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1.
Summary Atmospheric flows exhibit long-range spatiotemporal correlations manifested as the fractal geometry to the global cloud cover pattern concomitant with inverse power law form for power spectra of temporal fluctuations on all space-tie scales ranging from turbulence (centimetersseconds) to climate (kilometers-years). Long-range spatiotemporal correlations are ubiquitous to dynamical systems in nature and are identified as signatures ofself-organized criticality. Standard models in meteorological theory cannot explain satisfactorily the observed self-organized criticality in atmospheric flows. Mathematical models for simulation and prediction of atmospheric flows are nonlinear and do not possess analytical solutions. Finite precision computer realizations of nonlinear models give unrealistic solutions because ofdeterministic chaos, a direct consequence of round-off error growth in iterative numerical computations. Recent studies show that roundoff error doubles on an average for each iteration of iterative computations. Round-off error propagates to the main stream computation and gives unrealistic solutions in numerical weather prediction (NWP) and climate models which incorporate thousands of iterative computations in long-term numerical integration schemes. An alternative non-deterministic cell dynamical system model for atmospheric flows described in this paper predicts the observed self-organized criticality as intrinsic to quantumlike mechanics governing flow dynamics. The model provides universal quantification for self-organized criticality in terms of the statistical normal distribution. Model predictions are in agreement with a majority of observed spectra of time series of several standard climatological data sets representative of disparate climatic regimes. Universal spectrum for natural climate variability rules out linear trends. Man-made greenhouse gas related atmospheric warming will result in intensification of natural climate variability, seen immediately in high frequency fluctuations such as QBO and ENSO and even shorter timescales. Model concepts and results of analyses are discussed with reference to possible prediction of climate change.With 11 Figures 相似文献
2.
安徽淮北平原冬小麦气候适宜度分析及作物年景评估 总被引：1，自引：0，他引：1
选取安徽省淮北平原37个气象站1960-2016年逐日气象资料,构建气温、降水、日照及气候适宜度模型,分析气候变暖背景下冬小麦气候适宜度时空演变特征,揭示冬小麦生育期气候风险,评判农业气候年景。结果表明：淮北平原冬小麦不同生育期对气候因子适宜程度不同,单要素各生育期适宜度均为灌浆-乳熟期较高,返青-拔节期较低,其中降水适宜度分蘖期最低;全生育期温度适宜度最高、日照适宜度次之、降水适宜度最低,水分是冬小麦生长的限制因子。气候综合适宜度灌浆-乳熟期最高,分蘖期降水适宜度最低,并且其序列变异系数大,常遭遇秋冬连旱,引起产量波动;全生育期气候适宜度呈东高西低分布,淮北中东部较高,而淮北西部及沿淮地区较低,冬小麦生产风险相对较高。1961-2016年全生育期温度适宜度线性增大趋势显著,降水适宜度线性趋势不明显,而日照适宜度呈显著的线性减小趋势;综合来看,全生育期气候适宜度无明显线性增减趋势,空间上淮北东部略有增大,而西部及沿淮地区略有减小,气候风险增加。淮北平原多数年份气候适宜度适中,适宜性偏差年发生概率高于偏好年。基于气候适宜度评判冬小麦气候年景等级,评估结果与实际产量增减情况基本相符,表明农业气候年景模型评估精度能满足业务服务需求,具有推广应用价值。 相似文献
3.
