Changes in Global Vegetation Distribution and Carbon Fluxes in Response to Global Warming: Simulated Results from IAP-DGVM in CAS-ESM2

Terrestrial ecosystems are an important part of Earth systems, and they are undergoing remarkable changes in response to global warming. This study investigates the response of the terrestrial vegetation distribution and carbon fluxes to global warming by using the new dynamic global vegetation model in the second version of the Chinese Academy of Sciences (CAS) Earth System Model (CAS-ESM2). We conducted two sets of simulations, a present-day simulation and a future simulation, which were forced by the present-day climate during 1981–2000 and the future climate during 2081–2100, respectively, as derived from RCP8.5 outputs in CMIP5. CO₂ concentration is kept constant in all simulations to isolate CO₂-fertilization effects. The results show an overall increase in vegetation coverage in response to global warming, which is the net result of the greening in the mid-high latitudes and the browning in the tropics. The results also show an enhancement in carbon fluxes in response to global warming, including gross primary productivity, net primary productivity, and autotrophic respiration. We found that the changes in vegetation coverage were significantly correlated with changes in surface air temperature, reflecting the dominant role of temperature, while the changes in carbon fluxes were caused by the combined effects of leaf area index, temperature, and precipitation. This study applies the CAS-ESM2 to investigate the response of terrestrial ecosystems to climate warming. Even though the interpretation of the results is limited by isolating CO₂-fertilization effects, this application is still beneficial for adding to our understanding of vegetation processes and to further improve upon model parameterizations.     

Evaluating the Dependence of Vegetation on Climate in an Improved Dynamic Global Vegetation Model

The capability of an improved Dynamic Global Vegetation Model (DGVM) in reproducing the impact of climate on the terrestrial ecosystem is evaluated. The new model incorporates the Community Land ModelDGVM (CLM3.0-DGVM) with a submodel for temperate and boreal shrubs, as well as other revisions such as the two-leaf scheme for photosynthesis and the definition of fractional coverage of plant functional types (PFTs). Results show that the revised model may correctly reproduce the global distribution of tempera...     

Preliminary Assessment of the Common Land Model Coupled with the IAP Dynamic Global Vegetation Model

The Common Land Model（CoLM） was coupled with the IAP Dynamic Global Vegetation Model（IAPDGVM）, and the performance of this combined CoLMIAP model was evaluated. Offline simulations using both the original Common Land Model（CoLM-LPJ） and CoLM-IAP were conducted. The CoLM-IAP coupled model showed a significant improvement over CoLMLPJ, as the deciduous tree distribution decreased over temperate and boreal regions, while the distribution of evergreen trees increased over the tropics. Some biases in CoLM-LPJ were preserved, including the overestimation of evergreen trees in tropical savanna, the underestimation of boreal evergreen trees, and the absence of boreal shrubs. However, most of these biases did not exist in a further coupled simulation of IAP-DGVM with the Community Land Model（CLM）, for which the parameters of IAP-DGVM were optimized. This implies that further improvement is needed to deal with the differences between CoLM and CLM in parameterizations of landbased physical and biochemical processes.     

IAP大气-植被耦合模式的建立及其模拟

为了充分理解气候与植被之间在不同时间尺度上的反馈作用,需要把动态植被模式耦合到气候模式里.本研究通过引进动态植被模式VEGAS(VEgetation-Global Atmosphere-Soil),在中国科学院大气物理研究所9层(IAP9L)气候模式的基础上,初步建立了一个新的IAP大气一植被耦合模式IAP9L_VEGAS.对该模式积分多年的结果分析表明:IAP9L_VEGAS可以较合理地模拟出植被生态系统生产力和植被、土壤碳库的总量及其季节变化,而且该模式模拟的叶面积指数的全球分布与观测资料十分接近.与未耦合动态植被模式的IAP9L模式模拟结果的比较表明:在非洲和南美等热带雨林地区,IAP9L_VEGAS模拟的叶面积指数比IAP9L中根据经验设置的大3.5以上,更接近观测;此外,IAP9L-VEGAS模拟的降水和近地面气温均较IAP9L更加接近观测实况.     

