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1.
Forecasting thunderstorms is one of the most difficult tasks in weather prediction due to the scarce knowledge on how to characterise the mechanisms taking part in the formation of thunderstorms. New tools based upon the objective recognition of appropriate conceptual models have been developed in the last years. A good example of this are the statistical models, based on variables that characterise the preconvective atmospheric conditions.This paper presents the results obtained by applying a short-term forecast model to thunderstorms during the summer periods in León (Spain). This model makes use of the logistic function as a binary forecasting technique determining storm/no storm. The logistic function used was a combination of 15 previously selected meteorological variables. The model has been constructed with the data collected on 152 occasions, and it has been verified on 77 other occasions.The skill scores obtained show that the use of statistical models combining the data, provided by variables characterizing the preconvective conditions and the triggering mechanisms, represent an important step in the difficult task of short-term thunderstorm forecasting. 相似文献
2.
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
3.
科学合理地评估气象灾害造成的损失, 对减灾、防灾决策具有重要意义。为了建立不同气象灾害系统均能适用的投影寻踪回归 (projection pursuit regression, PPR) 矩阵表示灾情评估模型,在对气象灾情指标值进行规范变换基础上,规范变换后的各指标皆等效于同一个规范指标,因而只需构建对任意2个规范指标值适用的投影寻踪回归 (projection pursuit regression based on normalized index value, NV-PPR) NV-PPR (2) 模型和3个规范指标值适用的投影寻踪回归NV-PPR (3) 模型;对3个以上指标的气象灾害系统NV-PPR建模,只需将其分解为若干个NV-PPR (2) 模型和 (或) NV-PPR (3) 模型的组合即可。模型用于广东省台风和重庆市两起雷电灾情评估,并与其他方法的评估结果进行比较。结果表明:基于NV-PPR的气象灾情评估模型不受指标数量的限制,具有简单、实用的特点,该模型还可推广为适用于其他灾情评估。 相似文献
4.
2010年7月14～18日四川大暴雨过程区域模式预报性能分析 总被引：1，自引：0，他引：1
本文应用高空与地面常规观测资料,自动站资料以及2010年西南涡科学观测试验资料等,就西南区域气象中心运行的GRAPES模式、AREM模式、MM5模式以及基于WRF模式的RUC系统对发生在2010年7月14～18日四川大暴雨过程预报情况进行分析。结果表明,从降水预报,到影响系统,以及单点地面、高空要素预报,尽管各区域模式表现出对此大暴雨过程有一定的预报能力,但存在着不同程度差异,如降水落区、降水强度偏差,影响系统的偏离等。当分析模式定点预报时,预报偏差更为明显。相对而言,WRF模式预报结果略好于其它模式的预报。造成模式预报偏差的原因还有待作进一步分析研究。 相似文献
5.
2010年7月14～18日四川大暴雨过程区域模式预报性能分析 总被引：2，自引：0，他引：2
本文应用高空与地面常规观测资料,自动站资料以及2010年西南涡科学观测试验资料等,就西南区域气象中心运行的GRAPES模式、AREM模式、MM5模式以及基于WRF模式的RUC系统对发生在2010年7月14~18日四川大暴雨过程预报情况进行分析。结果表明,从降水预报,到影响系统,以及单点地面、高空要素预报,尽管各区域模式表现出对此大暴雨过程有一定的预报能力,但存在着不同程度差异,如降水落区、降水强度偏差,影响系统的偏离等。当分析模式定点预报时,预报偏差更为明显。相对而言,WRF模式预报结果略好于其它模式的预报。造成模式预报偏差的原因还有待作进一步分析研究。 相似文献
6.
Thunderstorms are the perennial feature of Kolkata (22° 32???N, 88° 20???E), India during the premonsoon season (April?CMay). Precise forecast of these thunderstorms is essential to mitigate the associated catastrophe due to lightning flashes, strong wind gusts, torrential rain, and occasional hail and tornadoes. The present research provides a composite stability index for forecasting thunderstorms. The forecast quality detection parameters are computed with the available indices during the period from 1997 to 2006 to select the most relevant indices with threshold ranges for the prevalence of such thunderstorms. The analyses reveal that the lifted index (LI) within the range of ?5 to ?12?°C, convective inhibition energy (CIN) within the range of 0?C150?J/kg and convective available potential energy (CAPE) within the ranges of 2,000 to 7,000?J/kg are the most pertinent indices for the prevalence thunderstorms over Kolkata during the premonsoon season. A composite stability index, thunderstorm prediction index (TPI) is formulated with LI, CIN, and CAPE. The statistical skill score analyses show that the accuracy in forecasting such thunderstorms with TPI is 99.67?% with lead time less than 12?h during training the index whereas the accuracies are 89.64?% with LI, 60?% with CIN and 49.8?% with CAPE. The performance diagram supports that TPI has better forecast skill than its individual components. The forecast with TPI is validated with the observation of the India Meteorological Department during the period from 2007 to 2009. The real-time forecast of thunderstorms with TPI is provided for the year?2010. 相似文献
7.
