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珠江三角洲地区重大短时强降水的基本流型与环境参量特征 总被引：8，自引：3，他引：5
为了了解珠江三角洲(简称珠三角)地区重大短时强降水(小时雨强≥50 mm)发生的环境特征,利用珠三角地区稠密自动气象站资料、探空资料、卫星资料等分析研究了近7年(2007—2013年)68个重大短时强降水事件的环境流型、T-lnp图形态和关键物理参数,结果表明珠三角地区重大短时强降水天气流型主要有台风型、西南季风型、北部湾低压型、冷(式)切变线型和热带云团型等5种;不同类型、不同季节出现的频率不同。台风型、西南季风型和北部湾低压型的大多数过程T-lnp图温度廓线和湿绝热线很接近,整层水汽含量丰富,对流有效位能(CAPE)大致呈"瘦弱"的狭长形形态;冷(式)切变线型温湿廓线呈上干下湿分布,CAPE大致呈较"胖"的狭长形;热带云团型温度廓线和湿绝热线很接近,CAPE形态较"胖"。850~500 hPa间温差△T_(85)都较小,一般在21~23℃,大气层结接近于湿中性层结,呈现弱的条件不稳定层结,表明大多数过程中有利于重大短时强降水发生的环境条件的关键点不是强对流预报中常关注的"高空冷空气的侵入",而是低层暖湿气流的输送;地面露点一般在23~25℃,暖云厚度在4100 m以上;大多数重大短时强降水发生前大气可降水量都在57 mm以上,其中台风型最大,其次是西南季风型、北部湾低压型、热带云团型,冷(式)切变线型最小,台风型、西南季风型、北部湾低压型CAPE一般小于1500 J·kg~1,属于比较温和的CAPE值,冷(式)切变线型、热带云团型平均CAPE≥1700 J·kg~(-1);对于所有类型对流抑制能(CIN)≤50 J·kg~1;除热带云团型外,大多数过程出现了低空急流;五种流型配置下,台风型、西南季风型大多处在弱到中等的0~6 km深层垂直风切变环境中,北部湾低压型和热带云团型处在弱的0~6 km垂直风切变环境中;冷(式)切变线型大多数过程处在中等强度的0~6 km垂直风切变环境中。可以将流型配置方法(分型)、重大短时强降水对应的关键环境参数以及根据箱线图展示的参数范围设定适宜的阈值的方法相结合,为珠三角地区显著强降水预报的改进提供有价值的参考。 相似文献
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To improve the accuracy of short-term(0–12 h) forecasts of severe weather in southern China, a real-time storm-scale forecasting system, the Hourly Assimilation and Prediction System(HAPS), has been implemented in Shenzhen, China. The forecasting system is characterized by combining the Advanced Research Weather Research and Forecasting(WRF-ARW)model and the Advanced Regional Prediction System(ARPS) three-dimensional variational data assimilation(3DVAR) package. It is capable of assimilating radar reflectivity and radial velocity data from multiple Doppler radars as well as surface automatic weather station(AWS) data. Experiments are designed to evaluate the impacts of data assimilation on quantitative precipitation forecasting(QPF) by studying a heavy rainfall event in southern China. The forecasts from these experiments are verified against radar, surface, and precipitation observations. Comparison of echo structure and accumulated precipitation suggests that radar data assimilation is useful in improving the short-term forecast by capturing the location and orientation of the band of accumulated rainfall. The assimilation of radar data improves the short-term precipitation forecast skill by up to9 hours by producing more convection. The slight but generally positive impact that surface AWS data has on the forecast of near-surface variables can last up to 6–9 hours. The assimilation of AWS observations alone has some benefit for improving the Fractions Skill Score(FSS) and bias scores; when radar data are assimilated, the additional AWS data may increase the degree of rainfall overprediction. 相似文献
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A nowcasting technique based on application of the particle filter blending algorithm 总被引：2，自引：1，他引：1
To improve the accuracy of nowcasting, a new extrapolation technique called particle filter blending was configured in this study and applied to experimental nowcasting. Radar echo extrapolation was performed by using the radar mosaic at an altitude of 2.5 km obtained from the radar images of 12 S-band radars in Guangdong Province, China. The first bilateral filter was applied in the quality control of the radar data; an optical flow method based on the Lucas–Kanade algorithm and the Harris corner detection algorithm were used to track radar echoes and retrieve the echo motion vectors; then, the motion vectors were blended with the particle filter blending algorithm to estimate the optimal motion vector of the true echo motions; finally, semi-Lagrangian extrapolation was used for radar echo extrapolation based on the obtained motion vector field. A comparative study of the extrapolated forecasts of four precipitation events in 2016 in Guangdong was conducted. The results indicate that the particle filter blending algorithm could realistically reproduce the spatial pattern, echo intensity, and echo location at 30- and 60-min forecast lead times. The forecasts agreed well with observations, and the results were of operational significance. Quantitative evaluation of the forecasts indicates that the particle filter blending algorithm performed better than the cross-correlation method and the optical flow method. Therefore, the particle filter blending method is proved to be superior to the traditional forecasting methods and it can be used to enhance the ability of nowcasting in operational weather forecasts. 相似文献
