极地研究

极地研究 ›› 2026, Vol. 38 ›› Issue (2): 189-206.DOI: 10.13679/j.jdyj.20250077

• 研究论文 • 上一篇    下一篇

北极地区CMA_GFS模式地面气象要素预报能力及误差特征分析

李哲1,2, 孙敬哲3,  陈军明2, 刘娟娟4, 杨毅1   

  1. 1兰州大学大气科学学院,甘肃省气候资源开发及防灾减灾重点实验室, 甘肃 兰州 730000;
    2中国气象科学研究院灾害天气科学与技术全国重点实验室, 北京 100081;
    3北京应用气象研究所, 北京 100029;
    4中国科学院大气物理研究所,大气科学和地球流体力学数值模拟国家重点实验室, 北京 100029
  • 收稿日期:2025-11-13 修回日期:2026-04-08 出版日期:2026-06-30 发布日期:2026-07-13
  • 通讯作者: 陈军明
  • 基金资助:
    中国气象局创新发展专项项目资助

Verification and evaluation of surface meteorological elements from the CMA_GFS model in the Arctic region

LI Zhe1,2, SUN Jingzhe3, CHEN Junming2, LIU Juanjuan4, YANG Yi1   

  1. 1Key Laboratory of Climate Resource Development and Disaster Prevention for Gansu Province, College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China;
    2State Key Laboratory of Severe Weather Meteorological Science and Technology (LaSW), Chinese Academy of Meteorological Sciences, Beijing 100081, China;
    3Beijing Institute of Applied Meteorology, Beijing 100029, China;
    4State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
  • Received:2025-11-13 Revised:2026-04-08 Online:2026-06-30 Published:2026-07-13

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摘要：

本文利用2023年1月、4月、7月和10月北极地区地面观测资料和GPM降水观测资料, 对CMA_GFS模式在北极地区2 m气温、2 m露点温度、地面气压、10 m风速和降水的预报性能进行了系统评估, 分析了其误差的时空分布特征及在极端增温事件背景下的预报表现, 并与GFS和IFS模式进行了对比分析。结果表明: CMA_GFS模式在北极地区连续气象要素预报中存在系统性误差结构特征, 气温、地面气压和风速表现为整体高估, 而露点温度表现出明显的季节依赖性偏差; 预报误差随预报时效增加逐渐增大, 且冬季误差显著大于夏季; 误差高值区主要集中在复杂下垫面和海陆交界处; 降水预报能够合理地再现降水结构, 在2~5 mm·d–1降水范围内具有较好的预报技巧; 在极端增温事件背景下, 模式对热力要素的预报误差明显增大。对比结果表明, CMA_GFS模式整体预报能力接近GFS模式, 但仍明显低于IFS模式; 降水预报性能优于GFS和IFS。本研究揭示了CMA_GFS模式在北极地区的误差结构特征及其主要影响因素, 为模式在极地地区的改进和业务应用提供了科学依据。


关键词: CMA_GFS, 检验评估, 地面气象要素, 北极地区

Abstract:

This study evaluates the forecast performance of the CMA_GFS model in the Arctic using surface observational data and GPM precipitation observations for January, April, July, and October 2023. The model performance for 2 m air temperature, 2 m dew point temperature, surface pressure, 10 m wind speed, and precipitation was systematically assessed. The spatiotemporal characteristics of forecast errors and the model performance under extreme warming events were analyzed, and comparisons were conducted with the GFS and IFS models. The results indicate that the CMA_GFS model exhibits systematic error structures in the prediction of continuous meteorological variables over the Arctic. Specifically, air temperature, surface pressure, and wind speed are generally overestimated, while the dew point temperature shows pronounced seasonal-dependent biases. Forecast errors increase with forecast lead time, and winter errors are significantly larger than those in summer. High-error regions are mainly concentrated over areas with complex underlying surfaces and near coastal boundaries. The precipitation forecasts can reasonably reproduce the overall precipitation structure and show relatively good predictive skill for precipitation events within the 2~5 mm·d–1 range. Under extreme warming events, the forecast errors of thermodynamic variables increase significantly. The comparison results further show that the overall forecast performance of the CMA_GFS model is comparable to that of the GFS model but remains inferior to that of the IFS model. However, the precipitation forecast skill of CMA_GFS is superior to that of both GFS and IFS. This study reveals the error structure characteristics of the CMA_GFS model in the Arctic and identifies their main influencing factors, providing a scientific basis for further model improvement and operational application in polar regions.


Key words: CMA_GFS, validation assessment, surface meteorological elements, Arctic region