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...     

区域气候模式对东亚气候时空演变特征的模拟研究

利用区域环境集成模式系统对东亚地区进行了1987年1月到1996年12月的长期积分试验,重点采用经验正交函数分析方法分析和比较模式模拟及观测气候主分量时空特征,从而考察区域气候模式对东亚地区的区域气候模拟能力.结果表明:(1) RIEMS能够较好地抓住地面气温年平均状况及其年变化和年际变率的主要特征;(2)尽管模式对降水的模拟能力没有对地面气温模拟的强,但RIEMS模式基本上能够模拟出降水的空间分布以及降水的季节变化特征,同时能够抓住降水的年际变率.       

中国南方夏季降水年际变化与高低纬环流关系的数值模拟

利用区域气候模式RegCM4.4对我国南方夏季降水和大气环流进行30 a的数值模拟,通过与降水观测对比发现,模式能够较好模拟出我国东部地区夏季平均降水和年际变率的空间分布,模拟的南方地区(30 °N以南)年际变率略偏小。观测的我国南方夏季平均降水与模拟降水相关系数为0.51。观测和模拟结果均表明,典型涝年,中纬异常反气旋前方的东北风携带干冷空气,低纬异常反气旋后方的西南风携带暖湿空气,在我国南方汇合,导致南方降水异常增多,模式具有模拟我国夏季南方降水年际变化的能力。通过边界敏感性试验,去除高纬侧边界强迫的年际变化,我国东部降水偏多,南方夏季降水年际变化强度显著变弱;去除低纬度侧边界强迫的年际变化,模拟的我国南方降水偏少,长江及以北降水偏多,降水的空间分布形态发生明显的变化,而我国南方夏季降水年际变化强度基本不变。因此,中高纬环流强迫可较大程度影响我国南方降水年际变化的强度,低纬度环流强迫异常则会改变我国东部降水空间分布形态。      

Influences of the interannual variability of vegetation LAI on surface temperature

通过两组模式的集合模拟,本论文研究了植被叶面积指数的年际变化对地表温度的影响。结果表明叶面积指数的年际变化的影响信号整体弱于大气变率的噪声。但是,就空间分布而言,热带地区的影响信号强于中高纬度地区。这主要是由于热带地区的叶面积指数通过影响地表蒸散发导致其与地表温度具有显著的线性关系。     

CMIP5模式对未来30a新疆夏季降水的预估

选用参与气候变化政府间合作委员会(IPCC)第5次评估报告的25个气候耦合模式(CMIP5),基于GPCP(Global Precipitation Climatology Project)降水资料,采用多种统计方法,综合评估模式历史试验对1979—2005年新疆夏季降水的模拟能力,优选出模拟性能较好的模式,进而利用其RCP8.5排放路径下的模拟结果来预估未来30 a(2021—2050年)新疆夏季降水的变化。从气候平均场和年际变率来看,25个CMIP5模式的模拟性能差异显著,部分模式可模拟出新疆夏季降水的主要空间分布特征,如伊犁河谷地区的降水中心以及南疆和东疆地区的少雨区。从优选出的9个模式的集合平均结果来看,对南疆西部山区与昆仑山北侧地区降水强度和范围模拟偏强,对年际变率的模拟偏弱,但其降水的空间分布与观测比较一致,可较准确地捕捉到高、低值中心,空间相关性也较好。因此,利用该集合平均结果对未来新疆降水进行预估是可信的。预估结果表明:(1)未来30 a北疆大部分地区和东疆部分地区夏季降水略微减少,伊犁河谷和南疆大部分地区显著增多,且增幅中心出现在南疆西部和昆仑山北侧地区;(2)山区年际变率较其他地区明显,且伊犁河谷、南疆西部和昆仑山北侧地区的年际变率呈现逐渐增大趋势;(3)降水变化与500 hPa环流配置异常密切相关,北疆地区偏南气流加强,表现为反气旋性环流,南疆地区偏东气流加强,表现为气旋性环流,因而导致未来新疆地区夏季降水南增北减。     

