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1.
Fragments of deep-ocean tidal records up to 3 days long belong to the same functional sub-space, regardless of the record’s origin. The tidal sub-space basis can be derived via Empirical Orthogonal Function (EOF) analysis of a tidal record of a single buoy. Decomposition of a tsunami buoy record in a functional space of tidal EOFs presents an efficient tool for a short-term tidal forecast, as well as for an accurate tidal removal needed for early tsunami detection and quantification [Tolkova, E., 2009. Principal component analysis of tsunami buoy record: tide prediction and removal. Dyn. Atmos. Oceans 46 (1–4), 62–82] EOF analysis of a time series, however, assumes that the time series represents a stationary (in the weak sense) process. In the present work, a modification of one-dimensional EOF formalism not restricted to stationary processes is introduced. With this modification, the EOF-based de-tiding/forecasting technique can be interpreted in terms of a signal passage through a filter bank, which is unique for the sub-space spanned by the EOFs. This interpretation helps to identify a harmonic content of a continuous process whose fragments are decomposed by given EOFs. In particular, seven EOFs and a constant function are proved to decompose 1-day-long tidal fragments at any location. Filtering by projection into a reduced sub-space of the above EOFs is capable of isolating a tsunami wave within a few millimeter accuracy from the first minutes of the tsunami appearance on a tsunami buoy record, and is reliable in the presence of data gaps. EOFs with ∼3-day duration (a reciprocal of either tidal band width) allow short-term (24.75 h in advance) tidal predictions using the inherent structure of a tidal signal. The predictions do not require any a priori knowledge of tidal processes at a particular location, except for recent 49.5 h long recordings at the location. 相似文献
2.
EOF/PCA诊断气象变量场问题的新探讨 总被引：13，自引：3，他引：10
进一步论证了经验正交函数/主分量分析(EOF/PCA)在气象变量场诊断中的物理内涵,证明基于EOF/PCA的R型和Q型展开,可描述为气象变量场主要振荡型分解和主要空间分布型分解两种方案.前者表明,气象变量场的准周期振荡可分解为各主分量的周期振荡,它们各自等价于不同网格点(或站点)以其载荷为权重的迭加周期振荡,因此,气象变量场准周期振荡可视为来自不同周期源(网格点或站点)的准周期振荡逐层叠加的结果;后者表明,气象变量场的水平空间分布可视为各种主要空间分布型的叠加,而Q型展开才是对各种主要空间分布型的正交分解.由此深化了EOF/PCA气象变量场诊断的物理内涵. 相似文献
3.
气象场序列几种插补方案的对比试验 总被引：1，自引：0，他引：1
采用基于 Ｅ Ｏ Ｆ Ｓ的主分量回归（ Ｐ Ｃ Ｒ）、 Ｅ Ｏ Ｆ Ｓ迭代法（ Ｉ Ｅ Ｏ Ｆ）和基于主分量典型相关的典型变量回归（ Ｃ Ｖ Ｒ）３ 种不同的统计插补计算方案,对同一区域同一种气象要素序列进行缺测资料的插补试验。结果表明,各种方案插补精度都与参数选择有关,无论缺测站点空间分布类型如何,当缺测点数小于 ６０ ％ 时,３ 种方案均有较好效果,以 Ｃ Ｖ Ｒ 最佳,且随缺测年数增长, Ｃ Ｖ Ｒ 优势更显著。 相似文献
4.
对1952—1980年我国连续的月地面气温用时间序列ARMA（p、q）模型进行随机建模。月温度由60个站组成，用经验正交函数加以展开，取不同的样本长度即348,336和300月，以便考察经验正交展开的稳定性。前四个主成分，即z1,z2,z3,z4取为多维时间序列的变数，因为它们的总方差贡献达99.26%。在这四个主成分序列中的决定性周期用周期图和最大熵方法加以揭露。对一维变量zi,(i=1,2,3,4)的ARMA（p,q）的模型识别用Pandit-Wu方法进行，这样就可求得实验模型。用zi模型的外推值来预报月温度场。距平预报的命中率评分为78.3%，高于目前的业务长期天气预报。 相似文献
5.
In an attempt to clearly separate the volcanic signal,we use a mixture of principal componentanalysis(PCA)and superposed epoch analysis to identify volcanic signal in the global surface tem-perature field.In this way,the spatial and temporal pattern of volcanic signals is identified in theglobal surface temperature records.Our results show that the strongest ENSO and volcanic signalsare related with the first and the third principal components respectively.Both ENSO and volcanicsignals have responses in the second principal component. 相似文献
6.
7.