我国气候对植被分布和净初级生产力影响的数值模拟

基于0.5°×0.5°经纬网格分辨率的一个全球植被动态模式,利用全国676个雨量站点1961～2000年日资料在0.5°×0.5°网格上插值得到的降水和气温资料作为模式气候强迫,模拟研究了中国区域近40年来的植被动态变化,估算了当前中国区域陆地植被净初级生产力,并分析气候与植被净初级生产力的相关性。结果表明:模拟的植被分布时空格局与实际观测的对应关系良好,模拟与观测的叶面积指数总体上比较一致;植被初级生产力空间分布及总量(约为4.64×1015g.a-1(C))的模拟比较理想。对模拟结果分析显示降水是影响净初级生产力的主要气候因子,而在干旱、半干旱地区温度与植被净初级生产力存在显著负相关关系。研究表明该模式能够比较合理地模拟气候对植被年际动态和生产力变化的影响,对于进一步深入研究气候与植被相互作用是有意义的。     

动态植被模型模拟的植被季节变化及其评估

利用MODIS卫星观测资料,对一个考虑了生态系统碳氮循环过程的动态植被模型ICM的模拟性能进行了评估.重点对反映植被动力学的关键参数--叶面积指数(LAI)的模拟结果与观测进行了对比分析,评估了ICM对LAI季节变化特征的模拟能力.结果表明,ICM基本能够模拟出植被的季节变化特征.总体而言,模拟值在低纬度和高纬度地区大...     

Development of the IAP Dynamic Global Vegetation Model

ABSTRACT The lAP Dynamic Global Vegetation Model （IAP-DGVM） has been developed to simulate the distribution and structure of global vegetation within the framework of Earth System Models. It incorporates our group＇s recent developments of major model components such as the shrub sub-model, establishment and competition parameterization schemes, and a process-based fire parameterization of intermediate complexity. The model has 12 plant functional types, including seven tree, two shrub, and three grass types, plus bare soil. Different PFTs are allowed to coexist within a grid cell, and their state variables are updated by various governing equations describing vegetation processes from fine-scale biogeophysics and biogeochemistry, to individual and population dynamics, to large-scale biogeography. Environmental disturbance due to fire not only affects regional vegetation competition, but also influences atmospheric chemistry and aerosol emissions. Simulations under observed atmospheric conditions showed that the model can correctly reproduce the global distribution of trees, shrubs, grasses, and bare soil. The simulated global dominant vegetation types reproduce the transition from forest to grassland （savanna） in the tropical region, and from forest to shrubland in the boreal region, but overestimate the region of temperate forest.     

西北地区陆地生态系统植被状态参数业务化遥感研究

植被指数(NDVI)和叶面积指数(LAI)是两个非常重要的陆地生态系统植被状态参数.我们首先利用最大值(MVC)合成方法使用先进遥感数据如MODIS、AVHRR3等得到旬合成植被指数(NDVI),然后利用最新的经验方法针对不同的陆地生态系统类型反演得到叶面积指数,重点研究了我国沙尘暴发生频率较高的我国西北地区植被覆被状态及其变化情况.植被指数能够反映区域,乃至全球范围植被年季状态,用于监测陆地生态系统植物光合作用活动及其变化.植被指数作为一个基础参数能够用于计算反演更高级别的陆地生态系统状态参数.叶面积指数直接影响植被的光合作用,蒸腾作用的变化和陆面过程的能量平衡状态.在沙尘暴预测研究中使用的起沙过程模型需要将叶面积指数作为一个关键输入变量,另外,绝大多数生态过程模型模拟碳、水循环时也都需要将叶面积指数作为一个非常重要的输入变量.我们总结了最新的叶面积指数经验反演方法,针对6钟不同的陆地生态系统类型应用不同经验模型计算得到了叶面积指数.     

一个海洋-大气-动态植被耦合模式评估——海洋环流模拟

利用中国科学院大气物理研究所（IAP）大气科学与地球流体力学数值模拟国家重点实验室(LASG)的全球耦合模式(GOALS〖CD*2〗AVIM),进行了100年积分。利用后40年的结果对模式耦合植被动态过程（AVIM）前后输出的海洋物理场对比分析。结果表明：耦合AVIM后的模式可以合理地模拟全球海洋温盐环流的气候态、季节变化,可以改进模式的模拟效果,在一定程度上克服了耦合AVIM前模式的缺点,使模拟结果更接近实测。由于植被〖CD*2〗大气的双向作用,在季节变化的模拟中,9月的改进效果大于3月的,北半球大于南半球;对于年平均气候态,耦合AVIM后的模式结果在热带海区海表面温度（SST）的模拟效果得到了明显改善,尤其是赤道太平洋海区的海温偏低现象得到了改善;在年际变化的模拟中,改善了耦合AVIM前模式模拟的年际变化分布,加大了赤道太平洋的标准差的模拟,使得耦合AVIM后模拟的年际变化大于耦合前;增强了耦合模式对赤道太平洋ENSO的模拟能力,较耦合AVIM前的模式模拟出了更多的ENSO基本特征,也改善了耦合AVIM前ENSO变化周期偏弱、偏短的现象;同样改善了对气候系统中存在的相互作用的模拟,对于热带印度洋SST变化与赤道太平洋SST的相互关联的模拟中,更加真实地模拟出了气候系统中存在的相互关联关系,体现出了AVIM动态植被过程对气候耦合模式的改善。     

