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1.
为进一步完善热带气旋大风风圈的分析和预报业务,利用中央气象台(NMC)发布的热带气旋报文资料、ERA5再分析资料,研究了2015年6月30日至2020年12月31日热带气旋最大强度时的7、10和12级风圈的非对称性特征及成因。统计结果表明: 热带气旋的7级风圈半径非对称性最大,10级次之,12级最小;非对称分布热带气旋的7、10和12级风圈最大半径大多分布在东北、东南和西北象限;同一热带气旋的7级和10级风圈最大半径大多分布在相同的象限。将7级风圈单一象限分布的热带气旋与多象限分布的热带气旋各按象限分布分成4类,分析4类7级风圈单一象限分布的热带气旋生成季节、地面10 m风特征及风圈非对称分布的成因发现:各类热带气旋具有明显的季节特征;地面10 m风场呈不对称分布;风圈非对称分布与西太平洋副热带高压、西南气流及地面冷高压等天气系统与热带气旋的相互作用造成的各象限位势高度梯度非对称分布密切相关。   相似文献   
2.
为评估用于超大城市综合气象观测试验的测风激光雷达,从最大有效探测高度和数据获取率两方面对测风激光雷达的探测能力进行分析,同时使用测风激光雷达与深圳气象梯度观测塔的测风资料从不同观测高度、不同观测值等方面进行对比分析,结果表明:测风激光雷达与深圳气象梯度观测塔的风速、风向一致性较好,相关系数分别为0.96、0.99,平均绝对误差分别为0.54 m/s、9.95 °,且不同高度层的测风结果也较为一致,但雨天和雾天条件对测风激光雷达的最大有效探测高度和数据获取率影响较大,设备探测能力受到一定的限制。   相似文献   
3.
基于比差分传播相移(KDP)的降水估计算法R(KDP)相较于传统基于水平反射率因子(ZH)的算法R(ZH)的表现更优。在雷达实际运行中,由于随机误差和后向散射相位(backscattering phase)的影响,可能出现负的KDP。运用一种基于变分的雷达定量降水估计混合算法(V-RQPE)。该算法用变分拟合方法重构差分相位(ΦDP),用一种新的稳健的边界条件求解方法,在消除随机误差的同时获得非负的KDP,进而进行降水估计。随后我们使用2017年5月7日广州S波段雷达的回波数据和地面雨量站观测数据进行验证,同时使用了六种不同的算法进行对比,结果显示,在1小时累计降水估计中,V-RQPE表现最好,在24小时累计降水估计中,V-RQPE和基于变分拟合的KDP的降水估计算法(R-VKDP)表现最好,实验结果表明变分拟合方法对雷达降水估计能力有显著提升。   相似文献   
4.
使用2020年3—9月逐时更新的CMA广东短临3 km数值模式(CMA-GD(R3)模式)1~12 h逐小时降水量资料,利用最优TS评分订正方法(OTS)对逐小时降水量进行分级订正,并分别从整体和分类型降水过程预报订正效果进行了检验和对比评估。结果表明:从整体预报订正性能来看,通过OTS方法对CMA-GD(R3)模式订正后,对于≥1 mm/h及以上量级的降水,OTS均有较好的订正能力,并且随着雨强的增加,其TS评分的改善比率越大;同时,OTS可有效减少各个预报时效的漏报率和空报率,其中漏报率减小更加明显,表现出明显的湿偏差(空报偏多)。从三类暴雨过程逐时降水预报订正效果来看,通过OTS订正之后,对于≥1 mm/h的降水,OTS对三类暴雨类型均有正的订正能力。其中在0.1 mm、1 mm、10 mm、20 mm、35 mm、50 mm 6个量级上,季风型的逐时降水预报表现最好,6个量级的TS评分值分别为0.403、0.232、0.053、0.023、0.009和0.004;在5 mm量级上锋面型的逐时降水预报表现最优,其TS值为0.102。从改善效果来看,经过OTS订正后,在1 mm量级上台风型改善率最大,在5 mm和10 mm量级上锋面型改善率最大,在20 mm、35 mm和50 mm量级上季风型改善率最大。   相似文献   
5.
