陆面热力因子应用于中国夏季降水预测的初步试验

基于对中国东部夏季降水与欧亚大陆土壤温度和全球海表温度的相关分析,选取不同关键区的土壤温度和海表温度作为夏季降水的预测因子。利用1961-1990年的资料,分别以土壤温度作为第1组预测因子,海表温度作为第2组预测因子,综合海表温度与土壤温度因子作为第3组预测因子,使用改进的典型相关分析和集合典型相关分析法对中国东部夏季降水场进行预测,建立了相应的预测模型。然后,利用1991—2010年的资料进行了独立样本预测试验。在独立样本预测试验中,综合海表温度与土壤温度因子建立的模型比只用海表温度进行预测的各项预测评分高,说明加入土壤温度因子后预测效果有所提高。基于陆面热力因子的预测模型对夏季降水有一定的技巧,而综合海温与陆面热力因子的预测模型对中国东部夏季降水有较高的预测能力。     

STUDY ON CANONICAL AUTOREGRESSION PREDICTION OF METEOROLOGICAL ELEMENT FIELDS*

Through extension of canonical correlation to the analysis of meteorological element fields (MEF), a concept from combination of canonical autocorrelation with canonical autoregression (CAR) is developed for short-term climatic prediction of MEFs with a formulated scheme. Experimental results suggest that the scheme is of encouraging usefulness to a weak persistence MEF,i.e., rainfall field and, in particular, to a strong persistance one like a SST field.     

STUDY ON CANONICAL AUTOREGRESSION PREDICTION OF METEOROLOGICAL ELEMENT FIELDS

Through extension of canonical correlation to the analysis of meteorological element fields(MEF), a concept from combination of canonical autocorrelation with canonical autoregression(CAR) is developed for short-term climatic prediction of MEFs with a formulated scheme. Experi-mental results suggest that the scheme is of encouraging usefulness to a weak persistence MEF,i.e., rainfall field and, in particular, to a strong persistance one like a SST field.     

中国业务动力季节预报的进展

利用动力模式开展季节到年际的短期气候预测 ,是目前国际上气候预测的发展方向。自 1996年以来 ,经过 8a多的研制和发展 ,国家气候中心已建立起第 1代动力气候模式预测业务系统 ,其中包括 1个全球大气 海洋耦合模式 (CGCM )、1个高分辨率东亚区域气候模式 (RegCM_NCC)和 5个简化的ENSO预测模式 (SAOMS) ,可用于季节—年际时间尺度的全球气候预测 ;全球海气耦合模式与区域气候模式嵌套 ,可以提供高分辨率的东亚区域气候模式制做季节预测。CGCM对 1982～ 2 0 0 0年夏季的历史回报试验表明 ,该模式对热带太平洋海表面温度和东亚区域的季节预测具有较好的预测能力。RegCM NCC的 5a模拟基本上能再现东亚地区主要雨带的季节进展。利用嵌套的区域气候模式RegCM NCC对 1991～ 2 0 0 0年的夏季回报表明 ,在预报主要季节雨带方面有一定技巧。 2 0 0 1～ 2 0 0 3年 ,CGCM和RegCM NCC的实时季节预报与观测相比基本合理。特别是 ,模式成功地预报了 2 0 0 3年梅雨季节长江和黄河之间比常年偏多的降水。SAOMS模式系统的回报试验表明 ,该系统对热带太平洋海表面温度距平有一定的预报能力 ,模式超前 6～ 12个月的回报与观测的相关系数明显高于持续预报。 1997～ 2 0 0 3年 ,SAOMS多模式集合实时预报与观测的相关系数达到     

北太平洋海温分布型指数的年际变化及预测

从预测中国夏季降水趋势分布的需要出发 ,定义了一个反映北太平洋海域表面温度变化的分布型指数。该指数较好地表征出海温的年际变化特征及厄尔尼诺和拉尼娜事件 ,及其与中国夏季降水分布型式有较清晰的相关关系。在分析分布型指数变化特征基础上构建了一个统计预测模式。模拟计算及 3 6个个例提前 6个月的预测试验结果表明 ,该模式可以较好地预测出北太平洋海温的变化趋势 ,为提前半年做出中国夏季降水趋势分布预测提供了依据     

