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 Model- DGVM （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 temperate and boreal shrubs, and improves the model performance with more realistic distribution of di？erent vege- tation types. The revised model also correctly reproduces the zonal distributions of vegetation types. In reproducing the dependence of the vegetation distribution on climate conditions, the model shows that the dominant regions for trees, grasses, shrubs, and bare soil are clearly separated by a climate index derived from mean annual precipitation and temperature, in good agreement with the CLM4 surface data. The dominant plant functional type mapping to a two dimensional parameter space of mean annual temperature and precipitation also qualitatively agrees with the results from observations and theoretical ecology studies.

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.

Evaluation of the New Dynamic Global Vegetation Model in CAS-ESM

In the past several decades, dynamic global vegetation models（DGVMs） have been the most widely used and appropriate tool at the global scale to investigate vegetation-climate interactions. At the Institute of Atmospheric Physics, a new version of DGVM（IAP-DGVM） has been developed and coupled to the Common Land Model（CoLM） within the framework of the Chinese Academy of Sciences＇ Earth System Model（CAS-ESM）. This work reports the performance of IAP-DGVM through comparisons with that of the default DGVM of CoLM（CoLM-DGVM） and observations. With respect to CoLMDGVM, IAP-DGVM simulated fewer tropical trees, more ＂needleleaf evergreen boreal tree＂ and ＂broadleaf deciduous boreal shrub＂, and a better representation of grasses. These contributed to a more realistic vegetation distribution in IAP-DGVM,including spatial patterns, total areas, and compositions. Moreover, IAP-DGVM also produced more accurate carbon fluxes than CoLM-DGVM when compared with observational estimates. Gross primary productivity and net primary production in IAP-DGVM were in better agreement with observations than those of CoLM-DGVM, and the tropical pattern of fire carbon emissions in IAP-DGVM was much more consistent with the observation than that in CoLM-DGVM. The leaf area index simulated by IAP-DGVM was closer to the observation than that of CoLM-DGVM; however, both simulated values about twice as large as in the observation. This evaluation provides valuable information for the application of CAS-ESM, as well as for other model communities in terms of a comparative benchmark.

Improvements of a Dynamic Global Vegetation Model and Simulations of Carbon and Water at an Upland-Oak Forest

The interest in the development and improvement of dynamic global vegetation models （DGVMs）, which have the potential to simulate fluxes of carbon, water and nitrogen, along with changes in the vegetation dynamics, within an integrated system, has been increasing. In this paper, some numerical schemes and a higher resolution soil texture dataset were employed to improve the Sheffield Dynamic Global Vegetation Model （SDGVM）. Using eddy covariance-based measurements, we then tested the standard version of the SDGVM and the modified version of the SDGVM. Detailed observations of daily carbon and water fluxes made at the upland oak forest on the Walker Branch Watershed in Tennessee, USA offered a unique opportunity for these comparisons. The results revealed that the modified version of the SDGVM did a reasonable job of simulating the carbon and water flux and the variation of soil water content （SWC）. However, at the end of the growing season, it failed to simulate the effect of the limitations on the soil respiration dynamics and as a result underestimated this respiration. It was also noted that the modified version overestimated the increase in the SWC following summer rainfall, which was attributed to an inadequate representation of the ground water and thermal cycle.

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.

Investigation of Uncertainties of Establishment Schemes in Dynamic Global Vegetation Models

