Nearly half of Greenland's post-Little Ice Age area loss occurred since 2000

Nearly half of Greenland's post-Little Ice Age area loss occurred since 2000 | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Nearly half of Greenland's post-Little Ice Age area loss occurred since 2000 Mohammad Salmani, Beata Csatho, Jason Briner, Sophie Nowicki, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9125064/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract The Greenland Ice Sheet has retreated since its historical maximum position (generally during the Little Ice Age; LIA, ~1300-1850 CE), but the rate and spatial pattern of recession between the LIA maximum and the satellite era remain poorly constrained. Here, we reconstruct the first continuous Greenland‑wide maximum observable LIA ice extent to quantify margin change across three multi‑decadal periods. We find widespread retreat from the LIA to the 1980s (~ -13,800 km²; -132 km2 yr-1), near‑equilibrium conditions during 1980s-2000s ( ~1,000 km²; +33 km2 yr-1), and renewed retreat during 2000s-2022 ( ~ -11,800 km²; −577 km2 yr-1). Taken together, our analysis yields a cumulative ice loss of ~24,600 km² since the LIA and an approximately four-fold post‑2000 acceleration relative to earlier retreat. These results indicate a clear departure from post‑LIA adjustments captured by our reconstruction and provide a Greenland‑wide historical baseline for constraining and evaluating ice sheet models. Earth and environmental sciences/Climate sciences/Cryospheric science Earth and environmental sciences/Solid Earth sciences/Geomorphology Earth and environmental sciences/Climate sciences/Palaeoclimate Earth and environmental sciences/Climate sciences/Climate change/Climate-change impacts Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Main The Greenland Ice Sheet (GrIS) has experienced significant retreat since the end of the Little Ice Age (LIA, ~1300-1850 CE), providing essential context for understanding contemporary ice loss and projecting future sea level contributions 1 . The mass imbalance observed in the satellite era after the 1990s, combined with widespread retreat of both land and marine ice margins, highlights a critical knowledge gap in understanding of ice sheet evolution from prior to the 1990s, such as during and since the LIA 2–5 . Available studies typically focus on glacier reconstructions across much longer timescales or examine the observational period of the past few decades when the ice sheet is already out of balance. This knowledge gap is particularly significant given the sensitivity of ice sheet projections to model initialization 6,7 , making historical baselines crucial for model validation and improving future projections. The GrIS created geomorphological signatures that mark its former extent. Among these features, trimlines—visible boundaries that separate recently ice-covered terrain from areas above or beyond the former ice margin—appear as distinctive boundaries in the landscape where differences in vegetation, weathering patterns, and surface characteristics create recognizable transitions between formerly glaciated and unglaciated terrain. These boundaries can be identified through remote sensing techniques that detect spectral contrasts and geomorphological features (Fig. 1). When systematically mapped, trimlines provide valuable insights into both the magnitude and pattern of ice retreat since the LIA maximum 8–10 . Despite its importance, a comprehensive, continuous outline of LIA maximum ice extent across Greenland has remained elusive. Regional studies have documented terminus positions for specific regions 11 or established retreat chronologies for individual outlet glaciers 12 , but a continuous circum-Greenland-wide dataset has yet to be produced and made publicly available. Challenges including variable data quality, complex nunatak delineation, and establishing synchronicity of maximum positions have complicated previous efforts 13 . However, additional studies have established that many prominent features, such as surface moraines and trimlines in Arctic environments, were likely formed during the LIA, and serve as a proxy for maximum ice extent 10,14 . Such findings support the use of geomorphological features for paleoenvironmental reconstruction and provide opportunities for comprehensive mapping using advanced remote sensing techniques and the availability of moderate-to-high spatial resolution, multispectral imagery. This study addresses aforementioned gaps by reconstructing the first comprehensive historical maximum ice extent since the LIA for the entire Greenland Ice Sheet by combining trimline mapping, the most advanced tidewater glacier terminus positions recorded in historical documents, and contemporary ice sheet boundary geometry reconstructions. We use “historical” to refer to ~1600 CE to the present and define the historical maximum as the most advanced glacier position reached during that period 15 . We divided the ice sheet into seven distinct operational subregions (Fig. S4), guided by the IMBIE (Ice Sheet Mass Balance Inter-comparison Exercise) basin boundaries and regional data availability, and implemented tailored methodologies to use the most appropriate datasets for each region while maintaining methodological consistency. The resulting dataset provides a crucial baseline for quantifying ice area changes since the LIA and contextualizing current observations within the longer-term GrIS history. We publicly release these new ice masks to facilitate geomorphic analyses and improve ice sheet model constraints. Results The comprehensive LIA maximum ice extent dataset generated here spans the entire GrIS, establishing a temporal baseline of the historical maximum ice extent. By comparing our reconstructed LIA ice margin with ice masks from the 1980s (PROMICE, 1978–1987), 2000s (CCI, 1999–2004), and 2022 (PROMICE, August 2022) (Fig. 2), we quantify basin-integrated ice-sheet area change and associated rates across three comparison periods (LIA–1980s, 1980s–2000s, and 2000s–2022). Accelerating ice sheet retreat From the LIA to the 1980s, Greenland lost −13,828 km² at an average rate of −131.9 [-145.1, -119.5] km 2 yr -1 (90% confidence intervals derived from Monte Carlo sampling of observation year uncertainties; see Methods), with the ice sheet experiencing systematic retreat across each of the seven major basins in Greenland 3 ; basin-level rates range from −34.1 [-42.0, -27.8] km 2 yr -1 in the Northwest (NW) to −5.9 [-7.2, -4.8] km 2 yr -1 in the Central West (CW). During the 1980s–2000 period, the ice sheet experienced relative equilibrium 2 with a modest net gain of +1,009 km² and an average change rate of +33.2 [25.1, 41.2] km 2 yr -1 ; the Northeast (NE) shows the largest net growth at +55.9 [50.9, 61.6] km 2 yr -1 , while most basins remain within a few km 2 yr -1 of balance. After 2000, retreat increased sharply, with Greenland losing −11,761 km² at an average rate of −576.7 [-604.8, -548.8] km 2 yr -1 —approximately 4.4 times the net LIA-1980s rate; the fastest basin-integrated retreat occurs in the Central East (CE) at −120.0 [-134.0, -107.6] km 2 yr -1 , while the CW exhibits more moderate retreat at −23.3 [−26.1, −20.9] km 2 yr -1 . Over the full LIA–2022 interval, Greenland lost −24,579 km² at a rate of −168.9 [-180.4, -157.7] km 2 yr -1 , with the NW showing the highest net retreat (−42.3 [-49.5, -36.4] km 2 yr -1 ) and the CW the most moderate net retreat (−7.3 [-8.5, -6.3] km 2 yr -1 ). Rates of ice-sheet area change reveal distinct temporal patterns across the three comparison periods, with spatiotemporal variations that highlight the diverse response of Greenland's ice margins to climate forcing (Figs. 2 and 3; Supplementary Tables S1 and S2). The systematic retreat across all basins from the LIA to the 1980s reflects a centennial-scale interval (late 19th century to 1978-1987) of net ice margin adjustment following the LIA maximum, with timing uncertainty accounted for in the rate estimates. The 1980s–2000 period shows overall stabilization compared to earlier in the last century, indicating that ice margins had largely reached equilibrium 16 . In contrast, post-2000 retreat is dominated by tidewater glacier dynamics in climatically sensitive regions, with concurrent retreat at land-terminating margins after 2000 across most basins 3,17 (Supplementary Methods SM1; Figs. S1-S3). These period statistics define three distinct, multi-decadal modes of ice-margin behavior (Fig. 2): (1) widespread retreat from the LIA maximum to the 1980s, (2) a period of relative stability with minor fluctuations from the 1980s to 2000, and (3) accelerated, widespread retreat after 2000. Regional variability and patterns Spatially, net LIA-2022 retreat has been most pronounced in the Northwest (NW) region, though the temporal dominance of this loss varies by sector. While the NW experienced its greatest total area loss during the long LIA-1980s interval of net adjustment, reflecting the widespread disintegration of floating ice tongues that characterized the historical margin 15,18 , the North (NO) region exhibits a contrasting pattern where the majority of its total retreat has occurred in the recent 2000-2022 period, highlighting the diverse response times of basin-scale dynamics 19 (Figs. 2 and 3). Ice margin segmentation analysis at 5-km intervals along Greenland's perimeter reveals that retreat is not limited to major outlet glaciers: widespread margin recession is evident along intervening coastal segments as well (Fig. 3). Localized retreat magnitudes reach >20 km at prominent outlets such as Jakobshavn Isbræ, Zachariae Isstrøm, and Upernavik, while intervening inter-fjord coasts commonly experienced <5 km of change 4 . At the regional scale, these transitions mirror the ice-sheet-wide pattern, with the Northwest region consistently exhibiting the most pronounced retreat signal across all periods. (see Supplementary Tables S1-S2 for complete basin-level statistics). Detailed analysis of Northwest retreat Ice margin analysis in Northwest Greenland is presented at higher spatial resolution to test whether the basin-integrated retreat signal is dominated by a small number of major tidewater outlets or expressed more broadly along the margin, and to identify discrete "hot spots" of margin change that are smoothed in basin-average area rates (Fig. 4). This higher-resolution transect also provides glacier-specific retreat statistics (Supplementary Table S5) that can be compared directly with individual outlet-glacier studies and used for targeted model evaluation. Between the LIA and 1985, the region experienced widespread retreat reaching up to 15 km at major marine-terminating outlets. The 1985-2000 period shows near-equilibrium conditions with minimal change across most segments and localized advance at