共查询到19条相似文献，搜索用时 163 毫秒
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场对场预报模型及其对降水的预报试验 总被引：1，自引：0，他引：1
用经验正交函数对预报因子场和预报对象场分别进行分解，将正交展开的时间系数作为预报因子和预报对象，提出了一种场对场预报模型，该模型考虑了预报系统的时变性，并利用云南５月份的雨量资料进行了预报试验。结果表明，用这种模型作区域性降水预报有一定的优越性。 相似文献
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动力延伸预报产品在广西月尺度降水滚动预测中的释用 总被引：1，自引：0，他引：1
对广西88个站全年各旬月尺度降水距平百分率作自然正交展开(EOF分解),选取累积方差贡献接近75%的前几个主成分为预报量.利用1982年至今的国家气候中心月动力延伸集合预报资料或回算实验资料,从月尺度平均500hPa位势高度、700hPaU、V向水平风速延伸预报场中选取初选预报因子,并运用EOF分解构建成综合预报因子,分别选取其中与各个预报分量相关程度高的主成分建立预报方程,滚动制作广西月尺度降水量预报.91个独立样本试验和实际应用证明,预报效果较好. 相似文献
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采用对站点气象要素场EOF(自然正交函数)展开，预报几个主要特征向量时间系数的思路，对国家气候中心的T63动力延伸预报产品解释应用，制作东北夏季定点、定量月气温预报。根据EOF展开的空间特征向量分布特征，分别对反映测站上空高度数值大小与长波系统强弱的高度距平、地转涡度等预报因子进行处理，进而建立预报模型。 相似文献
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利用球坐标系的正交系数族展开北半球５００ｈＰａ高度场，再用其展开系数与海南热带气旋长期预报六要素求相关，建立同期相关模型，并利用上年１－１２月５００ｈＰａ球谐系数及同年１－４月５００ｈＰａ球谐系数分别建立了海南省热带气旋长期预报六要素的预报模型。经使用检验，效果较好。 相似文献
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1动力延伸预报产品在辽宁短期气候预测中的释用《气象与环境学报》2006年第12期周德平基于1961年～2000年辽宁53个测站40a逐年的月气温距平和月降水距平百分率资料,根据EOF(经验正交函数)展开的空间特征向量分布特征,将前3个主要特征向量时间系数作为预报量,将500 hPa高度场的高度距平、地转涡度作为预报因 相似文献
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本文叙述用经验正交函数序列作梅雨结束期副热带高压天气形动的统计预报试验。试验用1960年6月1—30日20时每天的500毫巴高度资料统计计算经验函数。采用预报时间间隔为一天的时间序列自迴归方法,可以预报出副高西进、北抬与维持的趋势。预报结果几乎不受预报区域边界的影响,说明存在时间平流作用。 相似文献
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藻类叶绿素a浓度是反映太湖水体富营养化程度的重要参数指标。以太湖2010—2011年5—10月旬平均叶绿素a浓度和气象资料数据作为建模样本, 通过对气象资料进行主成分分析, 得到4种主要气象因子作为输入, 建立时间序列ARMA预测模型与BP神经网络预测模型, 并对2012年数据进行预测。利用两种模型在线性空间和非线性空间的预测优势, 将叶绿素a数据结构分解为线性自相关主体和非线性残差两部分。首先用ARMA模型预测序列的线性主体, 然后用BP模型对其非线性残差进行估计, 最终集成整个序列的预测结果, 建立了ARMA-BP预测模型。3种模型的预测效果为ARMA-BP＞BP＞ARMA。 相似文献
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Spatial patterns of mid-latitude large-scale ocean-atmosphere interaction on monthly to seasonal time scales have been observed to exhibit a similar structure in both the North Pacific and North Atlantic basins. These patterns have been interpreted as a generic oceanic response to surface wind anomalies, whereby the anomalous winds give rise to corresponding anomalous regions of surface heat flux and consequent oceanic cooling. This mechanistic concept is investigated in this study using numerical models of a global atmosphere and a mid-latitude ocean basin (nominally the Atlantic). The models were run in both coupled and uncoupled mode. Model output was used to generate multi-year time series of monthly mean fields. Empirical orthogonal function (EOF) and singular value decomposition (SVD) analyses were then used to obtain the principal patterns of variability in heat flux, air temperature, wind speed, and sea surface temperature (SST), and to determine the relationships among these variables. SVD analysis indicates that the turbulent heat flux from the ocean to the atmosphere is primarily controlled by the surface scalar wind speed, and to a lesser extent by air temperature and SST. The principal patterns of air-sea interaction are closely analogous to those found in observational data. In the atmosphere, the pattern consists of a simultaneous strengthening (or weakening) of the mid-latitude westerlies and the easterly trades. In the ocean there is cooling (warming) under the anomalously strong (weak) westerlies and trade winds, with a weaker warming (cooling) in the region separating the westerly and easterly wind regimes. These patterns occur in both coupled and uncoupled models and the primary influence of the coupling is in localizing the interaction patterns. The oceanic patterns can be explained by the principal patterns of surface heat flux and the attendant warming or cooling of the ocean mixed layer. 相似文献
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该文对1961—2002年我国长江三角洲地区36个地面观测站的年、月降水资料序列作均一性检验和订正试验, 以探讨我国年、月降水气候观测序列的均一化方法和思路。该文首先从与待检台站序列相关性较好、台站距离较近的台站中选取了若干站点作为待检台站的参考台站建立参考序列, 采用传统的标准正态检验 (SNHT) 方法, 对所研究的地区年降水的均一性进行了检验。检验结果显示, 该地区降水序列中存在非均一性现象。考虑到所选地区站点密度仍然不够, 文中还采用了一种不依赖于参考台站的思路, 对上述检验结果进行了进一步确认后, 最后对不连续序列进行了逐月订正调整。对比分析表明, 对序列的订正较为合理。在已有的研究基础上, 结合我国台站网络实际特点, 提出结合不同思路来研究我国降水量数据均一性是必要的和可行的, 应用该思路对于我国降水序列进行均一性研究具有一定的合理性和应用前景。 相似文献