目前，临近预报技术主要包括雷暴识别追踪和外推预报技术、数值预报技术以及以分析观测资料为主的概念模型预报技术等。其中，识别追踪和外推预报技术主要以雷达资料为基础，在这方面，交叉相关外推和回波特征追踪识别外推是比较成熟的技术，已经用于许多的临近预报业务系统中，其缺陷是预报时效较短，准确率也不是很高。随着精细数值天气预报技术和计算机技术的发展，利用多普勒天气雷达资料和其它中小尺度观测资料进行数值模式初始化，来预报雷暴的发生、发展和消亡已经成为一个研究的热点，该技术发展很快但还不成熟。概念模型预报技术主要是通过综合分析多种中小尺度观测资料，包括雷达和气象卫星资料等，在此基础上建立雷暴发生、发展和消亡的概念模型，特别是边界层辐合线和强对流的密切关系等，再结合数值模式分析预报和其它外推技术的结果，然后建立雷暴临近预报的专家系统，其不但可以获取雷暴和对流降水移动、发展的信息，还可以预报它们的生成和消亡。检验和定性评估也表明，将多种资料和技术集于一体的概念模型专家系统，其临近预报的准确率最高，时效也最长，是临近预报技术未来发展的主要趋势之一。NCAR的Auto Nowcaster系统是雷暴临近预报概念模型专家系统的一个典型代表。 相似文献
8.
Lu YANG Cong-Lan CHENG Yu XIA Min CHEN Ming-Xuan CHEN Han-Bin ZHANG Xiang-Yu HUANG 《大气科学进展》2023,40(5):937-951
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... 相似文献
9.
重大活动关键时段的定点预报一直是天气预报服务的难点,因此对2015年北京田径世锦赛开幕式天气的预报思路和方法进行分析总结,结果表明开幕式天气采取了时间、空间逐步递进的精细化预报思路,每个阶段的预报重点、使用的预报方法和信息资料是不同的。短期预报以天气诊断和数值预报方法为主,应用多尺度数值模式和集合预报产品,预报出开幕式当天在东北冷涡背景下北京东部的强对流天气和鸟巢出现弱降水的可能性;短时临近预报依据高时空分辨率的探测资料、快速更新的同化产品和中尺度模式,采用多资料融合技术,对稳定度、水汽和阵风锋等多要素综合分析,预判雷暴的生消变化,跟进预报了开幕式鸟巢地区无降水,保障活动顺利举行。 相似文献
10.
复共线性关系对逐步回归预报方程的影响研究 总被引：1，自引：0，他引：1
针对气象预报中常用的逐步回归预报建模方法,由于没有直接考虑筛选出的预报因子之间可能存在复共线性关系会影响气象预报方程的预报性能问题,提出了在初选的大量气象预报因子(自变量)中,采用条件数计算分析方法,选择复共线性关系小的预报因子组合建立预报模型的方法.以重要气象灾害的预报难点--台风预报为例,用大样本分别建立了12个台风移动经度、纬度的条件数预报方程和逐步回归预报方程.对比分析结果表明,由于条件数计算分析有效控制了预报因子间的复共线性关系,因此,在相同的预报因子(自变量)和预报对象(因变量)条件下,分月建立的条件数台风移动路径预报方程,虽然历史建模样本的拟合精度略低于逐步回归预报方程,但是对独立样本的预报精度明显提高,其中7、8和9月条件数预报方程的预报误差平均为153.9 km,而相应的逐步回归预报误差平均为229.2 km,两者相差75.3 km.进一步研究发现,在F值分别取1.0、2.0和3.0的情况下,建立的台风移动路径的逐步回归预报方程,其预报误差也明显大于条件数预报方程.另外,由于预报因子组合的复共线性的影响,逐步回归方程还出现了在个别点预报误差极大的不合理情况. 相似文献
11.