select locations. The 2000-2022 period exhibits renewed systematic retreat, with major outlets including Sermeq (Upernavik) and Rink glaciers showing pronounced landward margin migration. Cumulative LIA-2022 changes reveal distinct "hot spots" of retreat, particularly between 1100 and 2000 km along the coastline transect, corresponding to major marine-terminating outlets in the Upernavik region, while northern coastal segments remain relatively stable. This spatial analysis used 500 m segments grouped into 5 km intervals to capture both large outlet glaciers and intervening coast behavior. Discussion The reconstruction of ice extent around the entire perimeter of Greenland during the LIA presented in this study establishes a continuous observational baseline prior to the satellite era, revealing that the Greenland Ice Sheet has shifted between distinct regimes of retreat, stability, and acceleration over the last century. This new temporal framework facilitates an assessment of whether the current ice loss indicates a continuation of post-LIA adjustments or a significant deviation from established historical patterns. The ice sheet’s adaptation to post-LIA climate conditions is evidenced by the systematic net retreat that was documented from the LIA maximum to the 1980s. The multi-decadal period of net retreat across all seven major basins, despite lower average rates than in the 21st century, resulted in the largest cumulative ice area loss in our record due to its prolonged duration. The spatial coherence of this retreat signal indicates a unified climate forcing mechanism, presumably associated with net warming trajectory (including the pronounced early-20th-century warming followed by mid-century cooling) that followed the LIA climate minimum 20 . While our reconstruction does not resolve whether this net retreat occurred continuously or via episodic retreats punctuated by shorter intervals of stability, the widespread pre-1980s retreat indicates that GrIS margin response to post-LIA/industrial-era climate forcing began prior to the satellite era. Viewed in this longer context, the late-20th-century near-equilibrium interval can be interpreted as a transient pause within a longer retreat history rather than the onset of retreat 21–23 . Targeted analyses using historical photographs and reconstructions of ice-surface elevations at selected sites will help clarify this temporal pattern in future work. Perhaps a distinct feature of our reconstruction is the interval of net stability observed from the 1980s to 2000, a time period during which the majority of basins experienced near-equilibrium conditions and the ice sheet experienced modest net area gain 2,3 . This widespread equilibrium, which mirrors the stability observed in the ice sheet interior 24 , serves as a critical reference period for estimating surface mass balance and firn densification anomalies 16 . This ice-sheet stability may have been due to a combination of oceanic temperature variations in the North Atlantic and persistent atmospheric high-pressure systems over Greenland 25 . The cessation of retreat likely began earlier than the 1980s, though the timing was spatially asynchronous, representing a complex response to multiple climate drivers rather than a single, synchronous reversal 26,27 . The rates of GrIS area loss increased after 2000, with the mean post-2000 rate (~ −577 km 2 yr -1 ) roughly four times the LIA-1980s rate (~−132 km 2 yr -1 ), far exceeding the quasi-equilibrium 1980s-2000 advance (+33 km 2 yr -1 ) 2,3 . This recent increase, especially notable in the Northwest, North, and Southeast basins, indicates that the changes occurring post-2000 surpass the range of variability recorded since the LIA maximum, representing a departure from the retreat patterns observed during the previous time periods 4,23 . Although our research cannot definitively determine whether this acceleration surpasses the complete spectrum of post-LIA variability (e.g., we cannot rule out a brief period within the LIA-1980s period with retreat rates this high), it suggests that current retreat rates signify a deviation from the trends recorded since the maximum of the LIA. To assess whether post‑2000 retreat reflects localized tidewater dynamics or an ice‑sheet‑wide response, we classified margins as marine‑terminating, land‑terminating, and, for context, “marine‑influenced” (land segments within a glacier‑specific influence radius of nearby tidewater fronts; see Supplementary Methods SM1). Across all periods, marine‑terminating segments show the largest mean retreat, consistent with strong ocean forcing at major outlets 17,28 (Supplementary Figs. S1-S3). Importantly, land‑terminating margins—which comprise ~15,000-18,700 km of the perimeter versus ~4,000-5,300 km for marine‑terminating and ~10,700-14,500 km classified as marine‑influenced—shifted from near‑equilibrium or slight advance before 2000 to widespread retreat after 2000 across most basins. Together, these patterns indicate that recent change is not confined to fjords: an ice‑sheet‑wide atmospheric/surface mass‑balance signal is superimposed on pronounced ocean‑driven retreat at tidewater outlets. Our analysis has enabled complete spatial coverage of Greenland’s LIA ice extent. However, several limitations must be acknowledged. The historical LIA ice mask that we make accessible for community use is asynchronous in its timing, resulting in a reconstructed extent that represents a composite of maximum positions rather than a single synchronous snapshot. Additionally, our LIA–1980s comparison integrates change over a century-scale interval and cannot distinguish sustained retreat from discrete rapid retreats separated by stable (or locally advancing) periods within that interval. While multiple lines of evidence support the attribution of this ice-margin largely to the LIA, reliance on indirect evidence for temporal attribution introduces uncertainty in precise timing. Regional variations in source data quality necessitated region-specific methodological adaptations that may introduce subtle systematic biases, while the manual digitization process introduces subjective errors. In the Northwest and North, where the LIA margin extended over marine areas as floating ice shelves, our reconstruction was constrained by the positions of individual islands and limited historical records 18 , introducing substantial but unquantifiable positional uncertainty for these sectors. These limitations present opportunities for future methodological enhancement through integration of absolute dating techniques 26,29 , development of automated mapping approaches 8,30 , and derivation of historical grounding line positions from the reconstructed ice extent using surface elevation models and bed topography, which would provide additional constraints for ice sheet model initialization. Our reconstruction supplies essential boundary conditions for initializing and validating historical ice‑sheet model simulations and strengthens the contextual baseline for future projections 31,32 . As the Greenland Ice Sheet holds 7.4 meters of sea level equivalent 33 and has already committed to substantial future losses 7,34,35 , the post‑2000 state of disequilibrium documented here—with contemporary retreat exceeding the range of post‑LIA variability and proceeding at more than four times the LIA-1980s rate—indicates that current rates of ice-margin change represent a departure from natural variability. This shift has substantial implications for understanding the contributions of ice sheets to accelerating global sea level rise in a period characterized by unprecedented climate change 36 . Methods Creating the first historical maximum outline of the GrIS We divided Greenland into seven subregions—North, East, Southeast_Big, Southeast_Small, Northwest_Big, Northwest_Small, and Southwest (Supplementary Fig. S4)—guided by the IMBIE basin boundaries and regional data availability, to accommodate variability in terrain, spectral contrast, and source data coverage. Region-specific adaptations and data integration are summarized in the supplementary Methods SM3, with brief highlights provided below. Multiple datasets were systematically integrated across all regions to ensure comprehensive coverage, as detailed in Table 1. High-resolution multispectral satellite orthophoto mosaics (10-0.2 m resolution; Table 1) and 1978-1987 black-and-white aerial orthophotos 37 provided the primary visual basis for manual trimline digitization. Ice masks—including the Programme for Monitoring of the Greenland Ice Sheet (PROMICE) ice extent from the 1980s 38 and the European Space Agency (ESA) Climate Change Initiative (CCI) ice mask 39 —were employed selectively based on regional geometric accuracy requirements. The PROMICE 1980s ice mask was the primary basemap for gap-filling during manual digitization. These masks incorporated ice sheet boundaries and both strongly and weakly connected glaciers while excluding disconnected glaciers (hereafter termed the "connectivity rule" 39 ) to maintain consistent ice sheet boundary definitions. Because the connectivity rule was applied independently in each ice mask product, minor inconsistencies in connected/disconnected glacier classification between periods were identified and individually resolved to ensure consistent boundary definitions across all comparison epochs. For Northwestern Greenland, the more accurate manually-digitized PROMICE_NW ice mask 40 along with CCI dataset provided consistent checking and digitization guidance, and PROMICE_NW was used for the 1980s boundary. Historical datasets included a comprehensive moraine dataset (Table 1) for identifying former glacier extents, terminus position data from 1978-1987 41 , the TermPicks Dataset 42 for identifying most extensive terminus positions, and historical terminus positions derived from Bjørk et al. 11 for estimating 1930s calving front positions in Southeast Greenland. Topographic datasets included ArcticDEM 43 as shaded relief for moraine identification and geomorphological feature recognition. In select regions, manual trimline digitization was supplemented by machine learning classification approaches using spectral data, proximity to ice, and elevation data to identify trimzone regions 44 . Table 1. Data Sources for Greenland LIA Trimline Mapping. See Supplementary Table S4 for more details. Data Type Data Source Time Period Resolution/Error Regions Used Ref. Primary Remote Sensing Data Satellite orthophoto mosaic (Sentinel-2, SPOT, Asiaq) 2013-2020 10-0.2m All regions 45 Sentinel-2 Satellite Imagery 2015-2026 10m All regions 46 Greenland black-and-white orthophotographs 1978-1987 2m All regions 37 Arctic DEM Mosaic 2007-2023 2m Mostly East and Southeast 43 Ice Mask Datasets PROMICE ice mask 1980s 25m North, East, Southeast 47 PROMICE_NW Mask 1985 