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1.
Arne Bomblies 《Climatic change》2012,112(3-4):673-685
Seasonal total precipitation is well known to affect malaria transmission because Anopheles mosquitoes depend on standing water for breeding habitat. However, the within-season temporal pattern of the rainfall influences persistence of standing water and thus rainfall patterns can also affect mosquito population dynamics in water-limited environments. Here, using a numerical simulation, I show that intraseasonal rainfall pattern accounts for 39% of the variance in simulated mosquito abundance in a Niger Sahel village where malaria is endemic but highly seasonal. I apply a field validated coupled hydrology and entomology model. Using synthetic rainfall time series generated using a stationary first-order Markov Chain model, I hold all variables except hourly rainfall constant, thus isolating the contribution of rainfall pattern to variance in mosquito abundance. I further show the utility of hydrology modeling using topography to assess precipitation effects by analyzing collected water. Time-integrated surface area of pools explains 70% of the variance in simulated mosquito abundance from a mechanistic model, and time-integrated surface area of pools persisting longer than 7?days explains 82% of the variance. Correlations using the hydrology model output explain more variance in mosquito abundance than the 60% from rainfall totals. I extend this analysis to investigate the impacts of this effect on malaria vector mosquito populations under climate shift scenarios, holding all climate variables except precipitation constant. In these scenarios, rainfall mean and variance change with climatic change, and the modeling approach evaluates the impact of non-stationarity in rainfall and the associated rainfall patterns on expected mosquito activity.  相似文献   

2.
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   

3.
Change in climate variability in the 21st century   总被引：3，自引：0，他引：3  
As climate changes due to the increase of greenhouse gases, there is the potential for climate variability to change as well. The change in variability of temperature and precipitation in a transient climate simulation, where trace gases are allowed to increase gradually, and in the doubled CO2 climate is investigated using the GISS general circulation model. The current climate control run is compared with observations and with the climate change simulations for variability on three time-scales: interannual variability, daily variability, and the amplitude of the diurnal cycle. The results show that the modeled variability is often larger than observed, especially in late summer, possibly due to the crude ground hydrology. In the warmer climates, temperature variability and the diurnal cycle amplitude usually decrease, in conjunction with a decrease in the latitudinal temperature gradient and the increased greenhouse inhibition of radiative cooling. Precipitation variability generally changes with the same sign as the mean precipitation itself, usually increasing in the warmer climate. Changes at a particular grid box are often not significant, with the prevailing tendency determined from a broader sampling. Little change is seen in daily persistence. The results are relevant to the continuing assessments of climate change impacts on society, though their use should be tempered by appreciation of the model deficiencies for the current climate.  相似文献   

4.
Validation results of the MGO regional climate model (RCM) with 50-km resolution for Siberia are discussed. For the specification of side boundary conditions, the reanalysis data are used. It is shown that the model satisfactorily simulates the sea-level pressure and temperature fields for all seasons and the year as a whole. The lowest computational errors in the simulation of regional surface temperature arise in the fall and winter; in spring and summer, the temperature errors are slightly higher. The model slightly underestimates the variability of daily mean temperature in winter relative to the reanalysis data. In summer, on the contrary, the RCM-simulated variability exceeds the variability in reanalysis. In winter, the space distribution of model precipitation is in qualitative agreement with the data of observational analysis; in summer, the space variability of model precipitation is significantly higher than that of precipitation in the reanalysis, especially in the mountains. Agreement between time changes in precipitation and temperature anomalies in RCM and in the reanalysis is better in the areas with a relatively large number of weather stations. The model can be used for estimation of future climate changes in the above-mentioned region.  相似文献   

5.
 The inter-annual variability and potential predictability of 850 hPa temperature (T 850), 500 hPa geopotential (φ500) and 300 hPa stream function (ψ300) simulated by the models participating in the Atmospheric Model Intercomparison Project (AMIP) are examined. The total inter-annual variability is partitioned into a potentially predictable component which arises from the forcing implied by the prescribed SST and sea-ice evolution, or from sources internal to the simulated climate, and an unpredictable low frequency component induced by “weather noise”. There is wide variation in the ability to simulate observed inter-annual variability, both total and weather-noise induced. A majority of models under simulate seasonal mean φ500 variability in DJF and JJA and over simulate ψ300 variability in JJA. All but one model simulates less T 850 total inter-annual variability than in the analysed data. There is little apparent connection between gross model characteristics and the corresponding ability to simulate observed variability, with the possible exceptions of resolution. Received: 7 July 1996 / Accepted: 8 January 1998  相似文献   

