Subjects: Geosciences >> Atmospheric Sciences submitted time 2023-05-17 Cooperative journals: 《干旱区地理》
Abstract： Based on the weather phenomenon data from six national weather stations in northern Bayingol Prefecture of Xinjiang, China, the climatic characteristics of rain, snow, sleet, and rain to snow from October to April in the last 58 years (1961—2018) are analyzed. The results show that the major precipitation types in northern Bayingol Prefecture are rain in October and April, snow in December and January, and sleet and rain to snow mainly occur in November and March. The discrimination criterion and index of precipitation types are quantified using 10 physical variables closely related to the precipitation types transition discovered using sounding data from the Korla station from October 2003 to April 2018. The results show that: (1) Surface minimum temperature, nearsurface air temperature, temperature at 850 hPa, geopotential thickness between 500 hPa and 850 hPa, geopotential thickness between 700 hPa and 850 hPa, and 0 ℃ level height can completely distinguish the four precipitation types, and the temperature difference between 500 hPa and 850 hPa, temperature difference between 700 hPa and 850 hPa can distinguish rain, snow, and sleet better. (2) A phase state scoring method for precipitation forecasts was developed, and after a thorough analysis, the combined index accuracy was 92.06% and 94.36% for Korla-Yuli-Luntai Plain and Yanqi Basin, respectively, and the forecast score was 93.58%. (3) The characteristic layer temperature and temperature difference forecast rain and snow with more accuracy than sleet, the geopotential height and thickness forecast snow with greater accuracy than rain and sleet, and the geopotential thickness forecast rain to snow with greater accuracy than the characteristic layer temperature. These comprehensive precipitation type indices have a high reference value for distinguishing precipitation types in northern Bayingol Prefecture and can provide a scientific foundation for improving rain-snow phase transition forecasting accuracy.
Subjects: Geosciences >> Atmospheric Sciences submitted time 2022-04-13 Cooperative journals: 《干旱区地理》
Abstract：利用19612019年降雪期乌鲁木齐市5个国家气象站日降水资料、NCEP逐日4次0.25 0.25和11再分析资料，统计分析乌鲁木齐市暴雪特征及大尺度环流形势，归纳出现暴雪的3种典型环流类型，并分别选取典型个例进行诊断和对比分析。结果表明：（1）乌鲁木齐市暴雪发生频率以0.3次(10a)-1 趋势上升，具有准20 a振荡周期，发生次数最多为3月（40%），11月次之（32%）。 （2）乌鲁木齐市暴雪分为槽前西南气流型、高空槽东移型和强锋区型，强锋区型比例最高但降雪量 小，槽前西南气流型持续时间长且降雪量最大，高空槽东移型最少但影响面积更大且雪强更强。 （3）乌鲁木齐市暴雪的主要影响系统为300 hPa极锋急流、500 hPa偏西或西南气流、700 hPa低空偏北急流和850 hPa西北气流。（4）形成乌鲁木齐市暴雪的机制为低层偏北气流遇山堆积迫使暖湿空气抬升形成冷垫，并与500 hPa以上西南气流形成强垂直风切变和深厚的锋生区，但因三类过程强锋生维持时间和锋面斜率与伸展高度的不同使产生暴雪的原因有明显差异。（5）暴雪的水汽输送主要为西南、偏西和西北路径，槽前西南气流型和高空槽东移型在西南气流引导下直接输送至暴雪区上空，强锋区型则由水汽的接力输送形成水汽汇合。本研究对乌鲁木齐市暴雪天气系统结构特征进行了分类和归纳，为预报服务提供有效参考依据。
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