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1.
Monthly mean temperatures at 562 stations in China are estimated using a statistical downscaling technique. The technique used is multiple linear regressions （MLRs） of principal components （PCs）. A stepwise screening procedure is used for selecting the skilful PCs as predictors used in the regression equation. The predictors include temperature at 850 hPa （7）, the combination of sea-level pressure and temperature at 850 hPa （P＋T） and the combination of geo-potential height and temperature at 850 hPa （H＋T）. The downscaling procedure is tested with the three predictors over three predictor domains. The optimum statistical model is obtained for each station and month by finding the predictor and predictor domain corresponding to the highest correlation. Finally, the optimum statistical downscaling models are applied to the Hadley Centre Coupled Model, version 3 （HadCM3） outputs under the Special Report on Emission Scenarios （SRES） A2 and B2 scenarios to construct local future temperature change scenarios for each station and month, The results show that （1） statistical downscaling produces less warming than the HadCM3 output itself; （2） the downscaled annual cycles of temperature differ from the HadCM3 output, but are similar to the observation; （3） the downscaled temperature scenarios show more warming in the north than in the south; （4） the downscaled temperature scenarios vary with emission scenarios, and the A2 scenario produces more warming than the B2, especially in the north of China.  相似文献   

2.
统计降尺度法对华北地区未来区域气温变化情景的预估   总被引：31，自引：1，他引：31  
迄今为止，大部分海气耦合气候模式（AOGCM）的空间分辨率还较低，很难对区域尺度的气候变化情景做合理的预测。降尺度法已广泛用于弥补AOGCM在这方面的不足。作者采用统计降尺度方法对1月和7月华北地区49个气象观测站的未来月平均温度变化情景进行预估。采用的统计降尺度方法是主分量分析与逐步回归分析相结合的多元线性回归模型。首先，采用1961～2000年的 NCEP再分析资料和49个台站的观测资料建立月平均温度的统计降尺度模型，然后把建立的统计降尺度模型应用于HadCM3 SRES A2 和 B2 两种排放情景， 从而生成各个台站1950～2099年1月份和7月份温度变化情景。结果表明:在当前气候条件下，无论1月还是7月，统计降尺度方法模拟的温度与观测的温度有很好的一致性，而且在大多数台站，统计降尺度模拟气温与观测值相比略微偏低。对于未来气候情景的预估方面，无论1月还是7月，也无论是HadCM3 SRES A2 还是B2排放情景驱动统计模型，结果表明大多数的站点都存在温度的明显上升趋势，同时7月的上升趋势与1月相比偏低。  相似文献   

3.
A prerequisite of a successful statistical downscaling is that large-scale predictors simulated by the General Circulation Model (GCM) must be realistic. It is assumed here that features smaller than the GCM resolution are important in determining the realism of the large-scale predictors. It is tested whether a three-step method can improve conventional one-step statistical downscaling. The method uses predictors that are upscaled from a dynamical downscaling instead of predictors taken directly from a GCM simulation. The method is applied to downscaling of monthly precipitation in Sweden. The statistical model used is a multiple regression model that uses indices of large-scale atmospheric circulation and 850-hPa specific humidity as predictors. Data from two GCMs (HadCM2 and ECHAM4) and two RCM experiments of the Rossby Centre model (RCA1) driven by the GCMs are used. It is found that upscaled RCA1 predictors capture the seasonal cycle better than those from the GCMs, and hence increase the reliability of the downscaled precipitation. However, there are only slight improvements in the simulation of the seasonal cycle of downscaled precipitation. Due to the cost of the method and the limited improvements in the downscaling results, the three-step method is not justified to replace the one-step method for downscaling of Swedish precipitation.  相似文献   

4.
Two approaches of statistical downscaling were applied to indices of temperature extremes based on percentiles of daily maximum and minimum temperature observations at Beijing station in summer during 1960-2008. One was to downscale daily maximum and minimum temperatures by using EOF analysis and stepwise linear regression at first, then to calculate the indices of extremes; the other was to directly downscale the percentile-based indices by using seasonal large-scale temperature and geo-potential height records. The cross-validation results showed that the latter approach has a better performance than the former. Then, the latter approach was applied to 48 meteorological stations in northern China. The cross-validation results for all 48 stations showed close correlation between the percentile-based indices and the seasonal large-scale variables. Finally, future scenarios of indices of temperature extremes in northern China were projected by applying the statistical downscaling to Hadley Centre Coupled Model Version 3 (HadCM3) simulations under the Representative Concentration Pathways 4.5 (RCP 4.5) scenario of the Fifth Coupled Model Inter-comparison Project (CMIP5). The results showed that the 90th percentile of daily maximum temperatures will increase by about 1.5℃, and the 10th of daily minimum temperatures will increase by about 2℃ during the period 2011-35 relative to 1980-99.  相似文献   

