次季节-季节尺度热带气旋活动研究和预测技术进展

从外部强迫和大气内部变率两个方面回顾次季节-季节尺度西北太平洋热带气旋活动的主要影响因子及相关机制研究进展,分析统计、动力及混合动力-统计混合3类预测技术的发展历史和现状,对该领域尚未解决的主要科学问题及预测技术发展趋势进行了探讨。     

对流尺度集合预报成员数对降水预报的影响北大核心CSCD

选取2022年川渝地区发生的16个强降水个例开展对流尺度集合预报批量试验,并通过对31组初值采用不同集合成员数时的降水集合预报技巧进行检验评估和综合分析。结果表明:集合成员的降水预报技巧总体上大致相当,因而采用不同成员数时预报技巧差异也不明显;表征降水总体分布特征的Talagrand分布和预报失误概率以及表征降水概率预报技巧的相对作用特征面积随着成员数的增加而逐渐改进,但当成员数达到一定数值后继续增大成员数对预报改进不明显。总体而言,对流尺度集合预报成员数设置为16~18最适宜。     

北京气候中心次季节-季节预测系统对西南地区夏季降水次季节预报技巧评估及误差订正

利用北京气候中心(BCC)次季节-季节(Sub-seasonal to Seasonal,S2S)预测系统20年(1994-2013年)回报试验数据,在评估BCC S2S预测系统对中国西南地区夏季降水次季节预报性能基础上,进而采用基于奇异值分解(Singular Value Decomposition,SVD)的误差订...     

S2S模式对四川汛期极端降水的预测技巧分析

基于1995—2010年四川气象台站降水资料和世界气象组织次季节—季节(S2S)预测计划中8个模式的回报数据,采用命中率、误警率、Heidke技巧评分、误差和偏差5个指标评估分析了各模式对四川汛期极端降水事件的预测能力.结果表明,S2 S各模式对四川极端降水的预测技巧整体较低,表现为"低命中率,高误警率,预测值远小于实...     

NCEP CFSv2模式对川渝夏季降水次季节预测技巧评估及预报偏差分析

利用NCEP的第二代气候预测系统(CFSv2)提供的2000-2009年降水场历史回报试验资料以及川渝182个测站的降水实况资料。采用时间相关系数、均方根误差、距平相关系数、距平符号一致率以及PS评分等方法,对模式在川渝地区夏季降水以及夏季降水异常的次季节尺度预测技巧进行检验,并进一步分析了模式在概率密度和降水频次方面的预报偏差特征。结果表明：该模式对川渝夏季降水的可用预报时效为3候左右,能够较好地模拟出夏季降水的高值中心,但量级偏大。预报技巧高值区主要位于四川盆地西北部及渝东北地区,对攀西地区南部及川西高原部分地区也有一定的预报技巧。该模式也能够较好地把握川渝地区夏季降水异常偏少的趋势,有效预报技巧为2候以内。模式各时效预报与观测的降水概率密度主要集中在10 mm以下量级;模式预报各量级降水频次与实况相比均偏高得较为明显,且随着预报时效延长,偏差越大,其中偏高最为明显的是小雨频次。     

时空投影模型(STPM)的次季节至季节(S2S)预测应用进展

随着数值天气预报技术和季节动力预报系统的发展,短期天气预报及长期气候预测的能力持续提高,然而介于两者之间的次季节至季节(S2S,两周至三个月)预测技巧偏低,成为当今气象学界和业务服务的难题。南京信息工程大学国家特聘专家李天明教授团队于2012年研发了基于时空投影技术的统计预报模型(STPM),成功地对中国大陆降水和气温距平,以及区域极端降水、夏季高温、冬季低温和西太平洋台风群发事件等高影响天气进行提前10~30 d的预报,并在国家气候中心及多个省份开展了业务应用。STPM也成功应用于台湾春雨预报、南海季风爆发和ENSO预测等季节至年际变化的预测。本文对S2S预测的理论基础、STPM的发展和应用进行了完整的介绍,并讨论了S2S预测业务中所面临的挑战和未来展望。     

