主办单位：中国气象局沈阳大气环境研究所
国际刊号：ISSN 1673-503X
国内刊号：CN 21-1531/P
气象与环境学报

气象与环境学报 ›› 2020, Vol. 36 ›› Issue (6): 50-57.doi: 10.3969/j.issn.1673-503X.2020.06.006

• 论文 • 上一篇    下一篇

辽宁地区ECMWF模式气温预报检验及误差订正研究

金巍1,2(),刘卫华3,高凌峰4,王茜5,韩国敬1   

  1. 1. 鞍山市气象局, 辽宁 鞍山 114000
    2. 中国科学院空间天气学国家重点实验室, 北京 100190
    3. 大连气象信息中心, 大连 116000
    4. 辽阳市气象局, 辽宁 辽阳 111000
    5. 辽宁省气象服务中心, 辽宁 沈阳 110166
  • 收稿日期:2020-03-27 出版日期:2020-12-30 发布日期:2021-01-06
  • 作者简介:金巍, 女, 1968年生, 正研级高级工程师, 主要从事短期天气预报和气候预测研究, E-mail:lnyk_jw@163.com
  • 基金资助:
    辽宁省气象局的关键技术项目(LNG201901);2019年中国科学院国家空间科学中心空间天气学国家重点实验室开放课题

Research on the test and error correction in temperature forecasted by the ECWMF model in Liaoning province

Wei JIN1,2(),Wei-hua LIU3,Ling-feng GAO4,Qian WANG5,Guo-jing HAN1   

  1. 1. Anshan Meteorological Service, Anshan 114000, China
    2. State Key Laboratory of Space Weather, Chinese Academy of Sciences, Beijing 100190, China
    3. Dalian Meteorological Information Center, Dalian 116000, China
    4. Liaoyang Meteorological Service, Liaoyang 111000, China
    5. Meteorological Service Center of Liaoning Province, Shenyang 110166, China
  • Received:2020-03-27 Online:2020-12-30 Published:2021-01-06

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摘要：

利用2016—2018年ECMWF细网格模式12—36 h内2 m温度预报产品，选取辽宁地区65个城镇站点观测资料，评估预报产品在不同季节的预报准确率，并按季节分析固定误差订正方法和最优滑动周期订正方法对提高准确率的作用。结果表明：ECMWF模式预报产品对辽宁地区气温预报的准确率表现为，ECMWF模式最高气温冬季预报最优(城镇站点预报准确率为81.5%)，最低气温夏季预报最好(城镇站点预报准确率为84.3%)；采用最优滑动周期订正后，2016—2018年辽宁地区的最高气温和最低气温准确率较ECMWF模式自身分别提高了19.7%和20.5%，最低气温的预报准确率提高程度优于最高气温；在整个空间分布中，ECMWF模式对辽宁中部平原地区最高(低)气温预报准确率高于东、西部地区，辽宁东北部和西南部以及东南部的长白山余脉影响区域准确率明显低于其他区域。同时，在各季中，最高气温和夏季最低气温的订正预报能力优于其他季节；在地面晴、雨两种特征下，对辽宁地区24 h气温预报进行订正检验表明，该检验结果对辽宁地区最高(低)气温订正有一定补充作用，尤其是冬季降水出现时，最高气温预报补充订正效果最为显著。

关键词: 最高(低)气温, 误差订正, 分季集成, ECMWF模式

Abstract:

Based on the observation data from 65 stations in Liaoning province, the accuracy of the prediction products in different seasons was evaluated using the 2-meter temperature products within 12-36 hours from 2016 to 2018 predicted by the EC (ECMWF) model.The effect of the fixed error correction and optimal sliding period correction methods on improving the accuracy was analyzed.The results show that the accuracy of temperature in Liaoning province predicted by the EC model is as follows:that of the maximum temperature is the best in winter with the accuracy in the urban sites of 81.5%, and that of the minimum temperature is the best in summer with the accuracy in the urban sites of 84.3%.After the adoption of the optimal sliding cycle correction, the accuracy of the maximum and minimum temperature in Liaoning province from 2016 to 2018 is improved 19.7% and 20.5%, respectively, compared with the EC model.The prediction accuracy in the minimum temperature is higher than that in the maximum temperature.In whole spatial distribution, the prediction accuracy of the EC model for the maximum or minimum temperature in the central plain of Liaoning province is higher than that in the east and west parts, especially in the northeast, southwest, and southeast of Liaoning province.The accuracy in the areas affected by Changbai Mountain is significantly lower than that in other regions.At the same time, the correction prediction ability of the maximum and minimum temperature in summer is better than that in other seasons.Under the rainy and sunshine weather conditions, the correction test in temperature forecasted in Liaoning province is carried out.It is concluded that the test results have some supplementary effect on the correction of the maximum and minimum temperature in Liaoning province, especially when precipitation occurs in winter, the supplementary correction effect for the maximum temperature forecast is most significant.

Key words: Maximum or minimum temperature, Error correction, Seasonal integration, ECMWF model

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