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1.
There are a number of sources of uncertainty in regional climate change scenarios. When statistical downscaling is used to obtain regional climate change scenarios, the uncertainty may originate from the uncertainties in the global climate models used, the skill of the statistical model, and the forcing scenarios applied to the global climate model. The uncertainty associated with global climate models can be evaluated by examining the differences in the predictors and in the downscaled climate change scenarios based on a set of different global climate models. When standardized global climate model simulations such as the second phase of the Coupled Model Intercomparison Project （CMIP2） are used, the difference in the downscaled variables mainly reflects differences in the climate models and the natural variability in the simulated climates. It is proposed that the spread of the estimates can be taken as a measure of the uncertainty associated with global climate models. The proposed method is applied to the estimation of global-climate-model-related uncertainty in regional precipitation change scenarios in Sweden. Results from statistical downscaling based on 17 global climate models show that there is an overall increase in annual precipitation all over Sweden although a considerable spread of the changes in the precipitation exists. The general increase can be attributed to the increased large-scale precipitation and the enhanced westerly wind. The estimated uncertainty is nearly independent of region. However, there is a seasonal dependence. The estimates for winter show the highest level of confidence, while the estimates for summer show the least.  相似文献   

2.
We estimated how the possible changes in wind climate and state of the forest due to climate change may affect the probability of exceeding critical wind speeds expected to cause wind damage within a forest management unit located in Southern Sweden. The topography of the management unit was relatively gentle and the forests were dominated by Norway spruce (Picea abies (L.) Karst.). We incorporated a model relating the site index (SI) to the site productivity into the forest projection model FTM. Using estimated changes in the net primary production (NPP) due to climate change and assuming a relative change in NPP equal to a relative change in the site productivity, we simulated possible future states of the forest under gradual adjustment of SI in response to climate change. We estimated changes in NPP by combining the boreal-adapted BIOMASS model with four regional climate change scenarios calculated using the RCAO model for the period 2071–2100 and two control period scenarios for the period 1961–1990. The modified WINDA model was used to calculate the probability of wind damage for individual forest stands in simulated future states of the forest. The climate change scenarios used represent non-extreme projections on a 100-year time scale in terms of global mean warming. A 15–40% increase in NPP was estimated to result from climate change until the period 2071–2100. Increasing sensitivity of the forest to wind was indicated when the management rules of today were applied. A greater proportion of the calculated change in probability of wind damage was due to changes in wind climate than to changes in the sensitivity of the forest to wind. While regional climate scenarios based on the HadAM3H general circulation model (GCM) indicated no change (SRES A2 emission scenario) or a slightly reduced (SRES B2 emission scenario) probability of wind damage, scenarios based on the ECHAM4/OPYC3 GCM indicated increased probability of wind damage. The assessment should, however, be reviewed as the simulation of forest growth under climate change as well as climate change scenarios are refined.  相似文献   

3.
Observations as well as most climate model simulations are generally in accord with the hypothesis that the hydrologic cycle should intensify and become highly volatile with the greenhouse-gas-induced climate change, although uncertainties of these projections as well as the spatial and seasonal variability of the changes are much larger than for temperature extremes. In this study, we examine scenarios of changes in extreme precipitation events in 24 future climate runs of ten regional climate models, focusing on a specific area of the Czech Republic (central Europe) where complex orography and an interaction of other factors governing the occurrence of heavy precipitation events result in patterns that cannot be captured by global models. The peaks-over-threshold analysis with increasing threshold censoring is applied to estimate multi-year return levels of daily rainfall amounts. Uncertainties in scenarios of changes for the late 21st century related to the inter-model and within-ensemble variability and the use of the SRES-A2 and SRES-B2 greenhouse gas emission scenarios are evaluated. The results show that heavy precipitation events are likely to increase in severity in winter and (with less agreement among models) also in summer. The inter-model and intra-model variability and related uncertainties in the pattern and magnitude of the change is large, but the scenarios tend to agree with precipitation trends recently observed in the area, which may strengthen their credibility. In most scenario runs, the projected change in extreme precipitation in summer is of the opposite sign than a change in mean seasonal totals, the latter pointing towards generally drier conditions in summer. A combination of enhanced heavy precipitation amounts and reduced water infiltration capabilities of a dry soil may severely increase peak river discharges and flood-related risks in this region.  相似文献   