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Ediacaran successions occur widely in various depositional facies in South China and yield a series of fossil Lagerst?tten, providing a complete fossil record for the evolution of marine ecosystems after the terminal Cryogenian global glaciation. Carbonate-dominated Ediacaran successions in shallow water facies in South China record a nearly complete δ~(13)C profile that may reflect variations of marine carbon isotopic composition during the Ediacaran Period. The Ediacaran fossils andδ~(13)C profiles from South China permit stratigraphic correlation and subdivision of the Ediacaran strata. Based on biostratigraphic, chemostratigraphic, and geochronometric data from the Ediacaran successions in South China, we propose that the Ediacaran System in China can be subdivided into two series, with three stages in each series. The lower series is characterized by acanthomorphic acritarchs and the upper series by Ediacara-type macrofossils, and the two series are separated by the declining limb of a pronounced δ~(13)C negative excursion(EN3) in the upper Doushantuo Formation. The basal boundary of Stage1 is the same as the basal boundary of Ediacaran System, which has been defined at the base of the cap carbonate unit. Stage 2 represents the first radiation of Ediacaran microscopic organisms, with δ~(13)C feature representing by positive values(EP1). The base of the Stage 2 is placed at the first appearance level of a spiny acritarch species. Stage 3 is characterized by the occurrence of more diverse acritarchs and δ~(13)C feature EP2, with its basal boundary defined by a δ~(13)C negative excursion(EN2) occurring in the middle Doushantuo Formation. The basal boundary of Stage 4 is the same as the upper series. Stage 5 is marked by the occurrence of macrfossils of Miaohe biota, and its lower boundary can be placed at the level where δ~(13)C values transition from positive to negative in MNE, or the first appearance level of macrofossils of the Miaohe biota. Stage 6 is characterized by the occurrences of Ediacara-type Shibantan biota and Gaojiashan biota, with its lower boundary defined by the first appearance level of Conotubus hemiannulatus. The formal establishment of the aforementioned series and stages requires further and more detailed integrative stratigraphic study on the Ediacaran successions in China. Some of the Ediacaran successions in South China have great potential to become global standards in Ediacaran subdivision. 相似文献
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基于2016-2018年ECMWF模式温度预报和浙江省72个国家基本站观测资料,根据温度日变化特征,采用K-近邻(KNN)回归算法进行误差订正,改进浙江省172 h精细化温度预报。在KNN回归算法中,将模式起报时刻的温度视作“背景”,由模式预报减去起报时刻温度消除“背景”影响,得到温度日变化曲线,通过温度日变化曲线构建差异指标,选取历史相似个例。根据历史相似个例的误差特征,对温度预报进行订正,得到改进的温度预报。检验结果表明,KNN方案的温度预报平均绝对误差较ECMWF和30 d滑动平均误差订正方案(OCF)的分别减小26.2%和5.2%;日最高和最低温度预报误差绝对值小于2℃,准确率较ECMWF的分别提高14.8%和4.3%,较OCF的分别提高3.0%和1.3%。KNN方案对地形复杂地区的温度预报改进效果更为明显,对冷空气活动和夏季高温等天气过程预报改善效果也较稳定。 相似文献
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受季风槽影响,2018年8月30—31日华南地区出现一次极端暴雨过程,单日站点累计降水量达1?056.7 mm,刷新了广东有历史纪录以来新的极值。对于此次极端降水事件,常用的业务模式包括欧洲中期天气预报中心全球模式（ECMWF）、日本气象厅谱模式（JMA）和中国气象局广东快速更新同化数值预报系统（CMA-GD）,都低估了降水强度。利用深圳市气象局业务对流尺度集合预报系统分析了此次特大暴雨过程,结果表明：对流尺度集合预报系统对本次特大暴雨过程具有比较好的预报能力,概率匹配平均最大雨量达348.7 mm·(24 h)-1,集合平均的强降水中心和观测基本一致,观测极值附近区域发生大暴雨（≥150 mm）概率最大值达到80%。选取了较“好”和较“差”集合成员预报进行对比分析,发现较“好”成员预报的强降水中心位置和观测基本一致,而较“差”成员预报的降水中心位置则偏向福建地区。较 “好”成员预报出莲花山南侧地面中尺度辐合线较长时间的维持和缓慢移动,导致强降水雨团在莲花山脉附近不断地触发和维持,同时地形的阻挡作用使得对流系统在地形附近区域持续维持,造成了罕见的特大暴雨;而较“差”成员辐合区位于莲花山以北,对流形成后向东、向北移动,最终导致强降水预报位置偏向福建地区。 相似文献
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滇东早奥陶世阿莫里坎砂岩相沉积 总被引：2，自引：2，他引：2
根据沉积特征、大化石、遗迹化石及微体化石等诸方面证据，认为滇东早奥陶世地层属于广泛分布于西南欧、北非、中东及纽芬兰东部的阿莫里坎砂岩相沉积。 相似文献
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WAN Bin YUAN Xunlai CHEN Zhe GUAN Chengguo PANG Ke TANG Qing and RAO Xin 《《地质学报》英文版》2013,87(4):905-915
As a more efficient quantitative method for morphological analysis, geometric morphometrics is applied to the flabellate fossils Flabellophyton including Flabellophyton lantianensis and Flabellophyton strigata from Neoproterozoic Ediacaran Lantian biota, South China. Both traditional morphometric analysis (including diverging angle, length, and width distribution) and geometric morphometric analysis [including superposition of normalized area analysis, non-metric multidimensional scaling (n-MDS), Bray-Curtis similarity cluster analysis (CLUSTER) and analysis of similarities (ANOSIM)] were performed. The results indicate there are great interspecific morphological differences between F. lantianensis and F. strigata, in addition to some intraspecific variations within each species. Here we preliminarily suggest that the previously defined Flabellophyton should be subdivided into 2 genera at least: one marked by the dark transverse striated structure, and the other without. This recharacterization and reclassification work still needs further careful observation and comprehensive analysis with large number of flabellate fossils combining morphology, structure, population, and community-ecology study. 相似文献