25m Northwestern Greenland 40 CCI ice mask 2000s 30 m All regions 39 GIMP 2015 2015 15-30m Northwest 48 PROMICE 2022 2022 20 m All regions 49 Glacier Terminus Terminus Positions 1978-1987 10 m All regions 41 TermPicks "Most Extensive" Dataset 1900-2020 100 m All regions 42 Bjork et al. Supplementary Data 1930s - Southeast Greenland 11 Maps and Historical Imagery Danish Geodetic Institute topographic maps 1948-1953 1:250,000 scale Northwest Greenland 50 US Army Map Service maps 1947 1:250,000 scale North Greenland 51 Landsat Geocover 2000 2000 14.25m Northwest and Southeast 52 Higgins Petermann Glacier map ~1990 Schematic Petermann Glacier 53 Additional Resources Sentinel-2 Composite and Classification 2023 10m Multiple regions 44 Moraine Dataset Not dated - Most regions 50 We reconstructed the historical maximum ice extent by manually digitizing trimlines and maximum glacier termini using the imagery and ancillary datasets described below. Visual cues included vegetation boundaries, weathering contrasts, and subtle moraine ridges; historical topographic maps provided contextual checks. A unified basemap was compiled by mosaicking the PROMICE ice mask with the geometrically superior CCI mask where PROMICE exhibited distortions (primarily in SW and parts of NW and SE Greenland). The resulting polygon served as the reference surface against which all boundary modifications and terminus extensions were applied. Where visual evidence of trimlines was identified, the contemporary ice mask was extended outward to connect with the digitized trimline features. Conversely, where clear trimline evidence was absent, the contemporary ice mask boundaries were retained. Such areas are not influential on the overall results, as they include locations where there is little to no distance between the historical maximum position and the contemporary ice margin, such as on steep inland nunataks, areas with more recent historical maximums and little subsequent retreat, or areas simply with very little change over the study period. For outlet glaciers, we reconstructed maximum historical terminus positions using multiple datasets. The terminus positions from 1978 to 1987 (Table 1) dataset provided reliable historical calving front locations, supplemented with the TermPicks Dataset (Table 1) to identify the most extensive positions. We converted TermPicks polylines into 30 regularly spaced sample points. This density guaranteed the same number of nodes inside both narrow and wide termini. Then, we calculated the distance of each point to the CCI ice sheet boundary and summed the distances. For each glacier, we selected the terminus position with the greatest total distance, representing the maximum historical extent based on available data. In Southeast Greenland, we incorporated data from Bjørk et al. 11 to reconstruct the approximate 1930s calving front positions, extending our timeline farther into the past. Area change rate calculations and uncertainty quantification We estimate ice-sheet area-change rates for multiple periods by differencing polygonal ice-mask areas within IMBIE (Ice Sheet Mass Balance Inter‑comparison Exercise) 54 basins and dividing by the observation time span. Basin areas are geometrically fixed; the primary uncertainty arises from temporal ambiguity in dataset observation years. We propagated this timing uncertainty using Monte Carlo sampling (10,000 trials) in which start and end years were drawn from their documented ranges for each trial. The ice-sheet total rate was computed by summing basin rates within each trial, preserving basin-to-basin timing correlations. Results are reported as mean [5th percentile, 95th percentile], representing central estimates with 90% confidence intervals. Detailed methodology is provided in Supplementary Methods SM4. Regional methodological adaptations A uniform workflow applied across the GrIS is not feasible given Greenland’s complex topography, variable spectral contrast, and uneven data coverage. We therefore applied light, targeted adaptations by our defined subregions (summarized in Supplementary Methods SM3 and Fig. S4; Fig. 5). In the Southwest, Southeast_Small, and Northwest_Small, vegetation‑aided spectral contrast enabled direct manual trimline digitization using orthophotos, with CCI used for gap‑filling and TermPicks or 1978-1987 termini to extend margins to maximum observable extents. In the Southeast, persistent snow and complex topography limited trimline expression; we merged PROMICE with moraines, incorporated 1930s termini 11 , and verified against most‑extensive TermPicks. In the East, extensive nunataks required equal attention to interior and exterior boundaries via PROMICE and moraine integration with selective manual adjustments. In the Northwest, we compared PROMICE, CCI, and GIMP masks and adopted the manually digitized PROMICE_NW mask for superior geometry. In the North, glacier‑specific sources were required for floating‑tongue outlets (e.g., ERS‑1 SAR for Petermann; 1978 aerials for Steensby and Ryder; 2000 Landsat for C.H. Ostenfeld; additional cases in Supplementary Table S3). Procedural details and dataset choices are provided in SM3. In order to encircle the entire GrIS and map all ice margins, we mapped the most extensive observable trimline or terminus location across all available datasets, rather than focusing strictly on the oldest 22,55 . We acknowledge that these maximum positions are not synchronous across the GrIS, as glacier dynamics respond to both regional climate forcing and local topographic controls: in southern West Greenland they commonly predate 1850, whereas in parts of the north (e.g., Nugssuaq and Uummannaq) they can be as late as ~1920 15 . Thus, our approach leads to a comprehensive “maximum extent mask” that serves as a valuable reference for historical ice coverage that largely dates to the LIA. Temporal attribution and validation Multiple lines of evidence support our LIA temporal attribution. Cosmogenic nuclide dating (10Be, 36Cl) of moraines across Greenland reveals glacier advances during ~1200 CE, ~1450 CE, ~1720 CE, and ~1850s CE, spanning the LIA period 26,56–58 . Radiocarbon dating from proglacial lake sediments and reworked marine materials confirms maximum ice extents during the LIA 13,59 . The combination of available chronologies and historical observations provides robust confidence that our mapped features predominantly represent LIA maximum extents. Known exceptions, with historical maximum positions occurring within the 20th century, exist in land-based regions in southwest Greenland (e.g., immediately south of Isunnguata Sermia) 26 . Our dataset addresses nunataks through two versions: one including nunataks (representing historical ice-free terrain) and another without (showing a continuous ice surface). The version with nunataks provides the most accurate spatial representation of historical ice-free terrain, while the version without creates a continuous ice surface better suited for glaciological modelling and ice volume calculations 22 . Nunataks were incorporated by deriving initial boundaries from multiple ice masks, manual digitization of detectable trimlines, refinement using the moraine dataset, and manual adjustment of the ice masks nunataks to reflect their smaller LIA extents. Declarations Data availability The LIA maximum ice extent dataset generated in this study, including versions with and without nunataks is publicly available at https://doi.org/10.5281/zenodo.19007901. All other data sources used in this study are listed in Table 1 and Supplementary Table S4 with their respective DOIs. Code availability The code used for area change rate calculations, Monte Carlo uncertainty quantification, and ice margin retreat analysis is available at https://github.com/msalmani2/Greenland-LIA-Ice-Margin-Analysis. Acknowledgements We acknowledge support from NSF Award 2106971 to JB, SN; NSF Award 2004826 to JB, SN and BC; Heising Simons Foundation award 2025-5728 to SN and BC; NASA Awards 0NSSC21K0322 and 80NSSC21K0915 for BC and SN. ArcticDEM data and geospatial support were provided by the Polar Geospatial Center under NSF-OPP awards 1043681, 1542736, 1559691, 1810976, 2129685, and 2434541. The Programme for Monitoring of the Greenland Ice Sheet (PROMICE) and the Geological Survey of Denmark and Greenland (GEUS) are acknowledged for providing the PROMICE datasets. Furthermore, this study contains modified Copernicus Sentinel data [2015-2026] processed by the European Space Agency (ESA), which refers to the Sentinel-2 Satellite Imagery used in our primary remote sensing data. We also acknowledge the use of data from the MEaSUREs Greenland Ice Mapping Project (GIMP), provided through the NASA National Snow and Ice Data Center Distributed Active Archive Center. We thank the Ice Sheet Mass Balance Inter-comparison Exercise (IMBIE) for providing the drainage basin boundaries. Author Contributions B.C., S.N., J.P.B., and M.S. conceived and designed the study. H.E., J.P.B., B.C., I.P., and M.S. performed the manual trimline digitization. M.S., B.C., and I.P. integrated the trimline dataset with ice mask products. M.S. developed the analysis framework, including the coastline classification algorithm, area change rate calculations, Monte Carlo uncertainty quantification, and automated trimline classification. M.S. performed all data analysis and created all figures. M.S. wrote the manuscript with significant input from J.P.B., B.C., and H.G. S.N., A.C.L., and G.T. contributed expertise on ice sheet model applications and product usability. 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The influence of North Atlantic atmospheric and oceanic forcing effects on 1900–2010 Greenland summer climate and ice melt/runoff. Intl Journal of Climatology 33 , 862–880 (2013). Kelley, S. E., Briner, J. P., Young, N. E., Babonis, G. S. & Csatho, B. Maximum late Holocene extent of the western Greenland Ice Sheet during the late 20th century. Quaternary Science Reviews 56 , 89–98 (2012). Hill, E. A., Carr, J. R., Stokes, C. R. & Gudmundsson, G. H. Dynamic changes in outlet glaciers in northern Greenland from 1948 to 2015. The Cryosphere 12 , 3243–3263 (2018). Straneo, F. & Heimbach, P. North Atlantic warming and the retreat of Greenland’s outlet glaciers. Nature 504 , 36–43 (2013). Briner, J. P. et al. Holocene climate change in Arctic Canada and Greenland. Quaternary Science Reviews 147 , 340–364 (2016). Paul, F. et al. On the accuracy of glacier outlines derived from remote-sensing data. Ann. Glaciol. 