全球植被与大气之间碳通量的模式估计

用大气植被相互作用模式(AⅥM)模拟了全球陆地植被的净初级生产力(NPP)。AⅥM由相互耦合的两部分组成：物理过程，包括陆地表面水分和能量在土壤、植被与大气之间的传输；以及生理生态过程，如：光合、呼吸、干物质分配、凋落和物候等。全球的植被分为13类，土壤按质地分为6类。用EMDI提供的全球1637个包括不同植被类型的NPP观测点数据对模型进行了检验。NPP模拟的结果表明：全球陆地植被的平均NPP为405.13 g C m-2yr-1，不同植被类型的平均NPP变化范围在99.58 g C m-2yr-l(苔原)到996.2 g C m-2yr-l(热带雨林)之间。全球年总NPP为60.72 Gt C yr-l，其中最大的部分为热带雨林，15.84 Gt C yr-1，占全球的26.09％。最大的碳汇是在北半球的温带。模式模拟的NPP在全球的空间和季节分布是合理的。     

全球植被与大气之间碳通量的模式估计(英文)

用大气植被相互作用模式（AVIM）模拟了全球陆地植被的净初级生产力（NPP）。AVIM由相互耦合的两部分组成：物理过程，包括陆地表面水分和能量在土壤、植被与大气之间的传输；以及生理生态过程，如：光合、呼吸、干物质分配、凋落和物候等。全球的植被分为13类，土壤按质地分为6类。用EMDI提供的全球1637个包括不同植被类型的NPP观测点数据对模型进行了检验。NPP模拟的结果表明：全球陆地植被的平均NPP为405.13gCm-2yr-1，不同植被类型的平均 NPP变化范围在99.58 g Cm-2yr-1（苔原）到996.2 g Cm-2yr-1（热带雨林）之间。全球年总NPP为60.72GtCyr-1，其中最大的部分为热带雨林，15.84GtCyr-1，占全球的26.09％。最大的碳汇是在北半球的温带。模式模拟的NPP在全球的空间和季节分布是合理的。     

浅述植被双向反射模型

探讨了植被双向反射函数的基本概念和物理意义,并对现有的几种植被双向反射模型,几何光学模型,混浊介质模型,混合模型及计算机模拟模型的理论作简要的论述,并比较各类模型的特点。     

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.     

Impact of Spin-up Forcing on Vegetation States Simulated by a Dynamic Global Vegetation Model Coupled with a Land Surface Model

A dynamic global vegetation model (DGVM) coupled with a land surface model (LSM) is generally initialized using a spin-up process to derive a physically-consistent initial condition. Spin-up forcing, which is the atmospheric forcing used to drive the coupled model to equilibrium solutions in the spin-up process, varies across earlier studies. In the present study, the impact of the spin-up forcing in the initialization stage on the fractional coverages (FCs) of plant functional type (PFT) in the subsequent simulation stage are assessed in seven classic climate regions by a modified Community Land Model’s Dynamic Global Vegetation Model (CLM-DGVM). Results show that the impact of spin-up forcing is considerable in all regions except the tropical rainforest climate region (TR) and the wet temperate climate region (WM). In the tropical monsoon climate region (TM), the TR and TM transition region (TR-TM), the dry temperate climate region (DM), the highland climate region (H), and the boreal forest climate region (BF), where FCs are affected by climate non-negligibly, the discrepancies in initial FCs, which represent long-term cumulative response of vegetation to different climate anomalies, are large. Moreover, the large discrepancies in initial FCs usually decay slowly because there are trees or shrubs in the five regions. The intrinsic growth timescales of FCs for tree PFTs and shrub PFTs are long, and the variation of FCs of tree PFTs or shrub PFTs can affect that of grass PFTs.     

全球植被分布对气候影响的数值试验

利用一个新的陆－气双向耦合模式R42_AVIM, 通过有无植被覆盖的对比试验分析, 探讨了全球植被分布对气候和大气环流产生的潜在影响。得出: 陆面植被覆盖使得地表特征参数发生行星尺度的明显改变, 在叶面积指数大的热带和中高纬度森林带尤其显著。在现实植被分布下, 陆地表面反照率减小, 地表净辐射收支和地表潜热通量增加, 而地表感热通量减小。植被叶面积指数比较大的区域地表温度降低, 并且这种温度的改变一直延伸到对流层中上层, 在热带表现为斜压结构, 而在中高纬表现为相当正压结构。植被的存在使热带和中高纬度森林带的蒸发和相应的高层凝结潜热加热增强, 从而增强了经圈环流的上升支, 使得冬季在热带和南半球中纬度降水增多, 夏季在热带和北半球中高纬地区降水明显增多; 而经圈环流下沉支的增强致使副热带降水减少且更干旱。同时, 植被的存在使大陆潜热释放增强, 气温下降, 减小了海陆温度对比, 亚洲夏季风也有所减弱。     