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Long-Term Trend of Temperature Derived by Statistical Downscaling Based on EOF Analysis 总被引：1，自引：0，他引：1 
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下载免费PDF全文 This study analyzes the ability of statistical downscaling models in simulating the long-term trend of temperature and associated
causes at 48 stations in northern China in January and July 1961–2006. The statistical downscaling models are established
through multiple stepwise regressions of predictor principal components (PCs). The predictors in this study include temperature
at 850 hPa (T850), and the combination of geopotential height and temperature at 850 hPa (H850+T850). For the combined predictors,
Empirical Orthogonal Function (EOF) analysis of the two combined fields is conducted. The modeling results from HadCM3 and
ECHAM5 under 20C3M and SERS A1B scenarios are applied to the statistical downscaling models to construct local present and
future climate change scenarios for each station, during which the projected EOF analysis and the common EOF analysis are
utilized to derive EOFs and PCs from the two general circulation models (GCMs). The results show that (1) the trend of temperature
in July is associated with the first EOF pattern of the two combined fields, not with the EOF pattern of the regional warming;
(2) although HadCM3 and ECHAM5 have simulated a false long-term trend of temperature, the statistical downscaling method is
able to well reproduce a correct long-term trend of temperature in northern China due to the successful simulation of the
trend of main PCs of the GCM predictors; (3) when the two-field combination and the projected EOF analysis are used, temperature
change scenarios have a similar seasonal variation to the observed one; and (4) compared with the results of the common EOF
analysis, those of the projected EOF analysis have been much more strongly determined by the observed large-scale atmospheric
circulation patterns. 相似文献
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We examine the spatial patterns of variability of annual-mean temperature in the control runs of eight coupled atmosphere–ocean general circulation models (AOGCMs) and of observations. We characterize the patterns of variability using empirical orthogonal functions (EOFs) and using a new technique based on what we call quasi-EOFs. The quasi-EOFs are computed based on the spatial pattern of the correlation between the temperature variation at a given grid point and the temperature defined over a pre-determined reference region, with a different region used for each quasi-EOF. For the first four quasi-EOFs, the reference regions are: the entire globe, the Niño3 region, Western Europe, and Siberia. Since the latter three regions are the centers of strong anomalies associated with the El Niño, North Atlantic, and Siberian oscillations, respectively, the spatial pattern of the covariance with temperature in these regions gives the structure of the model or observed El Niño, North Atlantic, and Siberian components of variability. When EOF analysis is applied to the model control runs, the patterns produced generally have no similarity to the EOF patterns produced from observational data. This is due in some cases to large NAO-like variability appearing as part of EOF1 along with ENSO-like variability, rather than as separate EOF modes. This is a disadvantage of EOF analysis. The fraction of the model time-space variation explained by these unrealistic modes of variability is generally greater than the fraction explained by the principal observed modes of variability. When qEOF analysis is applied to the model data, all three natural modes of variability are seen to a much greater extent. However, the fraction of global time-space variability that is accounted for by the model ENSO variability is, in our analysis, less than observed for all models except the