54 , 171–182 (2013). Chang, W., Applegate, P. J., Haran, M. & Keller, K. Probabilistic calibration of a Greenland Ice Sheet model using spatially resolved synthetic observations: toward projections of ice mass loss with uncertainties. Geosci. Model Dev. 7 , 1933–1943 (2014). Gowan, E. J., Niu, L., Knorr, G. & Lohmann, G. Geology datasets in North America, Greenland and surrounding areas for use with ice sheet models. Earth Syst. Sci. Data 11 , 375–391 (2019). Morlighem, M. et al. BedMachine v3: Complete Bed Topography and Ocean Bathymetry Mapping of Greenland From Multibeam Echo Sounding Combined With Mass Conservation. Geophysical Research Letters 44 , (2017). Aschwanden, A. et al. Contribution of the Greenland Ice Sheet to sea level over the next millennium. Sci. Adv. 5 , (2019). Stokes, C. R., Bamber, J. L., Dutton, A. & DeConto, R. M. Warming of +1.5 °C is too high for polar ice sheets. Commun Earth Environ 6 , 351 (2025). Intergovernmental Panel On Climate Change (IPCC). Climate Change 2021 – The Physical Science Basis: Working Group I Contribution to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change . (Cambridge University Press, 2023). doi:10.1017/9781009157896. Korsgaard, N. J. et al. Digital elevation model and orthophotographs of Greenland based on aerial photographs from 1978–1987. Scientific Data 3 , 160032 (2016). Citterio, M. & Ahlstrøm, A. P. Brief communication“The aerophotogrammetric map of Greenland ice masses”. The Cryosphere 7 , 445–449 (2013). Rastner, P. et al. The first complete inventory of the local glaciers and ice caps on Greenland. The Cryosphere 6 , 1483–1495 (2012). Kjeldsen, K. K. North-west Greenland ice mask. GEUS Dataverse https://doi.org/10.22008/FK2/RTSYDD (2022). Korsgaard, N. Greenland Ice Sheet outlet glacier terminus positions 1978-1987 from aero-photogrammetric map data. GEUS Dataverse https://doi.org/10.22008/FK2/B2JYVC (2022). Goliber, S. & Black, T. TermPicks: A century of Greenland glacier terminus data for use in machine learning applications. Zenodo https://doi.org/10.5281/ZENODO.6557981 (2021). Porter, C. et al. ArcticDEM - Mosaics, Version 4.1. Harvard Dataverse https://doi.org/10.7910/DVN/3VDC4W (2023). Salmani, M. et al. A Machine-Learning Framework for Mapping Little Ice Age Maximum Glacial Extents. Preprint at https://doi.org/10.22541/essoar.177177422.24617832/v1 (2026). Klimadatastyrelsen. Satellite photo Greenland. Dataforsyningen (2020). European Space Agency. Sentinel-2 MSI Level-2A BOA Reflectance. https://doi.org/10.5270/S2_-znk9xsj (2022). Citterio, M. & Ahlstrøm, A. P. Ice extent. GEUS Dataverse https://doi.org/10.22008/FK2/PRWITW (2022). Howat, I. MEaSUREs Greenland Ice Mapping Project (GIMP) Land Ice and Ocean Classification Mask, Version 1. NASA National Snow and Ice Data Center Distributed Active Archive Center https://doi.org/10.5067/B8X58MQBFUPA (2017). Luetzenburg, G. et al. PROMICE-2022 Ice Mask. GEUS Dataverse https://doi.org/10.22008/FK2/O8CLRE (2025). Klimadatastyrelsen. Grønlands topografiske kortværk. Dataforsyningen (2001). U.S. Army Map Service. AMS C501 Greenland 1:250,000 Topographic Series. Polar Geospatial Center (1947). Tucker, C. J., Grant, D. M. & Dykstra, J. D. NASA’s Global Orthorectified Landsat Data Set. photogramm eng remote sensing 70 , 313–322 (2004). Higgins, A. K. North Greenland Glacier Velocities and Calf Ice Production. Polarforschung, Bremerhaven, Alfred Wegener Institute for Polar and Marine Research & German Society of Polar Research 60 , 1–23 (1991). Mouginot, J. & Rignot, E. Glacier catchments/basins for the Greenland Ice Sheet. 4156976 bytes Dryad https://doi.org/10.7280/D1WT11 (2019). Carrivick, J. L. et al. Accelerated Volume Loss in Glacier Ablation Zones of NE Greenland, Little Ice Age to Present. Geophysical Research Letters 46 , 1476–1484 (2019). Jomelli, V. et al. Paradoxical cold conditions during the medieval climate anomaly in the Western Arctic. Sci Rep 6 , 32984 (2016). Young, N. E., Schweinsberg, A. D., Briner, J. P. & Schaefer, J. M. Glacier maxima in Baffin Bay during the Medieval Warm Period coeval with Norse settlement. Sci. Adv. 1 , e1500806 (2015). Schweinsberg, A. D. et al. Multiple independent records of local glacier variability on Nuussuaq, West Greenland, during the Holocene. Quaternary Science Reviews 215 , 253–271 (2019). Briner, J. P., Stewart, H. A. M., Young, N. E., Philipps, W. & Losee, S. Using proglacial-threshold lakes to constrain fluctuations of the Jakobshavn Isbræ ice margin, western Greenland, during the Holocene. Quaternary Science Reviews 29 , 3861–3874 (2010). Additional Declarations There is NO Competing Interest. Supplementary Files LIASupplements.docx Supplementary Information TableS5GreenlandGlaciersIceMarginChange.pdf Supplementary Table 5 (Table S5) Cite Share Download PDF Status: Under Review Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9125064","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":606742977,"identity":"4e292f62-26b6-4bea-9d30-c2bbbd8addfa","order_by":0,"name":"Mohammad Salmani","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4UlEQVRIie3OoQoCQRCA4bGcZeDqCKJPIKwcnAbBZ7GYVlAEMRgOBJNoPfAprphPB84iWBe8IAgmwyWjuFqVW22G/cOGYT9mAGy2/6wQ6wddAsjG0HxOhNG8SCmEQrgH+p6AUN+S2pJPWzVJy95xXg/iCVWgOF1THvFVV7BMLuine00S8gCTkYGAJg6jr2TjnDnUCUj6+eSwy1jeGb1Q6i13TapXA4ml4N6MUZAmm9lzCxqIkn3uLRgpTQbBZkGeg91h03BYdJY3bruraRTEt1bFLXKk8sh7zm/fbTabzfapB4wJUR+7fErtAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0009-0006-5284-5875","institution":"University at Buffalo","correspondingAuthor":true,"prefix":"","firstName":"Mohammad","middleName":"","lastName":"Salmani","suffix":""},{"id":606742978,"identity":"8f78efb9-5424-4a83-a81a-942bb9133fd5","order_by":1,"name":"Beata Csatho","email":"","orcid":"","institution":"University at Buffalo","correspondingAuthor":false,"prefix":"","firstName":"Beata","middleName":"","lastName":"Csatho","suffix":""},{"id":606742979,"identity":"a6d32e58-f8c6-41a2-8bca-2d8926e954fd","order_by":2,"name":"Jason Briner","email":"","orcid":"https://orcid.org/0000-0002-8584-0978","institution":"University at Buffalo","correspondingAuthor":false,"prefix":"","firstName":"Jason","middleName":"","lastName":"Briner","suffix":""},{"id":606742980,"identity":"7c140386-41c2-4b2c-9e98-91d9d598f502","order_by":3,"name":"Sophie Nowicki","email":"","orcid":"","institution":"University at Buffalo","correspondingAuthor":false,"prefix":"","firstName":"Sophie","middleName":"","lastName":"Nowicki","suffix":""},{"id":606742981,"identity":"fac88a17-bbe2-4ae3-8ca0-b273f3d33576","order_by":4,"name":"Ivan Parmuzin","email":"","orcid":"","institution":"University at Buffalo","correspondingAuthor":false,"prefix":"","firstName":"Ivan","middleName":"","lastName":"Parmuzin","suffix":""},{"id":606742982,"identity":"4d31decc-4142-44ba-a2d6-461aa28dc3ca","order_by":5,"name":"Heidi Eberhardt","email":"","orcid":"","institution":"University at Buffalo","correspondingAuthor":false,"prefix":"","firstName":"Heidi","middleName":"","lastName":"Eberhardt","suffix":""},{"id":606742983,"identity":"1bbb5a38-6a6e-45b3-b419-b50b4025534b","order_by":6,"name":"Hui Gao","email":"","orcid":"","institution":"University at Buffalo","correspondingAuthor":false,"prefix":"","firstName":"Hui","middleName":"","lastName":"Gao","suffix":""},{"id":606742984,"identity":"6845b6af-3010-46c9-93bc-e4f21d2b2e27","order_by":7,"name":"Ana Carolina Luzardi","email":"","orcid":"","institution":"University at Buffalo","correspondingAuthor":false,"prefix":"","firstName":"Ana","middleName":"Carolina","lastName":"Luzardi","suffix":""},{"id":606742985,"identity":"870df2b7-dcc4-4549-860b-8673fc4d1257","order_by":8,"name":"Golsa Talebigheshlaghi","email":"","orcid":"","institution":"University at Buffalo","correspondingAuthor":false,"prefix":"","firstName":"Golsa","middleName":"","lastName":"Talebigheshlaghi","suffix":""}],"badges":[],"createdAt":"2026-03-14 21:35:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9125064/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9125064/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105053601,"identity":"881ac157-794c-45d4-9432-703bc402c433","added_by":"auto","created_at":"2026-03-20 10:57:50","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1549659,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eTrimlines of LIA maximum extent (yellow), 1980s ice extent (purple), and 2000s ice extent (orange) at representative locations in Greenland. A, Kangiata Nunaata Sermia (KNS) region with large outlet glaciers and nunataks. B, the complex nunatak terrain in the Helheim region. The visible-band composite from the satellite orthophoto mosaic (10-0.2 m resolution, 2013-2020) highlights spectral and geomorphological cues used for trimline identification. Inset map shows map locations within Greenland.\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-9125064/v1/111d590512d4231780751fc2.png"},{"id":105053600,"identity":"77c1cf7d-16e7-4ef5-95ac-c43557d9e352","added_by":"auto","created_at":"2026-03-20 10:57:50","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1098257,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eIntegrated analysis of Greenland ice margin change and regional area change rates across four temporal periods: (a) LIA to 1980s, (b) 1980s to 2000s, (c) 2000s to 2022, and (d) LIA to 2022. Circle markers around Greenland’s coastline indicate ice margin change magnitude for 5-km coastline segments, with circle radius and their colors proportional to absolute ice margin change (≤5, 10, 15, and \u0026gt;20 km). Basin names are abbreviated (NO = North, NE = Northeast, CE = Central East, SE = Southeast, SW = Southwest, CW = Central West, NW = Northwest). Basin colors correspond to area change rates (km\u003c/strong\u003e\u003c/em\u003e\u003csup\u003e\u003cem\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e\u003cstrong\u003e yr\u003c/strong\u003e\u003c/em\u003e\u003csup\u003e\u003cem\u003e\u003cstrong\u003e-1\u003c/strong\u003e\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e\u003cstrong\u003e). Each basin lists quantitative area change rates (mean values shown on map; full uncertainty intervals in Supplementary Table S1). Period definitions: LIA 1850-1900; 1980s 1978-1987; 2000s 1999-2004; 2022 fixed. Total Area Change and Total Area Change Rate (mean [5th percentile, 95th percentile]) are listed at bottom. Individual glacier retreat statistics are provided in Supplementary Table S5.\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-9125064/v1/3816d70c95a00fb7a8b5ea90.png"},{"id":105751795,"identity":"2a1b7f36-2955-4342-8bbc-70fa41e313ce","added_by":"auto","created_at":"2026-03-30 15:43:59","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1187899,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eIce margin changes across Greenland’s perimeter for four time periods. Bars show signed change for 5-km coastline segments along Greenland's perimeter, with units in km on the y-axis. Negative values indicate landward retreat (ice margin recession); positive values indicate seaward advance (ice margin expansion). The perimeter is traced clockwise from the northernmost point, so the North (NO) region appears at both edges. Regional divisions are indicated by curly brackets and labels, with major glacier names shown for geographic context.