Estimation of the Distribution of Global Anthropogenic Heat Flux

The radiance lights data in 2006 from the National Oceanic and Atmospheric Administration Air Force Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS) and authoritative energy data distributed by the United State Energy Information Administration were applied to estimate the global distribution of anthropogenic heat flux.A strong linear relationship was found to exist between the anthropogenic heat flux and the DMSP/OLS radiance data.On a global scale,the average value of anthropogenic heat flux is approximately 0.03 W m 2 and 0.10 W m 2 for global land area.The results indicate that global anthropogenic heat flux was geographically concentrated and distributed,fundamentally correlating to the economical activities.The anthropogenic heat flux concentrated in the economically developed areas including East Asia,Europe,and eastern North America.The anthropogenic heat flux in the concentrated regions,including the northeastern United States,Central Europe,United Kingdom,Japan,India,and East and South China is much larger than global average level,reaching a large enough value that could affect regional climate.In the center of the concentrated area,the anthropogenic heat flux density may exceed 100 W m 2,according to the results of the model.In developing areas,including South America,Central and North China,India,East Europe,and Middle East,the anthropogenic heat flux can reach a level of more than 10 W m 2 ;however,the anthropogenic heat flux in a vast area,including Africa,Central and North Asia,and South America,is low.With the development of global economy and urban agglomerations,the effect on climate of anthropogenic heat is essential for the research of climate change.     

Sensitivity of the Carbon Storage of Potential Vegetation to Historical Climate Variability and CO2 in Continental China

The interest in the national levels of the terrestrial carbon sink and its spatial and temporal variability with the climate and CO2 concentrations has been increasing. How the climate and the increasing atmospheric CO2 concentrations in the last century affect the carbon storage in continental China was investigated in this study by using the Modified Sheffield Dynamic Global Vegetation Model (M-SDGVM). The estimates of the M-SDGVM indicated that during the past 100 years a combination of increasing CO2 with historical temperature and precipitation variability in continental China have caused the total vegetation carbon storage to increase by 2.04 Pg C, with 2.07 Pg C gained in the vegetation biomass but 0.03 Pg C lost from the organic soil carbon matter. The increasing CO2 concentration in the 20th century is primarily responsible for the increase of the total potential vegetation carbon. These factorial experiments show that temperature variability alone decreases the total carbon storage by 1.36 Pg C and precipitation variability alone causes a loss of 1.99 Pg C. The effect of the increasing CO2 concentration alone increased the total carbon storage in the potential vegetation of China by 3.22 Pg C over the past 100 years. With the changing of the climate, the CO2 fertilization on China's ecosystems is the result of the enhanced net biome production (NBP), which is caused by a greater stimulation of the gross primary production (GPP) than the total soil-vegetation respiration. Our study also shows notable interannual and decadal variations in the net carbon exchange between the atmosphere and terrestrial ecosystems in China due to the historical climate variability.     

GRAPES全球模式的模式误差估计

现代数值天气模式考虑的物理过程和边界条件越来越复杂, 但是它描述的大气状态和真实的大气流体运动轨迹还有一定的差距, 存在模式误差。在以往的研究中, 模式误差往往被忽略, 在集合卡尔曼滤波同化系统中, 如果忽略模式误差会导致滤波发散现象。本文用不同分辨率的模式预报差异估计了GRAPES全球模式的模式误差, 研究发现模式误差随着分辨率降低而线性增加, 而且模式误差随着预报时效的增加呈现线性增长的趋势。     

Sensitivity of the Carbon Storage of Potential Vegetation to Historical Climate Variability and CO_2 in Continental China

The interest in the national levels of the terrestrial carbon sink and its spatial and temporal variabil-ity with the climate and CO2 concentrations has been increasing.How the climate and the increasing atmospheric CO2 concentrations in the last century affect the carbon storage in continental China was in-vestigated in this study by using the Modified Sheffeld Dynamic Global Vegetation Model(M-SDGVM).The estimates of the M-SDGVM indicated that during the past 100 years a combination of increasing CO2 with...     

Simulation and Evaluation of Terrestrial Ecosystem NPP with M-SDGVM over Continental China

Using the regional terrestrial Net Primary Production (NPP) from different observations and models over China, we validated the NPP simulations and explored the relationship between NPP and climate variation at interannual and decadal scales in the Modified Sheffield Dynamic Global Vegetation Model (M-SDGVM) during 1981–2000. M-SDGVM shows agreement with the NPP data from 743 sites under the Global Primary Production Data Initiative (GPPDI). The spatial and the zonal averaged NPP of M-SDGVM agree well with ...