6.
The forest succession model FORSKA was applied to a west-east transect across Central Europe using points from a global climate data set. Climate change experiments were undertaken for two general circulation model scenarios and two different site classes. The simulated climate changes lead to reduced forest productivity and a changed species composition on most sites. Under current climate, the broad scale pattern of the climatically driven distribution of forest communities is quite realistically reproduced. However, the resolution of climate data imposes limitations on the simulation of forest dynamics in subcontinental climate, because climate variability and extreme events are not well represented.  相似文献   

7.
利用1951—2010年中国160站气温、降水资料,分析中国代表性台站冬季和夏季气温、降水的气候值及气候变率在前后30 a的差异,并对结果使用不同方法进行显著性检验。结果表明,季气温气候平均值的变化总体与全球增暖一致,以升温为主,但夏季在秦岭以南及长江中游地区出现显著局部变冷现象;季气温气候变率的变化相对较小,冬季总体不显著,夏季仅有少数台站显著。降水的气候变化总体不明显,季降水气候值变化的空间分布复杂,冬季南方地区、夏季东部地区总体增加,冬、夏季降水气候变率的变化均不显著。理论检验方法（t检验、F检验）与随机模拟方法（EMC法）的显著性检验结果,对气温的差别较小、对降水的差别较大,这与样本距平序列是否服从正态分布有关。EMC法可在确保样本统计特征不变的情况下,通过多次随机模拟,无需考虑其理论统计分布特征,使检验结果更为可靠。  相似文献   

8.
This modeling study addresses the potential impacts of climate change and changing climate variability due to increased atmospheric CO2 concentration on soybean (Glycine max (L.) Merrill) yields in theMidwestern Great Lakes Region. Nine representative farm locations and six future climate scenarios were analyzed using the crop growth model SOYGRO. Under the future climate scenarios earlierplanting dates produced soybean yield increases of up to 120% above current levels in the central and northern areas of the study region. In the southern areas, comparatively small increases (0.1 to 20%) and small decreases (–0.1 to–25%) in yield are found. The decreases in yield occurred under the Hadley Center greenhouse gas run (HadCM2-GHG), representing a greater warming, and the doubled climate variability scenario – a more extreme and variableclimate. Optimum planting dates become later in the southern regions. CO2fertilization effects (555 ppmv) are found to be significant for soybean, increasing yields around 20% under future climate scenarios.For the study region as a whole the climate changes modeled in this research would have an overall beneficial effect, with mean soybean yield increases of 40% over current levels.  相似文献   

9.
The El Nin o-Southern Oscillation (ENSO) is modulated by many factors; most previous studies have emphasized the roles of wind stress and heat flux in the tropical Pacific. Freshwater flux (FWF) is another environmental forcing to the ocean; its effect and the related ocean salinity variability in the ENSO region have been of increased interest recently. Currently, accurate quantifications of the FWF roles in the climate remain challenging; the related observations and coupled ocean-atmosphere modeling involve large elements of uncertainty. In this study, we utilized satellite-based data to represent FWF-induced feedback in the tropical Pacific climate system; we then incorporated these data into a hybrid coupled ocean-atmosphere model (HCM) to quantify its effects on ENSO. A new mechanism was revealed by which interannual FWF forcing modulates ENSO in a significant way. As a direct forcing, FWF exerts a significant influence on the ocean through sea surface salinity (SSS) and buoyancy flux (Q B ) in the western-central tropical Pacific. The SSS perturbations directly induced by ENSO-related interannual FWF variability affect the stability and mixing in the upper ocean. At the same time, the ENSO-induced FWF has a compensating effect on heat flux, acting to reduce interannual Q B variability during ENSO cycles. These FWF-induced processes in the ocean tend to modulate the vertical mixing and entrainment in the upper ocean, enhancing cooling during La Nin a and enhancing warming during El Nin o, respectively. The interannual FWF forcing-induced positive feedback acts to enhance ENSO amplitude and lengthen its time scales in the tropical Pacific coupled climate system.  相似文献   