阿留申低压次季节尺度异常对北太平洋冬季降水的影响分析

利用1979—2018年的冬季逐日气象数据,研究了北太平洋地区冬季（12月至次年2月）阿留申低压次季节尺度变化特征,分析了次季节尺度阿留申低压异常与降水和极端降水异常之间的联系。选择1979—2018年共40个阿留申低压次季节尺度从异常增强到减弱的完整事件,记录下每个位相具体日期运用于合成分析。通过合成分析的结果可知：次季节尺度阿留申低压异常增强（减弱）时,北太平洋海盆区的降水呈现出明显的东多（少）西少（多）,同时副热带西太平洋略偏多（少）的分布型。次季节尺度蒸发异常和整层水汽输送散度异常能够解释以上降水异常的空间分布。在阿留申低压异常偏强时,自北太平洋中部向东北延伸至北美沿岸区域内大气河发生频率增加,使得海盆中部向东和东北汇聚更多的水汽,北美西海岸地区更易发生极端降水事件。     

南亚高压次季节尺度东西振荡对我国长江流域降水及水汽输送的影响

使用常规资料及HYSPLIT(Hybrid Single Particle Lagrangian Integrated Trajectory Model)模式,分析了早夏和晚夏期间南亚高压次季节尺度异常偏东事件和异常偏西事件发生时,我国长江流域降水及水汽输送异常特征。结果表明:早夏期间当南亚高压异常东伸时,西太平洋副热带高压可西伸至我国东南沿岸,此时,降水正异常场主要位于我国东部地区,表现为江淮区域降水异常偏多;而晚夏期间当南亚高压异常东伸时,西太平洋副热带高压的西脊点更偏东,降水正异常区位置比早夏偏西,表现为四川盆地的降水异常偏多。早夏期间,与南亚高压异常偏西事件相比,南亚高压异常偏东事件有利于更多的水汽从南方的水汽源地输送到我国江淮区域,加上此时江淮流域存在异常上升运动,动力和水汽条件共同使得江淮流域降水偏多。晚夏四川盆地地区有类似的结论。     

中国夏季降水的组合统计降尺度模型预测研究

现阶段的动力气候模式尚不能满足东亚区域气候预测的实际需求,这就需要动力和统计相结合的方法,将动力模式中具有较高预测技巧的大尺度环流信息应用到降水等气象要素的统计预测模型当中,以改善后者预测效果。本文中所介绍的组合统计降尺度模型,可将动力气候模式预测的大尺度环流变量和前期观测的外强迫信号作为预测因子来预测中国夏季降水异常。交叉检验结果显示,组合统计降尺度预测模型的距平相关系数较原始模式结果有较大提高。在实时夏季降水预测中,2013～2018年平均的预测技巧相对较高,趋势异常综合检验（PS）评分平均为71.5分,特别是2015～2018年平均的PS评分预测技巧达到72.7分,总体上高于业务模式原始预测和业务发布预测的技巧。该组合统计降尺度模型预测性能稳定,为我国季节预测业务提供了一种有效参考。     

MJO对我国降水影响的季节调制和动力-统计降尺度预测

利用1981—2016年中国区域CN05.1格点降水资料和EAR-Interim再分析资料,研究了季节循环对于热带大气季节内振荡(MJO)对我国降水影响的调制作用,并基于模式对MJO的预报建立了针对延伸期降水的动力-统计降尺度模型。结果表明,MJO对我国季节内降水异常的影响明显受到季节循环的调制。当MJO对流在热带印度洋活跃时,我国降水偏多的区域随季节由南向北推进;当MJO对流位于海洋性大陆地区时,在秋、冬季我国东部和高原大部分地区降水异常偏少,而到了春、夏季该关系反转。MJO对流和基本气流(特别是副热带西风急流)的位置和强度的变化所引起热带外环流响应的不同是造成这种季节性差异的重要原因。模式检验表明,BCC_AGCM2.2对目标候MJO的预报技巧可达18d以上,在此基础上利用模式预报MJO信息构建了随季节演变滚动的MJO动力-统计降尺度预测模型。独立样本检验表明,该模型在较长时效(10~20d)下对MJO高影响区低频降水异常的预报技巧高于模式的直接预报,特别是在MJO活跃时期对降水预报技巧的提升更加明显,这为MJO信号释用提供了新的思路。     