\u003c/strong\u003e\u003c/em\u003e \u003cem\u003e\u003cstrong\u003eIndividual period changes may not sum exactly to the cumulative (LIA–2022) change because intermediate ice masks have independent positional uncertainties.\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-9125064/v1/db6245e60dbc186ab5a7a9ee.png"},{"id":105053604,"identity":"369eb013-92d4-47fb-ad20-446e96e0be5d","added_by":"auto","created_at":"2026-03-20 10:57:50","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":977312,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eIce margin position change in Northwest Greenland. Each panel displays ice margin change (km) versus distance along the reference coastline (km) for sequential periods. Negative values indicate landward retreat from the reference position. Major outlet glacier names are labeled at the top of the figure. The geographic context map (right) displays three ice mask extents: PROMICE_2022 (green), PROMICE NW 1985 (orange), and LIA historical margin (blue) with labeled outlet glaciers.\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-9125064/v1/7fd5e8c695a7e3d7364533b2.png"},{"id":105053606,"identity":"91c537ee-f9a3-40f1-a6cc-2b10afce04af","added_by":"auto","created_at":"2026-03-20 10:57:50","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":857517,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eComprehensive trimline mapping processing workflow showing data availability assessment decision tree, region-specific methodological adaptations across seven subregions, and final dataset production. The workflow shows how spectral/geomorphological evidence availability determines the processing path, leading to direct manual digitization or region-based approaches based on local conditions.\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e","description":"","filename":"image8.png","url":"https://assets-eu.researchsquare.com/files/rs-9125064/v1/6570fe536e08565bb3e33e38.png"},{"id":107705053,"identity":"169de903-c515-4963-8bc6-ae2317b7606f","added_by":"auto","created_at":"2026-04-24 09:07:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":6069138,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9125064/v1/c0dfda4c-f24b-41b3-b51f-2f365af431df.pdf"},{"id":105053605,"identity":"5fef5869-4963-4601-be6b-6725a4e08f89","added_by":"auto","created_at":"2026-03-20 10:57:50","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":6804066,"visible":true,"origin":"","legend":"Supplementary Information","description":"","filename":"LIASupplements.docx","url":"https://assets-eu.researchsquare.com/files/rs-9125064/v1/866f902cf6dcb051d57df9fb.docx"},{"id":105053602,"identity":"9991b654-7799-4cf0-bd0e-277a852699d9","added_by":"auto","created_at":"2026-03-20 10:57:50","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":86188,"visible":true,"origin":"","legend":"Supplementary Table 5 (Table S5)","description":"","filename":"TableS5GreenlandGlaciersIceMarginChange.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9125064/v1/b1e9a7f7bc1f78151081e52b.pdf"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Nearly half of Greenland's post-Little Ice Age area loss occurred since 2000","fulltext":[{"header":"Main","content":"\u003cp\u003eThe Greenland Ice Sheet (GrIS) has experienced significant retreat since the end of the Little Ice Age (LIA, ~1300-1850 CE), providing essential context for understanding contemporary ice loss and projecting future sea level contributions\u003csup\u003e1\u003c/sup\u003e. The mass imbalance observed in the satellite era after the 1990s, combined with widespread retreat of both land and marine ice margins, highlights a critical knowledge gap in understanding of ice sheet evolution from prior to the 1990s, such as during and since the LIA\u003csup\u003e2\u0026ndash;5\u003c/sup\u003e. Available studies typically focus on glacier reconstructions across much longer timescales or examine the observational period of the past few decades when the ice sheet is already out of balance. This knowledge gap is particularly significant given the sensitivity of ice sheet projections to model initialization\u003csup\u003e6,7\u003c/sup\u003e, making historical baselines crucial for model validation and improving future projections.\u003c/p\u003e\n\u003cp\u003eThe GrIS created geomorphological signatures that mark its former extent. Among these features, trimlines\u0026mdash;visible boundaries that separate recently ice-covered terrain from areas above or beyond the former ice margin\u0026mdash;appear as distinctive boundaries in the landscape where differences in vegetation, weathering patterns, and surface characteristics create recognizable transitions between formerly glaciated and unglaciated terrain. These boundaries can be identified through remote sensing techniques that detect spectral contrasts and geomorphological features (Fig. 1). When systematically mapped, trimlines provide valuable insights into both the magnitude and pattern of ice retreat since the LIA maximum\u003csup\u003e8\u0026ndash;10\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eDespite its importance, a comprehensive, continuous outline of LIA maximum ice extent across Greenland has remained elusive. Regional studies have documented terminus positions for specific regions\u003csup\u003e11\u003c/sup\u003e or established retreat chronologies for individual outlet glaciers\u003csup\u003e12\u003c/sup\u003e, but a continuous circum-Greenland-wide dataset has yet to be produced and made publicly available. Challenges including variable data quality, complex nunatak delineation, and establishing synchronicity of maximum positions have complicated previous efforts\u003csup\u003e13\u003c/sup\u003e. However, additional studies have established that many prominent features, such as surface moraines and trimlines in Arctic environments, were likely formed during the LIA, and serve as a proxy for maximum ice extent\u003csup\u003e10,14\u003c/sup\u003e. Such findings support the use of geomorphological features for paleoenvironmental reconstruction and provide opportunities for comprehensive mapping using advanced remote sensing techniques and the availability of moderate-to-high spatial resolution, multispectral imagery.\u003c/p\u003e\n\u003cp\u003eThis study addresses aforementioned gaps by reconstructing the first comprehensive historical maximum ice extent since the LIA for the entire Greenland Ice Sheet by combining trimline mapping, the most advanced tidewater glacier terminus positions recorded in historical documents, and contemporary ice sheet boundary geometry reconstructions. We use \u0026ldquo;historical\u0026rdquo; to refer to ~1600 CE to the present and define the historical maximum as the most advanced glacier position reached during that period\u003csup\u003e15\u003c/sup\u003e. We divided the ice sheet into seven distinct operational subregions (Fig. S4), guided by the IMBIE (Ice Sheet Mass Balance Inter-comparison Exercise) basin boundaries and regional data availability, and implemented tailored methodologies to use the most appropriate datasets for each region while maintaining methodological consistency. The resulting dataset provides a crucial baseline for quantifying ice area changes since the LIA and contextualizing current observations within the longer-term GrIS history. We publicly release these new ice masks to facilitate geomorphic analyses and improve ice sheet model constraints.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThe comprehensive LIA maximum ice extent dataset generated here spans the entire GrIS, establishing a temporal baseline of the historical maximum ice extent. By comparing our reconstructed LIA ice margin with ice masks from the 1980s (PROMICE, 1978\u0026ndash;1987), 2000s (CCI, 1999\u0026ndash;2004), and 2022 (PROMICE, August 2022) (Fig. 2), we quantify basin-integrated ice-sheet area change and associated rates across three comparison periods (LIA\u0026ndash;1980s, 1980s\u0026ndash;2000s, and 2000s\u0026ndash;2022).\u003c/p\u003e\n\u003ch3\u003eAccelerating ice sheet retreat\u003c/h3\u003e\n\u003cp\u003eFrom the LIA to the 1980s, Greenland lost \u0026minus;13,828 km\u0026sup2; at an average rate of \u0026minus;131.9 [-145.1, -119.5] km\u003csup\u003e2\u003c/sup\u003e yr\u003csup\u003e-1\u003c/sup\u003e (90% confidence intervals derived from Monte Carlo sampling of observation year uncertainties; see Methods), with the ice sheet experiencing systematic retreat across each of the seven major basins in Greenland\u003csup\u003e3\u003c/sup\u003e; basin-level rates range from \u0026minus;34.1 [-42.0, -27.8] km\u003csup\u003e2\u003c/sup\u003e yr\u003csup\u003e-1\u003c/sup\u003e in the Northwest (NW) to \u0026minus;5.9 [-7.2, -4.8] km\u003csup\u003e2\u003c/sup\u003e yr\u003csup\u003e-1\u003c/sup\u003e in the Central West (CW). During the 1980s\u0026ndash;2000 period, the ice sheet experienced relative equilibrium\u003csup\u003e2\u003c/sup\u003e with a modest net gain of +1,009 km\u0026sup2; and an average change rate of +33.2 [25.1, 41.2] km\u003csup\u003e2\u003c/sup\u003e yr\u003csup\u003e-1\u003c/sup\u003e; the Northeast (NE) shows the largest net growth at +55.9 [50.9, 61.6] km\u003csup\u003e2\u003c/sup\u003e yr\u003csup\u003e-1\u003c/sup\u003e, while most basins remain within a few km\u003csup\u003e2\u003c/sup\u003e yr\u003csup\u003e-1\u003c/sup\u003e of balance. After 2000, retreat increased sharply, with Greenland losing \u0026minus;11,761 km\u0026sup2; at an average rate of \u0026minus;576.7 [-604.8, -548.8] km\u003csup\u003e2\u003c/sup\u003e yr\u003csup\u003e-1\u003c/sup\u003e\u0026mdash;approximately 4.4 times the net LIA-1980s rate; the fastest basin-integrated retreat occurs in the Central East (CE) at \u0026minus;120.0 [-134.0, -107.6] km\u003csup\u003e2\u003c/sup\u003e yr\u003csup\u003e-1\u003c/sup\u003e, while the CW exhibits more moderate retreat at \u0026minus;23.3 [\u0026minus;26.1, \u0026minus;20.9] km\u003csup\u003e2\u003c/sup\u003e yr\u003csup\u003e-1\u003c/sup\u003e. Over the full LIA\u0026ndash;2022 interval, Greenland lost \u0026minus;24,579 km\u0026sup2; at a rate of \u0026minus;168.9 [-180.4, -157.7] km\u003csup\u003e2\u003c/sup\u003e yr\u003csup\u003e-1\u003c/sup\u003e, with the NW showing the highest net retreat (\u0026minus;42.3 [-49.5, -36.4] km\u003csup\u003e2\u003c/sup\u003e yr\u003csup\u003e-1\u003c/sup\u003e) and the CW the most moderate net retreat (\u0026minus;7.3 [-8.5, -6.3] km\u003csup\u003e2\u003c/sup\u003e yr\u003csup\u003e-1\u003c/sup\u003e).