Grassland is one of the most widespread vegetation types worldwide and plays a significant role in regional climate and global
carbon cycling. Understanding the sensitivity of Chinese grassland ecosystems to climate change and elevated atmospheric CO2 and the effect of these changes on the grassland ecosystems is a key issue in global carbon cycling. China encompasses vast
grassland areas of 354 million ha of 17 major grassland types, according to a national grassland survey. In this study, a
process-based terrestrial model the CENTURY model was used to simulate potential changes in net primary productivity (NPP)
and soil organic carbon (SOC) of the Leymus chinensis meadow steppe (LCMS) under different scenarios of climatic change and elevated atmospheric CO2. The LCMS sensitivities, its potential responses to climate change, and the change in capacity of carbon stock and sequestration
in the future are evaluated. The results showed that the LCMS NPP and SOC are sensitive to climatic change and elevated CO2. In the next 100 years, with doubled CO2 concentration, if temperature increases from 2.7-3.9˚C and precipitation increases by 10% NPP and SOC will increase by 7-21%
and 5-6% respectively. However, if temperature increases by 7.5-7.8˚C and precipitation increases by only 10% NPP and SOC
would decrease by 24% and 8% respectively. Therefore, changes in the NPP and SOC of the meadow steppe are attributed mainly
to the amount of temperature and precipitation change and the atmospheric CO2 concentration in the future. 相似文献
4.
Summary We show that daily precipitation is characterized by a behaviour regulated by power laws. Both for the frequency distribution
of both event intensity and drought duration. In this respect, precipitation appears to follow self-organized criticality
laws, much as other geophysical phenomena such as avalanches and earthquakes. We use this feature to validate the simulation
of daily precipitation events in a multi-decadal regional climate model experiment for the European region. Our focus is on
the Italian peninsula and we show that both the model results and the station observations for daily precipitation intensity
and drought length follow power laws with comparable values of the relevant parameters. We suggest that complex systems theory
can provide useful tools for the validation of precipitation statistics in climate models. 相似文献
5.
We tested two approaches to forecast species distributions while balancing the impact of climate change against the inertia promoted by other influential factors that have been forecast as not changing. Given that mountain species are presumed to be more at risk due to climate warming, we selected an amphibian, a reptile, a bird, and a mammal species present in the Spanish mountains, to model their distributional response to climate change during this century. The climatic forecasts were made according to the general circulation models CGCM2 and ECHAM4 and to the A2 and B2 emission scenarios. We modelled the response of the species to spatial, topographic, human, and climatic variables separately. In our first approach, we compared each of these single-factor models using the Akaike Information Criterion, and produced a combined model weighting each factor (spatial, topographic, human, and climatic) according to Akaike weights. This procedure overestimated the best model, and the other factors were neglected in the combined model output. In our second approach, we produced a combined model using stepwise selection of the variables previously selected within each factor. In this way every factor was effectively represented in the combined explanatory model of the distributional response of the species to environmental conditions. This enabled the construction of models that combined climate with the other explanatory factors, to be later extrapolated to the future by replacing current climatic and human values with those expected from each emission and socio-economic scenario, while preserving spatial and topographic variables in the model. 相似文献
6.
The impact of climate change on agriculture has received wide attention by the scientific community. This paper studies how to assess the grain yield impact of climate change, according to the climate change over a long time period in the future as predicted by a climate system model. The application of the concept of a traditional ＂yield impact of meteorological factor （YIMF）＂ or ＂yield impact of weather factor＂ to the grain yield assessment of a decadal or even a longer timescale would be suffocated at the outset because the YIMF is for studying the phenomenon on an interannual timescale, and it is difficult to distinguish between the trend caused by climate change and the one resulting from changes in non-climatic factors. Therefore, the concept of the yield impact of climatic change （YICC）, which is defined as the difference in the per unit area yields （PUAY） of a grain crop under a changing and an envisaged invariant climate conditions, is presented in this paper to assess the impact of global climate change on grain yields. The climatic factor has been introduced into the renowned economic Cobb-Douglas model, yielding a quantitative assessment method of YICC using real data. The method has been tested using the historical data of Northeast China, and the results show that it has an encouraging application outlook. 相似文献
7.
利用文献[4],本文求出了考虑海气耦合时零维模式的平衡态,讨论了它们的稳定性和现代气候的敏感性问题。 结果表明:气候系统存在三个平衡态,两个稳定态分别表示冰期和间冰期气候;当考虑海气作用时,现代气候条件下的敏感性比不考虑海气作用时小,外参数变化为1%,温度平均变化为1°K左右。 在此基础上,就随机模式的反馈系数提出了不同的看法,对随机分析作了简略探讨,并用实际资料进行了检验。 相似文献
8.