5.
利用NCEP/NCAR再分析资料和NOAA海温资料,用EOF、相关分析等方法,分析了1960—2010年500 hPa和100 hPa等压面上北半球后冬(2月)极涡面积和前春(4月)北太平洋(20~60 °N,120 °E~120 °W)海表温度(SST)的变化特征,揭示了二者的时空联系。结果表明:近50 a来,(1)冬季北半球500 hPa和100 hPa极涡面积整体经历了先扩张后收缩的变化。春季北太平洋SST经历了先降低后升高的变化。其突变时间与500 hPa极涡面积的突变时间相近,均出现在1987年,且与后冬500 hPa大西洋欧洲大陆区(Ⅳ区)极涡面积相关更好。(2)春季北太平洋SST的EOF第一模态空间型表现为PDO,第二模态表现为三极子型,突变分别出现在1980s初期和中期。(3)北太平洋SST与500 hPa Ⅳ区极涡面积相关的空间分布表现为:当前期春季北太平洋中部海温异常偏高(低),南部和北部海温异常偏低(高),使得下一个冬季500 hPa Ⅳ区极涡面积的扩大(缩小),这种空间遥相关型对应着海温的第二模态。北太平洋海温异常以第一模态空间型居多,但是对后冬北半球极涡面积影响大的却是第二模态。(4)当前春北太平洋SST呈第二模态时,对应次年冬季中高纬度对流层温度"上冷下暖",极地东风和绕极西风环流加强,极涡面积偏大。  相似文献   

6.
Statistical downscaling of daily precipitation over Sweden using GCM output   总被引：3，自引：2，他引：1  
A classification of Swedish weather patterns (SWP) was developed by applying a multi-objective fuzzy-rule-based classification method (MOFRBC) to large-scale-circulation predictors in the context of statistical downscaling of daily precipitation at the station level. The predictor data was mean sea level pressure (MSLP) and geopotential heights at 850 (H850) and 700 hPa (H700) from the NCEP/NCAR reanalysis and from the HadAM3 GCM. The MOFRBC was used to evaluate effects of two future climate scenarios (A2 and B2) on precipitation patterns on two regions in south-central and northern Sweden. The precipitation series were generated with a stochastic, autoregressive model conditioned on SWP. H850 was found to be the optimum predictor for SWP, and SWP could be used instead of local classifications with little information lost. The results in the climate projection indicated an increase in maximum 5-day precipitation and precipitation amount on a wet day for the scenarios A2 and B2 for the period 2070–2100 compared to 1961–1990. The relative increase was largest in the northern region and could be attributed to an increase in the specific humidity rather than to changes in the circulation patterns.  相似文献   

7.
Summary Uncertainty analysis is used to make a quantitative evaluation of the reliability of statistically downscaled climate data representing local climate conditions in the northern coastlines of Canada. In this region, most global climate models (GCMs) have inherent weaknesses to adequately simulate the climate regime due to difficulty in resolving strong land/sea discontinuities or heterogeneous land cover. The performance of the multiple regression-based statistical downscaling model in reproducing the observed daily minimum/maximum temperature, and precipitation for a reference period (1961–1990) is evaluated using climate predictors derived from NCEP reanalysis data and those simulated by two coupled GCMs (the Canadian CGCM2 and the British HadCM3). The Wilcoxon Signed Rank test and bootstrap confidence-interval estimation techniques are used to perform uncertainty analysis on the downscaled meteorological variables. The results show that the NCEP-driven downscaling results mostly reproduced the mean and variability of the observed climate very well. Temperatures are satisfactorily downscaled from HadCM3 predictors while some of the temperatures downscaled from CGCM2 predictors are statistically significantly different from the observed. The uncertainty in precipitation downscaled with CGCM2 predictors is comparable to the ones downscaled from HadCM3. In general, all downscaling results reveal that the regression-based statistical downscaling method driven by accurate GCM predictors is able to reproduce the climate regime over these highly heterogeneous coastline areas of northern Canada. The study also shows the applicability of uncertainty analysis techniques in evaluating the reliability of the downscaled data for climate scenarios development. Authors’ addresses: Dr. Yonas B. Dibike, NSERC Research Fellow, OURANOS Consortium, 550 Sherbrooke Street West, 19th Floor, Montreal (QC) H3A 1B9, Canada; Philippe Gachon, Adaptation and Impact Research Division (AIRD), Atmospheric Science and Technology Directorate, Environment Canada at Ouranos, Montreal (QC), Canada; André St-Hilaire and Taha B. M. J. Ouarda, Institut National de la Recherche Scientifique Centre Eau, Terre & Environnement (INRS-ETE), University of Québec, 490 Rue de La Couronne, Québec (QC) G1K 9A9, Canada; Van T.-V. Nguyen, Department of Civil Engineering and Applied Mechanics, McGill University, 817 Sherbrooke Street West, Montreal (QC) H3A 2K6, Canada.  相似文献   