\u003c/p\u003e\n\u003cp\u003eRates of ice-sheet area change reveal distinct temporal patterns across the three comparison periods, with spatiotemporal variations that highlight the diverse response of Greenland\u0026apos;s ice margins to climate forcing (Figs. 2 and 3; Supplementary Tables S1 and S2). The systematic retreat across all basins from the LIA to the 1980s reflects a centennial-scale interval (late 19th century to 1978-1987) of net ice margin adjustment following the LIA maximum, with timing uncertainty accounted for in the rate estimates. The 1980s\u0026ndash;2000 period shows overall stabilization compared to earlier in the last century, indicating that ice margins had largely reached equilibrium\u003csup\u003e16\u003c/sup\u003e. In contrast, post-2000 retreat is dominated by tidewater glacier dynamics in climatically sensitive regions, with concurrent retreat at land-terminating margins after 2000 across most basins\u003csup\u003e3,17\u003c/sup\u003e (Supplementary Methods SM1; Figs. S1-S3).\u003c/p\u003e\n\u003cp\u003eThese period statistics define three distinct, multi-decadal modes of ice-margin behavior (Fig. 2): (1) widespread retreat from the LIA maximum to the 1980s, (2) a period of relative stability with minor fluctuations from the 1980s to 2000, and (3) accelerated, widespread retreat after 2000.\u0026nbsp;\u003c/p\u003e\n\u003ch3\u003eRegional variability and patterns\u003c/h3\u003e\n\u003cp\u003eSpatially, net LIA-2022 retreat has been most pronounced in the Northwest (NW) region, though the temporal dominance of this loss varies by sector. While the NW experienced its greatest total area loss during the long LIA-1980s interval of net adjustment, reflecting the widespread disintegration of floating ice tongues that characterized the historical margin\u003csup\u003e15,18\u003c/sup\u003e, the North (NO) region exhibits a contrasting pattern where the majority of its total retreat has occurred in the recent 2000-2022 period, highlighting the diverse response times of basin-scale dynamics\u003csup\u003e19\u003c/sup\u003e (Figs. 2 and 3).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIce margin segmentation analysis at 5-km intervals along Greenland\u0026apos;s perimeter reveals that retreat is not limited to major outlet glaciers: widespread margin recession is evident along intervening coastal segments as well (Fig. 3). Localized retreat magnitudes reach \u0026gt;20 km at prominent outlets such as Jakobshavn Isbr\u0026aelig;, Zachariae Isstr\u0026oslash;m, and Upernavik, while intervening inter-fjord coasts commonly experienced \u0026lt;5 km of change\u003csup\u003e4\u003c/sup\u003e. At the regional scale, these transitions mirror the ice-sheet-wide pattern, with the Northwest region consistently exhibiting the most pronounced retreat signal across all periods. (see Supplementary Tables S1-S2 for complete basin-level statistics).\u003c/p\u003e\n\u003ch3\u003eDetailed analysis of Northwest retreat\u003c/h3\u003e\n\u003cp\u003eIce margin analysis in Northwest Greenland is presented at higher spatial resolution to test whether the basin-integrated retreat signal is dominated by a small number of major tidewater outlets or expressed more broadly along the margin, and to identify discrete \u0026quot;hot spots\u0026quot; of margin change that are smoothed in basin-average area rates (Fig. 4). This higher-resolution transect also provides glacier-specific retreat statistics (Supplementary Table S5) that can be compared directly with individual outlet-glacier studies and used for targeted model evaluation. Between the LIA and 1985, the region experienced widespread retreat reaching up to 15 km at major marine-terminating outlets. The 1985-2000 period shows near-equilibrium conditions with minimal change across most segments and localized advance at select locations. The 2000-2022 period exhibits renewed systematic retreat, with major outlets including Sermeq (Upernavik) and Rink glaciers showing pronounced landward margin migration. Cumulative LIA-2022 changes reveal distinct \u0026quot;hot spots\u0026quot; of retreat, particularly between 1100 and 2000 km along the coastline transect, corresponding to major marine-terminating outlets in the Upernavik region, while northern coastal segments remain relatively stable. This spatial analysis used 500 m segments grouped into 5 km intervals to capture both large outlet glaciers and intervening coast behavior.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe reconstruction of ice extent around the entire perimeter of Greenland during the LIA presented in this study establishes a continuous observational baseline prior to the satellite era, revealing that the Greenland Ice Sheet has shifted between distinct regimes of retreat, stability, and acceleration over the last century. This new temporal framework facilitates an assessment of whether the current ice loss indicates a continuation of post-LIA adjustments or a significant deviation from established historical patterns.\u003c/p\u003e\n\u003cp\u003eThe ice sheet\u0026rsquo;s adaptation to post-LIA climate conditions is evidenced by the systematic net retreat that was documented from the LIA maximum to the 1980s. The multi-decadal period of net retreat across all seven major basins, despite lower average rates than in the 21st century, resulted in the largest cumulative ice area loss in our record due to its prolonged duration. The spatial coherence of this retreat signal indicates a unified climate forcing mechanism, presumably associated with net warming trajectory (including the pronounced early-20th-century warming followed by mid-century cooling) that followed the LIA climate minimum\u003csup\u003e20\u003c/sup\u003e. While our reconstruction does not resolve whether this net retreat occurred continuously or via episodic retreats punctuated by shorter intervals of stability, the widespread pre-1980s retreat indicates that GrIS margin response to post-LIA/industrial-era climate forcing began prior to the satellite era. Viewed in this longer context, the late-20th-century near-equilibrium interval can be interpreted as a transient pause within a longer retreat history rather than the onset of retreat\u003csup\u003e21\u0026ndash;23\u003c/sup\u003e. Targeted analyses using historical photographs and reconstructions of ice-surface elevations at selected sites will help clarify this temporal pattern in future work.\u003c/p\u003e\n\u003cp\u003ePerhaps a distinct feature of our reconstruction is the interval of net stability observed from the 1980s to 2000, a time period during which the majority of basins experienced near-equilibrium conditions and the ice sheet experienced modest net area gain\u003csup\u003e2,3\u003c/sup\u003e. This widespread equilibrium, which mirrors the stability observed in the ice sheet interior\u003csup\u003e24\u003c/sup\u003e, serves as a critical reference period for estimating surface mass balance and firn densification anomalies\u003csup\u003e16\u003c/sup\u003e. This ice-sheet stability may have been due to a combination of oceanic temperature variations in the North Atlantic and persistent atmospheric high-pressure systems over Greenland\u003csup\u003e25\u003c/sup\u003e. The cessation of retreat likely began earlier than the 1980s, though the timing was spatially asynchronous, representing a complex response to multiple climate drivers rather than a single, synchronous reversal\u003csup\u003e26,27\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eThe rates of GrIS area loss increased after 2000, with the mean post-2000 rate (~ \u0026minus;577 km\u003csup\u003e2\u003c/sup\u003e yr\u003csup\u003e-1\u003c/sup\u003e) roughly four times the LIA-1980s rate (~\u0026minus;132 km\u003csup\u003e2\u003c/sup\u003e yr\u003csup\u003e-1\u003c/sup\u003e), far exceeding the quasi-equilibrium 1980s-2000 advance (+33 km\u003csup\u003e2\u003c/sup\u003e yr\u003csup\u003e-1\u003c/sup\u003e)\u003csup\u003e2,3\u003c/sup\u003e. This recent increase, especially notable in the Northwest, North, and Southeast basins, indicates that the changes occurring post-2000 surpass the range of variability recorded since the LIA maximum, representing a departure from the retreat patterns observed during the previous time periods\u003csup\u003e4,23\u003c/sup\u003e. Although our research cannot definitively determine whether this acceleration surpasses the complete spectrum of post-LIA variability (e.g., we cannot rule out a brief period within the LIA-1980s period with retreat rates this high), it suggests that current retreat rates signify a deviation from the trends recorded since the maximum of the LIA.\u003c/p\u003e\n\u003cp\u003eTo assess whether post‑2000 retreat reflects localized tidewater dynamics or an ice‑sheet‑wide response, we classified margins as marine‑terminating, land‑terminating, and, for context, \u0026ldquo;marine‑influenced\u0026rdquo; (land segments within a glacier‑specific influence radius of nearby tidewater fronts; see Supplementary Methods SM1). Across all periods, marine‑terminating segments show the largest mean retreat, consistent with strong ocean forcing at major outlets\u003csup\u003e17,28\u003c/sup\u003e (Supplementary Figs. S1-S3). Importantly, land‑terminating margins\u0026mdash;which comprise ~15,000-18,700 km of the perimeter versus ~4,000-5,300 km for marine‑terminating and ~10,700-14,500 km classified as marine‑influenced\u0026mdash;shifted from near‑equilibrium or slight advance before 2000 to widespread retreat after 2000 across most basins. Together, these patterns indicate that recent change is not confined to fjords: an ice‑sheet‑wide atmospheric/surface mass‑balance signal is superimposed on pronounced ocean‑driven retreat at tidewater outlets.\u003c/p\u003e\n\u003cp\u003eOur analysis has enabled complete spatial coverage of Greenland\u0026rsquo;s LIA ice extent. However, several limitations must be acknowledged. The historical LIA ice mask that we make accessible for community use is asynchronous in its timing, resulting in a reconstructed extent that represents a composite of maximum positions rather than a single synchronous snapshot. Additionally, our LIA\u0026ndash;1980s comparison integrates change over a century-scale interval and cannot distinguish sustained retreat from discrete rapid retreats separated by stable (or locally advancing) periods within that interval. While multiple lines of evidence support the attribution of this ice-margin largely to the LIA, reliance on indirect evidence for temporal attribution introduces uncertainty in precise timing. Regional variations in source data quality necessitated region-specific methodological adaptations that may introduce subtle systematic biases, while the manual digitization process introduces subjective errors. In the Northwest and North, where the LIA margin extended over marine areas as floating ice shelves, our reconstruction was constrained by the positions of individual islands and limited historical records\u003csup\u003e18\u003c/sup\u003e, introducing substantial but unquantifiable positional uncertainty for these sectors. These limitations present opportunities for future methodological enhancement through integration of absolute dating techniques\u003csup\u003e26,29\u003c/sup\u003e, development of automated mapping approaches\u003csup\u003e8,30\u003c/sup\u003e, and derivation of historical grounding line positions from the reconstructed ice extent using surface elevation models and bed topography, which would provide additional constraints for ice sheet model initialization.