10.
It is important to improve estimates of large-scale carbon fluxes over the boreal forest because the responses of this biome to global change may influence the dynamics of atmospheric carbon dioxide in ways that may influence the magnitude of climate change. Two methods currently being used to estimate these fluxes are process-based modeling by terrestrial biosphere models (TBMs), and atmospheric inversions in which fluxes are derived from a set of observations on atmospheric CO2 concentrations via an atmospheric transport model. Inversions do not reveal information about processes and therefore do not allow for predictions of future fluxes, while the process-based flux estimates are not necessarily consistent with atmospheric observations of CO2. In this study we combine the two methods by using the fluxes from four TBMs as a priori fluxes for an atmospheric Bayesian Synthesis Inversion. By doing so we learn about both approaches. The results from the inversion indicate where the results of the TBMs disagree with the atmospheric observations of CO2, and where the results of the inversion are poorly constrained by atmospheric data, the process-based estimates determine the flux results. The analysis indicates that the TBMs are modeling the spring uptake of CO2 too early, and that the inversion shows large uncertainty and more dependence on the initial conditions over Europe and Boreal Asia than Boreal North America. This uncertainty is related to the scarcity of data over the continents, and as this problem is not likely to be solved in the near future, TBMs will need to be developed and improved, as they are likely the best option for understanding the impact of climate variability in these regions.  相似文献   

11.
Projections of vegetation distribution that incorporate the transient responses of vegetation to climate change are likely to be more efficacious than those that assume an equilibrium between climate and vegetation. We examine the non-equilibrium dynamics of a temperate forest region under historic and projected future climate change using the dynamic ecosystem model LPJ-GUESS. We parameterized LPJ-GUESS for the New England region of the United Sates utilizing eight forest cover types that comprise the regionally dominant species. We developed a set of climate data at a monthly-step and a 30-arc second spatial resolution to run the model. These datasets consist of past climate observations for the period 1901?C2006 and three general circulation model projections for the period 2007?C2099. Our baseline (1971?C2000) simulation reproduces the distribution of forest types in our study region as compared to the National Land Cover Data 2001 (Kappa statistic?=?0.54). Under historic and nine future climate change scenarios, maple-beech-basswood, oaks and aspen-birch were modeled to move upslope at an estimated rate of 0.2, 0.3 and 0.5?m?yr?1 from 1901 to 2006, and continued this trend at an accelerated rate of around 0.5, 0.9 and 1.7?m?yr?1 from 2007 to 2099. Spruce-fir and white pine-cedar were modeled to contract to mountain ranges and cooler regions of our study region under projected future climate change scenarios. By the end of the 21st century, 60% of New England is projected to be dominated by oaks relative to 21% at the beginning of the 21st century, while northern New England is modeled to be dominated by aspen-birch. In mid and central New England, maple-beech-basswood, yellow birch-elm and hickories co-occur and form novel species associations. In addition to warming-induced northward and upslope shifts, climate change causes more complex changes in our simulations, such as reversed conversions between forest types that currently share similar bioclimatic ranges. These results underline the importance of considering community interactions and transient dynamics in modeling studies of climate change impacts on forest ecosystems.  相似文献   

12.
It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The sub-continent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite-derived rainfall data from the Microwave Infrared Rainfall Algorithm (MIRA). This dataset covers the period from 1993 to 2002 and the whole of southern Africa at a spatial resolution of 0.1° longitude/latitude. This paper concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of present-day rainfall variability over southern Africa and is not intended to discuss possible future changes in climate as these have been documented elsewhere. Simulations of current climate from the UK Meteorological Office Hadley Centre’s climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. Secondly, the ability of the model to reproduce daily rainfall extremes is assessed, again by a comparison with extremes from the MIRA dataset. The results suggest that the model reproduces the number and spatial distribution of rainfall extremes with some accuracy, but that mean rainfall and rainfall variability is under-estimated (over-estimated) over wet (dry) regions of southern Africa.  相似文献   

13.
We compare, for the overlapping time frame 1962–2000, the estimate of the northern hemisphere mid-latitude winter atmospheric variability within the available 20th century simulations of 19 global climate models included in the Intergovernmental Panel on Climate Change—4th Assessment Report with the NCEP-NCAR and ECMWF reanalyses. We compute the Hayashi spectra of the 500 hPa geopotential height fields and introduce an ad hoc integral measure of the variability observed in the Northern Hemisphere on different spectral sub-domains. The total wave variability is taken as a global scalar metric describing the overall performance of each model, while the total variability pertaining to the eastward propagating baroclinic waves and to the planetary waves are taken as scalar metrics describing the performance of each model phenomenologically in connection with the corresponding specific physical process. Only two very high-resolution global climate models have a good agreement with reanalyses for both the global and the process-oriented metrics. Large biases, in several cases larger than 20%, are found in all the considered metrics between the wave climatologies of most IPCC models and the reanalyses, while the span of the climatologies of the various models is, in all cases, around 50%. In particular, the travelling baroclinic waves are typically overestimated by the climate models, while the planetary waves are usually underestimated, in agreement with what found is past analyses performed on global weather forecasting models. When comparing the results of similar models, it is apparent that in some cases the vertical resolution of the model atmosphere, the adopted ocean model, and the advection schemes seem to be critical in the bulk of the atmospheric variability. The models ensemble obtained by arithmetic averaging of the results of all models is biased with respect to the reanalyses but is comparable to the best five models. Nevertheless, the models results do not cluster around their ensemble mean. This study suggests caveats with respect to the ability of most of the presently available climate models in representing the statistical properties of the global scale atmospheric dynamics of the present climate and, a fortiori, in the perspective of modeling climate change.  相似文献   