The prolonged mei-yu/baiu system with anomalous precipitation in the year 2020 has swollen many rivers and lakes,caused flash flooding,urban flooding and landslides,and consistently wreaked havoc across large swathes of China,particularly in the Yangtze River basin.Significant precipitation and flooding anomalies have already been seen in magnitude and extension so far this year,which have been exerting much higher pressure on emergency responses in flood control and mitigation than in other years,even though a rainy season with multiple ongoing serious flood events in different provinces is not that uncommon in China.Instead of delving into the causes of the uniqueness of this year’s extreme precipitation-flooding situation,which certainly warrants in-depth exploration,in this article we provide a short view toward a more general hydrometeorological solution to this annual nationwide problem.A“glocal”(global to local)hydrometeorological solution for floods(GHS-F)is considered to be critical for better preparedness,mitigation,and management of different types of significant precipitation-caused flooding,which happen extensively almost every year in many countries such as China,India and the United States.Such a GHS-F model is necessary from both scientific and operational perspectives,with the strength in providing spatially consistent flood definitions and spatially distributed flood risk classification considering the heterogeneity in vulnerability and resilience across the entire domain.Priorities in the development of such a GHS-F are suggested,emphasizing the user’s requirements and needs according to practical experiences with various flood response agencies.  相似文献   
6.
This paper proposes a simple and powerful optimal integration (OPI) method for improving hourly quantitative precipitation forecasts (QPFs, 0-24 h) of a single-model by integrating the benefits of different bias- corrected methods using the high-resolution CMA-GD model from the Guangzhou Institute of Tropical and Marine Meteorology of China Meteorological Administration (CMA). Three techniques are used to generate multi-method calibrated members for OPI: deep neural network (DNN), frequency-matching (FM), and optimal threat score (OTS). The results are as follows: (1) The QPF using DNN follows the basic physical patterns of CMA-GD. Despite providing superior improvements for clear-rainy and weak precipitation, DNN cannot improve the predictions for severe precipitation, while OTS can significantly strengthen these predictions. As a result, DNN and OTS are the optimal members to be incorporated into OPI. (2) Our new approach achieves state-of-the-art performances on a single model for all magnitudes of precipitation. Compared with the CMA-GD, OPI improves the TS by 2.5%, 5.4%, 7.8%, 8.3%, and 6.1% for QPFs from clear-rainy to rainstorms in the verification dataset. Moreover, OPI shows good stability in the test dataset. (3) It is also noted that the rainstorm pattern of OPI relies heavily on the original model and that OPI cannot correct for deviations in the location of severe precipitation. Therefore, improvements in predicting severe precipitation using this method should be further realized by improving the numerical model’s forecasting capability.  相似文献   
7.
应用2017—2018年5—9月福建省观测资料对华南区域中尺度模式(GTRAMS-3 km-RUC)预报进行站点检验,建立和训练基于卷积神经网络的逐时降水分级订正模型,并与频率匹配法进行2017—2018年测试集的对比试验和2019年数据集的模拟业务检验,探讨了试验过程中遇到的样本不均衡、特征变量选取以及模型过拟合问题。结果表明:模式对于15 mm·h-1以上降水的预报能力弱,各订正方法对原始预报均有不同程度的改进作用。从评估指标来看,基于卷积神经网络的订正方法比频率匹配法表现出优势,其中相关系数判别方案下的网络模型对强降水预报的订正效果显著优于其他方法;在输入特征变量选取方面,应用主成分分析方案的模型训练收敛速度比相关系数判别方案更快,最佳训练期有所提前,但也更早进入严重的过拟合状态,而相关系数判别方案能够使网络模型的训练拥有更长的提升期以达到更具“潜力”的状态;基于卷积神经网络的订正方法对减少分类降水预报的漏报率、晴雨和弱降水预报的空报率具有显著作用,其优化程度明显超过频率匹配法。  相似文献   
8.
