共查询到20条相似文献，搜索用时 31 毫秒
1.
Predicting the occurrence of hailstorms is one of the most complicated tasks in weather forecasting because of the small area of land that is usually affected, and because of the short time hail events last. Today there are a number of parameters available that may be used to characterize preconvective conditions and predict the beginning of convection. However, forecast models based on stability indices should be developed separately for each geographic area.The databases available were used in this study with two aims in mind: determining which meteorological variables or indices obtained from a radiosonde in the study zone are more relevant in characterizing preconvective conditions; and, secondly, setting up an objective short-term forecast model for storms on the basis of one or more meteorological parameters.The logistic regression was used to establish the dichotomy risk/no risk of storms. A function was developed combining seven meteorological variables. The results show that the forecast model has a Probability of Detection of 0.87 and a False Alarm Ratio of 0.18. 相似文献
2.
J. L. Sánchez R. Fraile M. T. de la Fuente J. L. Marcos 《Meteorology and Atmospheric Physics》1998,68(3-4):187-195
Summary The combination of several thermodynamic variables based upon the data provided by a radiosounding can be useful for the forecasting of thunderstorms. As a matter of fact, there are many indices that allow the establishment of a storm risk prediction once they have been gauged. The problem comes when not all indices lead to the same prediction. In these cases, it is necessary to establish one single function based on the information provided by all the variables employed, which should be able to determine a two-fold prediction: risk or no risk. This article presents a statistic model for the short tem prediction of thunderstorms in the region of León (Spain). To reach this aim 15 meteorological variables were selected. These variables were easy to handle by non-expert staff, and they allowed the characterisation of the preconvective environment early in the morning on thunderstorm days. The variables have been properly combined and gauged with the help of a dense network of meteorological observers. The result has led to the construction of a reliable model. The discriminant quadratic model has been easily applied to determine in an objective and binary way the risk/no risk for the occurrence of thunderstorms.With 5 Figures 相似文献
3.
《Atmospheric Research》2010,95(4):715-725
Flash floods are associated with highly localized convective storms producing heavy rainfall. Quantitative precipitation forecasting of such storms will potentially benefit from explicit representations of deep moist convection in numerical weather prediction models. However, explicit representation of moist convection is still not viable in operational mesoscale models, which rely on convective parameterizations for issuing short to medium-range forecasts. In this study we evaluate a technique that uses regional Cloud-to-Ground (CG) lightning observations to define areas of deep moist convection in thunderstorms and adjust the model-generated precipitation fields in those regions. The study focuses on a major flash flood inducing storm in central Europe (23 August 2005) that was simulated with the aid of an operational weather forecasting system (POSEIDON system based on Eta/NCEP model). The performance of the technique is assessed using as reference distributed rainfall estimates from a network of radar observations. The results indicate that CG lightning data can offer sufficient information to increase the mesoscale model skill in reproducing local convective precipitation that leads to flash floods. The model error correction is shown to be proportional to the density of lightning occurrence, making the technique potentially suitable for operational forecasting of flash flood inducing thunderstorms. 相似文献
4.
利用双流国际机场2013—2018年的逐小时气象观测资料、欧洲中心ERA-interim逐6小时再分析资料、成都市气象局多普勒天气雷达产品资料,运用统计学方法分析双流机场雷暴月变化和日变化特征,并利用相关性分析筛选出双流机场雷暴天气预报因子,在此基础上基于二级逻辑回归法建立潜势预报模型（预报方程和消空方程）,最后进行数据的回代检验。结果表明：对流有效位能、K指数、850 hPa比湿、850与500 hPa假相当位温差、回波顶高、1.5º仰角基本反射率、3.4º仰角基本反射率、垂直累积液态水含量为雷暴天气的主要预报因子,据此建立的潜势预报模型对双流机场雷暴天气的预报具有一定指示性,且综合来看在夏季的预报效果更好。 相似文献
5.
