproduce the observed LAI spatial pattern but all of them overestimate the global mean LAI mainly due to overestimation of LAI in non-forested vegetated areas.Most CMIP6 models fail to capture the temporal variability in the annual LAI because of large biases in both the simulated trend magnitude and temporal pattern of interannual variability.The average LAI seasonal cycles in different latitude zones are roughly reproduced by the models,but 1-2 months delays in the LAI peak appear in the Arctic-boreal zone.Additionally,CMIP6 models overall overestimate tree height,and largely overestimate the global grass area but underestimate tree and shrub areas,especially in the middle and high latitudes.It should be kept in mind that such biases may have further impacts on the simulations of the related carbon and land-atmosphere interaction variables(e.g.,ecosystem production,carbon storage,transpiration,and temperature)for global change research.Hence,bias-correction should be made to improve reliability of vegetation structure and distribution when future projections and historical reconstructions.They also underscore the urgent need in development and parameterization of dynamic vegetation within Earth system models,such as phenology,allocation,and morphology schemes.

Evaluation of CMIP5 Earth System Models in Reproducing Leaf Area Index and Vegetation Cover over the Tibetan Plateau

The abilities of 12 earth system models（ESMs） from the Coupled Model Intercomparison Project Phase5（CMIP5） to reproduce satellite-derived vegetation biological variables over the Tibetan Plateau（TP） were examined.The results show that most of the models tend to overestimate the observed leaf area index（LAI）and vegetation carbon above the ground,with the possible reasons being overestimation of photosynthesis and precipitation.The model simulations show a consistent increasing trend with observed LAI over most of the TP during the reference period of 1986-2005,while they fail to reproduce the downward trend around the headstream of the Yellow River shown in the observation due to their coarse resolutions.Three of the models：CCSM4,CESM1-BGC,and NorESM1-ME,which share the same vegetation model,show some common strengths and weaknesses in their simulations according to our analysis.The model ensemble indicates a reasonable spatial distribution but overestimated land coverage,with a significant decreasing trend（-1.48%per decade） for tree coverage and a slight increasing trend（0.58%per decade） for bare ground during the period 1950-2005.No significant sign of variation is found for grass.To quantify the relative performance of the models in representing the observed mean state,seasonal cycle,and interannual variability,a model ranking method was performed with respect to simulated LAI.INMCM4,bcc-csm-1.1m,MPI-ESM-LR,IPSL CM5A-LR,HadGEM2-ES,and CCSM4 were ranked as the best six models in reproducing vegetation dynamics among the 12 models.

Global warming projections using the human–earth system model BNU-HESM1.0

Future climate change is usually projected by coupled earth system models under specific emission scenarios designed by integrated assessment models(IAMs),and this offline approach means there is no interaction between the coupled earth system models and the IAMs.This paper introduces a new method to design possible future emission scenarios and corresponding climate change, in which a simple economic and climate damage component is added to the coupled earth system model of Beijing Normal University(BNU-ESM). With the growth of population and technological expertise and the declining emission-to-output ratio described in the Dynamic Integrated Climate-Economy model, the projected carbon emission is 13.7 Gt C, resulting in a 2.4 °C warming by the end of the twenty-first century(2080–2099) compared with1980–1999. This paper also suggests the importance of the land and ocean carbon cycle in determining the CO2 concentration in the atmosphere. It is hoped that in the near future the next generation of coupled earth system models that include both the natural system and the social dimension will be developed.

Development of Climate and Earth System Models in China: Past Achievements and New CMIP6 Results

The Earth–Climate System Model(ECSM)is an important platform for multi-disciplinary and multi-sphere integration research,and its development is at the frontier of international geosciences,especially in the field of global change.The research and development(R&D)of ECSM in China began in the 1980 s and have achieved great progress.In China,ECSMs are now mainly developed at the Chinese Academy of Sciences,ministries,and universities.Following a brief review of the development history of Chinese ECSMs,this paper summarized the technical characteristics of nine Chinese ECSMs participating in the Coupled Model Intercomparison Project Phase 6 and preliminarily assessed the basic performances of four Chinese models in simulating the global climate and the climate in East Asia.The projected changes of global precipitation and surface air temperature and the associated relationship with the equilibrium climate sensitivity under four shared socioeconomic path scenarios were also discussed.Finally,combined with the international situation,from the perspective of further improvement,eight directions were proposed for the future development of Chinese ECSMs.