8.
降水作为全球水循环的重要组成,与人们的生产生活密切相关.有效的降水预测对于防灾减灾,以及经济的可持续发展至关重要.然而,由于影响降水过程的复杂性,当前降水预测还存在诸多挑战.针对我国东部夏季降水,我们提出年际增量结合经验正交分解的新统计预测方法.首先计算降水年际增量的主模态,然后针对主模态时间序列构建预测模型,用预测的...  相似文献   

9.
中国21世纪气候变化的情景模拟分析   总被引：33，自引：3，他引：33  
利用HadCM2和ECHAM4气候模式比较分析了温室气体排放综合效果相当于CO2浓度逐年递增1％情景下中国区域21世纪地面气温和降水量的变化趋势。结果表明：在温室气体渐进递增情景下，至21世纪末期，相对于1961-1990年的气候基准值，全国地面平均气温增幅可达5—6℃。与地面气温的变化相比，降水量的波动幅度较大，但全国范围内降水量变化的总趋势也是增加的。中国区域地面气温和降水量变化的地理分布显示：降水量的增加主要集中在南方区域，HadCM2预测21世纪末期降水增加可达0．9mm／d，ECHAM4预测可达0．6mm／d；ECHAM4模式模拟的气温增幅比HadCM2高，尤其是在冬季及中国北方和青藏高原地区，而HadCM2模式模拟的降水量的增加较大，但两个气候模式模拟的地面气温和降水量变化的总趋势大体一致。  相似文献   

10.
吴昊旻  黄安宁  何清  赵勇 《气象学报》2013,71(2):261-274
利用IPCC AR5中BCC-CSM1.1(Beijing Climate Center Climate System Model version 1.1)的历史试验和4类典型 排放路径情景下未来预估试验结果, 在使用CRU(Climatic Research Unit)资料验证BCC-CSM1.1性能的基础上, 采用趋势分 析、滑动平均以及经验正交函数(EOF)等方法, 研究2011-2060年中亚地区年平均气温的时空演变特征。与CRU 资料的对 比分析发现BCC-CSM1.1能较好地模拟过去109a(1901-2009年)中亚地区气温的显着上升趋势及气候态的空间分布特征。 预估试验结果表明, 中亚地区在未来50a整体呈现变暖趋势, 并且, 随着温室气体排放浓度的升高, 气温的升高趋势愈加明 显, 同时增温显着区域也明显增大。经验正交函数分解主要模态还是延续过去的分布特征:经验正交函数分解第1模态及其 所对应的时间系数显示中亚地区年平均地面气温在未来50a(2011-2060年)呈现出全场一致的升高趋势, 升高强度随着温 室气体排放浓度的增加而增强, 进一步的分析表明, 不同典型排放路径下预估的未来50a中亚地区年平均地面气温的经验正 交函数分解第1模态在中亚上空850hPa等压面上均对应有一个反气旋(气旋)性异常环流, 在这个异常环流控制下, 中亚地 区年平均地面气温变化表现为全场一致的特征。经验正交函数分解第2模态呈现出中亚地区地面气温变化南北反位相的基 本特征, 相应的时间系数主要表现为小幅度波动, 变化趋势特征不明显。  相似文献   

11.
Based on the surface 2?m monthly minimum temperature from the National Centers for Environmental Prediction/National Center for Atmospheric Research reanalysis dataset, the spatial and temporal characteristics of winter minimum temperature during 1961–2010 have been analyzed in China. Results showed that the minimum temperature in China has a significant increasing rate of 0.25° per decade calculated by the Mann–Kendall statistical test, which is consistent with the global warming trend. Empirical orthogonal function (EOF) analysis reveals that there are three main patterns that can explain more than 57.6% of the total variance of the winter minimum temperature. The EOF1, EOF2, and EOF3 account for 34.8%, 13.5%, and 13.5% of the total inter-annual variance, respectively. The EOF1, EOF2, and EOF3 patterns are synchronous in northern China, central China, and on the Tibetan Plateau. There exist a decrease trend in the corresponding time coefficients of EOF1 and EOF2 and an increase trend in that of EOF3 since the 1960s. Both the corresponding time coefficients of EOF1 and EOF2 have significant positive correlations with the 500?hPa geopotential heights of the Arctic region and negative correlations in the regions lower than 40°N, while a significant positive correlation is found between the corresponding time coefficients of EOF3 and 500?hPa geopotential heights in the low latitudes. This suggests that rapid warming occurs in northern China and on the Tibetan Plateau, while the weakest trend locates in southeast China. Thus, warming in winter is more pronounced at higher altitudes and latitudes. These patterns are tightly connected with the atmospheric circulation.  相似文献   