4.
This paper compares the results of the three state of the art climate-energy-economy models IMACLIM-R, ReMIND-R, and WITCH to assess the costs of climate change mitigation in scenarios in which the implementation of a global climate agreement is delayed or major emitters decide to participate in the agreement at a later stage only. We find that for stabilizing atmospheric GHG concentrations at 450?ppm CO2-only, postponing a global agreement to 2020 raises global mitigation costs by at least about half and a delay to 2030 renders ambitious climate targets infeasible to achieve. In the standard policy scenario??in which allocation of emission permits is aimed at equal per-capita levels in the year 2050??regions with above average emissions (such as the EU and the US alongside the rest of Annex-I countries) incur lower mitigation costs by taking early action, even if mitigation efforts in the rest of the world experience a delay. However, regions with low per-capita emissions which are net exporters of emission permits (such as India) can possibly benefit from higher future carbon prices resulting from a delay. We illustrate the economic mechanism behind these observations and analyze how (1) lock-in of carbon intensive infrastructure, (2) differences in global carbon prices, and (3) changes in reduction commitments resulting from delayed action influence mitigation costs.  相似文献   

5.
以全球气候模式NorESM1-M产生的RCP2.6、RCP4.5、RCP6.0、RCP8.5气候变化情景数据和原环保部推荐的土壤风蚀扬尘计算方法,模拟分析了未来气候变化对河北坝上砂粘壤土、粘壤土、壤粘土、砂壤土、砂粘土和风沙土草地土壤风蚀扬尘总可悬浮颗粒物(Total Suspended Particle,TSP)、PM10和PM2.5的季节及年排放速率的影响。结果表明:气候变化影响下坝上地区气温上升,年降水量和风速波动较大、并存在上升和下降的趋势。相比基准情景,在RCP2.6、RCP4.5、RCP6.0和RCP8.5情景下,各土壤风蚀扬尘TSP、PM10和PM2.5季节排放速率在春季分别高15%、47%、28%和46%;秋季分别高17%、54%、45%和38%;冬季分别低36%、42%、39%和44%;夏季,在RCP2.6情景下低1%,在RCP4.5、RCP6.0和RCP8.5情景下分别高14%、3%和7%;未来气候变化情景下,各土壤风蚀扬尘TSP、PM10和PM2.5年排放速率分别高25%、54%、35%和54%。基准和未来气候变化情景下,土壤风蚀扬尘TSP、PM10和PM2.5的季节和年排放速率及其差异从高到低均依次为砂粘壤土、风沙土、砂壤土、粘壤土、壤粘土和砂粘土。表明未来气候变化将使河北坝上地区草地土壤风蚀扬尘排放速率增加,但存在季节和气候变化情景方面的差异。  相似文献   

6.
Scenarios with daily time resolution are frequently used in research on the impacts of climate change. These are traditionally developed by regional climate models (RCMs). The spatial resolution, however, is usually too coarse for local climate change analysis, especially in regions with complex topography, such as Norway. The RCM used, HIRHAM, is run with lateral boundary forcing provided from two global medium resolution models; the ECHAM4/OPYC3 from MPI and the HadAM3H from the Hadley centre. The first is run with IPCC SRES emission scenario B2, the latter is run with IPCC SRES emission scenarios A2 and B2. All three scenarios represent the future time period 2071–2100. Both models have a control run, representing the present climate (1961–1990). Daily temperature scenarios are interpolated from HIRHAM to Norwegian temperature stations. The at-site HIRHAM-temperatures, both for the control and scenario runs, are adjusted to be locally representative. Mean monthly values and standard deviations based on daily values of the adjusted HIRHAM-temperatures, as well as the cumulative distribution curve of daily seasonal temperatures, are conclusive with observations for the control period. Residual kriging are used on the adjusted daily HIRHAM-temperatures to obtain high spatial temperature scenarios. Mean seasonal temperature grids are obtained. By adjusting the control runs and scenarios and improving the spatial resolution of the scenarios, the absolute temperature values are representative at a local scale. The scenarios indicate larger warming in winter than in summer in the Scandinavian regions. A marked west–east and south–north gradient is projected for Norway, where the largest increase is in eastern and northern regions. The temperature of the coldest winter days is projected to increase more than the warmer temperatures.  相似文献   