In Dynamic Global Vegetation Models （DGVMs）, the establishment of woody vegetation refers to flowering, fertiliza- tion, seed production, germination, and the growth of tree seedlings. It determines not only the population densities but also other important ecosystem structural variables. In current DGVMs, establishments of woody plant functional types （PFTs） are assumed to be either the same in the same grid cell, or largely stochastic. We investigated the uncertainties in the competition of establishment among coexisting woody PFTs from three aspects： the dependence of PFT establishments on vegetation states; background establishment; and relative establishment potentials of different PFTs. Sensitivity experi- ments showed that the dependence of establishment rate on the fractional coverage of a PFT favored the dominant PFT by increasing its share in establishment. While a small background establishment rate had little impact on equilibrium states of the ecosystem, it did change the timescale required for the establishment of alien species in pre-existing forest due to their disadvantage in seed competition during the early stage of invasion. Meanwhile, establishment purely fiom background （the scheme commonly used in current DGVMs） led to inconsistent behavior in response to the change in PFT specification （e.g., number of PFTs and their specification）. Furthermore, the results also indicated that trade-off between irtdividual growth and reproduction/colonization has significant influences on the competition of establishment. Hence, further development of es- tablishment parameterization in DGVMs is essential in reducing the uncertainties in simulations of both ecosystem structures and successions.

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.

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.

CLM3.0-DGVM中植物叶面积指数与气候因子的时空关系

作为陆面模型里植被的特征量,叶面积值数(LAI)和植被覆盖度在陆地-大气相互作用的相关研究里被广泛应用。LAI的模拟是动态植被模式(DVM)的核心任务之一,需要对模拟的LAI与气候因子间的时空关系进行评估以更好的了解模式性能以及理解植被-大气反馈过程。用1950—1999年的气象数据驱动通用陆面模式的动态植被模式(CLM3.0-DGVM)模拟得到的全球潜在植被的LAI和2001—2003年MODIS观测资料衍生出的LAI数据进行对比,并在此基础上研究当前气候条件下不同植物功能型(PFT)的LAI与不同气候因子在年际尺度上的时空关系,包括运用Moran系数理论分析空间自相关性、运用逐步回归算法构建空间最优一阶线性回归方程、分析模式LAI与气候因子间的滞后相关性。研究表明:1)以MODIS衍生数据作参照,改进后的CLM3.0-DGVM能较好地模拟不同PFTs的LAI年最大值的空间分布型,但是在物候模拟即LAI的季节循环上存在不足;2)植物LAI的分布具有正的空间自相关性。对潜在植物LAI和气候因子进行拟合时不同气候因子对不同PFTs的方差贡献不一样,一般降水最大、风速最小。这反映了陆地生态系统和气候间复杂的相互关系;3)模式模拟的LAI和气候因子有显著的1—2a的滞后相关,其中光照、降水和LAI的滞后相关性波动较大,而温度、比湿的较小,风速的不明显。这些基于CLM3.0-DGVM的结论在自然界的植物-气候相互作用系统中具有普遍意义:不同地区不同植物受不同气候因子的影响不一样;找出不同PFT的主要气候影响因子和理解其中最关键的生物物理和生物化学过程是至关重要的。进一步工作需要用更精确和更高分辨率的气候数据以及局地观测的LAI对DGVM做评估,同时DGVM本身也需要继续改进(例如加入农作物和灌溉过程的模拟)。

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 different historic datasets and are closest to the IGBP NPP. Compared to the 1980s, NPP in the 1990s increases in most of China with a high degree of spatial heterogeneity. The multi-year mean NPP of forest types is reasonably modeled （above 500 g C m-2 yr-1 ） while that of C 3 path of photosynthesis （C 3 ） grasslands is underestimated. The NPP of 7 M-SDGVM main plant functional types （PFTs） increases and the increment of the broad-leaved deciduous forest is the most obvious （5.05 g C m-2 yr-1 ）. During the studied period, the annual NPP of M-SDGVM over China increases, with significant fluctuations, at an average rate of 0.0164 Gt C yr-1 . Regulated by annual temperature and precipitation, the interannual variation of the total NPP shows more significant correlation with temperature （relativity and probability are R= 0.61, P = 0.00403） than precipitation （R = 0.40, P = 0.08352）. CO 2 fertilization may play a key role in the increase of terrestrial ecosystem NPP over continental China, and CO 2 stimulation increases with CO 2 concentrations, and also with the climate variability of the 1980s and 1990s.

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 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.