\u003c/p\u003e\n\u003cp\u003eOur reconstruction supplies essential boundary conditions for initializing and validating historical ice‑sheet model simulations and strengthens the contextual baseline for future projections\u003csup\u003e31,32\u003c/sup\u003e. As the Greenland Ice Sheet holds 7.4 meters of sea level equivalent\u003csup\u003e33\u003c/sup\u003e and has already committed to substantial future losses\u003csup\u003e7,34,35\u003c/sup\u003e, the post‑2000 state of disequilibrium documented here\u0026mdash;with contemporary retreat exceeding the range of post‑LIA variability and proceeding at more than four times the LIA-1980s rate\u0026mdash;indicates that current rates of ice-margin change represent a departure from natural variability. This shift has substantial implications for understanding the contributions of ice sheets to accelerating global sea level rise in a period characterized by unprecedented climate change\u0026nbsp;\u003csup\u003e36\u003c/sup\u003e.\u003c/p\u003e\n"},{"header":"Methods","content":"\u003ch3\u003eCreating the first historical maximum outline of the GrIS\u003c/h3\u003e\n\u003cp\u003eWe divided Greenland into seven subregions\u0026mdash;North, East, Southeast_Big, Southeast_Small, Northwest_Big, Northwest_Small, and Southwest (Supplementary Fig. S4)\u0026mdash;guided by the IMBIE basin boundaries and regional data availability, to accommodate variability in terrain, spectral contrast, and source data coverage. Region-specific adaptations and data integration are summarized in the supplementary Methods SM3, with brief highlights provided below.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMultiple datasets were systematically integrated across all regions to ensure comprehensive coverage, as detailed in Table 1. High-resolution multispectral satellite orthophoto mosaics (10-0.2 m resolution; Table 1) and 1978-1987 black-and-white aerial orthophotos\u003csup\u003e37\u003c/sup\u003e provided the primary visual basis for manual trimline digitization. Ice masks\u0026mdash;including the Programme for Monitoring of the Greenland Ice Sheet (PROMICE) ice extent from the 1980s\u003csup\u003e38\u003c/sup\u003e and the European Space Agency (ESA) Climate Change Initiative (CCI) ice mask\u003csup\u003e39\u003c/sup\u003e\u0026mdash;were employed selectively based on regional geometric accuracy requirements. The PROMICE 1980s ice mask was the primary basemap for gap-filling during manual digitization. These masks incorporated ice sheet boundaries and both strongly and weakly connected glaciers while excluding disconnected glaciers (hereafter termed the \u0026quot;connectivity rule\u0026quot;\u003csup\u003e39\u003c/sup\u003e) to maintain consistent ice sheet boundary definitions. Because the connectivity rule was applied independently in each ice mask product, minor inconsistencies in connected/disconnected glacier classification between periods were identified and individually resolved to ensure consistent boundary definitions across all comparison epochs. For Northwestern Greenland, the more accurate manually-digitized PROMICE_NW ice mask\u003csup\u003e40\u003c/sup\u003e along with CCI dataset provided consistent checking and digitization guidance, and PROMICE_NW was used for the 1980s boundary.\u003c/p\u003e\n\u003cp\u003eHistorical datasets included a comprehensive moraine dataset (Table 1) for identifying former glacier extents, terminus position data from 1978-1987\u003csup\u003e41\u003c/sup\u003e, the TermPicks Dataset\u003csup\u003e42\u003c/sup\u003e for identifying most extensive terminus positions, and historical terminus positions derived from Bj\u0026oslash;rk et al.\u003csup\u003e11\u003c/sup\u003e for estimating 1930s calving front positions in Southeast Greenland. Topographic datasets included ArcticDEM\u003csup\u003e43\u003c/sup\u003e as shaded relief for moraine identification and geomorphological feature recognition. In select regions, manual trimline digitization was supplemented by machine learning classification approaches using spectral data, proximity to ice, and elevation data to identify trimzone regions\u003csup\u003e44\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eTable 1. Data Sources for Greenland LIA Trimline Mapping. See Supplementary Table S4 for more details.\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"624\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003eData Type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003eData Source\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003eTime Period\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003eResolution/Error\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eRegions Used\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" style=\"width: 78px;\"\u003e\n \u003cp\u003ePrimary Remote Sensing Data\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003eSatellite orthophoto mosaic (Sentinel-2, SPOT, Asiaq)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e2013-2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e10-0.2m\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eAll regions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003csup\u003e45\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003eSentinel-2 Satellite Imagery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e2015-2026\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e10m\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eAll regions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003csup\u003e46\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003eGreenland black-and-white orthophotographs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e1978-1987\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e2m\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eAll regions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003csup\u003e37\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003eArctic DEM Mosaic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e2007-2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e2m\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eMostly East and Southeast\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003csup\u003e43\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\" style=\"width: 78px;\"\u003e\n \u003cp\u003eIce Mask Datasets\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003ePROMICE ice mask\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e1980s\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e25m\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eNorth, East, Southeast\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003csup\u003e47\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003ePROMICE_NW Mask\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e1985\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e25m\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eNorthwestern Greenland\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003csup\u003e40\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003eCCI ice mask\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e2000s\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e30 m\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eAll regions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003csup\u003e39\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003eGIMP 2015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e2015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e15-30m\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eNorthwest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003csup\u003e48\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003ePROMICE 2022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e2022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e20 m\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eAll regions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003csup\u003e49\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 78px;\"\u003e\n \u003cp\u003eGlacier Terminus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003eTerminus Positions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e1978-1987\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e10 m\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eAll regions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003csup\u003e41\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003eTermPicks \u0026quot;Most Extensive\u0026quot; Dataset\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e1900-2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e100 m\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eAll regions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003csup\u003e42\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003eBjork et al. Supplementary Data\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e1930s\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eSoutheast Greenland\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003csup\u003e11\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" style=\"width: 78px;\"\u003e\n \u003cp\u003eMaps and Historical Imagery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003eDanish Geodetic Institute topographic maps\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e1948-1953\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e1:250,000 scale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eNorthwest Greenland\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003csup\u003e50\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003eUS Army Map Service maps\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e1947\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e1:250,000 scale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eNorth Greenland\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003csup\u003e51\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003eLandsat Geocover 2000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e2000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e14.25m\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eNorthwest and Southeast\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003csup\u003e52\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003eHiggins Petermann Glacier map\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e~1990\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003eSchematic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003ePetermann Glacier\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003csup\u003e53\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 78px;\"\u003e\n \u003cp\u003eAdditional Resources\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003eSentinel-2 Composite and Classification\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e10m\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eMultiple regions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003csup\u003e44\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003eMoraine Dataset\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003eNot dated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eMost regions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003csup\u003e50\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;We reconstructed the historical maximum ice extent by manually digitizing trimlines and maximum glacier termini using the imagery and ancillary datasets described below. Visual cues included vegetation boundaries, weathering contrasts, and subtle moraine ridges; historical topographic maps provided contextual checks.