HadCM2 model, but within 20% for another three models. The space-time variation accounted for by the other modes is comparable to or somewhat larger than that observed in all models. As another teleconnection indicator, we examined both Southern Oscillation Index (SOI) and its relation to tropical Pacific Ocean temperature variations (the qEOF2 amplitude), and the North Atlantic Oscillation Index (NAOI) and its relation to North Atlantic region temperatures (the qEOF3 amplitude). All models exhibit a relationship between these indices, and the qEOF amplitudes are comparable to those observed. Furthermore, the models show realistic spatial patterns in the correlation between local temperature variations and these indices. 相似文献
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采用偏最小二乘回归建立了前汛期(4-6月)月降水量的预测模型,其中模型的输入因子是通过对3个前期月平均物理量场(海温场、500 hPa温度场和200 hPa高度场)大量的场相关因子采用系统降维的处理方法获得.为实现同时对多个站点的月降水量预测,将多站点的月降水量预测转换成多站点气候场的主分量预测,进一步利用气候场特征向量的近似不变性进行回算,从而得到多站点的逐站月降水量预测结果.对广西37个基本站的前汛期月降水量进行了6年独立样本检验,其预报结果显示该模型具有较好的预报能力. 相似文献
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基于低频振荡信号的中国南方冬半年持续性低温指数延伸期预报试验 总被引：4，自引：0，他引：4
利用1961-2009年36°N以南、108°E以东中国大陆191个站点逐日最低气温和NCEP/NCAR再分析日平均格点,研究与区域持续性低温事件有关的大气低频振荡信号,寻找可以在一定程度上表征不同类型区域持续性低温事件的指数,并尝试结合DERF2.0系统的预报产品进行持续性低温指数的延伸期预报试验。结果表明:（1）在研究范围内的区域持续性低温事件可以归纳为江北型、江南型和全区域型3类,其中江北型和江南型事件的环流背景差异体现在异常环流中心的纬度位置上,而全区域型事件属于增强型的江北型事件;（2）江北型和江南型区域平均最低气温时间序列的10-30 d低频分量的位相和强度变化与区域持续性低温事件的发生有显著关系,可以作为表征区域持续性低温事件指数和预报量;（3）100°-120°E范围内850 hPa温度场距平的经验正交函数分解前两个主模态具有显著的10-30 d变化周期,并且其空间结构分别与江北型和江南型事件的典型环流特征一致,前两个主模态时间系数能够作为持续性低温指数的预报因子;（4）检验结果表明,DERF2.0系统对上述预报因子有一定的预报能力。在延伸期预报时效内,利用统计学和动力学相结合的方法制作的持续性低温指数的预报效果好于模式直接预报的2 m气温,该预报方法有助于提升区域持续性低温事件的延伸预报能力。 相似文献
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Variables fields such as enstrophy, meridional-wind and zonal-wind variables are derived from monthly 500 hPa geopotential height anomalous fields. In this work, we select original predictors from monthly 500-hPa geopotential height anomalous fields and their variables in June of 1958 - 2001, and determine comprehensive predictors by conducting empirical orthogonal function (EOF) respectively with the original predictors. A downscaling forecast model based on the back propagation (BP) neural network is built by use of the comprehensive predictors to predict the monthly precipitation in June over Guangxi with the monthly dynamic extended range forecast products. For comparison, we also build another BP neural network model with the same predictands by using the former comprehensive predictors selected from 500-hPa geopotential height anomalous fields in May to December of 1957 - 2000 and January to April of 1958 - 2001. The two models are tested and results show that the precision of superposition of the downscaling model is better than that of the one based on former comprehensive predictors, but the prediction accuracy of the downscaling model depends on the output of monthly dynamic extended range forecast. 相似文献
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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
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Principal component or Empirical Orthogonal Function (EOF) analysis is applied to tsunameter records by treating them as two-dimensional signals, where the second dimension is created by breaking a single time series into cycles and treating the cycle number as a second dimension. Under certain conditions, principal components calculated from different records are shown to determine the same functional space. Signal decomposition into pre-calculated principal components is used to predict or extract the tidal component of a record. This work shows that EOF processing allows for short-term tidal predictions at tsunami buoy locations with the precision of more advanced methods and with minimal a priori knowledge about tidal dynamics. Also shown is that filtering in EOF domain is sensitive to the non-tidal component of a record and therefore presents a tool for early tsunami detection and quantification. 相似文献