Assessing the vulnerability of ecosystems to climate change based on climate exposure, vegetation stability and productivity

Background: Global warming has brought many negative impacts on terrestrial ecosystems, which makes the vulnerability of ecosystems one of the hot issues in current ecological research. Here, we proposed an assessment method based on the IPCC definition of vulnerability. The exposure to future climate was characterized using a moisture index(MI) that integrates the effects of temperature and precipitation. Vegetation stability, defined as the proportion of intact natural vegetation that remains unchanged under changing climate, was used together with vegetation productivity trend to represent the sensitivity and adaptability of ecosystems. Using this method, we evaluated the vulnerability of ecosystems in Southwestern China under two future representative concentration pathways(RCP 4.5 and RCP 8.5) with MC2 dynamic global vegetation model.Results:(1) Future(2017–2100) climate change will leave 7.4%(under RCP 4.5) and 57.4% of(under RCP 8.5) of areas under high or very high vulnerable climate exposure;(2) in terms of vegetation stability, nearly 45% of the study area will show high or very high vulnerability under both RCPs. Beside the impacts of human disturbance on natural vegetation coverage(vegetation intactness), climate change will cause obvious latitudinal movements in vegetation distribution, but the direction of movements under two RCPs were opposite due to the difference in water availability;(3) vegetation productivity in most areas will generally increase and remain a low vulnerability in the future;(4) an assessment based on the above three aspects together indicated that future climate change will generally have an adverse impact on all ecosystems in Southwestern China, with non-vulnerable areas account for only about 3% of the study area under both RCPs. However, compared with RCP 4.5, the areas with mid-and highvulnerability under RCP 8.5 scenario increased by 13% and 16%, respectively.Conclusion: Analyses of future climate exposure and projected vegetation distribution indicate widespread vulnerability of ecosystems in Southwestern China, while vegetation productivity in most areas will show an increasing trend to the end of twenty-first century. Based on new climate indicators and improved vulnerability assessment rules, our method provides an extra option for a more comprehensive evaluation of ecosystem vulnerability, and should be further tested at larger spatial scales in order to provide references for regional, or even global, ecosystem conservation works.

Evaluating the Tree Population Density and Its Impacts in CLM-DGVM

Vegetation population dynamics play an essential role in shaping the structure and function of terrestrial ecosystems. However, large uncertainties remain in the parameterizations of population dynamics in current Dynamic Global Vegetation Models （DGVMs）. In this study, the global distribution and probability density functions of tree population densities in the revised Community Land Model-Dynamic Global Vegetation Model （CLM-DGVM） were evaluated, and the impacts of population densities on ecosystem characteristics were investigated. The results showed that the model predicted unrealistically high population density with small individual size of tree PFTs （Plant Punetional Types） in boreal forests, as well as peripheral areas of tropical and temperate forests. Such biases then led to the underestimation of forest carbon storage and incorrect carbon allocation among plant leaves, stems and root pools, and hence predicted shorter time scales for the building/recovering of mature forests. These results imply that further improvements in the parameterizations of population dynamics in the model are needed in order for the model to correctly represent the response of ecosystems to climate change.

Combining European Earth Observation products with Dynamic Global Vegetation Models for estimating Essential Biodiversity Variables

Global,fast and accessible monitoring of biodiversity is one of the main pillars of the efforts undertaken in order to revert it loss.The Group on Earth Observations Biodiversity Observation Network(GEO-BON)provided an expert-based definition of the biological properties that should be monitored,the Essential Biodiversity Variables(EBVs).Initiatives to provide indicators for EBVs rely on global,freely available remote sensing(RS)products in combination with empirical models and field data,and are invaluable for decision making.In this study,we provide alternatives for the expansion and improvement of the EBV indicators,by suggesting current and future data from the European Space Agencýs COPERNICUS and explore the potential of RS-integrated Dynamic Global Vegetation Models(DGVMs)for the estimation of EBVs.Our review found that mainly due to the inclusion of the Sentinel constellation,Copernicus products have similar or superior potential for EBV indicator estimation in relation to their NASA counterparts.DGVMs simulate the ecosystem level EBVs(ecosystem function and structure),and when integrated with remote sensing data have great potential to not only offer improved estimation of current states but to provide projection of ecosystem impacts.We suggest that focus on producing EBV relevant outputs should be a priority within the research community,to support biodiversity preservation efforts.