7.
In this study, we analyse the uncertainty of the effect of enhanced greenhouse gas conditions on windiness projected by an ensemble of regional model simulations driven by the same global control and climate change simulations. These global conditions, representative for 1961–1990 and 2071–2100, were prepared by the Hadley Centre based on the IPCC SRES/A2 scenario. The basic data sets consist of simulated daily maximum and daily mean wind speed fields (over land) from the PRUDENCE data archive at the Danish Meteorological Institute. The main focus is on the results from the standard 50 km-resolution runs of eight regional models. The best parameter for determining possible future changes in extreme wind speeds and possible change in the number of storm events is maximum daily wind speed. It turned out during this study that the method for calculating maximum daily wind speed differs among the regional models. A comparison of simulated winds with observations for the control period shows that models without gust parameterisation are not able to realistically capture high wind speeds. The two models with gust parametrization estimate an increase of up to 20% of the number of storm peak (defined as gusts?≥?8 Bft in this paper) events over Central Europe in the future. In order to use a larger ensemble of models than just the two with gust parameterisation, we also look at the 99th percentile of daily mean wind speed. We divide Europe into eight sub-regions (e.g., British Isles, Iberian Peninsula, NE Europe) and investigate the inter-monthly variation of wind over these regions as well as differences between today’s climate and a possible future climate. Results show differences and similarities between the sub-regions in magnitude, spread, and seasonal tendencies. The model ensemble indicates a possible increase in future mean daily wind speed during winter months, and a decrease during autumn in areas influenced by North Atlantic extra-tropical cyclones.  相似文献   

8.
An analysis is presented of the dependence of the regional temperature and precipitation change signal on systematic regional biases in global climate change projections. The CMIP3 multi-model ensemble is analyzed over 26 land regions and for the A1B greenhouse gas emission scenario. For temperature, the model regional bias has a negligible effect on the projected regional change. For precipitation, a significant correlation between change and bias is found in about 30% of the seasonal/regional cases analyzed, covering a wide range of different climate regimes. For these cases, a performance-based selection of models in producing climate change scenarios can affect the resulting change estimate, and it is noted that a minimum of four to five models is needed to obtain robust precipitation change estimates. In a number of cases, models with largely different precipitation biases can still produce changes of consistent sign. Overall, it is assessed that in the present generation of models the regional bias does not appear to be a dominant factor in determining the simulated regional change in the majority of cases.  相似文献   

9.
The relationship between long-term climate goals and short/medium-term emission targets forms crucial information for the design of international climate policy. Since IPCC??s 4th Assessment Report (AR4), a large number of new scenario studies have been published. This paper reviews this new literature and finds that there is more flexibility in the timing of short-term emission reductions compared to the earlier scenarios assessed by the AR4. For instance, the current literature suggests that a peak of emissions in 2020 and even 2030 would be consistent with limiting temperature change to about 2??C in the long term. The timing when emissions peak depends on whether negative emissions in the long-term can be achieved. The recent scenarios further indicate that global emissions by 2050 should be 40?C80% below 2000 levels. Above all, the paper argues that there is no clear, single ??law?? that would directly determine the required emissions levels in 2020, but that instead policy-makers need to consider trade-offs between the likelihood of achieving long-term targets, the short-term costs, and their expectation with respect to future technologies (and their possible failure). The higher flexibility might be important in finding acceptable agreements on international climate policy.  相似文献   

10.
Dynamical downscaling of global climate simulations is the most adequate tool to generate regional projections of climate change. This technique involves at least a present climate simulation and a simulation of a future scenario, usually at the end of the twenty first century. However, regional projections for a variety of scenarios and periods, the 2020s or the 2050s, are often required by the impact community. The pattern scaling technique is used to estimate information on climate change for periods and scenarios not simulated by the regional model. We based our study on regional simulations performed over southern South America for present climate conditions and two emission scenarios at the end of the twenty first century. We used the pattern scaling technique to estimate mean seasonal changes of temperature and precipitation for the 2020s and the 2050s. The validity of the scalability assumptions underlying the pattern scaling technique for estimating near future regional climate change scenarios over southern South America is assessed. The results show that the pattern scaling works well for estimating mean temperature changes for which the regional changes are linearly related to the global mean temperature changes. For precipitation changes, the validity of the scalability assumption is weaker. The errors of estimating precipitation changes are comparable to those inherent to the regional model and to the projected changes themselves.  相似文献   