诊断分析在数值预报产品释用中的探讨

针对地方性天气预报特点，根据现有数值预报产品及实时控空资料的接收情况，作者利用中尺度数值预报模式ＭＭ４引入了中尺度信息，提出了一个实际可行的夏季降水预报方案，以求提高区域范围内具有明显突发性对流降水的预报能力。     

诊断分析在数值预报产品释用中的探讨

针对地方性天气预报特点，根据现有数值预报产品及实时探空资料的接收情况，作者利用中尺度数值预报模式ＭＭ４引入中尺度信息，提出一个实际可行的夏季降水预报方案，以求提高区域范围内具有明显突发性对流降水的预报能力。作法是用ＭＭ４模式计算逐日物理量诊断场，加入同期的欧洲中心数值预报产品，共计４１个场作为预报因子场；应用典型相关分析法，并结合逐步判别和逐步回归法，计算得出９个分区和８个单站中雨以上降水预报方程。降水预报方程的因子变量多数为中尺度诊断分析场构成的典型团子，可以认为，ＭＭ４模式计算得出的中尺度信息对预报中雨以上降水是有贡献的。     

An empirical model of decadal ENSO variability

This paper assesses potential predictability of decadal variations in the El Ni?o/Southern Oscillation (ENSO) characteristics by constructing and performing simulations using an empirical nonlinear stochastic model of an ENSO index. The model employs decomposition of global sea-surface temperature (SST) anomalies into the modes that maximize the ratio of interdecadal-to-subdecadal SST variance to define low-frequency predictors called the canonical variates (CVs). When the whole available SST time series is so processed, the leading canonical variate (CV-1) is found to be well correlated with the area-averaged SST time series which exhibits a non-uniform warming trend, while the next two (CV-2 and CV-3) describe secular variability arguably associated with a combination of Atlantic Multidecadal Oscillation (AMO) and Pacific Decadal Oscillation (PDO) signals. The corresponding ENSO model that uses either all three (CVs 1–3) or only AMO/PDO-related (CVs 2 and 3) predictors captures well the observed autocorrelation function, probability density function, seasonal dependence of ENSO, and, most importantly, the observed interdecadal modulation of ENSO variance. The latter modulation, and its dependence on CVs, is shown to be inconsistent with the null hypothesis of random decadal ENSO variations simulated by multivariate linear inverse models. Cross-validated hindcasts of ENSO variance suggest a potential useful skill at decadal lead times. These findings thus argue that decadal modulations of ENSO variability may be predictable subject to our ability to forecast AMO/PDO-type climate modes; the latter forecasts may need to be based on simulations of dynamical models, rather than on a purely statistical scheme as in the present paper.     

Impacts of New Implementing Strategies for Surface and Model Physics Perturbations in TREPS on Forecasts of Landfalling Tropical Cyclones

To improve the ensemble prediction system of the tropical regional atmosphere model for the South China Sea(TREPS) in predicting landfalling tropical cyclones(TCs), the impacts of three new implementing strategies for surface and model physics perturbations in TREPS were evaluated for 19 TCs making landfall in China during 2014–16. For sea surface temperature(SST) perturbations, spatially uncorrelated random perturbations were replaced with spatially correlated ones. The multiplier f, which is u...     

我国夏季降水与前期太平洋海温场关系的典型相关分析

对太平洋海温场与我国夏季降水之间的典型相关分析表明,海温场第一典型分布型的季节变化为：秋季东南高西北低、冬季东西低中间高、春夏季西北高东南低。典型主分量的时间变化规律清楚地反映出ＥｌＮｉｎｏ的演变过程。用ＣＣＡ短期气候预测模型对我国夏季降水的预报试验结果显示,我国的降水对因子场的响应存在明显的地区性差别,且预报效果同各区降水指数与典型主分量相关性的高低关系密切。     