土壤湿度年际异常对中国春、夏季气候模拟的影响

基于NCAR大气模式CAM3.1模式,设计了有、无土壤湿度年际异常两组试验对中国区域近40a(1961-2000年)气候进行了模拟。从气候态和年际变率的角度,通过分析两组试验的差值场来探讨土壤湿度年际异常对气候模拟的影响,并初步探讨了影响的可能机制。结果表明:模式模拟的温度和降水对土壤湿度的年际异常非常敏感,土壤湿度的年际变化对中国春夏季气候及其年际变率均有显著影响。当不考虑土壤湿度年际异常时,模式模拟的春夏季平均温度、最高温度、最低温度在我国大范围内降低,春夏季降水在东部大部分地区明显减少,西部增加。而模式模拟的春夏季温度、降水年际变率在中国大部分地区减弱。但当考虑土壤湿度的年际变化,则能在一定程度上提高模式对气候年际变率的模拟能力。在进一步分析表明土壤湿度年际异常时,主要通过改变地表能量通量和环流场,对温度、降水产生影响。当不考虑土壤湿度年际异常时,地表净辐射通量减少,地表温度降低,感热通量减少。感热通量差值场的空间变化和温度差值场的空间变化一致,感热通量对温度有一定影响。而潜热通量差值场的空间变化和降水的差值场的空间变化一致,可见降水受地表潜热通量的影响。土壤湿度年际异常引起的环流场的变化也是导致气候变化的原因之一,地表能量和环流场年际变率的改变对春夏季气候年际变率存在一定影响。     

1981-2008年中国陆地植被NPP对气候变化响应的敏感性试验

在验证CENTURY模型对中国陆地植被净初级生产力(Net Primary Productivity,NPP)模拟能力的基础上,利用该模型探讨了1981-2008年中国陆地植被NPP的年际变异和变化趋势对CO₂浓度、温度和降水变化的响应。结果表明,中国陆地植被NPP对不同气候因子的响应程度存在明显不同。其中,CO₂浓度变化对植被NPP年际变异的影响不显著,但能够引起中国大部分地区植被NPP趋势系数增大;温度对中国中高纬度地区植被NPP的年际变化影响显著,但就全国范围而言,植被NPP年际变异对温度变化的响应程度总体低于对降水变化的响应程度;降水变化是对中国植被NPP变化趋势起主导作用的气候因子。此外,综合考虑温度和降水变化的影响发现,植被NPP变化趋势的响应特征类似于降水单独变化时植被NPP变化趋势的响应特征。     

RIEMS2.0模式提高分辨率对中国气温模拟能力的影响

利用区域环境集成系统模式(RIEMS2.0)在60 km和30 km两种分辨率下进行中国区域的长期模拟试验(1991~2000年),开展不同分辨率下中国气温平均气候态和年际变率的模拟能力分析研究。结果表明:(1)RIEMS2.0能较好模拟出多数分区多年平均气温的空间分布,与观测空间分布较接近。随着水平分辨率的提高,模式模拟的气温空间分布模拟更精细,使得平均气温的模拟冷偏差减小,模拟结果更趋于实测。对年均温和冬季气温来说,中国及多数分区模拟与观测的偏差减少,且通过显著性检验(P0.01);对夏季气温来说,中国及多数分区的偏差增加,气温的模拟能力没有明显提高。(2)对年际变率来说,随着水平分辨率的提高,大部分区域模拟能力有一定程度的提高。特别是年均温和冬季气温的年际变率,多数地区模拟改进效果较好;而夏季气温年际变率的模拟在中国大部分地区没有明显改善。     