玛纳斯河年径流在气候变化影响下发生了变异,传统径流频率分析方法的一致性假设遭到破坏,本文根据玛纳斯河上游出山口1956—2014年水文气象资料,采用遥相关分析法,并基于GAMLSS理论分别建立以时间、气候因子为协变量的时变矩模型,将其拟合效果与传统P-III分布进行对比分析,利用最优分布模型进行年径流量设计。结果表明：北大西洋涛动指数（NAO）作为气候影响因子与年径流序列相关系数为-0.322,遥联性最佳;以累积气温亏损值、降雨量、NAO为协变量的LOGNO分布模型为最优分布模型,有效地描述了在气候变化影响下玛纳斯河年径流动态变化特征,并在不同设计保证率下设计年径流比传统P-III分布偏大3.08%~16.10%,各月径流设计值与P-III分布相差较大。其研究结果为玛纳斯河水资源的高效利用及科学管理提供参考依据。 相似文献
9.
One strand of research relates the magnitude of severe weather disasters to climatic and human development factors; another highlights dramatic growth in catastrophe losses. However, there have been few attempts to put the two strands together. Here we use an explicit modeling framework to determine the contribution of climate variability relative to human factors in reported catastrophe losses. We then examine how future climate change can be expected to affect losses from natural disasters. Simultaneous regression models are constructed from three equations in which the dependent variables are U.S. flood loss, U.S. hurricane loss and U.S. catastrophe loss. Then two kinds of simulation under two climate change scenarios explore how climate change would affect losses. The climate change scenarios respectively project 13.5% and 21.5% increases in annual precipitation. The first simulation increases only the mean value of annual precipitation; the second simulation assumes that the mean and standard deviation of annual precipitation change in the same proportion. Results show that the growth in reported losses from weather-related natural disasters is due mainly to three socioeconomic factors: inflation, population growth and growth in per capita real wealth. However, weather variables such as precipitation and the number of hurricanes per period also clearly affect losses. The three stage least squares (3SLS) simultaneous equation model shows that a 1% increase in annual precipitation would enlarge catastrophe loss by as much as 2.8%. These findings are suggestive as planning signals to decision makers. 相似文献
10.
The opposing effects of climate change and socio-economic development on the global distribution of malaria 总被引：1，自引：0，他引：1
Andreas Béguin Simon Hales Joacim Rocklöv Christofer Åström Valérie R. Louis Rainer Sauerborn 《Global Environmental Change》2011,21(4):1209-1214
The current global geographic distribution of malaria results from a complex interaction between climatic and non-climatic factors. Over the past century, socio-economic development and public health measures have contributed to a marked contraction in the distribution of malaria. Previous assessments of the potential impact of global changes on malaria have not quantified the effects of non-climate factors. In this paper, we describe an empirical model of the past, present and future-potential geographic distribution of malaria which incorporates both the effects of climate change and of socio-economic development. A logistic regression model using temperature, precipitation and gross domestic product per capita (GDPpc) identifies the recent global geographic distribution of malaria with high accuracy (sensitivity 85% and specificity 95%). Empirically, climate factors have a substantial effect on malaria transmission in countries where GDPpc is currently less than US$20,000. Using projections of future climate, GDPpc and population consistent with the IPCC A1B scenario, we estimate the potential future population living in areas where malaria can be transmitted in 2030 and 2050. In 2050, the projected population at risk is approximately 5.2 billion when considering climatic effects only, 1.95 billion when considering the combined effects of GDP and climate, and 1.74 billion when considering GDP effects only. Under the A1B scenario, we project that climate change has much weaker effects on malaria than GDPpc increase. This outcome is, however, dependent on optimistic estimates of continued socioeconomic development. Even then, climate change has important effects on the projected distribution of malaria, leading to an increase of over 200 million in the projected population at risk. 相似文献
11.
