The Ocean-Atmosphere coupled regimes and east asian winter monsoon (EAWM) activity

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中国冬夏季气温和降水异常耦合关系的SVD与MEOF分析对比

以揭示中国冬、夏季气温、降水之间的同期耦合时空特征为例,比较了SVD与MEOF分析所得主要正交模的相关关系及均衡性,论证了SVD方法在揭示两个要素场序列互相关关系上的优越性。结果表明:1) SVD的分解对象仅包含反映两种要素场相关关系的信息,而MEOF还包含了两个要素场各自的自相关信息,前者分解对象更纯粹。2) MEOF和SVD揭示的气温和降水空间耦合模态正负异常分布大致相似,但相较SVD所揭示的耦合模态,MEOF分析的冬、夏季气温、降水主要正交模存在不均衡现象,即一个主要MEOF正交模往往侧重描述两种异常要素场中的一种,这种差异在冬季尤为突出。SVD方法揭示了中国冬、夏季同期气温、降水间局域高温少降水或低温多降水是二者主要异常配置,且相关性夏强冬弱。3)比较SVD、MEOF方法同序正交模的相关系数和均衡度发现,SVD多数正交模的相关系数较MEOF的更大、更稳定,且均通过显著性检验,MEOF的冬季部分正交模相关系数未通过显著性检验; SVD主要正交模的均衡性冬季优于MEOF分析、夏季优于(第一模态)或者接近于(第二、三模态) MEOF分析。故SVD方法是揭示两要素之间耦合关系的更好方法。     

Coverage probability of bootstrap confidence intervals in heavy-tailed frequency models, with application to precipitation data

Bootstrap, a technique for determining the accuracy of statistics, is a tool widely used in climatological and hydrological applications. The paper compares coverage probabilities of confidence intervals of high quantiles (5- to 200-year return values) constructed by the nonparametric and parametric bootstrap in frequency analysis of heavy-tailed data, typical for maxima of precipitation amounts. The simulation experiments are based on a wide range of models used for precipitation extremes (generalized extreme value, generalized Pareto, generalized logistic, and mixed distributions). The coverage probability of the confidence intervals is quantified for several sample sizes (n?=?20, 40, 60, and 100) and tail behaviors. We show that both bootstrap methods underestimate the width of the confidence intervals but that the parametric bootstrap is clearly superior to the nonparametric one. Even a misspecification of the parametric model—often unavoidable in practice—does not prevent the parametric bootstrap from performing better in most cases. A tendency to narrower confidence intervals from the nonparametric than parametric bootstrap is demonstrated in the application to high quantiles of distributions of observed maxima of 1- and 5-day precipitation amounts; the differences increase with the return level. The results show that estimation of uncertainty based on nonparametric bootstrap is highly unreliable, especially for small and moderate sample sizes and for very heavy-tailed data.     

Coupled Modes of Rainfall over China and the Pacific Sea Surface Temperature in Boreal Summertime

In this study,monthly NCEP/NCAR reanalysis data and NOAA ERSST as well as observed precipitation data from 160 stations in China were used to investigate coupled modes affecting the rainfall over China and sea surface temperature (SST) in the Pacific during boreal summertime based on singular value decomposition (SVD) method.The SVD analysis revealed three remarkable coupled modes:rainfall over North China associated with an ENSO-like SST pattern (ENSO-NC),rainfall over the Yangtze River valley associated with SST anomalies in the western tropical Pacific (WTP-YRV),and rainfall over the Yellow River loop valley associated with tropical Pacific meridional mode-like SST pattern (TPMM-YRLV).These coupled SVD modes appear robust and closely correlated with the single field.Furthermore,the covariabilities among of the three coupled modes have different characteristics at the decadal time scale.In addition,the possible atmospheric teleconnections of the coupled rainfall and SST modes were discussed.For the ENSO-NC mode,anomalous low-pressure and high-pressure over the Asian continent induces moisture divergence over North China and reduces summer rainfall there.For the WTP-YRV mode,East Asia-Pacific teleconnection induces moisture convergence over the Yangtze River valley and enhances the summer rainfall there.The TPMM SST and the summer rainfall anomalies over the YRVL are linked by a circumglobal,wave-train-like,atmospheric teleconnection.     