基于北京市观象台雷达基数据和加密自动气象站数据,利用支持向量机算法建立了雷暴大风天气的有效识别模型。首先确立了9个用于识别雷暴大风的预报因子:回波顶高、最大反射率因子、最大反射率因子所在高度、垂直积分液态水含量、垂直积分液态水含量随时间变率、垂直积分液态水含量密度、雷暴大风发生前最大反射率因子下降高度、风暴移动速度、速度谱宽。通过计算各预报因子在大风和非大风样本中的概率分布,得到对应的各项预报因子雷暴大风的隶属度,利用得到的隶属度函数对样本进行归一化处理。确立核函数和模型参数,利用支持向量机建立雷暴大风天气的提前识别和临近预警模型。通过对北京2017年7月7日飑线和2012年5月19日块状回波引起的灾害大风典型个例的识别效果检验,得到两个个例预测的命中率、误判率和临界成功指数分别为92.0%,22.1%,73.0%和99.1%,40.5%,59.2%,对于提高雷暴大风预警预报的准确率有一定帮助。 相似文献
6.
目前,集合预报已成为天气预报业务的主要支撑。然而,由于数值模式本身的限制与不完善以及集合系统存在初值扰动、集合大小等方面的局限,常存在预报偏差。不同预报模式通常具有不同的物理过程参数化方案、初始条件等,导致其预报能力各有不同。为此,如何纠正预报偏差以及如何充分有效地利用不同模式的预报信息以获得更加准确的天气预报广受关注。近年来,利用统计理论与预报诊断,基于多个集合预报系统的多模式集成预报技术得到快速发展,已成为有效消除预报偏差从而提高天气预报技巧的一种统计后处理方法。针对气温、降水和风3个最基本的地面气象要素,首先依据预报形式将应用范围较广的简单集合平均、消除偏差集合平均、超级集合、贝叶斯模式平均、集合模式输出统计等加权或等权平均多模式集成技术,分成确定性预报和概率预报两大类,并做系统介绍。最后,讨论使用和发展多模式集成技术需要关注的问题,包括考虑参与集成的模式个数、发展降水及风速分级预报模型和发展基于机器学习的多模式集成新技术。 相似文献
7.
8.
9.
以中尺度非静力WRF模式的格点预报结果作为云模式的初值集合,经云模式的多初值雷暴预报及预报结果的集合分析,建立了雷暴云的集合预报方法。将该方法应用于南京周边地区未来一天雷暴天气的特征预报,并利用南京夏季9个雷暴天气的多普勒雷达资料（SCIT,storm cell identification and tracking）进行预报效果的检验。结果表明,雷暴云的集合预报对研究区域内未来一天雷暴强度、分布预报效果较好,尤其对强雷暴的分布有较强的预警预测能力。此外,雷暴持续时间概率密度分布的集合预报产品,在雷暴影响范围概率预报上的应用,提高了雷达对雷暴的预警监测能力。 相似文献
10.
雷暴与强对流临近天气预报技术进展 总被引：81，自引：22，他引：59
临近预报指0—6h(0—2h为重点)的高时空分辨率的天气预报,预报对象是该时段内出现明显变化的天气现象,主要包括雷暴、强对流、降水、冬季暴风雪、冻雨、沙尘暴、低能见度(雾)、天空云量等,其中,以雷暴和强对流天气的临近预报最具挑战性。综述了针对雷暴和强对流天气的以主观预报为主、结合客观算法的临近预报技术,同时讨论了高分辨率数值预报模式在临近预报中的应用。主观临近预报技术包括基于多普勒天气雷达观测数据并结合其他资料(常规高空和地面观测、气象卫星云图、快速同化循环的数值预报产品等)对雷暴生成、发展和衰减,特别是对强对流天气(包括强冰雹、龙卷、雷暴大风和对流性暴雨)的临近预报,客观算法包括几种应用最广的雷达回波或云图外推算法和强对流天气识别技术。高分辨率数值预报模式的应用包括与雷达回波外推融合延长临近预报时效,与各种观测资料融合得到快速更新的三维格点资料为雷暴和强对流近风暴环境的判断提供重要参考。 相似文献
11.
1. Introduction In recent decades, extreme weather events seem to be growing in frequency and risk due to water-related disasters. According to the World Meteorological Or- ganization report (ISDR and WMO, 2004) on World Water Day, 22 March 2004, the economic losses caused by water-related disasters, including floods, droughts and tropical cyclones, are on an increasing trend as follows: the yearly mean in the 1970s was about 131 billion US dollars, 204 billion dollars in the 1980s, and … 相似文献
12.
