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基于GNSS-IR的格陵兰岛雪深时空演变特征研究

何忠杰 张晖 卢静月 陈永昕 马媛 姜中山

地球与行星物理论评(中英文)2026,Vol.57Issue(6):732-742,11.
地球与行星物理论评(中英文)2026,Vol.57Issue(6):732-742,11.DOI:10.19975/j.dqyxx.2026-018

基于GNSS-IR的格陵兰岛雪深时空演变特征研究

Spatiotemporal characteristics of snow depth over Greenland using GNSS-IR

何忠杰 1张晖 1卢静月 1陈永昕 1马媛 1姜中山1

作者信息

  • 1. 中山大学 遥感科学与技术学院,珠海 519082
  • 折叠

摘要

Abstract

Snow cover dynamics in Greenland are a key driver of regional climate and global sea-level projec-tions,yet continuous snow depth data are scarce due to the harsh observational environment,thereby constraining an accurate understanding of cryosphere changes and surface energy balance in polar regions.We use the Global Navigation Satellite System Interferometric Reflectometry(GNSS-IR)technique to retrieve continuous snow depth series across Greenland.The open-source software package(gnssrefl)is employed to process GNSS signal-to-noise ratio(SNR)observations for this purpose.By optimally configuring key parameters(e.g.,elevation and azimuth angles),we retrieve the vertical distance from the antenna phase center to the reflecting surface.This distance is then used to derive the time series of snow depth.Ultimately,out of GNSS stations located in the marginal regions of Greenland,we successfully retrieve snow depth at 4 stations,as well as at 4 stations in the central regions,ensur-ing a diverse spatial representation.The experimental results indicate that:(1)The GNSS-IR technique performs well in different regions of Greenland.It provides absolute snow depth at marginal sites and primarily reflects snow and ice surface height variations at central sites.The GNSS-IR data show high consistency with nearby in-situ snow depth measurements in numerical values.(2)Snow depth variation shows a striking contrast between Greenland's east and west margins,reaching~1.5 m at eastern sites(MSVG,LYNS)versus only~0.2 m at western sites(SCBY,KAGA).The eastern stations are characterized by a pronounced seasonal accumulation-melt regime(near-complete summer ablation)as well as significant inter-annual variability in snow depth.(3)The MERRA-2(Mod-ern-Era Retrospective Analysis for Research and Applications,Version 2)and GLDAS-2(Global Land Data As-similation System,Version 2)reanalysis datasets generally capture the temporal trends of snow depth well at most sites,with correlation coefficients commonly exceeding 0.5.Nevertheless,both models systematically overesti-mate the specific values of snow depth,underscoring the critical need for other observational data to calibrate and constrain regional climate models.(4)Snow depth across Greenland demonstrates substantial spatial variability at both interannual and intra-annual scales.The marginal zones primarily exhibit intense intra-annual fluctuations driven by significant winter accumulation and summer ablation.In contrast,the snowpack in the central plateau re-mains relatively stable,characterized predominantly by interannual variations with negligible seasonal fluctuations.These result validate the effectiveness and reliability of GNSS-IR technology for snow depth monitoring in Green-land,providing crucial data support and a methodological complement for research on polar ice and snow mass bal-ance,as well as contributing to more accurate future climate projections.

关键词

GNSS-IR/格陵兰岛/雪深反演/冰冻圈

Key words

GNSS-IR/Greenland/snow depth retrieval/cryosphere

分类

天文与地球科学

引用本文复制引用

何忠杰,张晖,卢静月,陈永昕,马媛,姜中山..基于GNSS-IR的格陵兰岛雪深时空演变特征研究[J].地球与行星物理论评(中英文),2026,57(6):732-742,11.

基金项目

广东省基础与应用基础研究基金(2024A1515030169) Supported by the Guangdong Basic and Applied Basic Research Foundation(Grant No.2024A1515030169) (2024A1515030169)

地球与行星物理论评(中英文)

2097-1893

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