干旱气象 ›› 2019, Vol. 37 ›› Issue (2): 339-344.DOI: 10.11755/j.issn.1006-7639(2019)-02-0339

• 业务技术应用 • 上一篇    下一篇

北京智能网格温度客观预报方法(BJTM)及预报效果检验

戴翼1,何娜1,2,付宗钰1,亢妍妍1,郝翠1,2   

  1. 1.北京市气象台,北京 100089;
    2.中国气象局北京城市气象研究所,北京 100089
  • 出版日期:2019-04-30 发布日期:2019-04-30
  • 通讯作者: 何娜(1984— ),硕士,高级工程师,主要从事中尺度天气系统诊断分析及客观预报方法研究. E-mail:hena0105@163.com。
  • 作者简介:戴翼(1988— ),博士,工程师,主要从事模式评估及客观预报方法研究. E-mail:dy3050643006@126.com。
  • 基金资助:
    国家重点研发计划(2018YFF0300104)、气象预报业务关键技术发展专项(YBGJXM201703)、中央级公益性科研院所基本科研业务费专项(IUMKY201731)及北京市气象局科技项目(BMBKJ201703001)共同资助

Beijing Intelligent Grid Temperature Objective Prediction Method (BJTM) and Verification of Forecast Result

DAI Yi1, HE Na1,2, FU Zongyu1, KANG Yanyan1, HAO Cui1,2   

  1. 1. Beijing Municipal Weather Forecast Center, Beijing 100089, China;
    2. Institute of Urban Meteorology, CMA, Beijing 100089, China
  • Online:2019-04-30 Published:2019-04-30

摘要: 基于欧洲中心中期天气预报(ECMWF)精细化数值预报模式产品资料,采用一元线性回归以及克里金插值,发展了北京地区智能网格温度客观预报方法(Beijing intelligent grid temperature objective prediction method,BJTM),并对2017年1—12月北京地区55个考核站进行检验。结果表明,BJTM对ECMWF细网格模式的温度预报订正能力有显著提升,日最高、最低气温预报准确率分别提高25.4%和11.2%。2018年1—6月的业务运行结果也表明BJTM预报产品的预报结果优于同期ECMWF模式、中央台指导预报及预报员主观预报产品。BJTM可以有效提升北京地区温度预报的精细化能力和水平,有较好的业务应用价值。

关键词: 网格温度, 一元线性回归, 克里金插值, BJTM

Abstract: Based on the daily maximum and minimum temperature forecasting products of the European Center Medium-Term Weather Forecasting (ECMWF), the Beijing Intelligent Grid Objective Prediction Method (BJTM) has been developed by using the linear regression method and Kriging interpolation. The observation data of 55 appraisal stations in Beijing from January to December in 2017 were used as a test. The results show that BJTM had significantly improved the temperature forecast ability of the ECMWF fine-grid model. The accuracy of the forecasted daily maximum and minimum temperature from 1 to 7 days had been improved 25.4% and 11.2%, respectively. The operation results from January to June in 2018 also showed that the BJTM forecast product was better than that of the ECMWF model, the SCMOC and forecaster during the same period, respectively. The BJTM has significantly improved the refinement ability of temperature prediction in Beijing area, and it has better operational application value.

Key words: grid temperature, linear regression method, Kriging interpolation, BJTM

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