Journal of Arid Meteorology ›› 2022, Vol. 40 ›› Issue (4): 624-636.DOI: 10.11755/j.issn.1006-7639(2022)-04-0624

• Articles • Previous Articles     Next Articles

Research on temporal and spatial distribution of cloud macro and micro characteristic parameters in Qinghai Province based on FY-2G data

ZHANG Pengliang1(), ZHU Shizhen1, GONG Jing1(), ZHAO Bingyu2, WANG Bin3, ZHANG Boyue1, HOU Yonghui1   

  1. 1. Meteorological Disaster Prevention Technology Center of Qinghai Province, Xining 810001,China
    2. Meteorological Information Center of Qinghai Provincee, Xining 810001,China
    3. Meteorological Service Center of Qinghai Province, Xining 810001,China
  • Received:2021-08-09 Revised:2021-09-23 Online:2022-08-31 Published:2022-09-21
  • Contact: GONG Jing


张鹏亮1(), 朱世珍1, 龚静1(), 赵冰钰2, 王彬3, 张博越1, 侯永慧1   

  1. 1. 青海省气象灾害防御技术中心,青海 西宁 810001
    2. 青海省气象信息中心,青海 西宁 810001
    3. 青海省气象服务中心,青海 西宁 810001
  • 通讯作者: 龚静
  • 作者简介:张鹏亮(1985—),男,上海人,工程师,主要从事软件开发、人影决策指挥工作及相关研究
  • 基金资助:


Based on cloud macro and micro characteristic parameters (hereinafter referred to as cloud parameters) retrieved by the FY-2G geostationary satellite data, the temporal and spatial distribution of cloud characteristic parameters in Qinghai Province and 3 sub-regions from 2018 to 2020 were analyzed.The result show that the annual average cloud top height (CTH), cloud top temperature (CTT), overcooled layer depth (OLD), cloud optical depth (COD), effective radius (ER) and liquid water path (LWP) in Qinghai Province are 3.8 km, -9.7 ℃, 2.0 km, 7.1, 7.1 μm and 63.7 g∙m-2, respectively. Except for CTT, the monthly variation of cloud parameters in the Qaidam Basin and Northeastern Qinghai Province with the same latitude showed roughly two peaks and two valleys and its peaks basically appeared in May and November, and the valleys basically appeared in August, September, December and January. Each cloud parameter was roughly unimodal in Three River Source Region, with a peak in November. The spatial distribution of annual average of each cloud parameter was roughly distributed along the topography and mountain range. Except for CTT, high-value areas corresponded to high mountains, low-value areas corresponded to desert basins and low-altitude areas, there was a low-value area in four seasons in the Qaidam Basin, and its range was largest in summer. There were obvious high-value areas in the Three River Source Region and the Qilian Mountains in Qinghai in spring and winter. The OLD, COD and LWP in Three River Source region were larger in spring and autumn, OLD and LWP in the northeastern Qinghai region were largest in spring. Spring and autumn were good time for artificial rainfall enhancement for the purpose of water conservation, drought resistance and disaster reduction.

Key words: Qinghai Province, cloud parameters, temporal and spatial distribution


利用FY-2G静止卫星数据反演的云宏微观特征参量(简称“云参量”),对2018—2020年青海全省及3个子研究区云参量时空分布特征进行分析。结果表明:云顶高度(cloud top height, CTH)、云顶温度(cloud top temperature, CTT)、过冷层厚度(overcooled layer depth, OLD)、云光学厚度(cloud optical depth, COD)、云粒子有效半径(effective radius, ER)及液水路径(liquid water path, LWP) 6个云参量全省区域年平均值分别为3.8 km、-9.7 ℃、2.0 km、7.1、7.1 μm及63.7 g∙m-2。纬度相同的柴达木盆地、青海东北部除CTT外,其余云参量月变化大致呈双峰双谷分布,峰值基本出现在5、11月,谷值基本出现在8、9月及12、1月,三江源各云参量大致呈单峰分布,峰值基本在11月。各云参量年平均值空间分布均呈沿地形和山脉走向分布的特征,除CTT外,其余云参量高值区与高大山脉相对应、低值区与沙漠盆地及低海拔地区相对应,柴达木盆地在四季均存在一低值区,夏季低值区范围最大,三江源地区及青海祁连山区在春、冬季存在明显高值区。三江源地区OLD、COD及LWP在春季及秋季较大,青海东北部地区OLD、LWP在春季最大,而春、秋季则是进行以水源涵养、抗旱减灾等为目的的人工增雨作业的较佳时机。

关键词: 青海省, 云参量, 时空分布

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