11.
Knowledge of the likely future wind, wave and surge climate in Liverpool Bay is of importance for coastal flood defence management. We examine a 140-year time series (1960–2100) of wind and wave model projections at the WaveNet buoy location in Liverpool Bay and also of surge model projection at two ports in Liverpool Bay, namely Liverpool and Heysham. To this end we use model projections from the UK Climate Projections 09 (UKCP09) programme. We use a medium emissions scenario ensemble from the HadCM3 climate model sensitivity tests. A continental shelf model (CS3) with ~12 km resolution was used to separately simulate the waves and the surge. The models are forced by hourly wind and pressure data from the Met Office (Hadley Centre) regional climate model (RCM). Swell wave boundary conditions are generated over the full Atlantic using global climate model (GCM) winds. Analysis of significant changes in the statistics over time shows that there is little change in extreme wave and surge conditions in Liverpool Bay. Although there is a slight increase in the severity of the most extreme events, the frequency of extreme wind and wave events is slightly reduced, while the frequency of extreme surge events slightly increases over the 140-year period. From the model projections, we find that the trends in the local wind are directly reflected in the wave field within Liverpool Bay. The trends in the skew surge projections deviate slightly from those in the wind patterns.  相似文献   

12.
In order to evaluate the future potential benefits of emission regulation on regional air quality, while taking into account the effects of climate change, off-line air quality projection simulations are driven using weather forcing taken from regional climate models. These regional models are themselves driven by simulations carried out using global climate models (GCM) and economical scenarios. Uncertainties and biases in climate models introduce an additional “climate modeling” source of uncertainty that is to be added to all other types of uncertainties in air quality modeling for policy evaluation. In this article we evaluate the changes in air quality-related weather variables induced by replacing reanalyses-forced by GCM-forced regional climate simulations. As an example we use GCM simulations carried out in the framework of the ERA-interim programme and of the CMIP5 project using the Institut Pierre-Simon Laplace climate model (IPSLcm), driving regional simulations performed in the framework of the EURO-CORDEX programme. In summer, we found compensating deficiencies acting on photochemistry: an overestimation by GCM-driven weather due to a positive bias in short-wave radiation, a negative bias in wind speed, too many stagnant episodes, and a negative temperature bias. In winter, air quality is mostly driven by dispersion, and we could not identify significant differences in either wind or planetary boundary layer height statistics between GCM-driven and reanalyses-driven regional simulations. However, precipitation appears largely overestimated in GCM-driven simulations, which could significantly affect the simulation of aerosol concentrations. The identification of these biases will help interpreting results of future air quality simulations using these data. Despite these, we conclude that the identified differences should not lead to major difficulties in using GCM-driven regional climate simulations for air quality projections.  相似文献   

13.
Many scientific studies warn of a rapid global climate change during the next century. These changes are understood with much less certainty on a regional scale than on a global scale, but effects on ecosystems and society will occur at local and regional scales. Consequently, in order to study the true impacts of climate change, regional scenarios of future climate are needed. One of the most important sources of information for creating scenarios is the output from general circulation models (GCMs) of the climate system. However, current state-of-the-art GCMs are unable to simulate accurately even the current seasonal cycle of climate on a regional basis. Thus the simple technique of adding the difference between 2 × CO2 and 1 × CO2 GCM simulations to current climatic time series cannot produce scenarios with appropriate spatial and temporal details without corrections for model deficiencies. In this study a technique is developed to allow the information from GCM simulations to be used, while accommodating for the deficiencies. GCM output is combined with knowledge of the regional climate to produce scenarios of the equilibrium climate response to a doubling of the atmospheric CO2 concentration for three case study regions, China, Sub-Saharan Africa and Venezuela, for use in biological effects models. By combining the general climate change calculated with several GCMs with the observed patterns of interannual climate variability, reasonable scenarios of temperature and precipitation variations can be created. Generalizations of this procedure to other regions of the world are discussed.  相似文献   

14.
近50年中国风速变化多气候模式模拟检验   总被引：3，自引：0，他引：3  
江滢  罗勇  赵宗慈 《气象学报》2009,67(6):923-934
近年来,随着气候模式研究的快速发展,全球气候模式在模拟20世纪气候和气候变化特征,尤其是在模拟温度、降水等要素特征和变化及其人类活动对这些要素的影响等方面取得了丰硕的成果.然而,全球气候模式对近地层风速的模拟情况如何,目前仍缺少分析和检验.本文利用中国区域近地层风速观测资料,检验评估了参与IPCC AR4"20世纪气候耦合模式模拟"(20C3M)的19个伞球气候模式和国家气候中心新一代伞球气候模式(BCC_CSM1.0.1)模拟的1956-1999年中国近地层(10m)风速及其变化的模拟能力.研究发现,20个伞球气候模式基本上都能模拟出中国多年年(或季)平均风速分布状况,但模式模拟的平均风速一般小于观测值,尤以观测风速较大的北部和西北部地区模拟值偏小显著.气候模式模拟秋冬季风速分布的能力强于模拟夏春季的能力.模式基本上能模拟出冬、春季平均风速大于夏、秋季平均风速,但是模拟不出春、冬、夏、秋季平均风速依次减小的季节变化特征.模式及模式集成难以模拟出观测到的近50年中国年(或季)平均风速明显减小的变化趋势,少数模式能模拟出年(或季)平均风速略呈减小的变化趋势,但与观测值比相差约一个量级.模式对北部和西南部地区平均风速的变化模拟效果较好,而模式难以模拟东南-南部地区风速变化特征.  相似文献   