土壤湿度年际变化对中国区域极端气候事件模拟的影响研究Ⅱ.敏感性试验分析

利用NCARCAM3.1大气环流模式,设计了有、无土壤湿度年际异常的两组数值试验,探讨了土壤湿度年际异常对极端气候事件模拟的可能影响。结果表明,模式模拟的极端气候事件对土壤湿度异常十分敏感,土壤湿度异常对极端气候指标的多年平均空间分布、年际变率以及年际变化均具有重要影响。当不考虑土壤湿度的年际异常时:(1)模拟的暖夜日数、暖昼日数和热浪持续指数的发生频次在全国范围内均明显减少,而霜冻日数则明显增加。极端降水指标的响应表现出明显的空间差异,极端降水频次在江淮流域明显减小,而极端降水强度则表现为东北减弱、长江流域增强;中雨日数和持续湿期在我国大部分地区减少。(2)极端气温指标的年际变率在我国大部分地区呈减小趋势;而极端降水事件的变化则较为复杂,极端降水频次和极端降水强度的年际变率在长江以南有所增强,而北方地区则有所减弱。中雨日数和持续湿期的年际变率在我国呈现出较为一致的减少趋势。(3)模式对暖夜日数、霜冻日数的年际变化的模拟能力明显下降,并对4个极端降水指标的年际变化的模拟能力在全国多数区域均有不同程度的下降。     

RSM模式对中国东部夏季降水模拟能力的检验

本文利用美国国家环境预报中心NCEP(National Centers for Environmental Prediction)区域谱模式RSM(Regional Spectral Model)对中国东部地区夏季降水进行了为期20 a(1984—2003年)、水平分辨率为30 km的高精度模拟,并对模拟所得降水的气候态、年际变率、逐日变化以及极端事件进行了检验,和对造成降水偏差的大气环流特征进行了分析。结果表明RSM模拟所得夏季降水的空间分布、时间变率,以及降水量值都与实况相近,也基本可以再现夏季降水的年际变率分布情况,但是模拟所得的雨带存在偏南且偏弱的特点。对于逐日降水特征,RSM模拟所得季节内逐日降水变化与实况的走势基本一致,再现了夏季降水主要集中于东部和南部的特点,模拟出了江淮地区6月日降水区随时间北抬的特点。对于极端事件,模拟和实测的夏季不同雨强的天数分布对比表明模拟与实况基本接近,但是模拟的降水日大值中心较实况偏北;极端降水指数的计算结果也表明RSM模拟的极端降水情况与实况基本一致。综上,RSM模式对中国东部地区降水有着较好的模拟能力,可以用于中国东部地区的夏季降水气候特征研究。     

动态冠层模型ICM的改进及其对中高纬地区植被季节和年际变化的模拟试验

植被动态冠层模型Interactive Canopy Model(ICM)考虑了生态系统中较完整的碳氮循环过程,能够较为客观真实地描述较短时间尺度上植被的动态变化特征.本文在ICM原有碳氮分配方案基础上,考虑了植物花、果实等新生组织对碳氮分配的影响,假设新生组织碳库是花期以后植物的主要碳汇之一,并利用物候模型Fore-...     

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.     

The interactive climate and vegetation along the Pole-Equator belts simulated by a global coupled model

The interaction between climate and vegetation along four Pole-Equator-Pole （PEP） belts were explored using a global two-way coupled model, AVIM-GOALS, which links the ecophysiological processes at the land surface with the general circulation model （GCM）. The PEP belts are important in linking the climate change with the variation of sea and land, including terrestrial ecosystems. Previous PEP belts studies have mainly focused on the paleoclimate variation and its reconstruction. This study analyzes and discusses the interaction between modern climate and vegetation represented by leaf area index （LAI） and net primary production （NPP）. The results show that the simulated LAI variation, corresponding to the observed LAI variation, agrees with the peak-valley variation of precipitation in these belts. The annual mean NPP simulated by the coupled model is also consistent with PIK NPP data in its overall variation trend along the four belts, which is a good example to promote global ecological studies by coupling the climate and vegetation models. A large discrepancy between the simulated and estimated LAI emerges to the south of 15°N along PEP 3 and to the south of 18°S in PEP 1S, and the discrepancy for the simulated NPP and PIK data in the two regions is relatively smaller in contrast to the LAI difference. Precipitation is a key factor affecting vegetation variation, and the overall trend of LAI and NPP corresponds more obviously to precipitation variation than temperature change along most parts of these PEP belts.     

