气候变化情景下中国自然生态系统脆弱性研究——一个基于生态地理区域的研究(英文)

Assessment of vulnerability for natural ecosystem to climate change is a hot topic in climate change and ecology, and will support adapting and mitigating climate change. In this study, LPJ model modified according to features of China's natural ecosystems was employed to simulate ecosystem dynamics under A2, B2 and A1B scenarios. Vulnerability of natural ecosystem to climate change was assessed according to the vulnerability assessment model. Based on eco-geographical regions, vulnerability of natural ecosystem to climate change was analyzed. Results suggest that vulnerability for China's natural ecosystems would strengthen in the east and weaken in the west, but the pattern of ecosystem vulnerability would not be altered by climate change, which rises from southeast to northeast gradually. Increase in ecosystem vulnerable degree would mainly concentrate in temperate humid/sub-humid region and warm temperate humid/sub-humid region. Decrease in ecosystem vulnerable degree may emerge in northwestern arid region and Qinghai-Tibet Plateau region. In the near-term scale, natural ecosystem in China would be slightly affected by climate change. However, in mid-term and long-term scales, there would be severely adverse effect, particularly in the east with better water and thermal condition.     

Vulnerability of natural ecosystem in China under regional climate scenarios：An analysis based on eco-geographical regions

Assessment of vulnerability for natural ecosystem to climate change is a hot topic in climate change and ecology,and will support adapting and mitigating climate change. In this study,LPJ model modified according to features of China's natural ecosystems was employed to simulate ecosystem dynamics under A2,B2 and A1B scenarios. Vulnerability of natural ecosystem to climate change was assessed according to the vulnerability assessment model. Based on eco-geographical regions,vulnerability of natural ecosystem to climate change was analyzed. Results suggest that vulnerability for China's natural ecosystems would strengthen in the east and weaken in the west,but the pattern of ecosystem vulnerability would not be altered by climate change,which rises from southeast to northeast gradually. Increase in ecosystem vulnerable degree would mainly concentrate in temperate humid/sub-humid region and warm temperate humid/sub-humid region. Decrease in ecosystem vulnerable degree may emerge in northwestern arid region and Qinghai-Tibet Plateau region. In the near-term scale,natural ecosystem in China would be slightly affected by climate change. However,in mid-term and long-term scales,there would be severely adverse effect,particularly in the east with better water and thermal condition.     

Uncertainty of Climate Response to Natural and Anthropogenic Forcings Due to Different Land Use Scenarios

The A.M.Obukhov Institute of Atmospheric Physics,Russian Academy of Sciences (IAP RAS) climate model (CM) of intermediate complexity is extended by a spatially explicit terrestrial carbon cycle module.Numerical experiments with the IAP RAS CM are performed forced by the reconstructions of anthropogenic and natural forcings for the 16th to the 20th centuries and by combined SRES (Special Report on Emission Scenarios) A2-LUH (Land Use Harmonization) anthropogenic scenarios for the 21st century.Hereby,the impact of uncertainty in land-use scenarios on results of simulations with a coupled climate-carbon cycle model is tested.The simulations of the model realistically reproduced historical changes in carbon cycle characteristics.In the IAP RAS CM,climate warming reproduced in the 20th and 21st centuries enhanced terrestrial net primary production but terrestrial carbon uptake was suppressed due to an overcompensating increase in soil respiration.Around year 2100,the simulations the model forced by different land use scenarios diverged markedly,by about 70 Pg (C) in terms of biomass and soil carbon stock but they differed only by about 10 ppmv in terms of atmospheric carbon dioxide content.     

Development of flood exposure in the Netherlands during the 20th and 21st century

Flood risks of deltaic areas increase because of population growth, economic development, land subsidence and climatic changes such as sea-level rise. In this study, we analyze trends in flood exposure by combining spatially explicit historical, present, and future land-use data with detailed information on the maximum flood inundation in the Netherlands. We show that the total amount of urban area that can potentially become inundated due to floods from the sea or main rivers has increased six-fold during the 20th century, and may double again during the 21st century. Moreover, these developments took, and probably will take, place in areas with progressively higher potential inundation depths. Potential flood damage has increased exponentially over the 20th century (16 times) and is expected to continue to increase exponentially (∼ten-fold by 2100 with respect to 2000) assuming a high economic growth scenario. Flood damages increase more moderately (two- to three-fold by 2100 with respect to 2000) assuming a low growth scenario. The capacity to deal with catastrophic flood losses - expressed as the ratio damage/GDP - will, however, decrease slightly in the low growth scenario (by about 20%). This trend deviates from the historical trend of the 20th century, which shows an increasing capacity to cope with flood damage (almost doubling). Under the high growth scenario the capacity to deal with such losses eventually increases slightly (by about 25%). These findings illustrate that, despite higher projections of potential flood damage, high economic growth scenarios may not necessarily be worse than low growth scenarios in terms of the impact of floods.     

