湿热力平流参数在贵州初夏强降水中的运用

使用NCEP(1°×1°)再分析资料计算湿热力平流参数及其积分,通过对比分析2008—2009年初夏(5—6月)地面实况降水与该因子积分后的中心大值区的对应关系。理论分析表明:湿热力平流参数综合体现了锋区附近大气的动力、热力及水汽作用,相对于常用的相当位温、湿度等常用物理量来说,在一定程度上包含了广义位温及位温平流的相互作用,对实际非均匀饱和大气的动热力变化及水汽有较好的反映。统计分析也表明:积分后的湿热力平流参数中心值区与地面6小时强降水落区有较好的对应关系,它的变化趋势及移动方向与强降水区的变化也较一致,能作为短时强降水落区预报提供参考;利用NCEP/NCAR(1°×1°)再分析资料和Micaps地面实况降水资料,选取2009年6月7-9日发生在贵州的强降水过程为例,通过把湿热力平流参数与此次过程中动、热力场结合进行诊断分析,进一步表明该参数能综合地反应锋面强降水系统中的水汽、动力及热力的垂直结构特征,能作为造成强降水的锋面系统的示踪物。     

一次伴有尾随层状云类MCS强降水过程结构特征

利用常规观测资料、多普勒天气雷达资料及NCEP再分析资料,对2018年5月18日湖北省中东部地区一次尾随层状云类中尺度对流系统(MCS)的雷达回波特征和地面中尺度系统演变特征进行了分析。结果表明:1)短波槽东移南压,引导冷空气南下,与副热带高压外侧强劲的西南暖湿急流长时间在湖北省中东部地区交汇,形成有利于诱发MCS的大尺度环流背景;2)强降水的主要发生时段集中于尾随层状云降水回波对流线形成的初始阶段和成熟阶段,强雨团主要位于对流线附近及层状云降水回波头部,同时伴有雷暴大风天气;3)西南涡的发展为尾随层状云类MCS高效降水产生提供有利的环境场,边界层中尺度辐合线在对流的触发、发展、组织的过程中起到重要的作用,地形的抬升作用及阻挡作用,使MCS持续发展,同时,MCS后部"冷池"能量累积溢出形成雷暴冷出流与环境南风辐合,不断激发新的MCS;4)对流线附近存在明显的上升气流,环境风入流提供了充足的水汽供应,其前侧、后方分别有一支不同高度的下沉气流(出流或入流),并与环境风辐合,使MCS向前持续发展,并在后方不断激发新的MCS,造成较长时间的强降水。     

"121"跟踪监视系统简介及其应用

通过对“121”拨打情况进行实时跟踪和历史统计,分析了解“121”的动态发展。从而有针对性地对外加强宣传和对内调整“121”内容,提高其拔打率。“121”跟踪监视系统基于此而开发。     

Spatial prediction model and its application to chemistry of atmospheric precipitation in Jordan

This study is concerned with the spatial variability of some wet atmospheric precipitation parameters such as; pH, conductivity (EC). The study also depicts the spatial variability of some ions (cations and anions) of atmospheric precipitation in Jordan such as, Ca²⁺, Mg²⁺, Na⁺ and K⁺, HCO₃⁻, Cl⁻, NO₃⁻ and SO₄²⁻. The basis of the work is to establish a relationship through the cumulative semivariogram technique between the distance ratios and the spatial dependence structure of the chemical composition of atmospheric precipitation. All semivariogram models are constructed in this study in order to understand the behavior of the spatial distribution. The spatial distributions of rainwater parameters show differences from station to station which is expressed in terms of angle, where the larger the angle the weaker the correlation. The semivariogram (SV) models are constructed to show the variation of the rainfall chemistry in Jordan. The SV models show weak correlation between mountain and leeside mountain stations, i.e. mountain and desert stations. On the other hand, good correlations are observed when transferring from south to north of the country. The larger is the found angle, the weaker is the correlation. For most of the SV model the correlation is found to be very weak between desert and mountainous locality. The Standard Regional Dependence Factor (SRDF) is used for prediction of the distribution of rain fall parameters. It shows the relative error between observed and predicted values of rainwater parameters. The overall regional relative error between the observed and estimated concentrations remains less than 15%.     