Numerical simulation of the impact of vegetation index on the interannual variation of summer precipitation in the Yellow River Basin

Two sets of numerical experiments using the coupled National Center for Environmental Prediction General Circulation Model （NCEP/GCM T42L18） and the Simplified Simple Biosphere land surface scheme （SSiB） were carried out to investigate the climate impacts of fractional vegetation cover （FVC） and leaf area index （LAI） on East Asia summer precipitation, especially in the Yellow River Basin （YRB）. One set employed prescribed FVC and LAI which have no interannual variations based on the climatology of vegetation distribution; the other with FVC and LAI derived from satellite observations of the International Satellite Land Surface Climate Project （ISLSCP） for 1987 and 1988. The simulations of the two experiments were compared to study the influence of FVC, LAI on summer precipitation interannual variation in the YRB. Compared with observations and the NCEP reanalysis data, the experiment that included both the effects of satellite-derived vegetation indexes and sea surface temperature （SST） produced better seasonal and interannual precipitation variations than the experiment with SST but no interannual variations in FVC and LAI, indicating that better representations of the vegetation index and its interannual variation may be important for climate prediction. The difference between 1987 and 1988 indicated that with the increase of FVC and LAI, especially around the YRB, surface albedo decreased, net surface radiation increased, and consequently local evaporation and precipitation intensified. Further more, surface sensible heat flux, surface temperature and its diurnal variation decreased around the YRB in response to more vegetation. The decrease of surface-emitting longwave radiation due to the cooler surface outweighed the decrease of surface solar radiation income with more cloud coverage, thus maintaining the positive anomaly of net surface radiation. Further study indicated that moisture flux variations associated with changes in the general circulation also contributed to the precipitation interannual variation.     

Evaluation of the WRF Model with Different Land Surface Schemes： A Drought Event Simulation in Southwest China during 2009–10

The authors examined the performance of version 3.4.1 of the Weather Research and Forecasting Model（WRF） with various land surface schemes in simulating a severe drought event in Southwest China. Five numerical experiments were completed using the Noah land surface scheme, the Pleim-Xiu land surface scheme, the Noah-MP land surface schemes, the Noah- MP scheme with dynamic vegetation, and the Noah-MP scheme with dynamic vegetation and groundwater processes. In general, all the simulations reasonably reproduced the spatial and temporal variations in precipitation, but significant bias was also found, especially for the spatial pattern of simulated precipitation. The WRF simulations with the Noah-MP series land surface schemes performed slightly better than the WRF simulation with the Noah and Pleim-Xiu land surface schemes in reproducing the severe drought events in Southwest China. The leaf area index（LAI） simulated by the different land surface schemes showed significant deviations in Southwest China. The Pleim-Xiu scheme overestimated the value of LAI by a factor of two. The Noah-MP scheme with dynamical vegetation overestimated the magnitude of the annual cycle of the LAI, although the annual mean LAI was close to observations. The simulated LAI showed a long-term lower value from autumn 2009 to spring 2010 relative to normal years. This indicates that the LAI is a potential indictor to monitor drought events.     

北方玉米冠层光合有效辐射垂直分布及影响因子分析

玉米冠层内光合有效辐射（PAR）的大小直接影响冠层内叶片的光合作用,进而影响玉米净第一性生产力或作物产量的准确评估。为弄清玉米冠层内光合有效辐射的分布规律及其影响因子,基于锦州玉米农田生态系统于2006年生育期的光合有效辐射观测数据和叶面积指数动态观测数据,对玉米冠层光合有效辐射的垂直分布特征及其影响因子进行了分析。结果表明：玉米冠层内不同垂直层次叶片的PAR分布随生育期变化显著,与叶面积指数呈显著的负相关（R2=0.89）;玉米冠层光合有效辐射的消光系数K值在生育期呈动态变化,约为0.76,且表现为苗期较大、生育后期较小。分析表明,在进行光合有效辐射及与此密切相关的光合作用模拟时,应考虑消光系数的动态变化。     