This paper contributes to the literature underscoring the importance of climatic variance by developing a framework for incorporating the means and tails of the distributions of rainfall and temperature into empirical models of agricultural production. The methodology is applied to estimate the impact of climate change on the discrete choice decision to adopt irrigation since it is an important adaptation to climate change. We develop a discrete choice model for the decision to install irrigation capacity that captures the effects of both climate means and extremes. Climatic means and frequencies of climatic events in the upper tails of the temperature and precipitation distributions are used to estimate the parameters of a normal distribution for temperature and a Weibull distribution for precipitation. Using estimates from a probit model, we examine the independent effects of changing climatic mean and variance on the probability of adopting irrigation. Increasing the mean temperature, holding variance constant, shifts the entire distribution toward warmer temperatures—increasing the frequency of extreme temperatures. For precipitation, the specification captures the separate effects of mean rainfall, frequency of rainfall, and frequency of extreme events. The results show that the tails of the temperature and precipitation distributions, not the means, are the dominant climatic determinants in irrigation adoption. The results also show that water availability, soil characteristics, farm size and operator demographics are important determinants of irrigation. 相似文献
12.
基于全球土地利用类型和覆盖度,利用生长季多年平均（1982～2015年）归一化植被指数（Normalized Difference Vegetation Index,NDVI）和气候平均态（气温、降水量）数据,讨论了全球植被格局与气候因子之间的关系,建立了两者之间的多元回归模型,并分析了植被对气温和降水气候态敏感性的特征。植被与气候因子在气候梯度上存在明显的对应关系,回归模型可较好拟合气候态NDVI的全球分布格局,拟合与观测NDVI的相关系数达0.90。其中,常绿阔叶林、混交林、常绿针叶林、落叶阔叶林、农田和木本稀树草原空间分布的拟合能力较好（r>0.8）。不同土地覆盖类型的NDVI对气温、降水气候态的空间敏感性特征不同。整体而言,植被对气温和降水的敏感性呈现反相关关系（r=-0.6）。不同土地覆盖类型对气温表现出正/负敏感性,寒带灌木对气温的敏感性最强,而农作物、草原、裸地对气温负敏感性较大;植被对降水的敏感性均表现出正敏感性,其中落叶针叶林、草原和稀树草原对降水的空间敏感性较强。 相似文献
13.
W. N. Smith B. B. Grant R. L. Desjardins B. Qian J. Hutchinson S. Gameda 《Climatic change》2009,93(3-4):319-333
Under the threat of global warming it is important to determine the impact that future changes in climate may have on the environment and to what extent any adverse effects can be mitigated. In this study we assessed the impact that climate change scenarios may have on soil carbon stocks in Canada and examined the potential for agricultural management practices to improve or maintain soil quality. Historical weather data from 1951 to 2001 indicated that semi-arid soils in western Canada have become warmer and dryer and air temperatures have increased during the spring and winter months. Results from the Canadian Center for Climate Modelling and Analysis (CCCma) Coupled Global Climate Model (CGCM1,2) under two climate change forcing scenarios also indicated that future temperatures would increase more in the spring and winter. Precipitation increased significantly under the IPCC IS92a scenario and agreed with historical trends in eastern Canada whereas the IPCC SRES B2 scenario indicated very little change in precipitation and better matched historical trends in western Canada. The Century model was used to examine the influence of climate change on agricultural soil carbon (C) stocks in Canada. Relative to simulations using historical weather data, model results under the SRES B2 climate scenario indicated that agricultural soils would lose 160 Tg of carbon by 2099 and under the IS92a scenario would lose 53 Tg C. Carbon was still lost from soils in humid climatic regions even though C inputs from crops increased by 10–13%. Carbon factors associated with changes in management practices were also estimated under both climate change scenarios. There was little difference in factors associated with conversion from conventional to no-till agriculture, while carbon factors associated with the conversion of annual crops to perennial grass were lower than for historical data in semi-arid soils because water stress hampered crop production but were higher in humid soils. 相似文献
14.