Based on the observations of a squall line on 11 May 2020 and stratiform precipitation on 6 June 2020 from two X-band dual-polarization phased array weather radars (DP-PAWRs) and an S-band dual-polarization Doppler weather radar (CINRAD/SA-D), the data reliability of DP-PAWR and its ability to detect the fine structures of mesoscale weather systems were assessed. After location matching, the observations of DP-PAWR and CINRAD / SA-D were compared in terms of reflectivity (ZH), radial velocity (V), differential reflectivity (ZDR), and specific differential phase (KDP). The results showed that: (1) DP-PAWR has better ability to detect mesoscale weather systems than CINRAD/SA-D; the multi-elevation-angles scanning of the RHI mode enables DP-PAWR to obtain a wider detection range in the vertical direction. (2) DP-PAWR’s ZH and V structures are acceptable, while its sensitivity is worse than that of CINRAD/SA-D. The ZH suffers from attenuation and the ZH area distribution is distorted around strong rainfall regions. (3) DP-PAWR’s ZDR is close to a normal distribution but slightly smaller than that of CINRAD/SA-D. The KDP products of DP-PAWR have much higher sensitivity, showing a better indication of precipitation. (4) DP-PAWR is capable of revealing a detailed and complete structure of the evolution of the whole storm and the characteristics of particle phase variations during the process of triggering and enhancement of a small cell in the front of a squall line, as well as the merging of the cell with the squall line, which cannot be observed by CINRAD/SA-D. With its fast volume scan feature and dual-polarization detection capability, DP-PAWR shows great potential in further understanding the development and evolution mechanisms of meso-γ-scale and microscale weather systems.  相似文献   
9.
Based on four reanalysis datasets including CMA-RA, ERA5, ERA-Interim, and FNL, this paper proposes an improved intelligent method for shear line identification by introducing a second-order zonal-wind shear. Climatic characteristics of shear lines and related rainstorms over the Southern Yangtze River Valley (SYRV) during the summers (June-August) from 2008 to 2018 are then analyzed by using two types of unsupervised machine learning algorithm, namely the t-distributed stochastic neighbor embedding method (t-SNE) and the k-means clustering method. The results are as follows: (1) The reproducibility of the 850 hPa wind fields over the SYRV using China’s reanalysis product CMA-RA is superior to that of European and American products including ERA5, ERA-Interim, and FNL. (2) Theory and observations indicate that the introduction of a second-order zonal-wind shear criterion can effectively eliminate the continuous cyclonic curvature of the wind field and identify shear lines with significant discontinuities. (3) The occurrence frequency of shear lines appearing in the daytime and nighttime is almost equal, but the intensity and the accompanying rainstorm have a clear diurnal variation: they are significantly stronger during daytime than those at nighttime. (4) Half (47%) of the shear lines can cause short-duration rainstorms (≥20 mm (3h)-1 ), and shear line rainstorms account for one-sixth (16%) of the total summer short-duration rainstorms. Rainstorms caused by shear lines are significantly stronger than that caused by other synoptic forcing. (5) Under the influence of stronger water vapor transport and barotropic instability, shear lines and related rainstorms in the north and middle of the SYRV are stronger than those in the south.  相似文献   
10.
利用粤港澳闪电定位系统、广州多普勒天气雷达和自动气象站等资料, 分析了2017年6月2日发生在广州市中北部的一次强雷暴天气过程的地闪变化特征及闪电与雷达回波特征的关系。(1)本次强雷暴天气是华南一起典型的以西南急流和切变线为环流背景的强对流天气过程。在整个雷暴生命史中以负地闪为主, 占69.3%;正闪在雷暴发展的初始和结束阶段占比较大。(2)闪电频数分布与强雷达回波区域存在着较好的对应关系, 闪电活动位置稍有提前, 地闪频数峰值的时间比雷达回波峰值时间平均提前了11.1 min。(3)回波顶高是产生闪电的先决条件, 闪电较多分布在回波顶高9~15 km范围内, 地闪频数峰值落后于回波顶高峰值12~18 min。   相似文献   
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