12.
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13.
通过对1983—2002年国家气候中心NCC_CGCM季节预报模式的2月初始场的5个预测场 (500 hPa高度场,200 hPa经向风、纬向风场,850 hPa经向风、纬向风场) 与NCEP实况场的相关检验,指出模式预测与实况有一定差距,但也存在预报效果好的区域,其中预报效果最好的是200 hPa和850 hPa纬向风场,正相关达到95%信度的点数最多;500 hPa高度场正相关达到95%信度的点数最少;利用模式预报效果好的区域的预测值,对2003—2007年长江中下游区域夏季降水指数进行释用,预报准确率达到80%;对比模式在该地区的降水预报以及仅用模式高度场的解释预报发现,用挑选有用信息后的预报效果更好。该方法在全国其他14个区夏季降水的释用中,江南区和内蒙古区预报准确率也可达到80%。  相似文献   

14.
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   

15.
基于EOF分解的中期平均气温距平客观预报方法   总被引：1，自引：0，他引：1  
本文通过将500 hPa高度、850 hPa温度、海平面气压的预报与历史要素场进行EOF分解,并假定EOF分解空间函数(即特征向量)是基本稳定的,建立以EOF分解主分量系列的时间系数、预报站点附近基本要素值的时间序列与预报站点平均气温距平的多元线性逐步回归预报方程,结合ECMWF集合预报数值产品,生成全国范围未来10 d平均气温距平客观预报产品投入业务应用,并采用同号率方法检验。结果表明,客观预报产品在检验时段内,同号率平均值为0.77,明显高于ECMWF集合预报模式2 m温度直接计算得出的同类产品同号率0.63;该客观预报产品不仅在分布范围上,同时在距平幅度上预报效果均较好。此外,相关分析也证明同号率方法在检验中期时效气温距平预报中有其合理性。  相似文献   

16.
Summary Monthly mean temperature and monthly precipitation totals in two small catchments in the Czech Republic are estimated from large-scale 500 hPa height and 1000/500 hPa thickness fields using statistical downscaling. The method used is multiple linear regression. Whereas precipitation can be determined from large-scale fields with some confidence in only a few months of the year, temperature can be determined successfully. Principal components calculated separately from the height and thickness anomalies are identified as the best predictor set. The method is most accurate if the regression is performed using seasons based on three months. The test on an independent sample, consisting of warm seasons, confirms that the method successfully reproduces the difference in mean temperature between two climatic states, which indicates that this downscaling method is applicable for constructing scenarios of a future climate change. The ECHAM3 GCM is used for scenario construction. The GCM is shown to simulate surface temperature and precipitation with low accuracy, whereas the large-scale atmospheric fields are reproduced well; this justifies the downscaling approach. The observed regression equations are applied to 2xCO2 GCM output so that the model’s bias is eleminated. This procedure is then discussed and finally, temperature scenarios for the 2xCO2 climate are constructed for the two catchments. Received December 3, 1998 Revised December 4, 1999  相似文献   

17.
Summary  Four coupled atmosphere-ocean general circulation models were examined for the ability of their control runs to simulate present climate given present forcings. The area of study is mainly Cameroon and some of its surrounding areas (0–25° E, 5° S-30° N). These models are from the UK Meteorological Office Hadley Centre (HadCM2), the German Max-Planck-Institut für Meteorologie (ECHAM4), the Canadian Centre for Climate Modelling and Analysis (CGCM1) and the Australian Commonwealth Science and Industrial Research Organisation (CSIRO-Mk2). The ability of the models to reproduce the observed spatial and temporal patterns was studied. ECHAM4 and HadCM2 were found to reproduce the spatial pattern well, with a correlation of more than 90%. They also simulated the main annual features of both temperature and rainfall. The CSIRO-Mk2 model was slightly less successful and the CGCM1 had the worst results for the area, especially as concern rainfall. In view of these results, ECHAM4 and HADCM2 were used to evaluate projected changes in rainfall and temperature resulting from increased concentration of greenhouse gases in the atmosphere for the 30 year period 2040 to 2070. Received February 15, 1999/Revised March 10, 2000  相似文献   