显著经验正交函数分析及其在淮河流域暴雨研究中的应用 总被引：1，自引：0，他引：1
经验正交函数分解（EOF）是气候特征研究中常用的分析方法,但由于方法本身的原因,EOF 主要模态不一定都能有效揭示资料场包含的气候模态。利用中国基本站和基准站1950—2009年逐日降水资料,运用显著经验正交函数分解（Disˉ tinct EOF,DEOF）方法研究了淮河流域暴雨的统计特征。结果表明 DEOF 第1模态呈现了淮河流域暴雨量在南北方向上存在相反的变化,即流域中部、南部偏多（偏少）时,北部则偏少（偏多）,第1主成分具有显著的16—17 a 周期性变化,表明流域南北的旱涝变化存在年代际振荡;第2模态表现了淮河流域中部暴雨量的异常变化,第2主成分有明显的线性趋势,说明近50年来流域中部地区暴雨量有明显的上升趋势,并且在1990年前后由偏少转为偏多。对比 DEOF 和 EOF 的分析结果,发现DEOF 能排除资料场中与随机扩散模型相关性较高的空间特征,能抓住与随机扩散模型有显著差异的分布特征并凸出显示出来,能从较强的背景噪声中凸出物理信号,因而能更好地估计真实的气候模态。 相似文献
8.
C. V. Singh 《Meteorology and Atmospheric Physics》2004,85(4):227-234
Summary The present study involves the use of Empirical Orthogonal Function (EOF) analysis/Principal Component Analysis (PCA) to compare the dominant rainfall patterns from normal rainfall records over India, coupled with the major modes of the Outgoing Long-wave Radiation (OLR) data for the period (1979–1988) during the monsoon period (June–September). To understand the intraseasonal and interannual variability of the monsoon rainfall, daily and seasonal anomalies have been obtained by using the (EOF) analysis. Importantly, pattern characteristics of seasonal monsoon rainfall covering 68 stations in India are highlighted.The purpose is to ascertain the nature of rainfall distribution over the Indian continent. Based on this, the percentage of variance for both the rainfall and OLR data is examined. OLR has a higher spatial coherence than rainfall. The first principal component of rainfall data shows high positive values, which are concentrated over northeast as well as southeast, whereas for the OLR, the area of large positive values is concentrated over northwest and lower value over south India apart from the Indian ocean. The first five principal components explain 92.20% of the total variance for the rainfall and 99.50% of the total variance for the outgoing long-wave radiation. The relationship between monsoon rainfall and Southern Oscillations has also been examined and for the Southern Oscillations, it is 0.69 for the monsoon season. The El-Niño events mostly occurred during Southern Oscillations, i.e. Walker circulation. It has been found that the average number of low pressure system/low pressure system days play an important role during active (flood) or inactive (drought) monsoon year, but low pressure system days play more important role in comparison to low pressure systems and their ratio are (16:51) and (13:25) respectively. Significantly, the analysis identifies the spatial and temporal pattern characteristics of possible physical significance. 相似文献
9.
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
10.
J. Garc��a-Serrano B. Rodr��guez-Fonseca I. Blad�� P. Zurita-Gotor A. de la C��mara 《Climate Dynamics》2011,37(9-10):1727-1743
The dominant variability modes of the North Atlantic-European rotational flow are examined by applying a principal component analysis (PCA/EOF) to the 200?hPa streamfunction mid-winter anomalies (Jan?CFeb monthly means). The results reveal that, when this norm is used, the leading mode (EOF1) does not correspond to the traditional North Atlantic Oscillation (NAO, which appears in our analysis as the second leading mode, EOF2) but is the local manifestation of the leading hemispheric streamfunction EOF. The regression of this regional mode onto the global SST field exhibits a clear El Ni?o signature, with no signal over the Atlantic, while the associated upper height anomalies resemble the Tropical/Northern Hemisphere (TNH) pattern. East of North America, this TNH-like wavetrain produces a meridional dipole-like pattern at lower levels. Although in some ways this pattern resembles the NAO (EOF2), the dynamics of these two modes are very different in that only EOF2 is associated with a latitudinal shift of the North Atlantic stormtrack. Thus, the choice of the streamfunction norm in the EOF analysis allows the separation of two different phenomena that can produce similar dipolar surface pressure anomalies over the North Atlantic but that have different impact on European climate. These two modes also differ on their contribution to variability at lower levels: while NAO-EOF2 is mostly confined to the North Atlantic, TNH-EOF1 has a more annular, global character. At upper levels NAO-EOF2 also produces a global pattern but with no annular structure, reminiscent of the ??circumglobal?? teleconnection. 相似文献
11.