H. J. McMaster 《Climatic change》1999,43(2):455-476
This study was undertaken to determine the impact of potential global warming on the magnitude of hail losses to winter cereal crops within two areas situated on the western slopes of New South Wales, Australia. A model relating historical crop hail losses to climatic variables was developed for each area. These models included seasonal measures of vertical instability, low-level moisture and the height of the freezing level. In both areas, windshear was not found to be an important factor influencing seasonal crop hail losses. The two crop hail loss models were then used in conjunction with upper-air climatic data from three single mixed-layer global climate models (GCMs). Each GCM was run for 1 × CO2 conditions and for 2 × CO2 conditions. The enhanced greenhouse effect on climatic variables was taken to be the difference between their values for these two runs. Changes to climatic variables were then translated directly into changes in the percentage value of the winter cereal crop lost due to hail. In both areas, the three GCMs agreed concerning the direction of change in each of the variables used in the crop hail loss model. GCM simulations of the greenhouse effect resulted in a decline in winter cereal crop hail losses, with the exception of one GCM simulation at one location where losses increased slightly. None of the changes due to the enhanced greenhouse effect, however, were significant owing to a large observed seasonal variability of crop hail losses. Also, the simulated seasonal variability of crop hail losses did not change significantly due to the enhanced greenhouse effect. These results depended on two important assumptions. Firstly, it was assumed that the dominant relationships between climatic variables and crop hail losses in the past would remain the same in a future climate. Secondly, it was assumed that the single mixed-layer GCMs used in the study were correctly predicting climate change under enhanced greenhouse conditions. 相似文献
15.
16.
Attack of decay fungi on wood-based material depends primarily on the natural durability of wood, the local climatic conditions, and the likely climatic change. This study investigates the vulnerability of wood and structural timber in ground contact to decay fungi under high and medium emissions scenarios specified by the Intergovernmental Panel on Climate Change, and a future scenario in which the global emissions have been limited to 550?ppm through a range of successful intervention schemes. Nine general circulation models are applied to project the local climates of Brisbane, Sydney, and Melbourne in Australia. It was found that, under the three emissions scenarios, the median decay rate of wood by 2080, relative to that in 2010, could increase up to 10?% in Brisbane and Sydney, but could decrease by 12?% in Melbourne. For timber of less durable wood species 50?years after installation, the residual strength under climate change could be almost 25?% less than that without climate change. The coefficients of variation (COVs) of decay rate of wood are in the vicinity of 1.0 regardless of wood species. For residual strength of timber pole after 50?years of installation, the COVs range from 0.2 to 1.1, depending on the natural durability of timber and the site location. The high COVs due to the variability of natural durability of wood and of climate change, in combination with the likely changes in median residual strength of structural elements, will cause significant structural reliability issues of wood construction and need to be addressed in engineering design codes. 相似文献
17.
There is increasingly clear evidence that human influence has contributed substantially to the large-scale climatic changes that have occurred over the past few decades. Attention is now turning to the physical implications of the emerging anthropogenic signal. Of particular interest is the question of whether current climate models may be over- or under-estimating the amplitude of the climate system's response to external forcing, including anthropogenic. Evidence of a significant error in a model-simulated response amplitude would indicate the existence of amplifying or damping mechanisms that are inadequately represented in the model. The range of uncertainty in the factor by which we can scale model-simulated changes while remaining consistent with observed change provides an estimate of uncertainty in model-based predictions. With any model that displays a realistic level of internal variability, the problem of estimating this factor is complicated by the fact that it represents a ratio between two incompletely known quantities: both observed and simulated responses are subject to sampling uncertainty, primarily due to internal chaotic variability. Sampling uncertainty in the simulated response can be reduced, but not eliminated, through ensemble simulations. Accurate estimation of these scaling factors requires a modification of the standard "optimal fingerprinting" algorithm for climate change detection, drawing on the conventional "total least squares" approach discussed in the statistical literature. Code for both variants of optimal fingerprinting can be found on . 相似文献
18.
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。 相似文献
19.