The Impacts of the Interannual Variability of Vegetation on the Interannual Variability of Global Evapotranspiration: A Modeling Study

The impact of the interannual variability (IAV) of vegetation on the IAV of evapotranspiration is investigated with the Community Land Model (CLM3.0) and modified Dynamic Global Vegetation Model (DGVM). Two sets of 50-year off-line simulations are used in this study. The simulations begin with the same initial surface-water and heat states and are driven by the same atmospheric forcing data. The vegetation exhibits interannual variability in one simulation but not in the other simulation. However, the climatological means for the vegetation are the same. The IAV of the 50-year annual total evapotranspiration and its three partitions (ground evaporation, canopy evaporation, and transpiration) are analyzed. The global distribution of the evapotranspiration IAV and the statistics of evapotranspiration and its components in different ecosystems show that the IAV of ground evaporation is generally large in areas dominated by grass and deciduous trees, whereas the IAV of canopy evaporation and transpiration is large in areas dominated by bare soil and shrubs. For ground evaporation, canopy evaporation, and transpiration, the changes in IAV are larger than the mean state over most grasslands and shrublands. The study of two sites with the same IAV in the leaf area index (LAI) shows that the component with the smaller contribution to the total evapotranspiration is more sensitive to the IAV of vegetation. The IAV of the three components of evapotranspiration increases with the IAV of the fractional coverage (FC) and the LAI. The ground evaporation IAV shows the greatest increase, whereas the canopy evaporation shows the smallest increase.     

An Introduction to the Integrated Climate Model of the Center for Monsoon System Research and its simulated influence of El Niño on East Asian-western North Pacific climate

This study introduces a new global climate model--the Integrated Climate Model （ICM）--developed for the seasonal prediction of East Asian-western North Pacific （EA-WNP） climate by the Center for Monsoon System Research at the Institute of Atmospheric Physics （CMSR, IAP）, Chinese Academy of Sciences. ICM integrates ECHAM5 and NEMO2.3 as its atmospheric and oceanic components, respectively, using OASIS3 as the coupler. The simulation skill of ICM is evaluated here, including the simulated climatology, interannual variation, and the influence of E1 Nifio as one of the most important factors on EA-WNP climate. ICM successfully reproduces the distribution of sea surface temperature （SST） and precipitation without climate shift, the seasonal cycle of equatorial Pacific SST, and the precipitation and circulation of East Asian summer monsoon. The most prominent biases of ICM are the excessive cold tongue and unrealistic westward phase propagation of equatorial Pacific SST. The main interannual variation of the tropical Pacific SST and EA-WNP climate E1 Nifio and the East Asia-Pacific Pattern--are also well simulated in ICM, with realistic spatial pattern and period. The simulated E1 Nifio has significant impact on EA-WNP climate, as in other models. The assessment shows ICM should be a reliable model for the seasonal prediction of EA-WNP climate.     

Comparison of the Influence of Interannual Vegetation Variability between Offline and Online Simulations

This study investigates the influence of interannual vegetation variability. Two sets of offline and online simulations were performed using the Community Earth System Model. The interannual Global LAnd Surface Satellite （GLASS） leaf area index （LAI） dataset from 1985 to 2000 and its associated climatological LAI were used to replace the default climatological LAI data in version 4 of the Community Land Model （CLM4）. The re- sults showed that on a global scale, canopy transpiration and evaporation, as well as total evapotranspiration in offline simulations were significantly positively corre- lated with LAI, whereas ground evaporation and ground temperature showed significant negative correlation with LAI. However, the correlations in online simulations were reduced markedly because of interactive feedbacks between albedo, changed climatic factors and atmospheric variability. In the offline simulations, the fluctuations of differences in interannual variability of evapotranspiration and ground temperature focused on vegetation growing regions and the magnitudes were smaller. Those in online simulations spread over more regions and the magnitudes were larger. These results highlight the influence of interannual vegetation variability, particularly in online simulations, an effect that deserves consideration and attention when investigating the uncertainty of climate change.