利用广东省25个台站1980年至2012年4-9月份的降水量资料,采用小波分析、EOF和REOF方法对夏半年降水量的周期振荡、空间异常特征以及时间变化规律进行诊断分析研究。结果表明：广东省夏半年降水总量存在显著的4a、7a和13a周期振荡,且4a周期振荡信号最强,为第一主周期,7a和13a分别为第二、第三主周期。其主要异常模态表现为一致偏少或一致偏多、沿海与内陆反向型。广东省夏半年降水量的异常敏感区域为粤西北区、粤西南区和粤东北区。三个区域近几年夏半年降水量均表现为减少趋势,其中粤东北区降水量减少幅度较大。 相似文献
12.
The procedures involved in constructing data banks for use in climatological research are described, using examples from work done in the Climatic Research Unit. Such data banks will normally have two component parts: the meteorological records themselves, and the accompanying documentary and information systems.As a first step, meteorological records appropriate for the intended application of the data bank must be collected and stored, commonly in a computer. Individual records must then be merged into a form convenient for the user. For example, all records from one geographical region may be stored in one computer file. Procedures for quality control of the data are discussed. We emphasize the need to ensure that records are homogeneous, i.e., that they do not contain spurious jumps or trends caused by non-climatic factors such as site change or urbanization. Some techniques to correct inhomogeneities in meteorological records are described.The documentation accompanying the meteorological records enables users of the data bank to assess the suitability and reliability of the data. It has three components: first, information on the individual records such as start year, end year, altitude of the site, and geographical position; second, a list of data sources used in the compilation process; third, station histories which detail any known changes in site, instrumentation, etc. The station histories will be added to as work progresses on the data bank, to describe any attempts to homogenize records, and ultimately to give the compiler's assessment of the reliability of each record.User needs must be considered at all stages of data bank design and construction. Only in this way will a well-documented and easy-to-use system result. 相似文献
13.
E. Aguado 《Theoretical and Applied Climatology》1990,42(3):177-185
Summary This study investigates whether snowpack water equivalents in the northern and southern parts of the Sierra Nevada, or at high and low elevations in that range, have a tendency to acquire opposite departures from normal. Data from 28 snow courses were subjected to principal components analysis for February 1 and April 1 observations for the years 1954–1983. The first principal component indicated that there is a great deal of uniformity within the Sierra in terms of above- or below-normal accumulations in a given year. A second component had loadings depicting a pattern whereby high and low elevation sites have opposite departures from normal. Over the entire period of record this pattern accounted for a small percentage of the total variance, although in some years it was conspicuous. A third component indicated a tendency for northern and southern sites to have opposite departures from normal. Correlation coefficients were also obtained for 42 snow courses from 5 basins to further compare the relative influence of elevation and spatial separation. The correlation coefficients showed that elevation exerts a greater influence on the variation in departures from normal than does distance within drainage basins. These elevational differences in accumulation may have important consequences with regard to the timing of runoff and the availability of water stored in reservoirs.With 8 Figures 相似文献
14.
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
15.
主成分分析与聚类分析在青岛夏季气温变化研究中的应用 总被引：1，自引：1，他引：0
选用青岛站1951-2010年每年6-8月各月平均气温资料,通过SAS软件进行了主成分分析和聚类分析,分析了近60 a夏季气温的年际气候变化.主成分分析的结果表明,第一主成分反映青岛夏季气温距平,其正（负）方向反映夏季气温的正（负）距平,其强度反映气温偏高（低）的程度;第二主成分则反映同一年内夏季各月间气温的差异,其绝对值越大,表示各月气温差异越大.聚类分析的结果表明,青岛站夏季月平均气温的变化可以分为3类：1）6月、7月气温较低,在8月升温;2）7月平均气温最高,6月、8月相对较低;3）6月气温低,7、8两月气温较高.其中1993、2003年为第一类,2005年为第二类,其余为第三类. 相似文献
16.
Hui Ding Richard J. Greatbatch Wonsun Park Mojib Latif Vladimir A. Semenov Xuguang Sun 《Climate Dynamics》2014,42(1-2):367-379
The variability of the East Asian summer monsoon (EASM) is studied using a partially coupled climate model (PCCM) in which the ocean component is driven by observed monthly mean wind stress anomalies added to the monthly mean wind stress climatology from a fully coupled control run. The thermodynamic coupling between the atmospheric and oceanic components is the same as in the fully coupled model and, in particular, sea surface temperature (SST) is a fully prognostic variable. The results show that the PCCM simulates the observed SST variability remarkably well in the tropical and North Pacific and Indian Oceans. Analysis of the rainfall-SST and rainfall-SST tendency correlation shows that the PCCM exhibits local air-sea coupling as in the fully coupled model and closer to what is seen in observations than is found in an atmospheric model driven by observed SST. An ensemble of experiments using the PCCM is analysed using a multivariate EOF analysis to identify the two major modes of variability of the EASM. The PCCM simulates the spatial pattern of the first two modes seen in the ERA40 reanalysis as well as part of the variability of the first principal component (correlation up to 0.5 for the model ensemble mean). Different from previous studies, the link between the first principal component and ENSO in the previous winter is found to be robust for the ensemble mean throughout the whole period of 1958–2001. Individual ensemble members nevertheless show the breakdown in the relationship before the 1980’s as seen in the observations. 相似文献
17.