The aim of the present study is to develop an adaptive neuro-fuzzy inference system (ANFIS) to forecast the peak gust speed associated with thunderstorms during the pre-monsoon season (April?CMay) over Kolkata (22°32??N, 88°20??E), India. The pre-monsoon thunderstorms during 1997?C2008 are considered in this study to train the model. The input parameters are selected from various stability indices using statistical skill score analysis. The most useful and relevant stability indices are taken to form the input matrix of the model. The forecast through the hybrid ANFIS model is compared with non-hybrid radial basis function network (RBFN), multi layer perceptron (MLP) and multiple linear regression (MLR) models. The forecast error analyses of the models in the test cases reveal that ANFIS provides the best forecast of the peak gust speed with 3.52% error, whereas the errors with RBFN, MLP, and MLR models are 10.48, 11.57, and 12.51%, respectively. During the validation with the 2009 observations of the India Meteorological Department (IMD), the ANFIS model confirms its superiority over other comparative models. The forecast error during the validation of the ANFIS model is observed to be 3.69%, with a lead time of <12?h, whereas the errors with RBFN, MLP, and MLR are 12.25, 13.19, and 14.86%, respectively. The ANFIS model may, therefore, be used as an operational model for forecasting the peak gust speed associated with thunderstorms over Kolkata during the pre-monsoon season. 相似文献
13.
14.
Stanley A. Changnon 《Climatic change》2011,106(2):129-140
The temporal distributions of the nation’s four major storm types during 1950–2005 were assessed, including those for thunderstorms,
hurricanes, tornadoes, and winter storms. Storms are labeled as catastrophes, defined as events causing $1 million or more
in property losses, based on time-adjusted data provided by the insurance industry. Most catastrophic storms occurred in the
eastern half of the nation. Analysis of the regional and national storm frequencies revealed there was little time-related
relationship between storm types, reflecting how storm types were reported. That is, when tornadoes occurred with thunderstorms,
the type producing the greatest losses was the one identified by the insurance industry, not both. Temporal agreement was
found in the timing of relatively high incidences of thunderstorms, hurricanes, and winter storms during 2002–2005. This resulted
in upward time trends in the national losses of hurricane and thunderstorm catastrophes, The temporal increase in hurricanes
is in agreement with upward trends in population density, wealth, and insurance coverage in Gulf and East coastal areas. The
upward trends in thunderstorm catastrophes and losses result from increases in heavy rain days, floods, high winds, and hail
days, revealing that atmospheric conditions conducive to strong convective activity have been increasing since the 1960s.
Tornado catastrophes and their losses peaked in 1966–1973 and had no upward time trend. Temporal variability in tornado catastrophes
was large, whereas the variability in hurricane and thunderstorm catastrophes was only moderate, and that for winter storms
was low. 相似文献
15.
Zonda wind is a typical downslope windstorm over the eastern slopes of the Central Andes in Argentina,which produces extremely warm and dry conditions and creates substantial socioeconomic impacts.The aim of this work is to obtain an index for predicting the probability of Zonda wind occurrence.The Principal Component Analysis(PCA)is applied to the vertical sounding data on both sides of the Andes.Through the use of a binary logistic regression,the PCA is applied to discriminate those soundings associated with Zonda wind events from those that are not,and a probabilistic forecasting tool for Zonda occurrence is obtained.This index is able to discriminate between Zonda and non-Zonda events with an effectiveness close to 91%.The best model consists of four variables from each side of the Andes.From an eventbased statistical perspective,the probability of detection of the mixed model is above 97%with a probability of false detection lower than 7%and a missing ratio below 1%.From an alarm-based perspective,models exhibit false alarm rate below 7%,a missing alarm ratio lower than 1.5%and higher than 93%for the correct alarm ratio.The zonal component of the wind on both sides of the Andes and the windward temperature are the key variables in class discrimination.The vertical structure of Zonda wind includes two wind maximums and an unstable lapse rate at midlevels on the lee side and a wind maximum at 700 h Pa accompanied by a relatively stable layer near the mountain top. 相似文献
16.