A Data Analysis Framework for Earth System Simulation within an <i>In-Situ</i>Infrastructure

This paper presents a generic procedure to implement a scalable and high performance data analysis framework for large-scale scientific simulation within an in-situ infrastructure. It demonstrates a unique capability for global Earth system simulations using advanced computing technologies (i.e., automated code analysis and instrumentation), in-situ infrastructure (i.e., ADIOS) and big data analysis engines (i.e., SciKit-learn). This paper also includes a useful case that analyzes a globe Earth System simulations with the integration of scalable in-situ infrastructure and advanced data processing package. The in-situ data analysis framework can provides new insights on scientific discoveries in multiscale modeling paradigms.

数值预报AI气象大模型国际发展动态研究

数值预报是研究地球系统的重要工具,有助于加深科学家对大气、海洋、气候和环境等复杂系统之间相互作用和变化过程的理解,在防灾减灾、气候变化和环境治理等方面发挥着不可或缺的作用。随着模式复杂度和分辨率的提高,传统数值模式在气候变化研究和气候预测方面取得了迅速的进展,但也面临一些挑战,需要得到数据同化、集合耦合、高性能计算和不确定性分析等多方面的支持。而近年来,“AI+气象”的交叉研究在气象领域引起了广泛关注。基于多种深度学习架构的人工智能大模型,依托强大的计算资源和海量的数据进行训练,能够以新的科学范式进行高效数值预报。气象大模型不断涌现,一些科技公司如华为、英伟达、DeepMind、谷歌、微软等,以及国内外高校如清华大学、复旦大学、密歇根大学、莱斯大学等发布了多个涵盖临近预报、短时预报、中期预报和延伸期预报等不同领域的气象大模型。这标志着人工智能与气象领域的交叉融合已经达到新的高度。尽管气象大模型在现阶段取得了较大突破,但其发展仍然面临弱可解释性、泛化能力不足、极端事件预报强度偏低、智能预报结果过平滑、深度学习框架能力需要拓展等诸多挑战。

9.2ka BP亚洲弱季风事件的模拟研究

全新世发生了一系列的亚洲季风突变事件,其中距今9.2ka的弱季风事件较少受到关注,其存在与否以及成因机制仍然存在争议。本文利用通用地球系统模式(Community Earth SystemModel,CESM)进行全新世以来瞬变积分气候模拟试验得到的结果(NanjingNormalUniversity-12ka,NNU-12ka)对比重建资料和国际上已完成的过去21ka以来的瞬变积分模拟试验(Transient Climate Evolution over the last 21000 years,TraCE-21ka),探究了9.2ka亚洲弱季风事件的时空特征及其成因。结果表明:NNU-12ka太阳活动敏感性试验模拟出了9.6~9.4ka前后的亚洲弱季风事件,此时总太阳辐射减少了0.38Wm^(2),亚洲季风区夏季平均降水减少了0.17mmd^(-1)。而基于TraCE-21ka的全强迫试验结果表明,冰川融水和冰盖变化对该时期亚洲季风变化没有显著影响。NNU-12ka太阳活动试验中亚洲热带季风区夏季降水减少尤为明显,在我国东北地区降水略有增加。热带季风减弱的原因是由于太阳辐射的骤降导致亚洲海陆热力梯度减弱,加强亚洲陆地的海平面气压,引起热带季风区的异常下沉运动,抑制水汽向亚洲季风区输送,进而通过动力作用减弱季风。

A Brief Introduction to BNU-HESM1.0 and Its Earth Surface Temperature Simulations

Integrated assessment models and coupled earth system models both have their limitations in understanding the interactions between human activity and the physical earth system. In this paper, a new human--earth system model, BNU- HESM1.0, constructed by combining the economic and climate damage components of the Dynamic Integrated Model of Climate Change and Economy to the BNU-ESM model, is introduced. The ability of BNU-HESM1.0 in simulating the global CO2 concentration and surface temperature is also evaluated. We find that, compared to observation, BNU-HESM1.0 underestimates the global CO2 concentration and its rising trend during 1965-2005, due to the uncertainty in the economic components. However, the surface temperature simulated by BNU-HESM1.0 is much closer to observation, resulting from the overestimates of surface temperature by the original BNU-ESM model. The uncertainty of BNU-ESM falls within the range of present earth system uncertainty, so it is the economic and climate damage component of BNU-HESM 1.0 that needs to be improved through further study. However, the main purpose of this paper is to introduce a new approach to investigate the complex relationship between human activity and the earth system. It is hoped that it will inspire further ideas that prove valuable in guiding human activities appropriate for a sustainable future climate.

