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文章摘要
引用本文:孙敏,袁慧玲,杜予罡.2018.上海地区春季最高气温预报失败案例分析.气象,44(1):65-79.
上海地区春季最高气温预报失败案例分析
Analysis of the Spring Maximum 2 m Temperature Forecast Failure in Shanghai
投稿时间:2017-02-13  最后修改时间:2017-07-24
DOI:10.7519/j.issn.1000-0526.2018.01.006
中文关键词: 最高气温,预报失败案例,预报误差,集合预报,不确定性
英文关键词: maximum 2 m temperature, forecast failure, forecast error, ensemble forecast, uncertainty
基金项目:国家重点基础研究发展计划(973计划)(2013CB430106)、公益性行业(气象)科研专项(GYHY201206005)和国家自然科学基金项目(41675109)共同资助
作者单位
孙敏 上海中心气象台上海 200030;南京大学大气科学学院中尺度灾害性天气教育部重点实验室南京 210023 
袁慧玲 南京大学大气科学学院中尺度灾害性天气教育部重点实验室南京 210023;江苏省气候变化协同创新中心南京 210093 
杜予罡 上海中心气象台上海 200030 
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中文摘要:
      本文分析了2015年3月17—18日上海地区连续两天发生最高气温预报失误的天气背景,并使用当日实况观测和业务预报使用的数值模式资料,剖析预报失败的原因,分析表明:对天空状况的误判是导致17日预报失败的主要原因,且东南风预报偏强更进一步增大了预报误差;冷空气影响时间的判断失误是导致18日预报失败的主要原因。从模式预报的实时检验、预报的跳跃性和不确定性角度分析了预报中存在的问题:预报员应重视本地和上游实况,从传统对单一确定性模式预报的依赖向多模式多起报时次及能提供概率预报和不确定性信息的业务集合预报的分析思路转型。此外,还需加强对集合预报的系统性检验、评估及数值预报释用产品的开发,增加包含不确定性信息的公众天气预报发布形式。
英文摘要:
      Based on conventional surface and upper air observation data, the synoptic scale circulation of the maximum 2 m temperature forecast failure in Shanghai during 17-18 March 2015 is analyzed. Using the real time observations and numerical weather predictions, the causes of the forecast failure are investigated. The results show that the failure of the cloud cover forecast on 17 March was the main cause for the forecast failure. Meanwhile, the enhanced southeast winds further enlarged the forecast error. On 18 March, the misforecasted occurrence time of cold air advection into Shanghai mainly accounted for the forecast failure. The problems and recommendations in the forecast process were addressed, with the emphasis on the discrepancies between the real time observations and the forecasts, forecast jumpiness and forecast uncertainty. Forecasters should have paid more attention to the real time local and upstream observations, and different lead time forecasts from different models. More important, operational ensemble forecasts in a probabilistic sense were highly recommended instead of traditional deterministic forecasts of a single mo del. Therefore, it is necessary to systematically assess the ensemble forecast performance, develop new application and interpretation of NWP products, and provide more products of multi model ensemble forecasts with uncertainty information in public weather services.
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