基于WRF模式和CloudSat卫星资料对黄淮下游一次强对流天气过程的诊断分析和数值模拟
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国家重点基础研究发展计划(973计划)项目(2014CB441403);江苏高校优势学科建设工程资助项目(PAPD)


Simulation analysis of strong convective weather processes in Huanghuai River based on WRF model and CloudSat satellite data
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    摘要:

    利用CloudSat卫星资料和WRF中尺度模式,结合NCEP再分析资料及FY2G静止气象卫星资料,研究了发生在黄淮地区的一次深对流天气过程,分析了此次过程的天气特征、动力结构,重点分析了该次强对流过程中各水成物的时空演变特征。结果表明:(1)黄淮下游地区处于副高西北边缘,温度高,湿度大,对流潜势好。在地面冷锋和低层切变线的抬升触发下,气流不断辐合上升,同时高层冷平流与低层暖湿空气为强对流的发展提供了热力不稳定条件;(2)使用静止卫星TBB产品可以很好的定位、追踪深对流系统,但单一的TBB产品无法分辨深对流云和较厚的高云。本文结合CloudSat卫星资料和TBB产品把剖面上的云分为3种:非对流云(NDC),一般深对流云(DC),深对流核(DCC);(3)深对流云核(DCC)位于对流系统南部边缘,在3种云中DCC中冰相粒子粒径大、数浓度多、冰水含量大,且其最大值区域都位于12 km高度附近,这一区域可能是对流云内冰晶凝华增长、凇附增长、聚并增长形成大冰相粒子的关键发生区;(4)耦合了NSSL双参方案的WRF模式对于本次过程体现了较好的模拟效果,并通过模拟再现了此次天气过程中水成物的分布特征,发现本次过程深对流云中存在过冷水累积带特征。冰核核化形成的冰晶通过碰并过程形成雪晶,霰又由雪晶碰撞冻结过冷水滴以及过冷雨滴冻结产生,之后不断增长转化形成冰雹,雹增长到足够大后降落,其中雪晶和过冷水累积带对霰(雹胚)及雹的产生及增长至关重要。

    Abstract:

    By using the CloudSat satellite data and the WRF mesoscale model, combined with NCEP reanalysis data and FY2G stationary meteorological satellite data, a deep convective weather process occurred in the Huanghuai area was studied. The weather characteristics, dynamic structure, temporal and spatial evolution characteristics of hydrometeors in the severe convective weather process were analyzed emphatically. Results show that:(1)The downstream of Huanghuai river located in the northwest edge of western Pacific subtropical high, which had high temperature, high humidity and good condition of convection potential. The ground cold front and low-level shear line lifted the air flow, and made it continue convergence rising, and the configuration of high-level cold and low-level warm and humid air provided a thermal instability for the development of strong convection. (2)The stationary satellites TBB product could locate and track deep convection system, but a single TBB products could not distinguish between deep convective clouds and thick high clouds, so this paper combined CloudSat satellite data and TBB products and classified clouds to three classification as Non-Convective Cloud (NDC), general Deep Convective Cloud (DC)and Deep Convective Core (DCC). (3)The DCC was located at the southern edge of the convective system. The particle size of the ice particles was larger, the ice number concentration was more, the ice water content was larger in the DCC, and the maximum area is near 12 km. This area may be the key occurrence area of the formation of large ice particles. (4)The WRF model showed a favorable effect for this process and showed the distribution characteristics of hydrometeors. An accumulation of supercooled water and hail cycle growth characteristics in the cloud was found. Snow crystals generated through collision and coalescence of ice crystals, which were generated by nucleation of ice nucleus,and graupel generated by the snow crystal aggregated freeze droplets and with supercooled rain drops freezing. Then, graupel transformed into hail by cycle of growth, and hail would shoot when hail increased to large enough. The snow crystals and accumulation of supercooled water is critical to the generation and growth of the grape and hail.

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况祥,银燕,陈景华,肖辉.基于WRF模式和CloudSat卫星资料对黄淮下游一次强对流天气过程的诊断分析和数值模拟.气象科学,2018,38(3):331-341 KUANG Xiang, YIN Yan, CHEN Jinghua, XIAO Hui. Simulation analysis of strong convective weather processes in Huanghuai River based on WRF model and CloudSat satellite data. Journal of the Meteorological Sciences,2018,38(3):331-341

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  • 收稿日期:2017-03-13
  • 最后修改日期:2017-04-12
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  • 在线发布日期: 2018-07-16
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