2009—2017年廊坊“倒降”温气候特征及气象背景条件分析

Features and Weather Background Conditions of“Reverse”Temperature in Langfang from 2009 to 2017

利用河北省廊坊市9个国家气象观测站资料和中国气象局CMA下发MICAPS资料,采用数学统计的方法,对廊坊市2009—2017年"倒降"温气候特征及其出现时的气象背景条件进行分析.结果显示:廊坊"倒降"温区域在三河、大厂最少,在廊坊中南部区域分布相对均匀,且站次年变化呈缓慢上升趋势;"倒降"温日数冬季最多,春季最少,站次秋季最多,春季最少;"倒降"温日数在1月、12月出现得最多,站次在1月和7月出现得最多.从"倒降"温出现时的气象背景条件看,500 h Pa形势占比排名前3的是脊前西北气流、平直西风环流和槽前西南气流,地面形势占比排名前3的是高压底部、回流、高压前部;日最大风速风向主要分布在偏北风和偏东风,日最大风速、风力集中分布在2~5级;天气现象中降雨和轻雾出现的频率最高.从频率直方分布、核密度估计和正态分布密度的分布特征看,日平均相对湿度呈"单峰型"或"双峰型"分布,850 hPa变温呈"单峰型"分布.

Based on the data from 9 National Meteorological Observation Stations in Langfang City,Hebei Province and the MICAPS data issued by the China Meteorological Administration through CMA,using mathematical statistics,the characteristics of the "reverse" temperature in Langfang City from 2009 to 2017 and the accompanying meteorological background conditions were analyzed.The results show that the "reverse" temperature areas in Langfang are the least in Sanhe and Dachang,and the distribution in central and southern part of Langfang is relatively even.The annual change of stations shows a slow upward trend.The number of "reverse" temperature days is the most in winter and the least in spring,and the number of stations is the most in autumn and the least in spring.The number of "reverse" temperature days occurs the most in January and December,and the number of stations occurs the most in January and July.Tthe top three in the 500 hPa situation are the northwest airflow before the ridge,the straight westerly circulation and the southwest airflow before the trough,and the top three for the ground situation are high-pressure bottom,backflow,and highpressure front.The daily maximum wind speed and wind direction are mainly distributed in northerly wind and easterly wind,and the distribution of daily maximum wind speed and wind power is mainly concentrated in 2 to 5 levels.The frequency of rainfall and light fog is highest.From the distribution characteristics of frequency histogram distribution,kernel density estimation and normal distribution density, the daily average relative humidity is unimodal distribution or bimodal distribution,850 hPa variable temperature is unimodal distribution.