雷暴预警预报的研究进展 总被引：2，自引：1，他引：1
雷暴作为极端天气事件中的一种,不仅常产生强降水、破坏性大风和冰雹等严重的天气灾害,而且还伴有雷电,造成雷击灾害,给工农业生产和人民生活都可带来严重的损失。因此对雷暴的预警预报研究变得尤为重要,也促使其理论、技术及应用都取得了很大的发展。本文对有关雷暴预警预报技术的一些研究结果和进展如雷暴的潜势预报、雷暴的临近预报、雷电活动的观测信息在雷暴天气预警中的指示作用及雷暴云的数值模拟等方面进行了归纳和综述,总结了各方面研究所涉及的重要问题及主要进展,并对未来发展进行展望。 相似文献
17.
应用雷电定位系统和高空观测资料并结合雷达回波资料, 对广州地区雷暴过程云-地闪特征进行分析, 并就有、无云-地闪出现的两组不同对流天气过程的环境条件进行了比较研究。结果表明:广州地区的雷暴过程以负的云-地闪为主, 负云-地闪所占比例在90%以上。云-地闪发生频率与雷暴系统强度演变有直接联系, 对于同一系统来说, 随着系统回波强度的增强, 云-地闪发生的频率也增高。但不同系统中, 云-地闪发生频率有很大不同, 回波强(弱)的对流系统并不意味着云-地闪发生的频率就高(低)。有云-地闪记录的对流天气过程具有更大的垂直切变、更高的相对风暴螺旋度以及更多的对流抑制能量, 云-地闪现象更易于出现在更加有组织和更强的对流系统中。研究还发现广州及周边城市区域对雷暴系统回波强度及云-地闪现象可能有影响, 两个典型个例分析表明, 雷暴系统移经城市区域时回波强度减弱, 云-地闪发生频率减小, 雷暴移过城市区域后, 强度可重新加强, 云-地闪发生频率增大。 相似文献
18.
珠三角地区前汛期强对流潜势预报方法研究 总被引：3，自引：0，他引：3
利用2004—2006年前汛期探空资料计算的物理量,选取与强对流天气相关性好的大气温湿类(整层比湿积分IntegralQ)、层结稳定度类(K指数)、动力类(潜在下冲气流指数MDPI)、热力动力综合类(瑞士第一雷暴指数SWISS00)作为预报因子,通过对各指数的空间分布特征和数值进行二值Logistic回归分析,得到各指数的参数估算值,建立强对流诊断预报方程,得到前汛期强对流潜势预报因子P,从而制作珠江三角洲(以下简称珠三角)地区未来12小时出现强对流天气的潜势预报。并用此法回报2003—2006年3—6月前汛期的强对流天气。结果表明,P值大于0.9的准确率可达77.5%,P值小于0.5出现强天气的概率仅为3.8%。由于资料有限,对2007年3—4月发生的7次强对流的经验检验效果不明显,但P值小于0.5时不发生强对流的经验检验效果明显。此法对珠三角地区的短时强降水和雷雨大风等强对流天气的临近监测预警有较好的指示意义。 相似文献
19.
董爱民 《沙漠与绿洲气象(新疆气象)》2001,24(4):18-19
根据1992－1997年资料，从天气形势和能量分布特征对咸阳机场雷暴天气进行了初步分析，归纳出雷暴天气产生的主要天气系统。讨论了雷暴天气过程听能量分布特征和水汽条件，并在此基础上总结出雷暴天气的预报要点。 相似文献
20.
强对流天气预报业务包括监测、分析、预报、预警和检验等方面。对流初生识别、对流系统强度识别和对流天气类型识别等监测技术取得新进展,综合多源资料的监测技术已应用于中国气象局中央气象台业务。对流系统的触发、发展和维持机制等获得了新认识,我国不同类型强对流天气及其环境条件统计气候特征、分析规范及相应业务产品等为业务预报提供了必要基础和技术支撑。光流法、多尺度追踪技术以及应用模糊逻辑方法的临近预报技术等有明显进展,融合短时预报技术得到广泛应用,对流可分辨高分辨率数值 (集合) 预报及其后处理产品预报试验取得了显著成效,基于数值 (集合) 预报应用模糊逻辑方法的分类强对流天气短期预报技术为业务预报提供了技术支撑。强对流天气综合监测和多尺度自适应临近预报技术、多尺度分析技术以及融合短时预报技术、发展并应用模糊逻辑等方法的、基于高分辨率数值 (集合) 模式的区分不同强度等级和极端性的分类强对流天气精细化 (概率) 预报技术等是未来发展的主要方向。 相似文献