干旱区研究

干旱区研究 >

2025 , Vol. 42 >Issue 11: 2058 - 2070

DOI: https://doi.org/10.13866/j.azr.2025.11.09

水土资源

时相偏差对多年冰川变化研究的影响

  • 王慧 ,
  • 刘若曦 ,
  • 徐维新 ,
  • 郑照军 ,
  • 校瑞香 ,
  • 李蕙君 ,
  • 吴成娜
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  • 1.成都信息工程大学资源与环境学院，四川 成都 610225
    2.成都平原城市气象与环境四川省野外科学观测研究站，四川 成都 610225
    3.国家卫星气象中心，北京 100081
    4.青海省气象科学研究所，青海 西宁 810001
王慧（2002-），女，主要从事积雪遥感监测与变化研究. E-mail: 13980867805@163.com
徐维新. E-mail: weixin.xu@cuit.edu.cn

收稿日期: 2025-05-12

  修回日期: 2025-10-08

  网络出版日期: 2025-12-13

基金资助

三峡金沙江川云水电开发有限公司项目(4323020011);青海省科技计划项目(2023-ZJ-733);大学生创新项目(X202310621385)

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Impact of temporal phase bias on multiyear glacier changes

  • WANG Hui ,
  • LIU Ruoxi ,
  • XU Weixin ,
  • ZHENG Zhaojun ,
  • XIAO Ruixiang ,
  • LI Huijun ,
  • WU Chengna
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  • 1. College of Resources and Environment Science, Chengdu University of Information Technology, Chengdu 610225, Sichuan, China
    2. Chengdu Plain Urban Meteorology and Environment Observation and Research Station of Sichuan Province, Chengdu 610225, Sichuan, China
    3. National Satellite Meteorological Center, Beijing 100081, China
    4. Qinghai Institute of Meteorological Science, Xining 810001, Qinghai, China

Received date: 2025-05-12

  Revised date: 2025-10-08

  Online published: 2025-12-13

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摘要

卫星时相的季节性差异，可直接影响冰川多年变化趋势研究的准确性。利用2000—2023年暖季（6—9月）逐日MODIS影像，通过逐日积雪面积序列与冰川区逐年最小积雪面积建立统一对比标准，评估时相偏差对冰川时序变化的影响程度，分析冰川区积雪面积多年动态变化特征。结果表明：（1） 卫星影像时相偏差导致冰川面积估算偏差最高可达-23.25%，即使时相处于6—9月期间，偏差仍可达到7.75%。（2） 在消除时相偏差的影响后，发现已有的针对各拉丹东与阿尼玛卿地区冰川变化的研究结果，明显低估了近20 a来冰川变化的下降趋势，其中阿尼玛卿冰川面积缩减率达到17.03%，高于原有的认识。（3） 基于2000—2023年最小积雪面积时间序列，近24 a各拉丹东冰川区年缩减率为0.24%·a-1（累计减少5.42%），阿尼玛卿冰川区为0.43%·a-1（累计减少9.82%），各拉丹东冰川区年最小积雪面积下降趋势显著，而阿尼玛卿冰川区下降趋势不明显，这与已有的认识不同。（4） 以两个冰川区为典型代表，青藏高原腹地冰川区积雪面积通常在8月中上旬达到最小值，选取该时期或临近2旬的卫星影像，时相偏差一般小于0.5%，选择6月初或9月底的卫星影像，时相偏差可能带来12%以上的结果偏差，且6月的影像时相偏差一般小于9月。

关键词： 冰川变化; 时相偏差; 卫星遥感; 三江源

本文引用格式

王慧 , 刘若曦 , 徐维新 , 郑照军 , 校瑞香 , 李蕙君 , 吴成娜 . 时相偏差对多年冰川变化研究的影响[J]. 干旱区研究, 2025 , 42(11) : 2058 -2070 . DOI: 10.13866/j.azr.2025.11.09

Abstract

The seasonal difference in satellite time phase directly affects the accuracy of studies of multiyear changes in glaciers. In this study, we used the daily MODIS images for the warm season (June-September) from 2000 to 2023 to establish a unified comparison standard for the daily snow-area sequence and the annual minimum snow area in glacier areas, evaluate the impact of time-phase deviation on determinations of the temporal variations in glaciers, and analyze the multi-year dynamic-variation characteristics of the snow area in the glacier areas. The results show that: (1) The maximum deviation of glacier-area estimations caused by the time-phase deviation of satellite images is -23.25%, and the deviation is still as much as 7.75% even when the period is in the range from June to September. (2) After eliminating the influence of the time-phase deviation, we found that the existing research results for the changes in the Geladandong and Animachen glacier regions have significantly underestimated the downward trend of glacier changes in the past 20 years. In addition, the rate of reduction in the area of the Animachen glacier is 17.03%, which is greater than the original finding. (3) Based on the time series for the minimum area of snow cover from 2000 to 2023, the annual rate of reduction of the Geladandong glacier over the past 24 years is 0.24%·a-1 (a cumulative reduction of 5.42%), and that of the Animachen glacier is 0.43%·a-1 (a cumulative reduction of 9.82%). The annual minimum snow cover area of the Geladandong glacier exhibits a significant downward trend, while that of the Animachen glacier is not obvious, which is different from the current understanding. (4) Taking these two glacier regions as typical examples, we find that the snow-cover area in the glacier regions in the hinterland of the Qinghai-Xizang Plateau usually reaches its minimum during the first ten days of August. The time-phase deviation is generally less than 0.5% when the satellite images in this period or near 20 days are selected. If instead satellite images in early June or late September are selected, the time-phase deviation may may account for more than 12% of the resulting total deviation, and the time-phase deviation of the images in June is generally less than that in September.

Key words： glacier variations; temporal phase bias; satellite remote sensing; Three-River Source region

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