AN EVALUATION OF SEVERAL TURBULENCE SCHEMES FOR THE PREDICTION OF MEAN AND TURBULENT FIELDS IN COMPLEX TERRAIN 总被引：2，自引：0，他引：2
PETER J. HURLEY 《Boundary-Layer Meteorology》1997,83(1):43-73
A prognostic three-dimensional mesoscale model has been developed andused in one- and two-dimensional modes to evaluate ten local turbulenceclosure schemes. The schemes ranged from first-order to the two-equationprognostic schemes. Predictions by the models were compared for aone-dimensional convective boundary layer using mixed layer scaling andmeasurements to interpret the results. Two-dimensional simulations were alsoperformed for a sea-breeze flow and for flow over a hill. The results showedthat for all of the models considered, minor differences were produced in themean meteorological fields and in the vertical scalar fluxes, but majordifferences were apparent in the velocity variances and dissipation rate.Predicted tracer concentrations were very sensitive to the turbulence modelformulation for dispersion from a point source in the convective boundarylayer, particularly for the prediction of maximum concentrations. Predictedtracer concentrations from a surface volume source for the two-dimensionalsimulations were similar for all models, although the degree of mixing in themorning growth period produced some differences. Generally, good results forthe mean meteorological fields can be obtained with first-order schemes, evenif they underpredict the magnitude of turbulence in the convective boundarylayer, and reasonable tracer concentrations can also be obtained with thesemodels provided near-source effects are not important. The two-equationprognostic models performed best for the prediction of turbulence in theconvective boundary layer. 相似文献
12.
Alexander Arpaci Chris S. Eastaugh Harald Vacik 《Theoretical and Applied Climatology》2013,114(3-4):393-406
The interpretation and communication of fire danger warning levels based on fire weather index values are critical for fire management activities. A number of different indices have been developed for various environmental conditions, and many of them are currently applied in operational warning systems. To select an appropriate combination of such indices to work in different ecoregions in mountainous, hilly and flat terrain is challenging. This study analyses the performance of a total of 22 fire weather indices and two raw meteorological variables to predict wildfire occurrence for different ecological regions of Austria with respect to the different characteristics in climate and fire regimes. A median-based linear model was built based on percentile results on fire days and non-fire days to get quantifiable measures of index performance using slope and intercept of an index on fire days. We highlight the finding that one single index is not optimal for all Austrian regions in both summer and winter fire seasons. The summer season (May–November) shows that the Canadian build-up index, the Keetch Byram Drought Index and the mean daily temperature have the best performance; in the winter season (December–April), the M68dwd is the best performing index. It is shown that the index performance on fire days where larger fires appeared is better and that the uncertainties related to the location of the meteorological station can influence the overall results. A proposal for the selection of the best performing fire weather indices for each Austrian ecoregion is made. 相似文献
13.
消除系统性观测误差的时空梯度信息同化方法研究 总被引：1，自引：1，他引：0
随着气象观测手段的进步,各种气象观测资料在数值预报模式中的应用不断发展.然而由于观测资料存在观测误差,尤其一些非常规资料存在系统性偏差,且难以对此类误差进行充分订正,使得观测资料在数值预报模式同化应用过程中的作用没有被充分发挥.文中提出一种消去此类误差的时间及空间梯度信息变分同化方法,其特点在于不需要知道系统性偏差的具体估计,而是用一个梯度信息算子对原变量进行变换从而隐性回避此类误差.通过浅水波模式四维变分同化理想试验结果表明,此同化方法完全消除平整性系统性偏差对同化结果的影响,本身数值较小的模式变量更能够获得好的同化效果,大数值变量则可通过估算来确定适用范围.由于最优解不唯一性质的存在,同化效果更多的吸收观测场的整体时空梯度分布趋势而非观测量值本身,这对具有较低可信度的观测资料是适用的. 相似文献
14.
The quantitative precipitation forecast (QPF) performance by numerical weather prediction (NWP) methods depends fundamentally on the adopted physical parameterization schemes (PS). However, due to the complexity of the physical mechanisms of precipitation processes, the uncertainties of PSs result in a lower QPF performance than their prediction of the basic meteorological variables such as air temperature, wind, geopotential height, and humidity. This study proposes a deep learning model named QPFNet, which uses basic meteorological variables in the ERA5 dataset by fitting a non-linear mapping relationship between the basic variables and precipitation. Basic variables forecasted by the highest-resolution model (HRES) of the European Centre for Medium-Range Weather Forecasts (ECMWF) were fed into QPFNet to forecast precipitation. Evaluation results show that QPFNet achieved better QPF performance than ECMWF HRES itself. The threat score for 3-h accumulated precipitation with depths of 0.1, 3, 10, and 20 mm increased by 19.7%, 15.2%, 43.2%, and 87.1%, respectively, indicating the proposed performance QPFNet improved with increasing levels of precipitation. The sensitivities of these meteorological variables for QPF in different pressure layers were analyzed based on the output of the QPFNet, and its performance limitations are also discussed. Using DL to extract features from basic meteorological variables can provide an important reference for QPF, and avoid some uncertainties of PSs. 相似文献
15.
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
16.