动态植被模型对青藏高原植被的模拟检验

动态植被模型是研究植被变化对气候反馈和影响的重要模型工具。本文对耦合了动态植被(Dynamic Vegetation,DV)和碳氮(Carbon and Nitrogen,CN)模型的NCAR陆面过程模式CLM4.5(Community Land Model version 4.5)对青藏高原(以下简称高原)植被的模拟性能进行了评估,获得了定量化的偏差信息,并对高原植被和气候变化因子的关系进行了初步探讨。结果表明:模型能大致再现叶面积指数(Leaf area index,LAI)在历史时期的季节循环、长期变化趋势和空间分布,但空间变率较遥感资料大。模拟的乔木覆盖度偏大,草地覆盖度偏小,因此严重高估了植被高原南部和东部的LAI。与遥感观测相比,模拟的LAI呈现了1~2个月的滞后,这与模式本身的植被动力机制不完善和模式的降水驱动偏差有关。高原植被变化趋势的时空分布与表层土壤水和降水等气象因子的趋势变化显示出较好的一致性,表明在该研究时段,地表水循环的变化(主要是降水和土壤水含量)对高原植被生长可能起主导作用。

Fractional vegetation cover estimation in heterogeneous areas by combining a radiative transfer model and a dynamic vegetation model

A fractional vegetation cover(FVC)estimation method incorporating a vegetation growth model and a radiative transfer model was previously developed,which was suitable for FVC estimation in homogeneous areas because the finer-resolution pixels corresponding to one coarseresolution FVC pixel were all assumed to have the same vegetation growth model.However,this assumption does not hold over heterogeneous areas,meaning that the method cannot be applied to large regions.Therefore,this study proposes a finer spatial resolution FVC estimation method applicable to heterogeneous areas using Landsat 8 Operational Land Imager reflectance data and Global LAnd Surface Satellite(GLASS)FVC product.The FVC product was first decomposed according to the normalized difference vegetation index from the Landsat 8 OLI data.Then,independent dynamic vegetation models were built for each finer-resolution pixel.Finally,the dynamic vegetation model and a radiative transfer model were combined to estimate FVC at the Landsat 8 scale.Validation results indicated that the proposed method(R^(2)=0.7757,RMSE=0.0881)performed better than either the previous method(R^(2)=0.7038,RMSE=0.1125)or a commonly used method involving look-up table inversions of the PROSAIL model(R^(2)=0.7457,RMSE=0.1249).

Effects of Dynamic Vegetation on Global Climate Simulation Using the NCEP GFS and SSiB4/TRIFFID

Two global experiments were carried out to investigate the effects of dynamic vegetation processes on numerical climate simulations from 1948 to 2008.The NCEP Global Forecast System(GFS)was coupled with a biophysical model,the Simplified Simple Biosphere Model(SSi B)version 2(GFS/SSi B2),and it was also coupled with a biophysical and dynamic vegetation model,SSi B version 4/Top-down Representation of Interactive Foliage and Flora Including Dynamics(TRIFFID)(GFS/SSi B4/TRIFFID).The effects of dynamic vegetation processes on the simulation of precipitation,near-surface temperature,and the surface energy budget were identified on monthly and annual scales by assessing the GFS/SSi B4/TRIFFID and GFS/SSi B2 results against the satellite-derived leaf area index(LAI)and albedo and the observed land surface temperature and precipitation.The results show that compared with the GFS/SSiB2 model,the temporal correlation coefficients between the globally averaged monthly simulated LAI and the Global Inventory Monitoring and Modeling System(GIMMS)/Global Land Surface Satellite(GLASS)LAI in the GFS/SSi B4/TRIFFID simulation increased from 0.31/0.29(SSiB2)to 0.47/0.46(SSiB4).The correlation coefficients between the simulated and observed monthly mean near-surface air temperature increased from 0.50(Africa),0.35(Southeast Asia),and 0.39(South America)to 0.56,0.41,and 0.44,respectively.The correlation coefficients between the simulated and observed monthly mean precipitation increased from 0.19(Africa),0.22(South Asia),and 0.22(East Asia)to 0.25,0.27,and 0.28,respectively.The greatest improvement occurred over arid and semiarid areas.The spatiotemporal variability and changes in vegetation and ground surface albedo modeled by the GFS with a dynamic vegetation model were more consistent with the observations.The dynamic vegetation processes contributed to the surface energy and water balance and in turn,improved the annual variations in the simulated regional temperature and precipitation.The dynamic vegetation processes had the greatest influence on the spatiotemporal changes in the latent heat flux.This study shows that dynamic vegetation processes in earth system models significantly improve simulations of the climate mean status.