Skill Assessment of Copernicus Climate Change Service Seasonal Ensemble Precipitation Forecasts over Iran

Medium to long-term precipitation forecasting plays a pivotal role in water resource management and development of warning systems.Recently,the Copernicus Climate Change Service(C3S)database has been releasing monthly forecasts for lead times of up to three months for public use.This study evaluated the ensemble forecasts of three C3S models over the period 1993-2017 in Iran’s eight classified precipitation clusters for one-to three-month lead times.Probabilistic and non-probabilistic criteria were used for evaluation.Furthermore,the skill of selected models was analyzed in dry and wet periods in different precipitation clusters.The results indicated that the models performed best in western precipitation clusters,while in the northern humid cluster the models had negative skill scores.All models were better at forecasting upper-tercile events in dry seasons and lower-tercile events in wet seasons.Moreover,with increasing lead time,the forecast skill of the models worsened.In terms of forecasting in dry and wet years,the forecasts of the models were generally close to observations,albeit they underestimated several severe dry periods and overestimated a few wet periods.Moreover,the multi-model forecasts generated via multivariate regression of the forecasts of the three models yielded better results compared with those of individual models.In general,the ECMWF and UKMO models were found to be appropriate for one-month-ahead precipitation forecasting in most clusters of Iran.For the clusters considered in Iran and for the long-range system versions considered,the Météo France model had lower skill than the other models.     

Probabilistic Seasonal Prediction of Summer Rainfall over East China Based on Multi-Model Ensemble Schemes

The skill of probability density function (PDF) prediction of summer rainfall over East China using optimal ensemble schemes is evaluated based on the precipitation data from ˉve coupled atmosphere-ocean general circulation models that participate in the ENSEMBLES project. The optimal ensemble scheme in each region is the scheme with the highest skill among the four commonly-used ones: the equally-weighted ensemble (EE), EE for calibrated model-simulations (Cali-EE), the ensemble scheme based on multiple linear regression analysis (MLR), and the Bayesian ensemble scheme (Bayes). The results show that the optimal ensemble scheme is the Bayes in the southern part of East China; the Cali-EE in the Yangtze River valley, the Yangtze-Huaihe River basin, and the central part of northern China; and the MLR in the eastern part of northern China. Their PDF predictions are well calibrated, and are sharper than or have approximately equal interval-width to the climatology prediction. In all regions, these optimal ensemble schemes outperform the climatology prediction, indicating that current commonly-used multi-model ensemble schemes are able to produce skillful PDF prediction of summer rainfall over East China, even though more information for other model variables is not derived.     

Seasonal Forecasts of the Summer 2016 Yangtze River Basin Rainfall

The Yangtze River has been subject to heavy flooding throughout history,and in recent times severe floods such as those in 1998 have resulted in heavy loss of life and livelihoods.Dams along the river help to manage flood waters,and are important sources of electricity for the region.Being able to forecast high-impact events at long lead times therefore has enormous potential benefit.Recent improvements in seasonal forecasting mean that dynamical climate models can start to be used directly for operational services.The teleconnection from El Ni ?no to Yangtze River basin rainfall meant that the strong El Ni ?no in winter 2015/16 provided a valuable opportunity to test the application of a dynamical forecast system.This paper therefore presents a case study of a real-time seasonal forecast for the Yangtze River basin,building on previous work demonstrating the retrospective skill of such a forecast.A simple forecasting methodology is presented,in which the forecast probabilities are derived from the historical relationship between hindcast and observations.Its performance for2016 is discussed.The heavy rainfall in the May–June–July period was correctly forecast well in advance.August saw anomalously low rainfall,and the forecasts for the June–July–August period correctly showed closer to average levels.The forecasts contributed to the confidence of decision-makers across the Yangtze River basin.Trials of climate services such as this help to promote appropriate use of seasonal forecasts,and highlight areas for future improvements.     