15.
For the construction of regional climate change scenarios spanning a relevant fraction of the spread in climate model projections, an inventory of major drivers of regional climate change is needed. For the Netherlands, a previous set of regional climate change scenarios was based on the decomposition of local temperature/precipitation changes into components directly linked to the level of global warming, and components related to changes in the regional atmospheric circulation. In this study this decomposition is revisited utilizing the extensive modelling results from the CMIP5 model ensemble in support for the 5th IPCC assessment. Rather than selecting a number of GCMs based on performance metrics or relevant response features, a regression technique was developed to utilize all available model projections. The large number of projections allows a quantification of the separate contributions of emission scenarios, systematic model responses and natural variability to the total likelihood range. Natural variability plays a minor role in modelled differences in the global mean temperature response, but contributes for up to 50 % to the range of mean sea level pressure responses and local precipitation. Using key indicators (“steering variables”) for the temperature and circulation response, the range in local seasonal mean temperature and precipitation responses can be fairly well reproduced.  相似文献   

16.
Three statistical downscaling methods are compared with regard to their ability to downscale summer (June–September) daily precipitation at a network of 14 stations over the Yellow River source region from the NCEP/NCAR reanalysis data with the aim of constructing high-resolution regional precipitation scenarios for impact studies. The methods used are the Statistical Downscaling Model (SDSM), the Generalized LInear Model for daily CLIMate (GLIMCLIM), and the non-homogeneous Hidden Markov Model (NHMM). The methods are compared in terms of several statistics including spatial dependence, wet- and dry spell length distributions and inter-annual variability. In comparison with other two models, NHMM shows better performance in reproducing the spatial correlation structure, inter-annual variability and magnitude of the observed precipitation. However, it shows difficulty in reproducing observed wet- and dry spell length distributions at some stations. SDSM and GLIMCLIM showed better performance in reproducing the temporal dependence than NHMM. These models are also applied to derive future scenarios for six precipitation indices for the period 2046–2065 using the predictors from two global climate models (GCMs; CGCM3 and ECHAM5) under the IPCC SRES A2, A1B and B1scenarios. There is a strong consensus among two GCMs, three downscaling methods and three emission scenarios in the precipitation change signal. Under the future climate scenarios considered, all parts of the study region would experience increases in rainfall totals and extremes that are statistically significant at most stations. The magnitude of the projected changes is more intense for the SDSM than for other two models, which indicates that climate projection based on results from only one downscaling method should be interpreted with caution. The increase in the magnitude of rainfall totals and extremes is also accompanied by an increase in their inter-annual variability.  相似文献   

17.
This paper describes the development and application of a technique for using satellite altimeter measurements as boundary data to drive the nearshore spectral wave model, SWAN. The aim was to assess the impact in coastal areas of extreme events or changes in offshore climatology and to extend the usefulness of satellite altimetry further inshore.

For the purpose of verifying the technique, three test areas where both bathymetry and some in situ data were available were chosen. The technique could, potentially, be applied to any coastal location where there is bathymetric information although, as the results reported in this paper show, intelligence must be used in adapting the methodology for different sites. It is also necessary to have information on the local wind field from either models or measurements.

The experiments at the three test areas demonstrated that there is not a simple relationship between the offshore wave height climate and the inshore climate in a particular region. Important complicating factors are bathymetry, tidal range and incident wave angle. As was most clearly demonstrated in the Carmarthen Bay test area, bathymetric complexity leads to high spatial variation in the amount of wave energy dissipated close to the coast. In the study of extreme wave events described in this paper the exact value of the local wind field was not found to be critical.