14.
气象部门馆藏的西部最早的器测气象资料始于20世纪30年代,不能满足建立20世纪以来中国气候变化序列的需求,而古气候重建或气候模拟资料则可以延伸到器测时代以前。为了探讨长序列多源气候资料序列融合方法,采用贝叶斯方法对中国北疆地区8条树轮气温重建资料、器测资料与国际耦合模式比较计划第5阶段（CMIP5）模式模拟资料进行了融合试验。首先利用器测资料对气温代用资料进行校验与网格重建,并以此作为贝叶斯模型的先验分布,然后,用泰勒图选出了该区域气候模拟效果最佳的几个模式;最后将网格重建和气候模拟序列用贝叶斯模型进行了融合试验。结果表明,贝叶斯融合模型能有效提取各种数据来源的有用信息进行融合,融合结果的长期变化（线性）趋势更接近器测气候序列,并在一定程度上提高了序列的精度,减小了结果的不确定性;并且,融合结果能够纠正先验分布及气候模拟数据的明显偏差,为长年代气候序列重建提供了一个可行的思路。   相似文献   

15.
The Response of Arctic Sea Ice to Global Change   总被引：4，自引：0，他引：4  
The sea ice-covered polar oceans have received wider attention recently for two reasons. Firstly, the global conveyor belt circulation of the ocean is believed to be forced in the North and South Atlantic through deep water formation, which to a large degree is controlled by the variations of the sea ice margin and especially by the sea ice export to lower latitudes. Secondly, CO2 response experiments with coupled climate models show an enhanced warming in polar regions for increased concentrations of atmospheric greenhouse gases. Whether this large response in high latitudes is due to real physical feedback processes or to unrealistic simplifications of the sea ice model component remains to be determined. Coupled climate models generally use thermodynamic sea ice models or sea ice models with oversimplified dynamics schemes. Realistic dynamic-thermodynamic sea ice models are presently implemented only at a few modeling centers. Sensitivity experiments with thermodynamic and dynamic-thermodynamic sea ice models show that the more sophisticated models are less sensitive to perturbations of the atmospheric and oceanic boundary conditions. Because of the importance of the role of sea ice in mediating between atmosphere and ocean an improved representation of sea ice in global climate models is required. This paper discusses present sea ice modeling as well as the sensitivity of the sea ice cover to changes in the atmospheric boundary conditions. These numerical experiments indicate that the sea ice follows a smooth response function: sea ice thickness and export change by 2% of the mean value per 1 Wm-2 change of the radiative forcing.  相似文献   

16.
Climate variability parameters and air temperature trends in Russia, derived from observational data, are compared with those derived from climate modeling in the second half of the 20th-early 21st century, using the atmosphere-ocean general circulation model ensemble. The computation results from these models were used in the preparation of the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. It is demonstrated that the ensemble averaging allowed us to efficiently filter the internal climate variability and get relatively stable estimates of trends. As a whole, for Russia, these estimates are in good agreement with the observational data, both for a year on average, and in individual seasons. The comparison of model and observed air temperature trends on a regional scale turns out to be irrelevant in a number of cases because of a high inadequacy of trend estimates derived from the observational data.  相似文献   

17.
Under the impacts of climate variability and human activities, there are statistically significant decreasing trends for streamflow in the Yellow River basin, China. Therefore, it is crucial to separate the impacts of climate variability and human activities on streamflow decrease for better water resources planning and management. In this study, the Qinhe River basin (QRB), a typical sub-basin in the middle reach of the Yellow River, was chosen as the study area to assess the impacts of climate variability and human activities on streamflow decrease. The trend and breakpoint of observed annual streamflow from 1956 to 2010 were identified by the nonparametric Mann–Kendall test. The results showed that the observed annual streamflow decreased significantly (P?<?0.05) and a breakpoint around 1973 was detected. Therefore, the time series was divided into two periods: “natural period” (before the breakpoint) and “impacted period” (after the breakpoint). The observed annual streamflow decreased by 68.1 mm from 102.3 to 34.2 mm in the two periods. The climate elasticity method and hydrological model were employed to separate the impacts of climate variability and human activities on streamflow decrease. The results indicated that climate variability was responsible for 54.1 % of the streamflow decrease estimated by the climate elasticity method and 59.3 % estimated by the hydrological modeling method. Therefore, the climate variability was the main driving factor for streamflow decrease in the QRB. Among these driving factors of natural and anthropogenic, decrease in precipitation and increase in water diversion were the two major contributions of streamflow reduction. The finding in this study can serve as a reference for regional water resources management and planning.  相似文献   

