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影响青藏高原植被生理过程与大气CO2浓度及气候变化的相互作用 总被引：11，自引：0，他引：11
利用一陆面过程模式,初步模拟研究了青藏高原夏季风盛行期植被生理过程与大气CO2浓度及气候变化的相互作用。结果表明,气候以及大气CO2浓度变化对青藏高原地区的植被生理过程有较明显的影响,高温、高温和高CO2浓度将加强高原植被的光合作用和呼吸作用,有利于植被生长。高原植被也可通过生理过程,产生净CO2呼收,降低大气CO2含量,起到调整温室效应的作用,从而影响全球气候变化;当气温升高、大气CO2增加时,这种作用更加有效。青藏高原地区大气CO2浓度加倍,对高原地区气候的直接影响不明显。植被的存在也会影响区域气候变化,并可通过改变高原热源,进而影响高原及其周边地区气候变化。文中还归纳出了植被生理与气候相互作用的简单概念模型。 相似文献
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影响青藏高原植被生理过程与大气C02浓度及气候变化的相互作用 总被引：4，自引：0，他引：4
利用一陆面过程模式,初步模拟研究了青藏高原夏季风盛行期植被生理过程与大气CO2浓度及气候变化的相互作用.结果表明,气候以及大气CO2浓度变化对青藏高原地区的植被生理过程有较明显的影响,高温、高湿和高CO2浓度将加强高原植被的光合作用和呼吸作用,有利于植被生长.高原植被也可通过生理过程,产生净C02吸收,降低大气C02含量,起到调整温室效应的作用,从而影响全球气候变化;当气温升高、大气C02增加时,这种作用更加有效.青藏高原地区大气C02浓度加倍,对高原地区气候的直接影响不明显.植被的存在也会影响区域气候变化,并可通过改变高原热源,进而影响高原及其周边地区气候变化.文中还归纳出了植被生理与气候相互作用的简单概念模型. 相似文献
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利用动态植被模型CLM4-CNDV、区域气候模式RegCM4.6-CLM3.5和全球气候模式CAM4探究了当前气候状态下东亚区域可能的自然植被分布以及自然植被恢复对东亚区域气候产生的可能影响。结果表明,当前气候条件下,农作物区可能分布的自然植被为:蒙古高原以北、东北、华北平原和四川盆地的部分地区为裸土;东亚东南部及蒙古高原以北地区主要为林地;四川盆地及山东半岛主要为灌木;东北地区、东南沿海和长江中下游地区主要为草地。将农作物区恢复为自然植被后将对区域气候产生显著影响。其中,东亚东部大部分地区由于植被叶面积指数增加引起的蒸散发增强,使得夏季降水增加且温度降低显著;华北、四川盆地和广东中部平原地区植被叶面积指数减小,伴随区域内夏季降水显著减少且温度升高。而蒙古高原地区的气候变化不仅受区域内植被覆盖变化影响,还可能与印度地区和我国东南部植被变化引起的大气环流调整有关,使得蒙古高原西部冬季温度降低,而其东部夏季温度升高,同时夏季降水减少显著。研究所采用的试验方案是在相对理想的情况下进行的,但其结果为进一步区分不同地区植被覆盖变化的影响提供一定的参考。 相似文献
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中国近代土地利用变化对区域气候影响的数值模拟 总被引：26，自引：1，他引：26
利用国家气候中心改进的高分辨率区域气候模式(RegCM-NCC)模拟研究了中国近代历史时期土地利用/覆盖变化对中国区域气候的影响,模拟结果显示,1700年以来,以森林砍伐、草地退化及相应耕地面积扩大为主的土地利用变化可能对中国区域降水、温度产生了显著影响。1700—1900年期间,由于土地利用的变化使华北、西南等地区降水呈减少趋势,其他区域变化不明显,但近50年来却使长江中下游地区、西北、东北部分地区降水有所增加。1700—1800年间的土地利用变化使得除东北及长江流域地区外的大部分地区温度呈下降趋势,1900年以后有所升高,特别是近50年来中国大部分区域平均气温升高,与这一时期由于大气中温室气体排放浓度增加造成的温度升高相一致。另外,土地利用变化不仅使大气温度、湿度发生变化,还可引起基本流场的变化,使东亚冬、夏季风气流有所增强,这主要是由于植被变化改变了地面温度,使海、陆温差进一步增大的结果。因此,土地利用变化对区域尺度气候变化的影响是不容忽视的。 相似文献
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植被变化对中国区域气候影响的数值模拟研究 总被引：44，自引：5，他引：39
用高分辨率区域气候模式(RegCM-NCC)模拟了中国区域植被发生改变后引起的局地或区域气候变化。结果表明:大范围区域植被变化对区域降水、温度的影响非常显著,内蒙古地区土地荒漠化可导致中国北方大部分地区降水减少,尤其加剧了华北、西北地区的干旱,西北地区绿化有利于黄河流域降水增加,而长江流域和江南地区降水却有不同程度的减少,因此可在一定程度上减少这里的洪涝灾害;气温的变化比降水更显著,植被退化使当地气温明显升高,使中、低层大气变得干燥,近地层风速加大,而植树造林却使当地及周围地区冬偏暖、夏偏凉,大气变得湿润,近地层风速减小,有利于在一定程度上减少沙尘暴的发生。另外,植被变化对东亚冬、夏季风强度也有一定程度的影响,从而影响到中国东部地区降水的分布和冬季低温、冷害事件发生的强度。 相似文献
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利用中国1961-2013年661个气象台站观测资料以及亚洲夏季风指数,通过旋转正交分析（REOF）等方法,选择华北河套干旱气候区的代表站,分析了该区域气候干燥度的变化特征,发现该地区整体呈现干旱化趋势。在此基础上讨论了夏季风与气象因子对气候干燥度的影响,结果表明,南亚西区夏季风的年际及整体减弱趋势对华北河套地区气候干燥度的年际趋势变化影响最为显著,主要影响期在20世纪90年代之前,随着区域气候变暖,这种影响程度减弱。各气象要素对气候干燥度的影响存在年际与年代际差异,热力因子的年际变化对干燥度影响较小,而热力因子的年代际变化在20世纪90年代之后对干燥度的影响十分显著。这说明区域气候长期变暖导致当地水汽压差增大,相对湿度减小,空气需要更多的水分才能达到饱和,同时增大了潜在蒸发能力,加剧了华北河套气候区的干旱化。 相似文献
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利用1971—2006年环杭州湾地区25个气象站的降水、温度和云量资料及全球CO2年平均体积分数资料,采用LPJ全球动态植被模式（Lund-Potsdam-Jena Dynamic Global Vegetation Model）,通过模拟环杭州湾地区的植被年净初级生产力（Annual Net Primary Productivity,ANPP）,分析了该地区ANPP的变化特征,并探讨了植被ANPP变化的可能原因。结果表明：1）就环杭州湾地区,36a间植被ANPP均表现出不同程度的增加,尤其以嘉兴市北部、绍兴市东部较明显;全区平均增加速率为1.5243g·m-2·a-2;2）通过多元线性回归分析发现,环杭州湾地区平均云量与植被ANPP的关系最为密切,偏相关系数为-0.5175,而温度、降水与植被ANPP的关系不明显;同时,植被ANPP对气候变化的响应存在一定的地域性差异;3）在全区平均情况下,36a间由温度下降、降水增加、云量减小、CO2体积分数升高引起的植被ANPP变化趋势分别为-0.0813、-0.0171、0.7601、0.8673g·m-2·a-2,其对应的贡献率分别为-5.18%、-1.09%、48.38%、55.21%。由此可见,该地区植被ANPP变化的主要强迫因子是CO2体积分数和云量,而降水变化对植被ANNP的变化作用不大。 相似文献
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中国农田下垫面变化对气候影响的模拟研究 总被引：1，自引：0，他引：1
使用同期的美国国家环境预报中心/能源部(NCEP/DOE)再分析资料驱动区域气候耦合模式AVIM-RIEMS2.0,从遥感卫星图像资料中获取3期中国土地利用/覆盖数据中的农田植被类型,将其分别引入到AVIM-RIEMS2.0模式进行积分,研究中国农田下垫面变化对东亚区域气候的影响。结果表明:中国农田变化对气候影响具有冬季弱、夏季强的季节性变化,夏季气温和降水的差异在一些地区通过了95%的显著性检验;20世纪80年代农田扩张,林地、草地为主的植被类型转化为农田,植被变化区域的叶面积指数降低,反照率升高,且通过了95%的显著性检验,使得中国东部地区的气温由南到北呈现增加—减少—增加—减少的相间变化趋势,而降水的变化趋势大体相反;20世纪90年代农田面积减少,除东北地区外,农田变化引起的植被变化与80年代基本相反,叶面积指数变化、反照率以及由此导致的气候各要素也呈现大体相反的变化趋势;不同时期农田变化引起的植被类型转化的差异,使850 hPa风场变化趋势基本相反,可能是导致气温和降水变化趋势差异的主要原因之一。 相似文献
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This study examines the role of vegetation dynamics in regional predictions of future climate change in western Africa using
a dynamic vegetation model asynchronously coupled to a regional climate model. Two experiments, one for present day and one
for future, are conducted with the linked regional climate-vegetation model, and the third with the regional climate model
standing alone that predicts future climate based on present-day vegetation. These simulations are so designed in order to
tease out the impact of structural vegetation feedback on simulated climate and hydrological processes. According to future
predictions by the regional climate-vegetation model, increase in LAI is widespread, with significant shift in vegetation
type. Over the Guinean Coast in 2084–2093, evergreen tree coverage decreases by 49% compared to 1984–1993, while drought deciduous
tree coverage increases by 56%. Over the Sahel region in the same period, grass cover increases by 31%. Such vegetation changes
are accompanied by a decrease of JJA rainfall by 2% over the Guinean Coast and an increase by 23% over the Sahel. This rather
small decrease or large increase of precipitation is largely attributable to the role of vegetation feedback. Without the
feedback effect from vegetation, the regional climate model would have predicted a 5% decrease of JJA rainfall in both the
Guinean Coast and the Sahel as a result of the radiative and physiological effects of higher atmospheric CO2 concentration. These results demonstrate that climate- and CO2-induced changes in vegetation structure modify hydrological processes and climate at magnitudes comparable to or even higher
than the radiative and physiological effects, thus evincing the importance of including vegetation feedback in future climate
predictions. 相似文献
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This study aims at exploring potential impacts of land-use vegetation change (LUC) on regional climate variability and extremes. Results from a pair of Australian Bureau of Meteorology Research Centre (BMRC) climate model 54-yr (1949-2002) integrations have been analysed. In the model experiments, two vegetation datasets are used, with one representing current vegetation coverage in China and the other approximating its potential coverage without human intervention. The model results show potential impacts ... 相似文献
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Holger Göttel Jörn Alexander Elke Keup-Thiel Diana Rechid Stefan Hagemann Tanja Blome Annett Wolf Daniela Jacob 《Climatic change》2008,87(1-2):35-50
In the context of the EU-Project BALANCE () the regional climate model REMO was used for extensive calculations of the Barents Sea climate to investigate the vulnerability
of this region to climate change. The regional climate model REMO simulated the climate change of the Barents Sea Region between
1961 and 2100 (Control and Climate Change run, CCC-Run). REMO on ~50 km horizontal resolution was driven by the transient
ECHAM4/OPYC3 IPCC SRES B2 scenario. The output of the CCC-Run was applied to drive the dynamic vegetation model LPJ-GUESS.