SVD揭示的印度洋海气相互作用模态及其与中国降水的联系

利用1958-1999年6-8月平均的GISST(Global Indian Sea Surface Temperature)海表温度资料和同期850 hPa水平风场等NCEP/NCAR再分析资料,作了向量奇异值分解,并对各个模态作了相应分析,发现前两个模态可以很好地表示出印度洋海气耦合的主要部分:第1模态是印度洋海温对ENSO信号的滞后响应;第2模态反映了存在于印度洋的海-气相互作用现象,是ENSO和IOD(Indian Ocean Dipole,印度洋偶极子)的混合模态.讨论了前两个模态与中国夏季降水等变化的联系,发现印度洋海温单极模态与我国华南夏季降水存在负相关,与长江流域及其以北地区存在正相关;印度洋偶极型海温与我国降水的关系不典型.     

Potential Predictability of Sea Surface Temperature in a Coupled Ocean--Atmosphere GCM

Using the Flexible Global Ocean--Atmosphere--Land System model (FGOALS) version g1.11, a group of seasonal hindcasting experiments were carried out. In order to investigate the potential predictability of sea surface temperature (SST), singular value decomposition (SVD) analyses were applied to extract dominant coupled modes between observed and predicated SST from the hindcasting experiments in this study. The fields discussed are sea surface temperature anomalies over the tropical Pacific basin (20^oS--20^oN, 120^oE--80^oW), respectively starting in four seasons from 1982 to 2005. On the basis of SVD analysis, the simulated pattern was replaced with the corresponding observed pattern to reconstruct SST anomaly fields to improve the ability of the simulation. The predictive skill, anomaly correlation coefficients (ACC), after systematic error correction using the first five modes was regarded as potential predictability. Results showed that: 1) the statistical postprocessing approach was effective for systematic error correction; 2) model error sources mainly arose from mode 2 extracted from the SVD analysis---that is, during the transition phase of ENSO, the model encountered the spring predictability barrier; and 3) potential predictability (upper limits of predictability) could be high over most of the tropical Pacific basin, including the tropical western Pacific and an extra 10-degrees region of the mid and eastern Pacific.     

两种四维奇异值分解同化方法的比较及误差分析

4DSVD是最近提出的一种新的资料同化方法。目前还存在一些需要解决的问题,比如如何选取样本,如何得到支撑大气吸引子的基向量以及选取基向量的个数问题等等。作者利用奇异值分解(SVD)与经验正交函数分解(EOF)两种方法来获得支撑大气吸引子的基向量,推导了基于这两种方法的4DSVD分析场的理论公式,并用简单的数值试验比较了基于这两种方法的4DSVD分析场的空间相关系数和误差,初步分析了分析场与基向量个数的关系以及与样本选取的关系和分析误差的来源及各种误差对分析误差影响的相对大小。结果表明,用SVD方法作为获得支撑大气吸引子基向量的方法得到的分析场较EOF方法稳定,分析场与基向量个数有密切关系,观测误差、模式误差和观测代表性误差是分析误差的主要来源,且其引起的分析误差随着基向量个数增多而增大。     

Impact of the LMDZ atmospheric grid configuration on the climate and sensitivity of the IPSL-CM5A coupled model

The IPSL-CM5A climate model was used to perform a large number of control, historical and climate change simulations in the frame of CMIP5. The refined horizontal and vertical grid of the atmospheric component, LMDZ, constitutes a major difference compared to the previous IPSL-CM4 version used for CMIP3. From imposed-SST (Sea Surface Temperature) and coupled numerical experiments, we systematically analyze the impact of the horizontal and vertical grid resolution on the simulated climate. The refinement of the horizontal grid results in a systematic reduction of major biases in the mean tropospheric structures and SST. The mid-latitude jets, located too close to the equator with the coarsest grids, move poleward. This robust feature, is accompanied by a drying at mid-latitudes and a reduction of cold biases in mid-latitudes relative to the equator. The model was also extended to the stratosphere by increasing the number of layers on the vertical from 19 to 39 (15 in the stratosphere) and adding relevant parameterizations. The 39-layer version captures the dominant modes of the stratospheric variability and exhibits stratospheric sudden warmings. Changing either the vertical or horizontal resolution modifies the global energy balance in imposed-SST simulations by typically several W/m² which translates in the coupled atmosphere-ocean simulations into a different global-mean SST. The sensitivity is of about 1.2 K per 1 W/m² when varying the horizontal grid. A re-tuning of model parameters was thus required to restore this energy balance in the imposed-SST simulations and reduce the biases in the simulated mean surface temperature and, to some extent, latitudinal SST variations in the coupled experiments for the modern climate. The tuning hardly compensates, however, for robust biases of the coupled model. Despite the wide range of grid configurations explored and their significant impact on the present-day climate, the climate sensitivity remains essentially unchanged.     

一种适用于有限差分模式的负载平衡区域分解方法

分布式内存并行处理在数值天气预报等超大规模科学计算中已经得到了广泛的应用。中尺度模式由于分辨率高 ,计算量大 ,需使用更多的处理机进行并行运算。另一方面 ,由于复杂的物理过程的采用 ,增加了不同天气的计算量的不平衡。但是 ,目前所广泛使用的并行处理方法在处理机数量较多时不能很好地均衡计算负载 ,引起并行计算效率的降低。本文提出了一种新的非规则区域分解负载分配方法。并与已有的负载分配方法进行了分析试验对比 ,该方法能更有效地平衡负载 ,取得更好的加速效果     

青藏高原地面加热及上空环流场与东侧旱涝预测的关系

应用奇异值分解(SVD)技术研究了青藏高原地面加热场与高原上空100 hPa高度场及其东侧川渝地区夏季降水场的时空联系和旱涝预测的关系.结果表明:地面加热场与高度场的第一模态代表了两场间的主要耦合特征,具有高度的时空相关;前期青藏高原地面加热场通过影响后期高原上空100 hPa高度场,导致未来高原东侧川渝地区夏季降水异常;加热场-高度场-降水场之间的这种非同步关系,反映了川渝地区旱涝灾害的影响因子和物理成因; 前期高原地面加热场与前期100 hPa高度场SVD第一模态的变化,是高原东侧地区未来夏季旱涝异常的预测信号.并由此提出了一种基于SVD技术的旱涝预测思路.     

MSSA-SVD典型回归模型及其用于ENSO预报的试验

文中提出了一种基于多通道奇异谱分析 (MSSA)的广义典型混合回归模式。其基本思想是 ,利用MSSA SVD提取预报因子场和预报变量场的显著耦合振荡信号 ,对它们的前几个显著典型分布型建立多元线性统计气候预报模式。经对Nino海区各季海温距平所进行的短期气候预测试验表明 ,其预报效果优于其它统计预报方案 ,从而为探索ENSO预测方法提供了一种新的思路     

Teleconnections：Summer Monsoon over Korea and India

This study investigates the relationship between the summer monsoon rainfall over Korea and India,by using correlation analysis and Singular Value Decomposition(SVD).Results reveal that summer monsoon rainfall over Korea is negatively(significant at the 99% level) correlated with the rainfall over the northwest and central parts of India.In addition,coupled spatial modes between the rainfall over Korea and India have been identified by the SVD analysis.The squared covariance fraction explained by the first mode is 70% and the correlation coefficient between the time coefficients of the two fields is significant at the 99% level,indicating that the coupled mode reflects a large part of the interaction between the summer monsoon rainfall over Korea and India.The first mode clearly demonstrates the existence of a significant negative correlation between the rainfall over the northwest and central parts of India and the rainfall over Korea.Possible mechanisms of this correlation are investigated by analyzing the variation of upper-level atmospheric circulation associated with the Tibetan high using NCEP/NCAR Reanalysis data.     