Different influences of two types of El Niños on the Indian Ocean SST variations

By comparing correlation of sea surface temperature (SST) and vertical circulation with canonical El Niño and El Niño Modoki, we find that El Niño Modoki has an effect on the Indian Ocean different from traditional El Niño. There exists obvious Indian Ocean basin mode (IOBM) after canonical El Niño, while insignificant SST anomalies exist in the Indian Ocean after El Niño Modoki. Anomalous downdraft and updraft appear over the eastern and western Indian Ocean, respectively, during canonical El Niño, while anomalous updraft is weak over the Indian Ocean during El Niño Modoki. Besides, the strength of El Niño Modoki is slightly weaker than that of canonical El Niño. According to previous studies, two mechanisms can explain IOBM after canonical El Niño: tropospheric temperature (TT) mechanism and ocean dynamics. However, both of them do not exist during El Niño Modoki. Comparing with the complicated oceanic processes, it is convenient to verify the observed TT anomalies and test the possible mechanism using the simple model. Therefore, we pay more attention on the question why TT mechanism does not work during El Niño Modoki. Using a linear barocinic model (LBM), we demonstrate that the strength of SST anomalies and cold SST anomalies in the eastern Pacific have an influence on TT anomalies. Especially, cold SST anomalies in the eastern Pacific cancel the effects of warm SST anomalies in the central Pacific on TT anomalies. It suggests that the SST anomalies in the eastern Pacific are important for the TT mechanism in two types of El Niño.     

不同区域海温异常对中国夏季旱涝影响的诊断研究和预测试验

利用季降水异常的典型集合相关预测模式, 研究了前期和同期不同季节全球海表温度距平场与中国夏季旱涝的遥相关分布特征以及这种相关型随季节的变化, 揭示了全球海温的异常变化在中国夏季旱涝中的信号特征.研究表明, 全球不同区域海温对我国夏季降水的影响存在着明显的季节差异.全球特定的海温分布可以作为中国夏季旱涝预报的信号因子.选取不同区域及不同时段的海温场作为因子场分别对1998、 1999年这两个典型年份的我国夏季降水进行了诊断研究和预测试验, 并通过不同区域海温的影响权重做集成预测.试验结果表明:不同区域海温的集成预测不仅可以有效地提高预测的准确性, 而且可以揭示不同时段不同区域海温的异常变化在夏季旱涝中的强信号现象.     

基于海气耦合环流模式的ENSO预测

Predictions of ENSO are described by using a coupled atmosphere-ocean general circulation model. The initial conditions are created by forcing the coupled system using SST anomalies in the tropical Pacific at the background of the coupled model climatology. A series of 24-month hindcasts for the period from November 1981 to December 1997 are carried out to validate the performance of the coupled system. Correlations of SST anomalies in the Nino3 region exceed 0.54 up to 15 months in advance and the rms errors are less than 0.9℃. The system is more skillful in predicting SST anomalies in the 1980s and less in the 1990s. The model skills are also seasonal-dependent, which are lower for the predictions starting from late autumn to winter and higher for those from spring to autumn in a year-time forecast length. The prediction, beginning from March, persists 8 months long with the correlation skill exceeding 0.6, which is important in predictions of summer rainfall in China. The predictions are succesful in many aspects for the 1997-2000 ENSO events.     

春季海温对中国夏季降水影响的诊断研究和预测试验

文中利用季降水异常集合的典型相关预测模式 ,以全球春季 (3～ 5月 )海温场作为因子场 ,对中国夏季降水场进行了诊断研究 ,并对 1998,1999及 2 0 0 0年这几个典型的中国夏季降水进行了回报试验。结果表明 ,春季海温与中国夏季降水之间存在较好的关系 ,春季海温在较大程度上决定了中国夏季降水雨带及其分布类型。考虑面积因子的集合典型相关预测方案对中国夏季降水具有较强的回报能力 ,此模式不仅能诊断出降水场和海温场中一些比较典型的空间模态和时间变化规律 ,而且可以再现 1998和 2 0 0 0年中国大部分地区的旱涝灾害。揭示了全球春季海温的异常变化在中国夏季 (6～ 8月 )降水异常中的作用。     

Improved ENSO forecasts by assimilating sea surface temperature observations into an intermediate coupled model

A simple method for initializing intermediate coupled models (ICMs) using only sea surface temperature (SST) anomaly data is comprehensively tested in two sets of hindcasts with a new ICM. In the initialization scheme, both the magnitude of the nudging parameter and the duration of the assimilation are considered, and initial conditions for both atmosphere and ocean are generated by running the coupled model with SST anomalies nudged to the observations. A comparison with the observations indicates that the scheme can generate realistic thermal fields and surface dynamic fields in the equatorial Pacific through hindcast experiments. An ideal experiment is performed to get the optimal nudging parameters which include the nudging intensity and nudging time length. Twelve-month-long hindcast experiments are performed with the model over the period 1984–2003 and the period 1997–2003. Compared with the original prediction results, the model prediction skills are significantly improved by the nudging method especially beyond a 6-month lead time during the two different periods. Potential problems and further improvements are discussed regarding the new coupled assimilation system.     