西南地区持续性气候事件的未来变化预估

利用RegCM4.0区域气候模式单向嵌套BCC_CSM1.1模式输出资料进行连续积分获得的模拟预估数据,对西南地区未来2025-2055年在两种温室气体排放情景下持续性干期和持续湿期事件的特征及其相对于历史基准期的变化进行了预估分析。结果表明,最长持续干期和湿期在RCP4.5和RCP8.5两种情景下的变化趋势不一致,RCP8.5情景下的最长湿期和持续湿期事件的发生频次相较RCP4.5并没有大幅增加,而是比RCP4.5情景具有更高的年际变率特征。相对于历史基准期,两种情景下的最长持续性气候事件的日数和发生频次在西南地区的东南部区域显著性增加,而在川西高原地区显著减少。对于持续干期发生的频次FCDD和最长持续湿期而言,四川中部以及四川、云南和贵州三省邻接处在RCP4.5情景下表现为显著增加的区域在RCP8.5情景下转变为显著减少。未来几十年西南地区持续性湿期和干期的分布特征可能更加趋于不均匀。     

中国气温未来情景的降尺度模拟

由于GCM模拟的气温数据分辨率不高,很难用于区域尺度上各种生态系统的模拟。本文基于长时间序列（1964～2007年）的全国气温观测数据,结合经纬度数据、以及DEM、坡向、坡度等系列地形特征数据,利用空间统计方法,在构建年平均气温降尺度模型的基础上,运用高精度曲面建模（HASM）方法对HadCM3的A1Fi、A2a和B2...     

金苞花组培苗安全养护的气候环境条件

本文以金苞花为例,尝试了组培苗从试管内到自然条件下安全养护的小气候环境模拟并获得成功,提出了“关键阶段,过渡阶段和适应阶段”的三段安全养护措施及其相应的气象条件。这对名贵花卉的商业性生产是有意义的。     

成都城市发展对气候影响的初步探讨

本文通过成都城市发展前后气候要素变化的对比分析,探索了城市化对成都市气候影响的基本规律,并用统计方法得出了城市“热岛”强度(△T,△Tmin)与城市人口总户数及建成区面积密切相关的客观事实,为改善和治理成都城市气候提供了一定的依据。     

Waiting Time Distribution of Emissions in Complex Coronal Mass Ejections

The waiting time distribution of emissions in Coronal Mass Ejections (CMEs) with several emissions is examined. We define the waiting time as the time interval between the commencement of an emission and the commencement of the next emission considered as parts of a unique CME. The distribution seems to follow a power-law. Two classes of CMEs several emissions are considered: “close” and “separate” depending on angular distance between emissions.     

Empirical nonergodic shaking scenarios based on spatial correlation models: An application to central Italy

This paper provides a new methodological framework to generate empirical ground shaking scenarios, designed for engineering applications and civil protection planning. The methodology is useful both to reconstruct the ground motion pattern of past events and to generate future shaking scenarios, in regions where strong‐motion datasets from multiple events and multiple stations are available. The proposed methodology combines (1) an ad‐hoc nonergodic ground motion model (GMM) with (2) a spatial correlation model for the source region‐, site‐, and path‐systematic residual terms, and (3) a model of the remaining aleatory error to take into account for directivity effects. The associated variability is a function of the type of scenario generated (bedrock or site, past or future event) and it is minimal for source areas where several events have occurred and for sites where recordings are available. In order to develop the region‐specific fully nonergodic GMM and to compute robust estimation of the residual terms, the approach is calibrated on a highly dense dataset compiled for the area of central Italy. Example tests demonstrate the validity of the approach, which allows to simulate acceleration response spectra at unsampled sites, as well as to capture peculiar physical features of ground motion patterns in the region. The proposed approach could be usefully adopted for data‐driven simulations of ground shaking maps, as alternative or complementary tool to physic‐based and stochastic‐based approaches.