湖北农业科学 ›› 2021, Vol. 60 ›› Issue (8): 81-86.doi: 10.14088/j.cnki.issn0439-8114.2021.08.015

• 资源·环境 • 上一篇    下一篇

局地气候对徐州市站点间低温异常差异影响研究

孙磊, 吕翔, 胡慎慎, 王珂玮   

  1. 徐州市气象局,江苏 徐州 221002
  • 收稿日期:2020-06-15 发布日期:2021-05-07
  • 作者简介:孙 磊(1986-),男,江苏泰州人,工程师,主要从事预报服务研究,(电话)13615108151(电子信箱)kyoslsl@163.com。
  • 基金资助:
    江苏省气象局预报员专项(JSYBY201710)

Research on the impact of local climate on the differences of low temperature anomalies in Xuzhou city

SUN Lei, LYU Xiang, HU Shen-shen, WANG Ke-wei   

  1. Xuzhou Meteorological Bureau,Xuzhou 221002,Jiangsu,China
  • Received:2020-06-15 Published:2021-05-07

摘要: 收集徐州市6个人工站点日最低温度实况以及相应气候背景资料,以徐州站为标准站,统计站点间偏差分布规律,进行样本资料统计并分型,分为两端型、东部型、西部型和全部型。应用正交函数及统计分析等方法,对造成站点间温度大值差异的主要气象因子,主要包括环境风向、风速、湿度、冷空气影响等进行相关性特征分析并提炼修正方法。结果表明,丰县最易出现较明显偏差;当同时出现2站及以上站点偏差时,考虑负偏差,不考虑正偏差;当平均风速≤0.5 m/s时,不考虑风向影响,当平均风速≥0.5 m/s时,徐州市受偏南风影响时不利于降温,沛县受东风到东南风、睢宁县受南风到西南风影响时不利于降温,丰县、邳州市和新沂市风向特征不明显;大值偏差出现频率西部地区在秋、冬季最高,而东部地区则是春季最高,均是夏季出现最少;当无冷平流,受局地风向风速环境条件影响为主时,着重考虑两端型,当存在冷平流影响时,主要关注西部型和东部型。通过主观订正降低站点偏差失分,进一步提升精细化预报水平。

关键词: 低温, 数据分析, 气象因子, 预报准确率

Abstract: The data of daily minimum temperature and corresponding climatic background at 6 artificial stations in Xuzhou city were collected. Taking Xuzhou station as the standard station, the error distribution between stations was analyzed, and the data were classified into two types: Two-terminal type, eastern type, western type and whole type. By using the methods of orthogonal function and statistical analysis, the correlation characteristics of the main meteorological factors which cause the great difference of temperature between stations, including wind direction, wind speed, humidity, cold air, etc., were analyzed and the correction methods were refined. The results showed that Feng county was the most prone to appear obvious errors; When the average wind speed was less than 0.5 m/s, the influence of wind direction was not considered. When the average wind speed was more than 0.5 m/s, Xuzhou city was not conducive to cooling when it was affected by southerly wind. Pei county was not conducive to cooling when it was affected by east to southeast wind and Suining county was affected by south to southwest wind. The characteristics of wind direction in Feng county, Pizhou city and Xinyi city were not obvious; The occurrence frequency of large-value errors was highest in autumn and winter in the west, and highest in spring and least in summer in the east; When there was no cold advection, the influence of local wind direction and wind speed environment was dominant, the two-terminal type should be considered, and when there was cold advection, the western type and eastern typeshould be paid more attention. Through subjective revision, the error of site could be reduced and the level of fine forecasting could be further improved.

Key words: low temperature, data analysis, meteorological factors, forecast accuracy

中图分类号: