一种分离时间尺度的统计降尺度模型的建立和应用——以华北汛期降水为例

针对预报量变化中存在受不同物理因子控制的不同时间尺度变率特征, 本文提出了分离时间尺度的统计降尺度模型。应用滤波方法, 将不同尺度的变率分量分开, 在各自对应的时间尺度上利用不同的大尺度气候因子分别建立降尺度模型。华北汛期 (7～8月) 降水具有年际变率和年代际变率, 本文以华北汛期降水为例利用分离时间尺度的统计降尺度模型进行预测研究。采用的预报因子来自海平面气压场、 500 hPa位势高度场、 850 hPa经向风场和海表温度场以及一些已知的大尺度气候指数。利用基于交叉检验的逐步回归法建立模型。结果表明, 年际尺度上, 华北汛期降水与前期6月赤道中东太平洋海温以及同期中国东部的低层经向风密切相关; 年代际尺度上, 在东印度洋—西太平洋暖池海温的作用下, 华北降水与前期6月西南印度洋海平面气压有同步变化关系。年际模型和年代际模型的结果相加得到对总降水量的降尺度结果。1991～2008年的独立检验中, 模型估计的降水和观测降水的相关系数是0.82, 平均均方根误差是14.8%。结合模式的回报资料, 利用降尺度模型对1991～2001年的华北汛期降水进行回报试验。相比于模式直接预测的降水, 降尺度模型预测的结果有明显改进。改进了模式预测中年际变率过小的问题, 与观测降水的相关系数由0.12提高到0.45。     

An Approach for Improving Short-Term Prediction of Summer Rainfall over North China by Decomposing Interannual and Decadal Variability简

A statistical downscaling approach was developed to improve seasonal-to-interannual prediction of summer rainfall over North China by considering the effect of decadal variability based on observational datasets and dynamical model outputs.Both predictands and predictors were first decomposed into interannual and decadal components.Two predictive equations were then built separately for the two distinct timescales by using multivariate linear regressions based on independent sample validation.For the interannual timescale,850-hPa meridional wind and 500-hPa geopotential heights from multiple dynamical models＇ hindcasts and SSTs from observational datasets were used to construct predictors.For the decadal timescale,two well-known basin-scale SST decadal oscillation （the Atlantic Multidecadal Oscillation and the Pacific Decadal Oscillation） indices were used as predictors.Then,the downscaled predictands were combined to represent the predicted/hindcasted total rainfall.The prediction was compared with the models＇ raw hindcasts and those from a similar approach but without timescale decomposition.In comparison to hindcasts from individual models or their multi-model ensemble mean,the skill of the present scheme was found to be significantly higher,with anomaly correlation coefficients increasing from nearly neutral to over 0.4 and with RMSE decreasing by up to 0.6 mm d-1.The improvements were also seen in the station-based temporal correlation of the predictions with observed rainfall,with the coefficients ranging from-0.1 to 0.87,obviously higher than the models＇ raw hindcasted rainfall results.Thus,the present approach exhibits a great advantage and may be appropriate for use in operational predictions.     

前期高度场和海温场变化对我国汛期降水的影响

利用1952～2001年我国160个测站汛期降水和前期500 hPa高度场和太平洋海温场资料以及三因子最佳子集回归求最大复相关系数的方法,把前期不同时间步长、不同时段的高度场和海温场同时作为预报因子与汛期降水求相关.结果发现:前期两个场共同作为预报因子比把其中某场单独作为预报因子的相关要好.并且存在着较好的"隔多季度相关"现象.预报因子具有实际预报意义的最佳时段为上一年的6～9月.影响我国汛期降水的最佳预报因子主要集中于高度场和海温场具有重要天气气候意义的关键区域.汛期降水可预报性在北方和长江以南均较好.     

