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冰川冻土 ›› 2020, Vol. 42 ›› Issue (3): 791-800.doi: 10.7522/j.issn.1000-0240.2019.0077

• 冰冻圈与全球变化 • 上一篇    下一篇

1953 - 2016年华山积雪变化特征及其与气温和降水的关系

李亚丽1(), 雷向杰2(), 李茜2, 余鹏1, 韩婷3   

  1. 1.陕西省气象信息中心,陕西 西安 710015
    2.陕西省气候中心,陕西 西安 710015
    3.宝鸡文理学院,陕西 宝鸡 721016
  • 收稿日期:2018-10-17 修回日期:2019-10-16 出版日期:2020-10-31 发布日期:2020-12-08
  • 通讯作者: 雷向杰 E-mail:yalisongli@126.com;lei_xiang_jie@sina.com
  • 作者简介:李亚丽(1978 - ), 女, 陕西韩城人, 高级工程师, 2008年在兰州大学获硕士学位, 从事气象资料应用分析与气候变化研究. E-mail: yalisongli@126.com
  • 基金资助:
    中国气象局气候变化专项(CCSF201845);陕西省气象局面上科研项目(2016M-4)

The variation characteristics of snow cover in the Mount Hua from 1953 to 2016 and its relationship to air temperature and precipitation

Yali LI1(), Xiangjie LEI2(), Qian LI2, Peng YU1, Ting HAN3   

  1. 1.Meteorological Information Center of Shaanxi Province,Xi’an 710015,China
    2.Climate Center of Shaanxi Province,Xi’ an 710015,China
    3.Baoji University of Arts and Sciences,Baoji 721016,Shaanxi,China
  • Received:2018-10-17 Revised:2019-10-16 Online:2020-10-31 Published:2020-12-08
  • Contact: Xiangjie LEI E-mail:yalisongli@126.com;lei_xiang_jie@sina.com

摘要:

利用华山气象站1953 - 2016年气象观测资料和1989 - 2016年Landsat TM卫星遥感影像数据, 分析华山积雪变化的基本特征及其与气温、 降水和大气环流的关系。结果表明: 1953 - 2016年华山平均积雪日数78.5 d, 积雪主要出现在每年的10月 - 次年5月, 64 a来积雪初日推迟, 终日提前, 初终间日数减少, 年度、 冬半年、 冬季积雪日数分别以8.3 d?(10a)-1、 7.6 d?(10a)-1、 4.7 d?(10a)-1的减少率显著减少。1981 - 2016年华山年度最大积雪深度减少趋势不显著, 年度累积积雪深度以88.2 cm?(10a)-1的减少率显著减少, 一年中积雪日数、 最大积雪深度和累积积雪深度的减少(小)趋势均以3月最为显著。1989 - 2016年华山区域积雪面积、 浅雪和深雪面积减少趋势不明显。1953 - 2016年华山年度、 冬半年、 冬季平均气温升高, 降水量减少。积雪日数与平均气温存在显著的负相关, 与降水量存在显著的正相关, 气温是影响华山积雪日数的最主要因素。年度、 冬半年和冬季积雪日数突变年份与相应时段平均气温突变年份相近。1953 - 2016年华山冬半年、 冬季平均气温和降水量均与大气环流指数相关显著, 华山冬半年和冬季积雪日数与同期西藏高原指数、 印缅槽强度指数、 南极涛动指数和西太平洋副高西伸脊点指数为明显的负相关, 与850 hPa东太平洋信风指数、 亚洲区极涡面积指数为明显正相关。

关键词: 华山, 积雪, 卫星遥感, 积雪指数, 气候变化, 大气环流

Abstract:

The basic variation characteristics of snow cover in the Mount Hua and its relationship to temperature and precipitation were analyzed by using linear tendency estimate, M-K inspection, correlation analysis and path analysis, based on the snow cover observation data in the Mount Hua weather station from 1953 to 2016 and satellite remote sensing data from 1989 to 2016. The results demonstrated that: (1) Average days of snow cover were 78.5 d. Snow cover mainly occurred from October to the following May. The beginning date of snow cover had delayed; the ending date of snow cover had advanced; the days from the beginning to the ending had decreased; the days of snow cover had decreased significantly with the rates of winter half year and winter from 1953 to 2016; the annual, winter half year and winter snow days had significantly reduced by 8.3 d?(10a)-1, 7.6 d?(10a)-1, 4.7 d?(10a)-1, respectively. There was no significant decreasing trend of annual maximum snow depth and annual accumulated snow depth had decreased significantly with the rate of 88.2 cm?(10a)-1 from 1981 to 2016. Monthly decreasing trend of snow cover days, maximum snow depth and accumulated snow depth were the most significant in March during the 36 years. There was no obvious decrease of snow cover area, light snow cover area and deep snow cover area in the Mount Hua from 1989 to 2016. (2) From 1953 to 2016 average temperature had risen, precipitation had decreased, the days of snow cover had a significant negative correlation with average temperature and a significant positive correlation with precipitation in the Mount Hua. Temperature was the key factor impacting snow cover days in year, winter half year and winter. The annual, winter half year and winter days of snow cover all had changed abruptly in the years close to the year that average temperature changed abruptly. (3) Average temperature and precipitation had significantly correlated with atmospheric circulation index in winter half year and in winter from 1953 to 2016. The snow cover days of winter and winter half year had negatively correlated with atmospheric circulation indexes, such as Tibet Plateau Region index, India-Burma Trough intensity index, Antarctic Oscillation and Western Pacific Sub Tropical High Western Ridge Point index, and had positively correlated with East Pacific 850 hPa Trade Wind index and Asia Polar Vortex area index significantly.

Key words: Mount Hua, snow cover, satellite remote sensing, Normalized Difference Snow Index (NDSI), climate change, atmospheric circulation

中图分类号: 

  • P426.63+5