ECMWF业务预报模式地面气温预报的不一致性特征研究
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国家自然科学基金资助项目(91437218);灾害天气国家重点实验室开放课题(2014LASW-A01)


Study on the inconsistency characteristics of surface air temperature forecasts of the ECMWF operational forecast model
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    摘要:

    为探讨ECMWF业务预报模式 (以下简称ECMWF)的地面气温预报不一致性问题,本文利用2015年12月1日—2016年11月30日业务预报中常用的地面气温预报数据,研究ECMWF地面气温预报产品在不同季节里的不一致性指数分布及变化特征。结果表明:各个季节不一致性指数有不同的特点,冬季不一致性指数最大,大值区主要分布在除华南和青藏高原外的大部分区域;而夏季不一致性指数最小,在青藏高原地区不一致性指数相对较大;春、秋两季不一致性指数大小均处于冬、夏季之间。此外,研究还发现冬季地面气温预报不一致性指数单日变化较大,而夏季较小。夏季不同起报时间的地面气温预报比较稳定。

    Abstract:

    In this paper,the inconsistency index distribution and variation characteristics of the ECMWF surface air temperature forecasts over China were studied based on the surface 2 m air temperature forecast data of the ECMWF operational forecast model,during the period of December 1,2015 to November 30,2016,along with the calculation of the Jumpiness index of the forecast.The results revealed that the annual mean forecast inconsistency index of the surface air temperature forecasts over China decreased from north to south,with two areas of maximum values over Tibetan Plateau and eastern Inner Mongolia,respectively,thus indicating that the forecast jumpiness over these two areas is quite high.Among the four seasons of a year,the forecast inconsistency index of the surface air temperature is the greatest during the boreal winter,and smallest in the boreal summer,while there is little difference between the forecast inconsistency indexes in spring and autumn,the inconsistency indexes thereof lying between those in winter and summer.The inconsistency index of the surface air temperature forecast on a given day during boreal summer is slightly different from the summer average value of the inconsistency index,while that on a day during the boreal winter is significantly different from the winter average value of the inconsistency index.

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夏旻惠,智协飞,2020. ECMWF业务预报模式地面气温预报的不一致性特征研究[J].大气科学学报,43(4):652-662. XIA Minhui, ZHI Xiefei,2020. Study on the inconsistency characteristics of surface air temperature forecasts of the ECMWF operational forecast model[J]. Trans Atmos Sci,43(4):652-662. DOI:10.13878/j. cnki. dqkxxb.20200323001

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  • 收稿日期:2020-03-23
  • 最后修改日期:2020-06-24
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  • 在线发布日期: 2020-08-31
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