海河流域夏季降水与北半球环流异常的相关

使用1981—2013年6—8月的月平均海河流域站点降水资料以及NCEP/NCAR再分析资料,采用SVD方法分析了北半球高度场环流异常与海河流域夏季降水的关系。结果表明夏季海河流域的一致型降水异常主要受热带地区高度场异常的影响,而北半球中高纬的高度异常分布对海河流域东南部降水异常有重要作用。热带及中高纬地区的高度场异常与副热带西风急流和流域上空的水汽输送有一定的对应关系,急流强度和位置的变化以及水汽辐合异常造成海河流域降水异常,尤其中高纬高度异常的这种对应关系更加明显,并且两个地区的高度异常分布对应的海河流域异常水汽输送有不同来源。     

Evaluation and Improvement of a SVD-Based Empirical Atmospheric Model

An empirical atmospheric model(EAM) based on the singular value decomposition(SVD) method is evaluated using the composite El Ni(?)o/Southern Oscillation(ENSO) patterns of sea surface temperature (SST) and wind anomalies as the target scenario.Two versions of the SVD-based EAM were presented for comparisons.The first version estimates the wind anomalies in response to SST variations based on modes that were calculated from a pair of global wind and SST fields(i.e.,conventional EAM or CEAM).The second version utilizes the same model design but is based on modes that were calculated in a region-wise manner by separating the tropical domain from the remaining extratropical regions(i.e.,region-wise EAM or REAM). Our study shows that,while CEAM has shown successful model performance over some tropical areas, such as the equatorial eastern Pacific(EEP),the western North Pacific(WNP),and the tropical Indian Ocean(TIO),its performance over the North Pacific(NP) seems poor.When REAM is used to estimate the wind anomalies instead of CEAM,a marked improvement over NP readily emerges.Analyses of coupled modes indicate that such an improvement can be attributed to a much stronger coupled variability captured by the first region-wise SVD mode at higher latitudes compared with that captured by the conventional one. The newly proposed way of constructing the EAM(i.e.,REAM) can be very useful in the coupled studies because it gives the model a wider application beyond the commonly accepted tropical domain.     

The mid-latitude horizontal and vertical structure of the zonally asymmetric intraseasonal and interannual ozone variability in boreal winters

 A singular value decomposition (SVD) is used to calculate SVD-selected fields of ozone and geopotential, which exhibit maximum covariance, from the observed zonally asymmetric total ozone field and that of the three-dimensional geopotential field thus leaving almost purely dynamical induced variations in the remaining ozone field. This procedure was applied to Total Ozone Mapping Spectrometer data (TOMS) and to geopotential values from the National Centers for Environmental Prediction in the boreal mid-latitudes in the winter months of 1979–1992. Intraseasonal variability (December–February) and trend-eliminated interannual winter mean variability of total ozone and geopotential are analyzed. The first four modes of SVD analysis explain more than 70% of the covariance for the intraseasonal variability and more than 80% of that for the interannual variability. The vertical structure of geopotential regression maps reveals a clear wave-1 pattern for modes one and two and a wave-2 pattern for modes three and four. These patterns show differently but generally westward tilted phases and are more complex at heights below 70 hPa. Further a linear transport model of a conservative tracer was applied to each individual geopotential mode found by the SVD analysis in connection with an observed height and latitude dependent zonal mean ozone distribution. The model results of total ozone reproduce the spatial patterns of the SVD-selected total ozone field quite well whereas their magnitudes are variously underestimated. This method allows us to assess the vertical distribution of the contribution of single modes to the total ozone variability. Maximum contributions are found between 150 and 70 hPa. Smaller amplitude maxima are found around 10 hPa, which result from contributions of horizontal advection of ozone alone. These results reflect an expected dynamical link between the variability of the zonally asymmetric parts of geopotential and ozone. Received: 7 November 1997 / Accepted: 10 June 1998     