Three 40-member ensemble experiments and a 700?year control run are used to study initial value predictability in the North Pacific in Community Climate System Model version 3 (CCSM3). Our focus is on the leading two empirical orthogonal functions (EOFs) of subsurface temperature variability, which together produce an eastward propagating mode. Predictability is measured by relative entropy, which compares both the mean and spread of predictions of ensembles to the model??s climatological distribution of states. Despite the fact that EOF1, which is structurally similar to the observational Pacific Decadal Oscillation (PDO), has pronounced spectral peaks on decadal time scales, its predictability is less than 6?years. Additional predictability resides in the tendency of EOF1 to evolve to EOF2, primarily through simple advective processes. The propagating mode represented by the combination of EOF1 and EOF2 is predictable for about a decade. Information in both the mean and spread of predicted ensembles contribute to this predictability. Among the leading 15 EOFs, EOF1 is the least predictable mode in terms of the rate at which the corresponding principal component disperses in the ensemble experiments. However, it can produce enhanced predictability of the whole system by inducing EOF2, which is one of the two EOFs with the slowest dispersion rate. The first two EOFs can also enhance the ensemble mean (or ??signal??) component of predictability of the entire system. For typical amplitude initial states, this component contributes to predictability for about 6?years. For initial states with unusually high amplitude projections onto these two EOFs, this contribution can last much longer. The major findings from the three ensemble experiments are replicated and generalized when the initial condition predictability for each of many hundreds of different initial states is estimated. These estimates are derived from the behavior of a linear inverse model (LIM) that is based on the intrinsic variability present in the control run. 相似文献
18.
利用辽宁省25个台站1960—2005年逐候的降水资料，运用降水集中度和集中期分别讨论了辽宁省降水时空分布特征和变化规律，同时对多水年和少水年的集中度进行了比较。结果表明降水集中度和集中期能够定量地表征降水量在时空场上的非均一性，降水集中度平均为0．655，最大为0．749，最小为0．509；集中期平均为40．953候，最大值为45．221候，最小值为37．697候。年降水集中度和汛期降水集中度均呈减小趋势，汛期降水集中度减小的趋势明显。降水集中度的EOF分析显示取前3个特征值对应的特征向量可解释70％以上的方差。第一特征向量表现为全省一致性，而第二特征向量表征为东南与西北地区的反相，第三特征向量表征为东部山区与西部和沿海地区的反相。多水年的降水集中度明显比少水年的偏大且多水年的降水集中度分布较少水年复杂。 相似文献
19.
Yaeji Lim Seongil Jo Jaeyong Lee Hee-Seok Oh Hyun-Suk Kang 《Asia-Pacific Journal of Atmospheric Sciences》2012,48(2):125-134
A new statistical postprocessing method is proposed for seasonal climate prediction. The proposed method is based on a combination of independent component analysis (ICA) and canonical correlation analysis (CCA). Since the classical CCA cannot handle high-dimensional data wherein the number of variables is larger than the number of observations, ICA is pre-performed to reduce the dimension of the data. It is well known that empirical orthogonal function (EOF) analysis is a popular method for dimension reduction in the climatology community; however, loss of information occurs when the data is not Gaussian distributed. To extend the scope of distribution assumption and improve the prediction ability simultaneously, we propose the ICA-based method. This study focuses on the prediction of future precipitation for the boreal summer (June?CJuly?CAugust; JJA) through 29 years (1979?C2007) on East Asia region. Results of the proposed ICA-based method show an improvement in seasonal climate prediction in terms of correlation and root mean square error as compared with those of the GCM simulation and the EOF/CCA method. 相似文献
20.
华南前汛期降水预测模型及其预测试验 总被引：2，自引：0，他引：2
将中国华南区域分为东、西2个区,对每个区(8个站)的前汛期(4—6月)平均降水量作自然正交展开(EOF),选取各区累积方差贡献超过75%的前4个主分量作为预报分量。再利用偏最小二乘回归方法结合均生函数方法,提出一种同时考虑预报量自身显著变化周期和前期物理量因子对预报量未来变化影响的预报模型,分别建立东、西区前汛期平均降水量的偏最小二乘回归预报方程。试验结果表明,新的预报模型的预报效果比单纯采用前期物理量因子的逐步回归模型更好,并且其预报能力的提高具有合理的分析依据。 相似文献