CMIP6计划中我国地球气候系统模式北极海冰空间分布的模拟评估

世界气候研究计划(WCRP)正在组织实施第6次国际耦合模式比较计划(CMIP6)。本文选取了参加CMIP6的9个中国大陆地球气候系统模式的北极海冰输出结果与同时段海冰遥感观测数据进行比较,评估了各个模式1980年至2014年北极海冰密集度和其长期趋势的空间分布。研究表明,所有的模式都可以较好地模拟出3月北极海盆海冰的分布情况,误差主要分布在海冰边缘地区,其中鄂霍茨克海的中部以及巴伦支海地区误差最大,最高值可达90%。与3月相比,模式对9月海冰空间分布的模拟效果不佳,在北极海盆地区以及海冰边缘地区均存在15%以上的误差。在海冰密集度长期趋势空间分布方面,3月,9个模式总体高估了海冰下降区的海域面积,在鄂霍茨克海、巴伦支海以及格陵兰海北部海域为模式误差大值区(大于50%)。模式在模拟9月海冰下降趋势的区域及量级上较3月都有更大的偏差。另外,9个模式对海冰密集度多年平均季节变化的模拟能力与其对长期趋势的模拟能力有一定关联,对海冰密集度季节变化模拟准确的模式,其海冰长期趋势的模拟也较接近观测。海冰分量模式中参数化方案的改进可以明显提高模式的模拟能力。

区域地球系统模式研究进展

区域地球系统模式是区域气候模式下一阶段的主要发展目标。本文阐述了发展区域地球系统模式的重要意义,分析了近年来区域地球系统模式的研究进展和典型案例,指出其多圈层通量耦合、空间分辨率提高以及耦合数据同化的三个共性特征。建议以开源共创的方式整合各界研究力量,加快建设我国自主可控的区域地球系统模式;围绕新建立的模式开展跨学科研究,特别关注其中多圈层、多尺度过程的相互作用;围绕高分辨率区域地球系统模式建立区域数字孪生监测预警平台,用于关键区域的防灾减灾和关键决策支撑。

中国地球系统模式对全球地表入射短波辐射和大气逆辐射的模拟效果评估

以云和地球辐射能量系统(CERES)数据集为准,量化了中国地球系统模式对地表入射短波辐射和大气逆辐射时空变化的模拟性能,明确了多模式间模拟结果存在不确定性的区域。结果表明:中国模式均能模拟出北半球地表入射短波辐射和大气逆辐射“夏高冬低”的季节变化特征。陆地上,中国模式对两个辐射分量月均值的模拟结果与CERES相当,在海洋上低于CERES结果。中国模式能模拟出地表入射短波辐射下降、大气逆辐射上升的年际变化趋势。对于2001—2014年均值,中国模式模拟的地表入射短波辐射在海洋和陆地上较CERES分别偏低3.3和3.0 W·m^(-2),模拟的大气逆辐射在海洋上与CERES结果相当,在陆地上较CERES低1.3 W·m^(-2)。除南北纬30°附近之外,中国模式在其他纬度均低估地表入射短波辐射,以热带和北极最为明显。模式对大气逆辐射的模拟偏差呈纬向波动特征,模拟误差大值出现在高大山脉处。中国模式模拟地表入射短波辐射不确定性极大的区域分布在热带雨林和南极洲沿海,模拟大气逆辐射不确定性极大的区域分布在格林兰岛、青藏高原、安第斯山脉和南极洲沿海。

Developed and Developing World Contributions to Climate System Change Based on Carbon Dioxide,Methane and Nitrous Oxide Emissions

One of the key issues in international climate negotiations is the formulation of targets for emissions reduction for all countries based on the principle of ＂common but differentiated responsibilities＂. This formulation depends primarily on the quantitative attribution of the responsibilities of developed and developing countries for historical climate change. Using the Commuity Earth System Model（CESM）, we estimate the responsibilities of developed countries and developing countries for climatic change from 1850 to 2005 using their carbon dioxide, methane and nitrous oxide emissions. The results indicate that developed countries contribute approximately 53%–61%, and developing countries approximately 39%–47%, to the increase in global air temperature, upper oceanic warming, sea-ice reduction in the NH, and permafrost degradation. In addition, the spatial heterogeneity of these changes from 1850 to 2005 is primarily attributed to the emissions of greenhouse gases（GHGs）in developed countries. Although uncertainties remain in the climate model and the external forcings used, GHG emissions in developed countries are the major contributor to the observed climate system changes in the 20 th century.