18.
 Until now, most paleoclimate model-data comparisons have been limited to simple statistical evaluation and simple map comparisons. We have applied a new method, based on fuzzy logic, to the comparison of 17 model simulations of the mid-Holocene (6 ka BP) climate with reconstruction of three bioclimatic parameters (mean temperature of the coldest month, MTCO, growing degree-days above 5 °C, GDD5, precipitation minus evapotranspiration, P−E) from pollen and lake-status data over Europe. With this method, no assumption is made about the distribution of the signal and on its error, and both the error bars related to data and to model simulations are taken into account. Data are taken at the drilling sites (not using a gridded interpolation of proxy data) and a varying domain size of comparison enables us to make the best common resolution between observed and simulated maps. For each parameter and each model, we compute a Hagaman distance which gives an objective measure of the goodness of fit between model and data. The results show that there is no systematic order for the three climatic parameters between models. None of the models is able to satisfactorily reproduce the three pollen-derived data. There is larger dispersion in the results for MTCO and P−E than for GDD5. There is also no systematic relationship between model resolution and the Hagaman distance, except for P−E. The more local character of P−E has little chance to be reproduced by a low resolution model, which can explain the inverse relationship between model resolution and Hagaman distance. The results also reveal that most of the models are better at predicting 6 ka climate than the modern climate. Received: 27 May 1998 / Accepted: 8 January 1999  相似文献   

19.
东亚夏季风对于我国东部气候具有重要影响,呈现出多种时间尺度的变化特征。在理解东亚夏季风过去和当前的变化机理、预测和预估其未来变化等方面,气候系统模式发挥着不可替代的作用。但是当前的气候模式在东亚夏季风的模拟上尚存在诸多不足,这使得其模拟结果存在不确定性,既制约了我们对过去和当前季风变化机理的准确理解,又降低了未来预测预估结果的可信度。关于造成季风模拟偏差的原因,既涉及模式本身的性能问题,又与模拟系统的构建、强迫资料的误差、乃至我们当前对季风变化规律自身的认知水平有关。本文以时间尺度为序,从气候态、日变化、年际变率、年代际变率、长期气候变化和未来预估等季风学界关注的热点问题角度,本着总结成绩、归纳问题、寻找机遇、面对挑战的目的,从七个方面系统总结了当前气候模式的水平,归纳了其主要偏差特征,讨论了影响模式性能的可能因素。内容涉及模式分辨率和地形效应、对流和云辐射效应的作用、与季风相关的热带海气相互作用关键过程、内部变率（太平洋年代际振荡）、自然变率（太阳辐照度变化和火山气溶胶强迫）和人为辐射强迫（人为温室气体和气溶胶排放）对季风变化的不同影响、热力和动力过程及气候敏感度对季风环流（副高）和降水预估不确定性的影响等。最后从优化参数、实现场地观测和过程模拟的协同、发展高分辨和对流解析模式等角度,讨论了提升东亚夏季风模拟能力的技术途径。  相似文献   

20.
Climate warming in the mid- to high-latitudes and high-elevation mountainous regions is occurring more rapidly than anywhere else on Earth, causing extensive loss of glaciers and snowpack. However, little is known about the effects of climate change on alpine stream biota, especially invertebrates. Here, we show a strong linkage between regional climate change and the fundamental niche of a rare aquatic invertebrate—the meltwater stonefly Lednia tumana—endemic to Waterton-Glacier International Peace Park, Canada and USA. L. tumana has been petitioned for listing under the U.S. Endangered Species Act due to climate-change-induced glacier loss, yet little is known on specifically how climate impacts may threaten this rare species and many other enigmatic alpine aquatic species worldwide. During 14 years of research, we documented that L. tumana inhabits a narrow distribution, restricted to short sections (~500 m) of cold, alpine streams directly below glaciers, permanent snowfields, and springs. Our simulation models suggest that climate change threatens the potential future distribution of these sensitive habitats and the persistence of L. tumana through the loss of glaciers and snowfields. Mountaintop aquatic invertebrates are ideal early warning indicators of climate warming in mountain ecosystems. Research on alpine invertebrates is urgently needed to avoid extinctions and ecosystem change.  相似文献   

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