18.
黄淮地区夏季降水的统计降尺度预测   总被引：3，自引：2，他引：1       下载免费PDF全文
利用1991-2011年黄淮地区夏季降水、NCEP/NCAR再分析资料和国家气候中心第2代动力气候模式（BCC_CSM1.1m）夏季回报结果,研究黄淮地区夏季降水降尺度预测模型和可预报性来源。诊断发现,黄淮地区夏季降水与同期南亚高压、乌拉尔山附近阻塞高压、西风急流、西太平洋赤道上空200 hPa纬向风场呈明显正相关。分析BCC_CSM1.1m对夏季环流的回报结果发现,模式对200 hPa和500 hPa位势高度场、200 hPa纬向风场和850 hPa经向风场上影响黄淮地区夏季降水的部分关键区域有较好的模拟能力。利用模式预报技巧较高且对黄淮地区夏季降水的影响有物理含义的环流特征作为预测因子,对比预测因子进行独立性筛选前后分别建立的降尺度预测模型发现,黄淮地区夏季降水预测与实况的距平符号一致率由61%提高到72%。预测技巧来源分析发现,降尺度预测能力与BCC_CSM1.1m对影响黄淮地区夏季降水的3个关键因子乌拉尔山附近环流、南亚高压、西太平洋赤道上空西风强弱的预测技巧密切相关,尤其是模式对西太平洋赤道上空西风的模拟能力起到决定性作用。  相似文献   

19.
基于NCEP/NCAR再分析资料, 采用EOF分解、滑动t检验、相关系数等方法对黑龙江省初夏降水及其前兆信号进行了诊断分析。结果表明, 黑龙江全省初夏降水距平的空间分布以总体一致型为主, 此外, 还呈现东西反向型。总体一致型模态时间系数在1993年前后有明显的突变点。分析突变点前后降水主成分与500hPa位势高度、200 hPa纬向风、850 hPa矢量风以及前期海温的关系, 发现在突变前后影响初夏降水的同期主要系统均为东北冷涡和高空西风急流轴, 但冬季(北半球, 下同)澳大利亚周边海温对初夏降水的影响在突变前后存在明显变化。突变前在澳洲西北部, 暖海温造成东亚南高北低环流, 东北冷涡强, 高空急流偏北; 突变后在澳洲东北部, 冷海温导致东亚“+, -, +”波列, 东北冷涡弱, 高空急流偏南。   相似文献   

20.
This study provides some guidance on the choice of predictor variables from both reanalysis products and the third version of the Canadian Coupled Global Climate Model (CGCM3) outputs for regression-based statistical downscaling models (SDMs) for climate change application in southern Québec (Canada). Twenty CGCM3 grid points and four surface observation sites in the study area were employed. Twenty-five deseasonalized predictors and four deseasonalized predictands (daily maximum and minimum temperatures, precipitation occurrence and wet day precipitation amount) were used to investigate correlation coefficients among predictors and to evaluate their predictive ability when used in a multiple linear regression (MLR) downscaling model. The basic statistical characteristics of vorticity at 1,000-, 850- and 500-hPa levels, U-component of velocity at 1,000-hPa level, temperature at 2?m (T 2) and wind direction at 1,000- and 500-hPa level of CGCM3 showed a larger difference with those of the NCEP reanalysis data. Therefore, those seven variables require high caution to be included as predictors in statistical downscaling models. Specific humidity at 1,000-, 850- and 500-hPa levels, geopotential height at 850- and 500-hPa levels and T 2 were the most sensitive predictors for future climate conditions (i.e. A1B and A2 emission scenarios). Specific humidity and geopotential height at different levels and T 2 were important explainable predictors for the daily temperatures. Mean sea level pressure, specific humidity, U and V components and divergence showed potential as predictors for daily precipitation. Spatial explained variance of MLRs between predictors of every different CGCM3 grid points and the four predictands showed large values at the CGCM3 grid points located near the observation sites, whereas relatively small values were shown at the CGCM3 grid points located more than 400?km from the sites. The explained variance of the downscaled predictands by predictors of three or four CGCM3 grid points located near the observation site produced 2–5% larger R-squares than those by predictors of the nearest grid point. The results illustrated that the use of predictors from more than one AOGCM grid points located near the observation site can increase the skill of the MLR downscaling models.  相似文献   

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