A Seasonal Prediction Model for the Summer Rainfall in Northeast China Using the Year-To-Year Increment Approach

Using the year-to-year increment approach, this study investigated the relationship of selected climatic elements with the increment time series of the summer rainfall between successive years in Northeast China, including the soil moisture content, sea surface temperature, 500 hPa geopotential height, and sea level pressure in the preceding spring for the period 1981–2008. Two spring predictors were used to construct the seasonal prediction model: the area mean soil moisture content in Northwest Eurasia and the 500 hPa geopotential height over Northeast China. Both the cross-validation and comparison with previous studies showed that the above two predictors have good predicting ability for the summer rainfall in Northeast China.     

基于MM5模式的站点暴雨预报方法研究

基于对MM5模式输出产品的解释应用,建立了站点定量的暴雨MOS预报方法。从临沂中尺度数值预报模式产品中挑选x1（模式预报降水）,…,x12（沙氏指数）等12个模式产品和物理诊断因子为基本可能预报因子,又添加它们自身的非线性型xi^2xi^3,xi^1/2,1nxi,e^xi（i=1,…,12）和各因子间非线性交互作xixj（i=1,…,11,j=i＋1,…,12）型的126个可能预报因子。用非线性逐步判别做晴、雨二级判别,然后对雨型样本做逐步回归,得到暴雨的MOS预报方法。检验结果表明：该模型对暴雨有较强的预报能力,可应用于实际预报业务中。     

一种夏季大范围降水趋势分布的预报方法

综合考虑了影响夏季降水异常的大气、海洋因子和降水变化规律，提出了一种大范围降水异常分布的统计预报方法。用１９９１－１９９４年的独立资料检验，取得了满意效果。     

山东省飞机增雨降水区分级预报方法研究

利用1997～2000年春秋季山东主要降水天气系统中尺度客观分析和降水模拟资料，统计分析了与降水密切相关的15个因子，并对因子的稳定性进行检验。用全部入选因子的前5个主成分作为新的预报因子，建立全省25个区域0～6h和0～12h平均降水量的3类判别方程，判别效果较好。以此方法为基础建立的决策系统为增雨作业指挥提供了实用性技术工具。     

影响长江中下游夏季降水的前期潜在预报因子评估

利用1951～2006年美国NOAA海温资料、NCEP/NCAR再分析资料和青藏高原雪深等资料,根据前期海—陆—气因子对夏季长江流域降水的影响,本文搜集并整理了影响长江中下游夏季降水的40个预报因子,并讨论了前期因子与夏季降水在不同阶段的相关稳定性.通过相关和历史回报方法,讨论了前期关键因子与东亚夏季大气环流之间的关系...     

A Causality-guided Statistical Approach for Modeling Extreme Mei-yu Rainfall Based on Known Large-scale Modes—A Pilot Study

Extreme Mei-yu rainfall (MYR) can cause catastrophic impacts to the economic development and societal welfare in China. While significant improvements have been made in climate models, they often struggle to simulate local-to-regional extreme rainfall (e.g., MYR). Yet, large-scale climate modes (LSCMs) are relatively well represented in climate models. Since there exists a close relationship between MYR and various LSCMs, it might be possible to develop causality-guided statistical models for MYR prediction based on LSCMs. These statistical models could then be applied to climate model simulations to improve the representation of MYR in climate models. In this pilot study, it is demonstrated that skillful causality-guided statistical models for MYR can be constructed based on known LSCMs. The relevancy of the selected predictors for statistical models are found to be consistent with the literature. The importance of temporal resolution in constructing statistical models for MYR is also shown and is in good agreement with the literature. The results demonstrate the reliability of the causality-guided approach in studying complex circulation systems such as the East Asian summer monsoon (EASM). Some limitations and possible improvements of the current approach are discussed. The application of the causality-guided approach opens up a new possibility to uncover the complex interactions in the EASM in future studies.     