《Climate Policy》2001,1(4):433-449
One of the most controversial conclusions to emerge from many of the first generation of integrated assessment models (IAMs) of climate policy was the perceived economic optimality of negligible near-term abatement of greenhouse gases. Typically, such studies were conducted using smoothly varying climate change scenarios or impact responses. Abrupt changes observed in the climatic record and documented in current models could substantially alter the stringency of economically optimal IAM policies. Such abrupt climatic changes — or consequent impacts — would be less foreseeable and provide less time to adapt, and thus would have far greater economic or environmental impacts than gradual warming. We extend conventional, smooth IAM analysis by coupling a climate model capable of one type of abrupt change to a well-established energy–economy model (DICE). We compare the DICE optimal policy using the standard climate sub-model to our version that allows for abrupt change — and consequent enhanced climate damage — through changes in the strength (and possible collapse) of the North Atlantic thermohaline circulation (THC). We confirm the potential significance of abrupt climate change to economically optimal IAM policies, thus calling into question all previous work neglecting such possibilities — at the least for the wide ranges of relevant social and climate system parameters we consider. In addition, we obtain an emergent property of our coupled social–natural system model: “optimal policies” that do consider abrupt changes may, under relatively low discount rates, calculate emission control levels sufficient to avoid significant abrupt change, whereas “optimal policies” disregarding abrupt change would not prevent this non-linear event. However, there is a threshold in discount rate above which the present value of future damages is so low that even very large enhanced damages in the 22nd century, when a significant abrupt change such as a THC collapse would be most likely to occur, do not increase optimal control levels sufficiently to prevent such a collapse. Thus, any models not accounting for potential abrupt non-linear behavior and its interaction with the discounting formulation are likely to miss an important set of possibilities relevant to the climate policy debate. 相似文献
20.
Attribution of Maize Yield Increase in China to Climate Change and Technological Advancement Between 1980 and 2010 
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下载免费PDF全文 GUO Jianping ZHAO Junfang WU Dingrong MU Ji XU Yanhong 《Acta Meteorologica Sinica》2014,28(6):1168-1181
Crop yields are affected by climate change and technological advancement. Objectively and quantitatively evaluating the attribution of crop yield change to climate change and technological advancement will ensure sustainable development of agriculture under climate change. In this study, daily climate variables obtained from 553 meteorological stations in China for the period 1961-2010, detailed observations of maize from 653 agricultural meteorological stations for the period 1981-2010, and results using an Agro-Ecological Zones (AEZ) model, are used to explore the attribution of maize (Zea mays L.) yield change to climate change and technological advancement. In the AEZ model, the climatic potential productivity is examined through three step-by-step levels: photosynthetic potential productivity, photosynthetic thermal potential productivity, and climatic potential productivity. The relative impacts of different climate variables on climatic potential productivity of maize from 1961 to 2010 in China are then evaluated. Combined with the observations of maize, the contributions of climate change and technological advancement to maize yield from 1981 to 2010 in China are separated. The results show that, from 1961 to 2010, climate change had a significant adverse impact on the climatic potential productivity of maize in China. Decreased radiation and increased temperature were the main factors leading to the decrease of climatic potential productivity. However, changes in precipitation had only a small effect. The maize yields of the 14 main planting provinces in China increased obviously over the past 30 years, which was opposite to the decreasing trends of climatic potential productivity. This suggests that technological advancement has offset the negative effects of climate change on maize yield. Technological advancement contributed to maize yield increases by 99.6%-141.6%, while climate change contribution was from-41.4% to 0.4%. In particular, the actual maize yields in Shandong, Henan, Jilin, and Inner Mongolia increased by 98.4, 90.4, 98.7, and 121.5 kg hm-2 yr-1 over the past 30 years, respectively. Correspondingly, the maize yields affected by technological advancement increased by 113.7, 97.9, 111.5, and 124.8 kg hm-2 yr-1, respectively. On the contrary, maize yields reduced markedly under climate change, with an average reduction of-9.0 kg hm-2 yr-1. Our findings highlight that agronomic technological advancement has contributed dominantly to maize yield increases in China in the past three decades. 相似文献