动态全球植被模型的研究进展

植被与气候之间的相互作用是一个复杂的过程,为了研究植被与气候之间相互作用的机理和评价气候变化对植被影响,植被模型得以迅速发展,并从静态的植被模型发展到了动态全球植被模型(Dynamic Global Vegetation Model,DGVM)。DGVM主要模拟植被的生理过程、植被动态、植被物候和营养物质循环,包括动态的生物地球化学模型和动态的生物地球物理模型两类。国际上应用最广泛的DGVM有LPJI、BIS、VECODE和TRIFFID等。目前DGVM研究的焦点主要有4个:①模型本身的完善;②不同模型比较研究;③与气候模型的耦合研究;④碳数据同化系统研究。

陆地生态系统模型及其与气候模式耦合的回顾

陆地生态系统和气候系统通过能量通量、水汽通量、物质交换相互影响、作用。作者对陆地生态系统模型及其与气候模式耦合的研究进行综述和讨论,总结了当代5类主要全球陆地生态系统模型,即生物地理模型、生物地球化学模型、森林林窗模型、陆面生物圈模型和动态全球植被模型,以及它们与气候模式耦合的研究进展。阐述了动态全球植被模型及其与气候模式耦合研究在全球变化研究的重要作用。最后,对未来模拟研究的方向进行了分析。

气候年际变率对全球植被平均分布的影响

采用改进后的通用陆面模式的动态植被模式(CLM-DGVM)研究当前气候条件下气候年际变率对全球潜在植被平均分布的影响。设计两组区域数值实验,一组使用基于NCEP再分析资料衍生的1960—1999年多年气象数据循环驱动,对照实验使用这40a的气候平均态或单年气象资料驱动(即没有气候年际变率),分别考察有无气候年际变化对热带、温带和寒带的潜在植被分布平衡态的影响。在此基础上以1950—1999年上述数据及对应的气候平均态为驱动做两组全球实验。结果表明气候年际变率导致全球植被总覆盖度下降,其中树和灌木减少而草增加;全球平均覆盖度的变化按常绿树、草、灌木、落叶树顺序递减,而相对变化(即格点覆盖度差异的绝对值的全球平均值与气候平均态下植物覆盖度的比值)按灌木、草、落叶树、常绿树顺序递减。在温度、降水、风速、比湿、光照、气压等6种气候因子中降水年际变率对于植被平均分布影响最显著。受降水影响,当年降水小于1200mm时植被总覆盖度的差异随其变率增加而下降,其它时候影响不明显。年降水小于1500mm时树减少,幅度随其年际变率变大而增加。常绿树无论降水多寡均减少,而落叶树在年降水大于1500mm时随其变率变大而增加。草在年降水小于1500mm、变率为中等时差异最大,降水较大时其年际变化对草的影响不大。温度年际变率对落叶树分布影响不大而使常绿树减少,尤其是在寒带,其幅度大致随变率增加而变大。草主要在温度高于-10℃增加而灌木在温度低于0℃增加。植被总体覆盖度在温度高于0℃时受影响普遍降低,降低的区域对应于温度年际变率较大的区域。以上结果说明用气候模式或生物地理模式预测未来植物分布时要同时考虑气候平均态和气候变率两方面的变化。