印度夏季风与我国华北夏季降水量

本文分析了1891—1983的93年降水资料,说明印度夏季风雨量与我国华北夏季降水量有相似的气候统计特征,而且两者存在稳定的、显著的正相关关系。文中还分析了与两者相联系的大气环流过程,并指出华北夏季降水量的多少与印度夏季风雨量丰欠在春季4月有共同的先兆。     

汛期大～暴雨的降水概率预报模式

应用阶梯函数变换预报因子 ,经过相关比筛选 ,进行 REEP构造分量级降水概率预报方程 ,应用不同时刻资料和对 NWP产品统计释用方法构造分时刻预报方程 ,并对其预报结果进行了综合的集合预报。实用表明 ,预报模式对大～暴雨的概率具有一定的预报能力。     

我国东部夏季三类雨型的诊断和预测方法研究

采用三级逐步判别方法对我国东部地区夏季(6、7、8月)降水进行客观诊断和预测。结果表明，利用6个测站的夏季降水量即可定量诊断我国夏季雨型。利用冬季500hPa极涡面积和北半球遥相关型指数建立起来的三级判别函数只包含7个因子。历史拟合率为38/39，试报效果也较好，从而为我国东部地区夏季降水型的客观预报提供了有应用价值的预报模型。     

Teleconnections between Ethiopian summer rainfall and sea surface temperature: part II. Seasonal forecasting

A seasonal forecasting system that is capable of skilfully predicting rainfall totals on a regional scale would be of great value to Ethiopia. Here, we describe how a statistical model can exploit the teleconnections described in part 1 of this pair of papers to develop such a system. We show that, in most cases, the predictors selected objectively by the statistical model can be interpreted in the light of physical teleconnections with Ethiopian rainfall, and discuss why, in some cases, unexpected regions are chosen as predictors. We show that the forecast has skill in all parts of Ethiopia, and argue that this method could provide the basis of an operational seasonal forecasting system for Ethiopia.     

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     

THE INDIAN SUMMER MONSOON AND SUMMER RALNFALL IN NORTH CHINA

The analyses have been made of the summer precipitation data over Indian and North China during1891—1983.The statistic results show that the climatic characteristics of the Indian summer monsoon rainfallare similar to summer rainfall in North China,and a steady and significant positive correlation exists be-tween them.The circulation systems associated with the Indian monsoon and the rainfall in North China in summerhave also been discussed.It is found that there are same predictors in April to be used for the forecast ofNorth China rainfall and Indian monsoon.     

Impact of Climate Change on Agricultural Production in the Sahel – Part 2. Case Study for Groundnut and Cowpea in Niger

During the last 30 years, the climate of the West African Sahel has undergone various changes, especially in terms of rainfall. This has large consequences for the poor-resource farmers depending mainly on rainfed agriculture. This paper investigates the impacts of current climate variability and future climate change on groundnut and cowpea production in Niger for three major agricultural regions, including the groundnut basin.Niger was one of the largest West African groundnut producing and exporting countries. Groundnut production – as a cash crop – dropped fromabout 312,000 tons in the mid 1960s (about 68% exported) to as low as 13,000tons in 1988 and increased again to 110,000 tons in 2000. Cowpea, a food crop, showsa different tendency, going from 4,000 tons in the mid fifties to a maximum of 775,000 tons in 1997, and its cultivated area is still increasing. It is also a cash crop in local economies (especially for women).To highlight the impact of climate change on groundnut and cowpea production (significantly determined by rainfall in July, August and September), the following components of the rainfall regime were calculated for the period 1951–1998: mean annual and monthly rainfall, beginning, end and lengthof the rainy season, number of rainy days per month, amount of rainfall per rainy day and the maximum length of dry spell per month. Three sub-periods whose duration varied per region were defined: for Dosso 1951–1968,1969–1984 and 1985–1998; for Maradi 1951–1970, 1971–1987 and1988–1998; and for Zinder 1951–1966, 1967–1984 and 1985–1998. A change in rainfallregime components was observed between the three sub-periods, which were characterized in chronological order by wet, dry and intermediate conditions. To assess the impact of climate variability and change on groundnut and cowpea production, a statistical modeling approach has been followed, based on thirteen predictors as described and discussed in the preceding paper. Climate change is mimicked in terms of reduced total amount of rainfall for the three main rainfall months and an increased temperature, while maintaining other significant predictors at a constant level. In 2025,production of groundnut is estimated to be between 11 and 25% lower, while cowpeayield will fall maximally 30%. Various strategies to compensate thispotential loss are presented for the two crops.     