The results of the vegetation model were used to repeat the CCC-Run with dynamic vegetation fields. The feedback effect of
the modified vegetation on the climate change signal is investigated and discussed with focus on precipitation, temperature
and snow cover. The effect of the offline coupled vegetation feedback run is much lower than the greenhouse gas effect. 相似文献
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Martin Schmidt Doris Klein Christopher Conrad Stefan Dech Heiko Paeth 《Theoretical and Applied Climatology》2014,115(1-2):341-353
Vegetation cover is a crucial component of the Earth’s climate system but, still, our understanding of the mechanisms governing the reciprocal influence between atmosphere and vegetation is limited. In this study, we investigate the unilateral atmospheric impact on vegetation cover in tropical and northern Africa, differentiated into regions with different circulation regimes and into detailed land-cover classes. In contrast to former studies, climate predictors from a regional climate model are used as input for a multiple regression model. Climate models provide consistent data without gaps at high spatial resolution, a considerably larger set of available climate variables and the perspective to transfer the statistical relationships to future projections, e.g., in the context of anthropogenic climate change. Indeed, robust climate predictors which drive up to 70 % of observed interannual vegetation variability could be extracted from the climate model. Besides precipitation and temperature, global radiation, and relative humidity play an important role. The statistical transfer functions are plausible in terms of the affected regions and land-cover classes and draw a rather complex picture of the atmosphere–vegetation relation in Africa. 相似文献
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Modeling Dynamic Vegetation Response to Rapid Climate Change Using Bioclimatic Classification 总被引：2，自引：0，他引：2
Modeling potential global redistribution of terrestrial vegetation frequently is based on bioclimatic classifications which relate static regional vegetation zones (biomes) to a set of static climate parameters. The equilibrium character of the relationships limits our confidence in their application to scenarios of rapidly changing climate. Such assessments could be improved if vegetation migration and succession would be incorporated as response variables in model simulations. We developed the model MOVE (Migration Of VEgetation), to simulate the geographical implications of different rates of plant extirpation and in-migration. We used the model to study the potential impact on terrestrial carbon stocks of climate shifts hypothesized from a doubling of atmospheric greenhouse gas concentration. The model indicates that the terrestrial vegetation and soil could release carbon; the amount of this carbon pulse depends on the rate of migration relative to the rate of climate change. New temperate and boreal biomes, not found on the landscape today, increase rapidly in area during the first 100 years of simulated response to climate change. Their presence for several centuries and their gradual disappearance after the climate ceases to change adds uncertainty in calculating future terrestrial carbon fluxes. 相似文献
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Influence of dynamic vegetation on climate change arising from increasing CO<Subscript>2</Subscript>
A dynamic global vegetation model (DGVM) is coupled to an atmospheric general circulation model (AGCM) to investigate the
influence of vegetation dynamics on climate change under conditions of global warming. The model results are largely in agreement
with observations and the results of previous studies in terms of the present climate, present potential vegetation, present
net primary productivity (NPP), and pre-industrial carbon budgets. The equilibrium state of climate properties are compared
among pre-industrial, doubled, and quadrupled atmospheric CO2 values using DGVM–AGCM and current AGCM with fixed vegetation to evaluate the influence of dynamic vegetation change. We
also separated the contributions of temperature, precipitation and CO2 fertilization on vegetation change. The results reveal an amplification of global warming climate sensitivity by 10% due
to the inclusion of dynamic vegetation. The total effects of elevated CO2 and climate change also lead to an increase in NPP and vegetation coverage globally. The reduction of albedo associated with
this greening results in enhanced global warming. Our separation analysis indicates that temperature alters vegetation at
high latitudes such as Siberia or Alaska, where there is a switch from tundra to forest. On the other hand, CO2 fertilization provides the largest contribution to greening in arid/semi-arid region. Precipitation change did not cause
any drastic vegetation shift. 相似文献
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Responses of vegetation distribution to climate change in China 总被引：1，自引：1，他引：0
Climate plays a crucial role in controlling vegetation distribution and climate change may therefore cause extended changes. A coupled biogeography and biogeochemistry model called BIOME4 was modified by redefining the bioclimatic limits of key plant function types on the basis of the regional vegetation–climate relationships in China. Compared to existing natural vegetation distribution, BIOME4 is proven more reliable in simulating the overall vegetation distribution in China. Possible changes in vegetation distribution were simulated under climate change scenarios by using the improved model. Simulation results suggest that regional climate change would result in dramatic changes in vegetation distribution. Climate change may increase the areas covered by tropical forests, warm-temperate forests, savannahs/dry woodlands and grasslands/dry shrublands, but decrease the areas occupied by temperate forests, boreal forests, deserts, dry tundra and tundra across China. Most vegetation in east China, specifically the boreal forests and the tropical forests, may shift their boundaries northwards. The tundra and dry tundra on the Tibetan Plateau may be progressively confined to higher elevation. 相似文献