白银市春末夏初干旱成因分析及预测

通过白银市春末夏初干旱指数[1] 与北半球 50 0hPa、10 0hPa海平面气压和太平洋海温的月平均环流典型年的对比分析、相关分析发现 ,春末夏初干旱与这些环流背景有密切关系 ,在此基础上 ,提取了选入预测模型的因子。用 3种方法建立预测模型 ,再进行预测集成 ,试报了 1991～ 1998年的春末夏初干旱指数 ,效果很好     

EXPERIMENTS WITH SHORT-TERM CLIMATE PREDICTION MODELS ON SSTA OVER THE NINO OCEANIC REGION

Predictions of averaged SST monthly anomalous series for Nino 1-4 regions in the context of auto-adaptive filter are made using a model combining the singular spectrum analysis (SSA) and auto-regression (AR). The results have shown that the scheme is efticient in forward forecaning of the strong ENSO event in 1997-1998, it is of high reliability in retrospective forecasting of three corresponding historical strong ENSO events. It is seen that the scheme has stable skill and large accuracy for experiments of both independent samples and real cases.With modifications, the SSA-AR scheme is expected to become an efficient model in routine predictions of ENSO.     

因子的可预报性和预报模型适用性研究初探

本文从因子场与预报量场之间的整体相关性着手，通过典型相关分析来提取因子信息，用求得的典型变量作为新预报因子，经试用表明，新因子的可预报性比原因子有明显提高。 在预报模型的选择上，本文提出了依据预报模型对历史样本实际预测精度的优劣来衡量预报模型的预测能力，从而选用对历史样本预测精度较高的预报模型作未来预报。     

Predictability of Indian Ocean sea surface temperature using canonical correlation analysis

There is strong evidence that Indian Ocean sea surface temperatures (SSTs) influence the climate variability of Southern Asia and Africa; hence, accurate prediction of these SSTs is a high priority. In this study, we use canonical correlation analysis (CCA) to design empirical models to assess the predictability of tropical Indian Ocean SST from sea level pressure (SLP) and SST themselves with lead-times up to one year. One model uses the first twelve empirical orthogonal functions (EOFs) of SLP over the Indian Ocean using different lead-times to predict SST. A CCA model with EOFs of SST as the predictor at the same lead-times is compared to SLP as a predictor and shows the auto-correlation of the system. A CCA using the first five extended empirical orthogonal functions (EEOFs) of sea level pressure over the Indian Ocean basin for an interval of two years combined with SST EOFs as predictors is found to produce the greatest correlation between forecast and observed SSTs. This model obtains higher skill by explicitly considering the development in time of SLP anomalies in the region. The skill of this model, assessed from retroactive forecasts of an 18 year period, shows improvement relative to other empirical forecasts particularly for the central and eastern Indian Ocean and boreal autumn months preceding the Southern Hemisphere summer rainfall season. This is likely due to the limited domain of this model identifying modes of variability that are more pronounced in these areas during this season. Finally, a nonlinear canonical correlation analysis (NLCCA) derived from a neural network is used to analyze the leading nonlinear modes. These nonlinear modes differ from the linear CCA modes with distinct cold and warm SST phases suggesting a nonlinear relationship between SST and SLP over the tropical Indian Ocean.     

The sensitivity of sub-Saharan precipitation to Atlantic SST

The climate model of the Goddard Institute for Space Studies (Hansen et al., 1983) is used to study the sensitivity of sub-Saharan rainfall to Atlantic Ocean SST. Initial changes of SST in the South Atlantic Ocean on March 1st are shown to reduce the June–August sub-Saharan precipitation totals using the model version with an interactive ocean that updates SST. Evidence is offered in support of theories that link Sahel drought with anomalously warm SST in the eastern South Atlantic and the study compares the model's response to spatially coherent SST anomalies with the response to random SST perturbations. The physical processes whereby SST and sea-level pressure synoptics influence the African summer monsoon are discussed in reference to the simulations. Predictibility of Sahel summer rainfall based on spring SST patterns or spring atmospheric circulation patterns is implied by the results. The SST/Sahel drought links are discussed for projections of future climate characteristics.