Pacific Ocean sea-surface temperature variability and predictability of rainfall in the early and late parts of the Indian summer monsoon season

For central India and its west coast, rainfall in the early (15 May–20 June) and late (15 September–20 October) monsoon season correlates with Pacific Ocean sea-surface temperature (SST) anomalies in the preceding month (April and August, respectively) sufficiently well, that those SST anomalies can be used to predict such rainfall. The patterns of SST anomalies that correlate best include the equatorial region near the dateline, and for the early monsoon season (especially since ~1980), a band of opposite correlation stretching from near the equator at 120°E to ~25°N at the dateline. Such correlations for both early and late monsoon rainfall and for both regions approach, if not exceed, 0.5. Although correlations between All India Summer Monsoon Rainfall and typical indices for the El Ni?o-Southern Oscillation (ENSO) commonly are stronger for the period before than since 1980, these correlations with early and late monsoon seasons suggest that ENSO continues to affect the monsoon in these seasons. We exploit these patterns to assess predictability, and we find that SSTs averages in specified regions of the Pacific Ocean in April (August) offer predictors that can forecast rainfall amounts in the early (late) monsoon season period with a ~25% improvement in skill relative to climatology. The same predictors offer somewhat less skill (~20% better than climatology) for predicting the number of days in these periods with rainfall greater than 2.5?mm. These results demonstrate that although the correlation of ENSO indices with All India Rainfall has decreased during the past few decades, the connections with ENSO in the early and late parts have not declined; that for the early monsoon season, in fact, has grown stronger in recent decades.     

Statistical models for predicting rainfall in the Caribbean

Summary Separate predictive models are created for the Caribbean early wet season (May–June–July) and late wet season (August–September–October). Simple correlations are used to select predictors for a Caribbean rainfall index and predictive equations are formulated using multiple linear regression. The process is repeated after long term trends are removed from the Caribbean rainfall index and the models validated using a number of statistical methods. Four variables are confirmed as predictors for the early season: Caribbean sea surface temperature anomalies, tropical North Atlantic sea level pressure anomalies, vertical shear anomalies in the equatorial Atlantic, and the size of the Atlantic portion of the Western Hemisphere Warm Pool. Only the first two are retained in the late season model. On the interannual time-scale, equatorial Pacific sea surface temperature anomalies become significant in both seasons. The NINO3 index is retained among the predictors for the early season, and zonal gradients of sea surface temperature between the equatorial Pacific and tropical Atlantic are retained for the late season. The results also indicate spatial variation in the importance of the seasonal predictors.     

山东夏季降水量场预测模型研究及预测试验

从预测山东夏季降水场的需要出发，用山东1961－2001年夏季降水资料，研究了山东夏季降水的基本分布型式及其与北半球500hPa月平均高度、大气环流特征量及北太平洋海温之间关系。结果表明：不同的分布型存在不同的前期预测强信号。以这些强信号为主要预报因子结合考虑降水趋势振荡，构建出山东夏季降水场预测模型，并进行了预测试验。     

一次暴雨天气过程的物理量分析

对2002年发生在闽东的一次暴雨天气过程进行分析。结果表明：螺旋度和对流有效位能对暴雨的预报有指示意义，暴雨产生在低层正螺旋度中心与高层负螺旋度中心相配合和中低层有不稳定能量储存的高能区。在暴雨强盛期，螺旋度呈中低层正值，高层负值的上下配置，最大值位于700hPa。对流有效位能大值区与暴雨中心相对应，对流有效位能的时空变化能较好地反映暴雨的时空演变特征。利用中尺度数值模式输出的结果对不稳定能量场进行分析表明，位势不稳定能量的释放是暴雨产生发展的可能机制之一。