This work was a first trial combining wave climatology derived from satellite altimetry with a third generation coastal wave model so was necessarily experimental. The general trends and patterns of spatial variation obtained are encouraging but there remains significant, unquantifiable uncertainty in the results. Better observations of nearshore waves, improved understanding of the joint probability distribution of water level and waves as well as more knowledge of future climate change would all improve accuracy.  相似文献   

18.
Projections of a drier, warmer climate in the U.S. Southwest would complicate management of the Colorado River system—yet these projections, often based on coarse resolution global climate models, are quite uncertain. We present an approach to understanding future Colorado River discharge based on land surface characterizations that map the Colorado River basin’s hydrologic sensitivities (e.g., changes in streamflow magnitude) to annual and seasonal temperature and precipitation changes. The approach uses a process-based macroscale land surface model (LSM; in this case, the Variable Infiltration Capacity hydrologic model, although methods are applicable to any LSM) to develop sensitivity maps (equivalent to a simple empirical model), and uses these maps to evaluate long-term annual streamflow responses to future precipitation and temperature change. We show that global climate model projections combined with estimates of hydrologic sensitivities, estimated for different seasons and at different change increments, can provide a basis for approximating cumulative distribution functions of streamflow changes similar to more common, computationally intensive full-simulation approaches that force the hydrologic model with downscaled future climate scenarios. For purposes of assessing risk, we argue that the sensitivity-based approach produces viable first-order estimates that can be easily applied to newly released climate information to assess underlying drivers of change and bound, at least approximately, the range of future streamflow uncertainties for water resource planners.  相似文献   

19.
依据IPCC第六次评估报告（AR6）第一工作组报告第四章的内容,对未来全球气候的预估结果进行解读。报告对21世纪全球表面气温、降水、大尺度环流和变率模态、冰冻圈和海洋圈的可能变化进行了系统评估,并对2100年以后的气候变化做了合理估计。评估指出全球平均表面气温将在未来20年内达到或超过1.5℃,平均降水也将增加,但随季节和区域而异,同时变率将增大。大尺度环流和变率模态受内部变率影响较大。到21世纪末,北冰洋可能出现无冰期;全球海洋会继续酸化,平均海平面将持续上升,百年内上升幅度依赖不同排放情景,都在2100年后继续升高。在最新的评估中采用多种约束方法,减小了预估不确定性的范围。AR6对于低排放情景以及“小概率高增暖情节”的关注为应对气候变化提供了更多、更完整的信息。综合报告的评估结果指出,未来需要进一步减小区域,特别是季风区气候预估的不确定性,并从科学研究和模式发展两方面加强我国气候预估能力的建设。  相似文献   

20.
A variable-grid atmospheric general circulation model, LMDZ, with a local zoom over southeast China is used to investigate regional climate changes in terms of both means and extremes. Two time slices of 30?years are chosen to represent, respectively, the end of the 20th century and the middle of the 21st century. The lower-boundary conditions (sea-surface temperature and sea-ice extension) are taken from the outputs of three global coupled climate models: Institut Pierre-Simon Laplace (IPSL), Centre National de Recherches Météorologiques (CNRM) and Geophysical Fluid Dynamics Laboratory (GFDL). Results from a two-way nesting system between LMDZ-global and LMDZ-regional are also presented. The evaluation of simulated temperature and precipitation for the current climate shows that LMDZ reproduces generally well the spatial distribution of mean climate and extreme climate events in southeast China, but the model has systematic cold biases in temperature and tends to overestimate the extreme precipitation. The two-way nesting model can reduce the ??cold bias?? to some extent compared to the one-way nesting model. Results with greenhouse gas forcing from the SRES-A2 emission scenario show that there is a significant increase for mean, daily-maximum and minimum temperature in the entire region, associated with a decrease in the number of frost days and an increase in the heat wave duration. The annual frost days are projected to significantly decrease by 12?C19?days while the heat wave duration to increase by about 7?days. A warming environment gives rise to changes in extreme precipitation events. Except two simulations (LMDZ/GFDL and LMDZ/IPSL2) that project a decrease in maximum 5-day precipitation (R5d) for winter, other precipitation extremes are projected to increase over most of southeast China in all seasons, and among the three global scenarios. The domain-averaged values for annual simple daily intensity index (SDII), R5d and fraction of total rainfall from extreme events (R95t) are projected to increase by 6?C7, 10?C13 and 11?C14%, respectively, relative to their present-day values. However, it is clear that more research will be needed to assess the uncertainties on the projection in future of climate extremes at local scale.  相似文献   

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