夏季降水日数的准确预测,对于保障农业、运输业、电力等行业的有序进行具有重要现实意义.利用连云港市气象局提供的1951—2012年夏季降水数据对连云港地区的降水日数特征进行分析,难以直观地发现夏季降水日数随时间分布的规律.为进一步探索降水日数的发生规律,结合国家气候中心网站提供的多种气候因子数据,基于CART决策树算法构建了连云港地区夏季降水日数是否偏多与是否偏少的分类与预测模型.该模型可以发现在多种气候因子不同条件下,夏季降水日数是否偏多（偏少）的规律,模型的分类与预测都具有良好的效果.利用52 a的数据样本训练模型,模型的训练准确率为90.38%（86.54%）,再用剩余10 a数据样本检验模型,测试准确率为80%（80%）,并且得到规则集,方便气象业务人员使用以及决策服务人员参考.同时,为降水日数的预测提供了数据挖掘的新思路. 相似文献
17.
豫北多时效归一化棉铃虫气象预报模式 总被引：4，自引：0，他引：4
按照棉铃虫繁育规律,将棉铃虫周年活动期划分为秋季预蛹期、越冬期、春季羽化期、夏季危害期4个阶段,分阶段选取有昆虫学、统计学意义的气象因子,通过归一化处理和加权组合,组成棉铃虫气象指数,建立多时效、归一化棉铃虫气象预报模式和分析、评价指标。结果显示：气象条件与棉铃虫发生程度密切相关,各时段预报模式的复相关系数达0.7780~0.8780,回代拟合率为96.7%,回归效果极显著。经试报应用,取得较好效果。结论认为：将诸多气象因子作无量纲化处理,不但便于因子间相互组合,还可提高模式的预报精度;将棉铃虫周年繁育期划分为秋季预蛹期、越冬期、春季羽化期、夏季危害期,突出了阶段性特点,分阶段组建预报模式,预报效果较好。对组合因子的生物学意义,有待生物学试验认定。 相似文献
18.
The summer monsoon rainfall totals for 31 meteorological subdivisions of India for the years 1901-1980 are analysed. The analysis reveals that four leading eigenvectors (EVs) are significant and account for 65 % of the total variance.The spatial pattern of the first EV exhibits in phase fluctuations over almost the whole India. The large coefficients of this vector can be considered as representative of the conditions of large-scale flood and drought over the country. The second pattern reveals the fluctuations mostly over the North Indian region (north of 20o latitude) probably in association with the Western Disturbances. The third pattern indicates fluctuations over the North-West and the North-East India in opposite phase and the fourth pattern exhibits the characteristic features of fluctuations associated with ‘break’. The spectral analysis of the coefficients of these EVs revealed quasi-periodicities of 2-5 years.On the basis of examination of the elements of these EVs the country has been divided into seven homogeneous regions. Rainfall indices of these regions and of the four EVs have been examined for seek-ing for association with some oceanic and atmospheric variables. The association is significant for the coefficients of the first EV and for the rainfall indices of central and South India. Among all the variables examined, Darwin pressure tendencies have the highest association and appear to be of special significance in prediction of the monsoon rainfall. 相似文献
19.
利用基于张弛逼近的四维数据同化技术,构建了广东深圳的千米格距网格化气象数据集,由于同化了深圳及周边可获得的高频次观测数据,气象数据集基本准确表现出几种关键气象要素的年际变化和月变化特征。在网格化气象数据集基础上开发了“深圳市细网格气候信息平台”,并通过平台推出了若干精细气候数据产品:精细风玫瑰、逐网格风能等。这些数据产品已经在格点气温预报、风能示范项目选址以及详细规划的自然通风评估中发挥了实际作用。这些探索表明,网格化气象数据集的建立,有望为城市的网格化精细管理和建设提供气象科技支撑。 相似文献
20.
Usage of multivariate geostatistics in interpolation processes for meteorological precipitation maps
Long-term meteorological data are very important both for the evaluation of meteorological events and for the analysis of their effects on the environment. Prediction maps which are constructed by different interpolation techniques often provide explanatory information. Conventional techniques, such as surface spline fitting, global and local polynomial models, and inverse distance weighting may not be adequate. Multivariate geostatistical methods can be more significant, especially when studying secondary variables, because secondary variables might directly affect the precision of prediction. In this study, the mean annual and mean monthly precipitations from 1984 to 2014 for 268 meteorological stations in Turkey have been used to construct country-wide maps. Besides linear regression, the inverse square distance and ordinary co-Kriging (OCK) have been used and compared to each other. Also elevation, slope, and aspect data for each station have been taken into account as secondary variables, whose use has reduced errors by up to a factor of three. OCK gave the smallest errors (1.002 cm) when aspect was included. 相似文献