集合变换卡尔曼滤波局地化对区域集合初始扰动的影响

集合变换卡尔曼滤波(ensemble transform Kalman filter, ETKF)是一种有效的集合预报初始扰动构造方案。但是,有限的集合样本、相同的集合成员设置以及预报模式误差等可能会使两个距离较远的状态变量产生虚假相关,从而影响ETKF集合扰动的质量。为了有效解决远距离虚假相关问题,将局地化思想引入ETKF方案。本文针对GRAPES区域集合预报系统(GRAPES REPS),对ETKF初值扰动局地化方案的效果进行了试验分析,为进一步改善和优化局地化方案(LETKF方案)提供依据。通过一周的连续试验,从暴雨个例、集合预报多种评分检验等方面分析了LETKF初始扰动方案所产生的集合预报质量。结果表明,区域集合预报中集合变换卡尔曼滤波初始扰动的局地化方案能够更加合理地捕捉到快速增长的分析误差的物理结构,更准确地再现数值模式预报误差的线性与非线性传播和演变特征。该局地化方案可以较好地改进预报质量,提高降水预报的准确率,尤其是针对小雨、中雨、暴雨量级的预报。相对于现有区域集合预报的业务系统GRAPES REPS,基于局地化ETKF初始扰动方案的区域集合预报具有较明显的优势。总体来看,LETKF初始扰动方案可更好地改善区域集合预报的质量。     

东亚-北太平洋副热带海气耦合模态及其对降水的影响

利用53年的NCEP/NCAR再分析资料和英国气象局Hadley气候预测和研究中心的海表面温度资料,使用SVD方法研究了东亚-北太平洋地区表层海温(SST)异常与大气环流异常间的主要耦合模态.分析结果表明,中纬度北太平洋地区存在两种主要的海-气耦合模态,第一模态是海温异常分布的纬向型,第二模态主要表现为经向海温差异分布.两种空间耦合模态共同反映出中纬度北太平洋地区大气和海洋的异常中心有很强的局地耦合性.在第一模态的正(负)异常年,东亚-北太平洋地区主要为负(正)的降水异常,在第二模态的正(负)异常年,东亚和北太平洋的大部分地区出现降水正(负)异常,北美西岸及以西的部分区域出现降水的负(正)异常.两个模态所对应的降水差异显示,海气耦合模态的循环变化有利于形成我国降水分布南北差异的改变.     

SVD方法在气象场诊断分析中的普适性

本文首次从理论上推导证明两个气象场的奇异值分解（ＳＶＤ）在气象场时空分布耦合信号的诊断分析中具有普适性。结果表明，两个场的ＳＶＤ求解准则不同于典型相关分析（ＣＣＡ），且ＣＣＡ模型可视为ＳＶＤ之特例，尤其当各个场经ＰＣＡ滤波后，其ＣＣＡ完全与ＳＶＤ等价。ＳＶＤ分析的结果不但可完全代替ＣＣＡ，且计算更简便，所得耦合信号的物理解释更清晰，特别适合于大尺度气象场的遥相关型研究。     

Assessment of the impacts of climate change and brackish irrigation water on rice productivity and evaluation of adaptation measures in Ca Mau province,Vietnam

This paper presents applications of the peaks-over-threshold methodology for both the univariate and the recently introduced bivariate case, combined with a novel bootstrap approach. We compare the proposed bootstrap methods to the more traditional profile likelihood. We have investigated 63 years of the European Climate Assessment daily precipitation data for five Hungarian grid points, first separately for the summer and winter months, then aiming at the detection of possible changes by investigating 20 years moving windows. We show that significant changes can be observed both in the univariate and the bivariate cases, the most recent period being the most dangerous in several cases, as some return values have increased substantially. We illustrate these effects by bivariate coverage regions.     

Nonparametric analysis of high wind speed data

In this paper, nonparametric curve estimation methods are applied to analyze time series of wind speeds, focusing on the extreme events exceeding a chosen threshold. Classical parametric statistical approaches in this context consist in fitting a generalized Pareto distribution (GPD) to the tail of the empirical cumulative distribution, using maximum likelihood or the method of the moments to estimate the parameters of this distribution. Additionally, confidence intervals are usually computed to assess the uncertainty of the estimates. Nonparametric methods to estimate directly some quantities of interest, such as the probability of exceedance, the quantiles or return levels, or the return periods, are proposed. Moreover, bootstrap techniques are used to develop pointwise and simultaneous confidence intervals for these functions. The proposed models are applied to wind speed data in the Gulf Coast of US, comparing the results with those using the GPD approach, by means of a split-sample test. Results show that nonparametric methods are competitive with respect to the standard GPD approximations. The study is completed generating synthetic data sets and comparing the behavior of the parametric and the nonparametric estimates in this framework.