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Analysis of Mesoscale Convective Systems Associated With a Warm-Sector Rainstorm Event Over South China 总被引:1,自引:1,他引:0
With multiple meteorological data, including precipitation from automatic weather stations, integrated satellite-based precipitation (CMORPH), brightness temperature (TBB), radar echoes and NCEP reanalysis, a rainstorm event, which occurred on May 26, 2007 over South China, is analyzed with the focus on the evolution characteristics of associated mesoscale-β convective systems (Mβcss). Results are shown as follows. (1) The rainstorm presents itself as a typical warm-sector event, for it occurs within a surface inverted trough and on the left side of a southwesterly low-level jet (LLJ), which shows no obvious features of baroclinicity. (2) The heavy rainfall event is directly related to at least three bodies of Mβcss with peak precipitation corresponding well to their mature stages. (3) The Mβcss manifest a backward propagation, which is marked with a new form of downstream convection different from the more usual type of forward propagation over South China, i.e., new convective systems mainly form at the rear part of older Mβcss. (4) Rainstorm-causing Mβcss form near the convergence region on the left side of an 850-hPa southwesterly LLJ, over which there are dominantly divergent air flows at 200 hPa. Different from the typical flow pattern of outward divergence off the east side of South Asia High, which is usually found to be over zones of heavy rains during the annually first rainy season of South China, this warm-sector heavy rain is below the divergence region formed between the easterly and southerly flows west of the South Asian High that is moving out to sea. (5) The LLJ transports abundant amount of warm and moist air to the heavy rainfall area, providing advantageous conditions for highly unstable energy to generate and store at middle and high levels, where corresponding low-level warm advection may be playing a more direct role in the development of Mβcss. As a triggering mechanism for organized convective systems, the effect of low-level warm advection deserves more of our attention. Based on the analysis of surface mesoscale airflow in the article, possible triggering mechanisms for Mβcss are also discussed. 相似文献
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采用统计调查分析方法,对京津冀地区2014年霾气象服务情况进行调查。在此基础上,统计分析了公众对霾的认知程度、防护措施及预报服务评价等情况,并利用直接损失评估法和疾病成本法等方法,对北京地区2014年霾健康气象服务减少的健康人口损失和经济损失进行了估算。研究发现,京津冀地区的公众对霾的认知度和关注度极高,但公众对霾预报气象服务满意程度仍有较大的提升空间;七成以上的公众会根据霾预报服务信息采取适当的防护措施。经估算,北京市2014年由于PM_(2.5)造成的健康人口损失数为3085人,占总死亡人数的2.3%,造成的健康经济损失值为24.52亿元;未来在与2014年同等的PM_(2.5)暴露浓度之下,公众采用相应气象服务后,在不同的情景下所接受的PM_(2.5)年平均暴露浓度减少5%和10%的情况下,北京市每年可能减少的健康人口损失数为113~226人,可能减少健康经济损失值为0.9~1.8亿元。 相似文献
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利用2013年中国气象局与国家统计局共同调查的全国公众气象服务评价统计数据,根据经济学中费用-效益分析的有关理论,分析了不同区域、不同人群特征的公众对有偿气象服务的支付意愿和使用频次,并利用"支付意愿法"和"国家投入法",定量评估了2013年广东地区的公众对气象服务的支付意愿总额以及公众期望政府为气象服务投入的经费总额。通过分析,发现广东省有偿气象服务市场巨大,某些群体对付费业务的接受程度和支付意愿都要高出其他群体,愿意付出一定费用获得更优质、更有针对性的气象服务,为此建议进一步研究用户需求和支付意愿,更好地定位有偿服务的潜在用户群,为该人群推出定制化气象服务产品,满足这部分群体的气象需求。 相似文献
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利用2009—2015年江淮夏季雷暴大风观测资料和NCEP再分析资料,按整层可降水量将雷暴大风环境划分为干、湿两种环境,结果发现湿环境雷暴大风日约占总雷暴大风日数的86%。基于物理量参数和Logistic回归方法构建了江淮夏季干、湿环境下区域雷暴大风的潜势预报模型。西南区、东南区和北区湿环境雷暴大风的最显著预报因子分别是冰雹指数(CS)、K指数和沙氏指数(SI)。干环境雷暴大风的最显著预报因子是总指数(TT)。相对于大风指数(WINDEX),综合考虑热力学作用和高空水平动量信息的新大风指数(GUSTEX)对江淮干、湿环境雷暴大风的预报指示意义更好。通过历史样本回报确立了预报模型的概率阈值,并利用2016年独立样本试预报检验证明Logistic模型预报效果良好。 相似文献
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