Abstract: Snow cover dynamics in Greenland are a key driver of regional climate and global sea-level projections, 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, ensuring 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 (Modern-Era Retrospective Analysis for Research and Applications, Version 2) and GLDAS-2 (Global Land Data Assimilation 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 overestimate 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 remains 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 Greenland, providing crucial data support and a methodological complement for research on polar ice and snow mass balance, as well as contributing to more accurate future climate projections.