黔西南短时强降水时空特征分析

利用黔西南州2006—2016年8县站全年逐小时降水量,对短时强降水特征及其与暴雨的关系进行分析,得出:(1)87%的短时强降水集中在20～40 mm/h,空间基本特征为"东多西少";94%的短时强降水出现在5—8月,3个级别的短时强降水都是在6月到达峰值;20～40 mm/h的短时强降水频次明显大于其它级别,60 mm/h的短时强降水只在夏季出现过;短时强降水主要出现在夜间,占总频次的70%,白天为低发时段,其中46%的短时强降水出现在前半夜,后半夜占25%,上午出现的频次最少,且3个级别的短时强降水都是在前半夜出现的频次最多。(2)黔西南州68%的暴雨天气中伴有短时强降水,二者的相关系数为0.94;所有短时强降水累计频次、暴雨日数与暴雨过程中出现的短时强降水的累积频次三者的空间分布基本特征均为"东多西少";暴雨量与当日最大小时降水量为显著正相关关系。     

基于CEEMDAN-SE-ARIMA组合模型的东北夏季降水预测

针对传统时间序列模型无法有效预测模态混叠数据的不足,本文提出了一种基于CEEMDAN-SE-ARIMA的组合模型,并且对东北地区2016—2020年夏季降水量进行了实证分析。首先,基于完全自适应集合经验模态分解方法,将降水时间序列分解为多个本征模态分量,并根据不同分量样本熵的计算结果进行分量序列重构。然后,针对每一个重构分量,构建自回归移动平均预测模型。最后,将各分量的预测值进行叠加,得到组合模型的预测值。此外,还构建了ARIMA单一模型和其他组合模型,旨在与CEEMDAN-SE-ARIMA组合模型对比。结果表明：CEEMDAN-SE-ARIMA组合模型考虑了时间序列的模态混叠特征,能有效提高东北地区夏季降水时序模型的预测能力,具有良好的预测应用价值。预测结果较单一模型和其他组合模型均有所提高,MASE降低了0.02～0.91 mm, RMSE降低了0.80～130.49 mm, MAE降低了2.52～129.84 mm, MAPE降低了1.08～35.53 mm。CEEMDAN-SE-ARIMA模型在降水变率较小的西北部区域预测效果更好,对东南部区域的极值分布中心预测较为准确。     

改进后TREC外推方法在台风临近降雨预报中的应用

本文提出了一种改进后的COTREC方法(CLTREC)。在传统COTREC方法基础上,增加了相邻时刻回波强度连续约束检验和矢量全变分修正,从而使得反演的雷达回波移动矢量场更为连续。选取了3个登陆台风个例,对方法进行检验。结果表明,CLTREC方法比传统COTREC方法的外推移动矢量场更平滑,台风环流特征也更合理。基于CLTREC外推预报的降水形状、强度和位置都与观测更为接近,1 h的台风定量降雨预报与观测相关系数达0.7以上。总体而言,相比传统的COTREC方法,CLTREC方法改善了台风短时临近降雨预报精度。     

Total deformation and its role in heavy precipitation events associated with deformation-dominant flow patterns

In this paper, it is elucidated that the total deformation （TD）, defined as the square root of the sum of squared stretching deformation and squared shearing deformation, is an invariant independent of the coordinate system used. An idealized flow field is then constructed to demonstrate the confluence effect of a non-divergent and irrotational deformation field on moisture transport. To explore the characteristics and role of TD, one heavy rainfall case that occurred in the middle and lower reaches of the Yangtze River （MRYR） over China, associated with a front with shear line, is analyzed using the Weather Research and Forecasting （WRF） model output data. It is found that right before the occurrence of precipitation, the effect of the confluence induced by deformation on moisture transport provides a favorable condition for precipitation. During the precipitation, both location and orientation of the zone of large TD coincide with the confluent shear line. The rainhands are nearly parallel with, and located lightly to the south of the zones of large TD and the confluent shear line. The TD in the lower troposphere increases in value as precipitation persists. When TD approaches its maximal value, the next 6-hour precipitation reaches its peak correspondingly. A tendency equation for TD is derived. The analysis of linear correlation and RMS difference between individual terms in the total deformation equation and the sum of the terms shows that the pressure gradient plays a major role in determining the local change of total deformation.     

高原地区NCEP热通量再分析资料的检验及在夏季降水预测中的应用

青藏高原对周边地区的天气气候有重要影响,为了寻求表征高原热力作用的新的、长时间序列的资料源,本文首先用高原地区NCEP1982～1994年间逐月月平均2.5.× 2.5.Lat./Lon.的地面热通量再分析格点资料对照实测值等进行了检验,然后用EOF分析方法分析了高原地面热源强度的空间分布特征,最后利用再分析资料和降水量实测资料,初步分析了高原地面热源强度对我国夏季降水的影响.主要结果如下:(1)高原地区的地面热通量再分析资料能较好地反映该区热源强度的年及年际变化特征,该再分析资料是可用的;(2)高原地区地面热源强度的分布存在较大的区域性差异;(3)高原西北、东北及西南区早春(2～4月)、夏季(6～8月)的地面热源强度分别与南疆、河西及长江流域的夏季降水存在反相关关系.     

GRAPES_MESO模式预报降水相态诊断及应用研究

当地面气温在0℃附近时,降水相态通常比较复杂,降水相态预报一直是天气预报的难点之一。本文根据降水粒子在下落过程中的热力结构,利用BTC算法、修订的BTC算法、Ramer算法、Bourgouin算法4种计算方案,通过GRAPES_MESO中尺度模式提供所需参数,对落到地面的降水相态进行诊断,诊断的降水相态包括雨、雪、冻雨和冰粒4种,然后利用集成方法获得大概率且破坏程度大的降水相态预报产品。基于2个冬季降水个例,研究发现4种计算方案都能较合理地得到雨雪分界线,以及降雨、降雪落区范围。其中,修订后的BTC算法可以修正原始BTC算法对降雪的诊断偏差,并且预测的冰粒比原始冰粒更少。Ramer算法会比其他几种算法获得更多的冻雨事件,而Bourgouin算法最接近合成算法的结果。对于不确定性较大的中间态的冻雨和冰粒预报,鉴于其高影响特性,方案倾向于过高估计冻雨和冰粒的预报落区。集成的最终降水相态产品反映其发生的概率大或影响程度大,能为防灾减灾提供有效的警示信息。     

成飞飞行区域短时强降水时空分布特征及强降水指数分析

成飞飞行空域包含高原、盆地、山区等多种地形,局地气候显著,短时强降水频发。该文使用国家气象信息中心2017—2021年多资料融合逐小时降水数据、国家自动站探空观测数据。统计分析发现,盆地周围沿山地区为盆地短时强降水高发区;101～102°E,31～32°N区域为高原短时强降水高发区。利用百分位法得到高原地区强对流指数阈值：CAPE值≥1930.5 J·kg^-1,BCAPE值≥1974.7 J·kg^-1,抬升指数≥2.6℃,大气可降水量≥86.1 mm,K指数≥37.2℃,SI指数≤-0.9℃。盆地地区强对流指数阈值：CAPE值≥2230.6 J·kg^-1,BCAPE值≥2264.4 J·kg^-1,抬升指数≥1.8℃,大气可降水量≥93.0 mm,K指数≥40.8℃,SI指数≤-1.8℃。建立短时强降水不同下垫面强对流指数阈值,为今后短时强降雨客观预报提供新的思路和方向。     

2008-2012年南京短时强降水特征分析

利用2008-2012年南京自动气象观测站逐时降水量的观测资料,分析南京短时强降水的发生规律,包括短时强降水的年变化、月变化、日变化和空间分布等特征。结果表明：2008-2012年南京雨强大于50 mm/h^-1的致灾性短时强降水过程的发生次数呈显著增长趋势;短时强降水天气主要出现在6-9月,其中7-8月出现日数最多,雨强最大;春雨期短时强降水最易发生在凌晨,梅雨期短时强降水最易发生在上午和傍晚,台汛期短时强降水最易发生在上午;下半夜-凌晨短时强降水出现次数较少,傍晚前后是短时强降水多发时段;短时强降水天气的空间分布具有明显的城郊差异;城市化效应不能引起城区的局地降雨,但在大尺度天气系统过境时,会使城区的对流活动较郊区更活跃,且城市下风向地区的降水也因此增强。     

江西暴雨气候特征及降水极值重现期分析

利用1961—2020年江西省83个国家气象观测站日雨量资料,采用线性倾向估计法、年最大值法以及耿贝尔Ι型极值分布理论,对江西年平均暴雨日数、暴雨降水量、暴雨贡献率、暴雨强度等的变化特征以及不同重现期的降水极值进行了分析.结果表明:1)江西各地年均暴雨日数呈西南向东北递增分布;大部分地区年暴雨日数呈增加趋势,并呈现西部和南部增加略慢,东部和东北部快速增加态势;尤其是江西东北地区既是暴雨高发中心,同时也是暴雨日数增长中心.2)江西各地年平均暴雨降水量和暴雨贡献率均呈东北多、西南少分布;景德镇和上饶为暴雨降水量和暴雨贡献率高值区也是增长中心;赣州北部和吉安南部为暴雨降水量和暴雨贡献率低值区,但呈现明显增长趋势.3)江西各地平均暴雨强度呈现较明显的北部大、南部小的分布特征;暴雨强度呈现西部增强、东部减弱的趋势.4)江西不同重现期的日雨量极值呈现东北大、西南小的分布,高值区主要分布在上饶、景德镇和抚州一带,低值区主要在吉安南部和赣州.     

Percentile-based neighborhood precipitation verification and its application to a landfalling tropical storm case with radar data assimilation

The traditional threat score based on fixed thresholds for precipitation verification is sensitive to intensity forecast bias.In this study, the neighborhood precipitation threat score is modified by defining the thresholds in terms of the percentiles of overall precipitation instead of fixed threshold values. The impact of intensity forecast bias on the calculated threat score is reduced. The method is tested with the forecasts of a tropical storm that re-intensified after making landfall and caused heavy flooding. The forecasts are produced with and without radar data assimilation. The forecast with assimilation of both radial velocity and reflectivity produce precipitation patterns that better match observations but have large positive intensity bias.When using fixed thresholds, the neighborhood threat scores fail to yield high scores for forecasts that have good pattern match with observations, due to large intensity bias. In contrast, the percentile-based neighborhood method yields the highest score for the forecast with the best pattern match and the smallest position error. The percentile-based method also yields scores that are more consistent with object-based verifications, which are less sensitive to intensity bias, demonstrating the potential value of percentile-based verification.     

Moderate to heavy cold-weather precipitation occurrences in Tehran and the associated circulation types

Large-scale atmospheric circulations associated with 133 moderate to heavy cold-weather precipitation events recorded at Mehrabad station in Tehran, Iran, during the period 1951–2013 are analysed. To this end, the performance of un-rotated, orthogonally rotated and obliquely rotated solutions of T-mode principal component analysis (PCA) is examined in classifying the atmospheric circulations into a few representative circulation types (CTs). The T-mode PCAs were applied to the 500-hPa geopotential height for the events in a domain from 10^°E to 70^°E and from 20^°N to 50^°N. The first six leading principal components were retained and then orthogonally and obliquely rotated using varimax and promax solutions, respectively. Statistical inter-comparison of the CTs obtained using the three solutions suggests that the obliquely rotated solution is the better choice for circulation classification in the present study. The six CTs obtained using the oblique rotation were then linked to the daily total precipitation and daily mean temperature variability at Tehran station as well as to the standardized anomalies of the daily total precipitation and mean daily temperature of a dense network of stations distributed across Iran. It is found that the CTs identified, though generally comparable in producing significant precipitation in Tehran, vary in their potential to bring cold weather and generate snowfall in Tehran specifically and in the country in general. While the first three CTs give rise to regional patterns of standardized precipitation anomalies centred in Tehran, the next three CTs leave a pronounced precipitation signature almost across the whole country. As regards the standardized temperature anomalies, with the exception of one CT that causes deep and widespread negative standardized anomalies over most parts of the country, the other CTs are characterized with a dipolar structure of a deep intrusion of cold weather to the west and prevailing warm weather to the east of the country.     

一次强降水超级单体风暴过程分析

概述了2006年6月16日影响大连机场的一次由强降水超级单体导致的“黑昼”天气的天气背景,应用卫星云图分析了雷暴云团的演变过程;利用大连市气象局新一代天气雷达资料,分析了强降水超级单体的雷达回波特征。结果表明:“黑昼”现象出现的主要原因是高空受东北冷涡控制,东北冷涡底部干冷空气与暖湿东南气流汇合,在大连地区上空形成了强降水超级单体。新一代天气雷达图像上强度图的演变与强降水超级单体模式相吻合;剖面图上显示出强降水超级单体的明显结构;存在着中气旋和中等到强的垂直风切变;分析了此次过程中出现冰雹的相关因子。     

21世纪中国极端降水事件预估

评估分析了欧洲中期天气预报中心（European Centre for Medium-range Weather Forecasts,ECMWF）细网格模式（以下简称EC-thin）在长三角地区汛期（5-9月）的暴雨预报评分及ECMWF降水极端天气预报指数（EFI）对暴雨预警的指示作用。研究发现：（1）EC-thin降水和降水EFI对暴雨预报的ETS评分随着预报时效的延长而明显降低,在短时效内,细网格模式降水预报占优,超过60 h后,降水EFI的评分相对更好。（2）对EC-thin降水而言,在不同的预报时效采用不同的降水阈值来预报暴雨,可望达到最佳的评分效果。短期时效内该阈值随着预报时效的延长,大致从55 mm逐渐下降到35 mm。（3）对于降水EFI而言,12-36 h内EFI为0.65~0.7时,暴雨预报ETS评分最高。随着预报时效的延长逐渐下降,60-84 h内EFI为0.55~0.6时,暴雨预报ETS评分最高。（4）在不同预报时效内,采用合理的方式和阈值综合考虑EC-thin降水和降水EFI,可望得到更高的暴雨预报评分。

     

Soil moisture retrieval from satellite images and its application to heavy rainfall simulation in eastern China

The soil water index (SWI) from satellite remote sensing and the observational soil moisture from agricultural meteorological stations in eastern China are used to retrieve soil moisture. The analysis of correlation coefficient (CORR), root-mean-square-error (RMSE) and bias (BIAS) shows that the retrieved soil moisture is convincible and close to the observation. The method can overcome the difficulties in soil moisture observation on a large scale and the retrieved soil moisture may reflect the distribution of the real soil moisture objectively. The retrieved soil moisture is used as an initial scheme to replace initial conditions of soil moisture (NCEP) in the model MM5V3 to simulate the heavy rainfall in 1998. Three heavy rainfall processes during 13–14 June, 18–22 June, and 21–26 July 1998 in the Yangtze River valley are analyzed. The first two processes show that the intensity and location of simulated precipitation from SWI are better than those from NCEP and closer to the observed values. The simulated heavy rainfall for 21–26 July shows that the update of soil moisture initial conditions can improve the model’s performance. The relationship between soil moisture and rainfall may explain that the stronger rainfall intensity for SWI in the Yangtze River valley is the result of the greater simulated soil moisture from SWI prior to the heavy rainfall date than that from NCEP, and leads to the decline of temperature in the corresponding area in the heavy rainfall days. Detailed analysis of the heavy rainfall on 13–14 June shows that both land-atmosphere interactions and atmospheric circulation were responsible for the heavy rainfall, and it shows how the SWI simulation improves the simulation. The development of mesoscale systems plays an important role in the simulation regarding the change of initial soil moisture for SWI.     

Synoptic and regional patterns of heavy precipitation in Austria

Summary Seven synoptic patterns responsible for heavy precipitation in Austria were identified with a trajectory clustering method. Back trajectories at different levels, at different times during each day, and from different locations in Austria were utilised together with one potential vorticity value. In addition, seven regions within Austria with similar daily precipitation were identified. The response of heavy precipitation in each of these regions to the synoptic patterns was studied. The results correspond to the synoptic experience and reflect known meteorological situations, such as southerly and northerly Stau or the Vb pattern. The analyses are based on the 15-year re-analysis of the ECMWF (1979–1993), used to calculate the back trajectories, and daily precipitation sums of 131 climate stations in Austria. This paves the way to future applications in climate change research, as the necessary input data are also available from global climate models. The clustering was performed with a promising new procedure, a combination of hierarchical and iterative (K-means) clustering.     

1909号超强台风“利奇马”强降水特征的诊断

基于TRMM卫星降雨资料、MERRA-2卫星位势高度、风速、垂直速度等资料，对1909号台风"利奇马"的移动特征及其引发浙江、江苏、山东等地暴雨进行诊断分析.分析结果发现，台风"利奇马"是北上型台风，移动路径主要受副高与1910号台风"罗莎"等系统影响.在北上的过程中，由于台风倒槽与西风槽携带的冷空气配合，且存在大量不稳定能量，引发了此次强降水过程.此外，低空急流及西风槽为降水提供了良好的动力上升条件，南海西南季风与台风"罗莎"是台风"利奇马"充沛的水汽与能量来源，为暴雨提供了良好的水汽条件.