秦岭北麓降雨与渭河洪水的关系

用水文学方法,使用1954—2002年水文年鉴资料和2003—2005年报汛资料,研究发现秦岭北麓降雨与渭河洪水的洪峰流量、洪水总量有密切关系,认为秦岭北麓山区是渭河洪水的重要产流区,利用秦岭北麓降雨和气象部门的降雨数值预报,可以预估渭河下游洪水情况,提高渭河洪水预报的时效。     

Improving Precipitation Forecasts over the Global Tropical Belt

Summary  This study explores the nowcasting and short-range forecasting (up to 3 days) skills of rainfall over the tropics using a high resolution global model. Since the model-predicted rainfall is very sensitive to model parameters, four key model parameters were first selected. They are the Asselin filter coefficient, the fourth order horizontal diffusion coefficient, the surface moisture flux coefficient, and the vertical diffusion coefficient. The optimal values were defined as those which contributed to the best one day rainfall forecasts in the present study. In order to demonstrate and improve the precipitation forecast skill, several numerical experiments were designed using the 14-level Florida State University Global Spectral Model (FSUGSM) at a resolution of T106. Comparisons were also made of the short-range forecasts obtained from a control experiment subjected to normal mode initialization (NMI) versus experiments based on physical initialization (PI). The latter experiments were integrated using the original FSUGSM and a modified version. This modified FSUGSM was developed here by applying a reverse cumulus parameterization alorithm to the regular forecast model, which restructures the vertical humidity distribution and constrains the large-scale model’s moisture error growth during the model integration. An improved short-range rainfall prediction skill was achieved from the modified FSUGSM in this study. The results showed a better agreement between model-based and observed rainfall intensity and pattern. Received January 18, 1999     

强降水和冰雹对流许可尺度集合预报个例试验

利用对流许可尺度集合预报系统,针对2015年4月28日夜间移动到江苏南部和上海地区,伴随短时强降水和冰雹的一次强对流过程,使用初始多源融合分析场对集合预报结果影响进行了分析。结合上海南汇双偏振雷达基数据观测,对12～14 h预报时效的反射率因子、差分反射率及冰雹集合预报结果进行了定性和定量的评估,分析了改进初始水物质分布,同时增加小尺度信息对于模式预报结果的影响。主要结果为:(1)对反射率因子预报的评估显示,初始场调整了水物质分布且增加了小尺度信息的试验(以下简称ADAS试验),对降水的范围、分布特征及评分都有明显改进(2)由于差分反射率在较小的距离内变化剧烈,对其准确预报难度较大,ADAS试验虽然预报强度偏强,但整体的位置和强度与实况更为接近,特别在大粒子预报方面具有更高的技巧,能够对微物理过程相关特征更好地进行描述;(3)使用地面人工观测和双偏振雷达观测对冰雹概率预报评估的结果显示,ADAS试验预报的高概率降雹区与观测落区接近,对冰雹落区预报具有一定的指示意义。通过多源融合分析调整初始水物质分布并增加小尺度信息的集合预报试验改善了较长预报时效的强降水和冰雹概率预报,具有更高的可信度,双偏振变量预报具有区分强降水与冰雹的优势,通过与观测的对比可以更好地评估模式对微物理过程描述的准确性。     

Evaluation of the Added Value of Probabilistic Nowcasting Ensemble Forecasts on Regional Ensemble Forecasts

Ensemble forecasting systems have become an important tool for estimating the uncertainties in initial conditions and model formulations and they are receiving increased attention from various applications. The Regional Ensemble Prediction System(REPS), which has operated at the Beijing Meteorological Service(BMS) since 2017, allows for probabilistic forecasts. However, it still suffers from systematic deficiencies during the first couple of forecast hours. This paper presents an integrated prob...     

Bias-Corrected Short-Range Ensemble Forecasts for Near-Surface Variables during the Summer Season of 2010 in Northern China

A running mean bias （RMB） correction ap- proach was applied to the forecasts of near-surface variables in a seasonal short-range ensemble forecasting experiment with 57 consecutive cases during summer 2010 in the northern China region. To determine a proper training window length for calculating RMB, window lengths from 2 to 20 days were evaluated, and 16 days was taken as an optimal window length, since it receives most of the benefit from extending the window length. The raw and 16-day RMB corrected ensembles were then evaluated for their ensemble mean forecast skills. The results show that the raw ensemble has obvious bias in all near-surface variables. The RMB correction can remove the bias reasonably well, and generate an unbiased ensemble. The bias correction not only reduces the ensemble mean forecast error, but also results in a better spreaderror relationship. Moreover, two methods for computing calibrated probabilistic forecast （PF） were also evaluated through the 57 case dates： 1） using the relative frequency from the RMB-eorrected ensemble; 2） computing the forecasting probabilities based on a historical rank histogram. The first method outperforms the second one, as it can improve both the reliability and the resolution of the PFs, while the second method only has a small effect on the reliability, indicating the necessity and importance of removing the systematic errors from the ensemble.     

天山北坡酿酒葡萄成熟期降雨特征及其影响分析

掌握新疆天山北坡酿酒葡萄成熟期降雨特征,对科学制定酿酒葡萄种植规划,采取趋利避害的生产管理技术措施具有实际意义。基于天山北坡35个气象站1961-2016年8-9月逐日降雨资料,采用线性趋势法和ArcGIS空间插值技术,对过去56a该区域酿酒葡萄成熟期（8-9月）降雨日数、降雨量、连阴雨天气次数、连阴雨天气降雨强度等要素的时空变化进行研究,并对照前人关于该区域酿酒葡萄种植气候适宜性区划成果,对酿酒葡萄不同适宜种植区葡萄成熟期降雨特征及其影响进行分析。结果表明：天山北坡酿酒葡萄成熟期（8-9月）降雨日数、降雨量、连阴雨天气次数、降雨强度、大量以上降雨日数的空间分布均总体呈现随海拔高度的升高而增加的特点。1961-2016年,研究区酿酒葡萄成熟期除降雨日数总体以-1.16d·10a-1的倾向率极显著 (P=0.001)减少,大量以上降雨日数以0.07d·10a-1的倾向率显著 (P=0.05)增多外,降雨量、连阴雨天气次数、连阴雨天气日数及其降雨量变化趋势均不显著。天山北坡酿酒葡萄种植气候最适宜和适宜区葡萄成熟期的降雨量、降雨日数、连阴雨天气次数、连阴雨天气日数及其降雨量都很小,期间总降雨量大多不足40 mm、降雨日数少于20 d、大量以上降雨日数不足1 d、连阴雨天气次数少于0.3次、连阴雨天气日数少于5d、连阴雨天气降雨量不足25mm,该分区降雨量以及连阴雨天气少,对提高酿酒葡萄产量和品质十分有利。酿酒葡萄次适宜种植区葡萄成熟期降雨天气稍多,降雨量40～90 mm、降雨日数20～25 d、大量以上降雨日数1～2 d、连阴雨天气次数0.3～1.0次、连阴雨天气日数5～8 d、连阴雨天气降雨量25～40 mm,对酿酒葡萄产量和品质有一定不利影响。天山北坡8-9月降雨量90 mm以上、降雨日数30d以上、大量以上降雨日数2d以上、连阴雨天气次数多于1.0次、连阴雨天气日数8d以上、连阴雨天气降雨量40 mm以上的区域均在海拔1500m以上的山区,该区域恰恰也是酿酒葡萄不适宜种植区,因此对酿酒葡萄无影响。综上所述,新疆天山北坡酿酒葡萄种植区尤其是适宜及最适宜种植区葡萄成熟期的降雨量、降雨日数、连阴雨天气次数和日数都较小,且近56a稳定少变,因此,对该区域酿酒葡萄生产的影响较小。     

ETKF方法在区域集合预报中的初步应用

理论上,集合卡尔曼变换(ETKF--The Ensemble Transform Kalman filter)方法产生的集合扰动在观测空间具有等概率分布的特征,这一特点恰好可以弥补业务集合预报中常用的初值生成方法--Breeding 方法的不足.依据ETKF理论和方法,利用GRAPES-Meso中尺度模式建立了简单的基于ETKF的中尺度集合预报试验平台,并选取2005年11月8-12日出现的一次降雨过程进行集合预报试验,旨在研究ETKF方法用于集合预报时,对随时间变化的区域非线性系统,在有限集合数的条件下的特征.试验结果揭示了利用ETKF方法进行实际区域模式下集合预报的可行性及其一些基本性质,并指出试验当中存在的不足及今后研究的重点.