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA unified basemap was compiled by mosaicking the PROMICE ice mask with the geometrically superior CCI mask where PROMICE exhibited distortions (primarily in SW and parts of NW and SE Greenland). The resulting polygon served as the reference surface against which all boundary modifications and terminus extensions were applied. Where visual evidence of trimlines was identified, the contemporary ice mask was extended outward to connect with the digitized trimline features. Conversely, where clear trimline evidence was absent, the contemporary ice mask boundaries were retained. Such areas are not influential on the overall results, as they include locations where there is little to no distance between the historical maximum position and the contemporary ice margin, such as on steep inland nunataks, areas with more recent historical maximums and little subsequent retreat, or areas simply with very little change over the study period.\u003c/p\u003e\n\u003cp\u003eFor outlet glaciers, we reconstructed maximum historical terminus positions using multiple datasets. The terminus positions from 1978 to 1987 (Table 1) dataset provided reliable historical calving front locations, supplemented with the TermPicks Dataset (Table 1) to identify the most extensive positions. We converted TermPicks polylines into 30 regularly spaced sample points. This density guaranteed the same number of nodes inside both narrow and wide termini. Then, we calculated the distance of each point to the CCI ice sheet boundary and summed the distances. For each glacier, we selected the terminus position with the greatest total distance, representing the maximum historical extent based on available data. In Southeast Greenland, we incorporated data from Bj\u0026oslash;rk et al.\u003csup\u003e11\u003c/sup\u003e to reconstruct the approximate 1930s calving front positions, extending our timeline farther into the past.\u003c/p\u003e\n\u003ch3\u003eArea change rate calculations and uncertainty quantification\u003c/h3\u003e\n\u003cp\u003eWe estimate ice-sheet area-change rates for multiple periods by differencing polygonal ice-mask areas within IMBIE (Ice Sheet Mass Balance Inter‑comparison Exercise)\u003csup\u003e54\u003c/sup\u003e basins and dividing by the observation time span. Basin areas are geometrically fixed; the primary uncertainty arises from temporal ambiguity in dataset observation years. We propagated this timing uncertainty using Monte Carlo sampling (10,000 trials) in which start and end years were drawn from their documented ranges for each trial. The ice-sheet total rate was computed by summing basin rates within each trial, preserving basin-to-basin timing correlations. Results are reported as mean [5th percentile, 95th percentile], representing central estimates with 90% confidence intervals. Detailed methodology is provided in Supplementary Methods SM4.\u003c/p\u003e\n\u003ch3\u003eRegional methodological adaptations\u003c/h3\u003e\n\u003cp\u003eA uniform workflow applied across the GrIS is not feasible given Greenland\u0026rsquo;s complex topography, variable spectral contrast, and uneven data coverage. We therefore applied light, targeted adaptations by our defined subregions (summarized in Supplementary Methods SM3 and Fig. S4; Fig. 5). In the Southwest, Southeast_Small, and Northwest_Small, vegetation‑aided spectral contrast enabled direct manual trimline digitization using orthophotos, with CCI used for gap‑filling and TermPicks or 1978-1987 termini to extend margins to maximum observable extents. In the Southeast, persistent snow and complex topography limited trimline expression; we merged PROMICE with moraines, incorporated 1930s termini\u003csup\u003e11\u003c/sup\u003e, and verified against most‑extensive TermPicks. In the East, extensive nunataks required equal attention to interior and exterior boundaries via PROMICE and moraine integration with selective manual adjustments. In the Northwest, we compared PROMICE, CCI, and GIMP masks and adopted the manually digitized PROMICE_NW mask for superior geometry. In the North, glacier‑specific sources were required for floating‑tongue outlets (e.g., ERS‑1 SAR for Petermann; 1978 aerials for Steensby and Ryder; 2000 Landsat for C.H. Ostenfeld; additional cases in Supplementary Table S3). Procedural details and dataset choices are provided in SM3.\u003c/p\u003e\n\u003cp\u003eIn order to encircle the entire GrIS and map all ice margins, we mapped the most extensive observable trimline or terminus location across all available datasets, rather than focusing strictly on the oldest\u003csup\u003e22,55\u003c/sup\u003e. We acknowledge that these maximum positions are not synchronous across the GrIS, as glacier dynamics respond to both regional climate forcing and local topographic controls: in southern West Greenland they commonly predate 1850, whereas in parts of the north (e.g., Nugssuaq and Uummannaq) they can be as late as ~1920\u003csup\u003e15\u003c/sup\u003e. Thus, our approach leads to a comprehensive \u0026ldquo;maximum extent mask\u0026rdquo; that serves as a valuable reference for historical ice coverage that largely dates to the LIA.\u003c/p\u003e\n\u003ch3\u003eTemporal attribution and validation\u003c/h3\u003e\n\u003cp\u003eMultiple lines of evidence support our LIA temporal attribution. Cosmogenic nuclide dating (10Be, 36Cl) of moraines across Greenland reveals glacier advances during ~1200 CE, ~1450 CE, ~1720 CE, and ~1850s CE, spanning the LIA period\u003csup\u003e26,56\u0026ndash;58\u003c/sup\u003e. Radiocarbon dating from proglacial lake sediments and reworked marine materials confirms maximum ice extents during the LIA\u003csup\u003e13,59\u003c/sup\u003e. The combination of available chronologies and historical observations provides robust confidence that our mapped features predominantly represent LIA maximum extents. Known exceptions, with historical maximum positions occurring within the 20th century, exist in land-based regions in southwest Greenland (e.g., immediately south of Isunnguata Sermia)\u003csup\u003e26\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eOur dataset addresses nunataks through two versions: one including nunataks (representing historical ice-free terrain) and another without (showing a continuous ice surface). The version with nunataks provides the most accurate spatial representation of historical ice-free terrain, while the version without creates a continuous ice surface better suited for glaciological modelling and ice volume calculations\u003csup\u003e22\u003c/sup\u003e. Nunataks were incorporated by deriving initial boundaries from multiple ice masks, manual digitization of detectable trimlines, refinement using the moraine dataset, and manual adjustment of the ice masks nunataks to reflect their smaller LIA extents.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eData availability\u003c/p\u003e\n\u003cp\u003eThe LIA maximum ice extent dataset generated in this study, including versions with and without nunataks is publicly available at https://doi.org/10.5281/zenodo.19007901. All other data sources used in this study are listed in Table 1 and Supplementary Table S4 with their respective DOIs.\u003c/p\u003e\n\u003cp\u003eCode availability\u003c/p\u003e\n\u003cp\u003eThe code used for area change rate calculations, Monte Carlo uncertainty quantification, and ice margin retreat analysis is available at https://github.com/msalmani2/Greenland-LIA-Ice-Margin-Analysis.\u003c/p\u003e\u003cp\u003eAcknowledgements\u003c/p\u003e\n\u003cp\u003eWe acknowledge support from NSF Award 2106971 to JB, SN; NSF Award 2004826 to JB, SN and BC; Heising Simons Foundation award 2025-5728 to SN and BC; NASA Awards 0NSSC21K0322 and 80NSSC21K0915 for BC and SN. ArcticDEM data and geospatial support were provided by the Polar Geospatial Center under NSF-OPP awards 1043681, 1542736, 1559691, 1810976, 2129685, and 2434541. The Programme for Monitoring of the Greenland Ice Sheet (PROMICE) and the Geological Survey of Denmark and Greenland (GEUS) are acknowledged for providing the PROMICE datasets. Furthermore, this study contains modified Copernicus Sentinel data [2015-2026] processed by the European Space Agency (ESA), which refers to the Sentinel-2 Satellite Imagery used in our primary remote sensing data. We also acknowledge the use of data from the MEaSUREs Greenland Ice Mapping Project (GIMP), provided through the NASA National Snow and Ice Data Center Distributed Active Archive Center. We thank the Ice Sheet Mass Balance Inter-comparison Exercise (IMBIE) for providing the drainage basin boundaries.\u003c/p\u003e\n\u003cp\u003eAuthor Contributions\u003c/p\u003e\n\u003cp\u003eB.C., S.N., J.P.B., and M.S. conceived and designed the study. H.E., J.P.B., B.C., I.P., and M.S. performed the manual trimline digitization. M.S., B.C., and I.P. integrated the trimline dataset with ice mask products. M.S. developed the analysis framework, including the coastline classification algorithm, area change rate calculations, Monte Carlo uncertainty quantification, and automated trimline classification. M.S. performed all data analysis and created all figures. M.S. wrote the manuscript with significant input from J.P.B., B.C., and H.G. S.N., A.C.L., and G.T. contributed expertise on ice sheet model applications and product usability. All authors discussed the results and analysis and commented on the manuscript.\u003c/p\u003e\n\u003cp\u003eCompeting Interests\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003eAdditional Information\u003c/p\u003e\n\u003cp\u003eSupplementary Information is available for this paper.\u003c/p\u003e\n\u003cp\u003eCorrespondence and requests for materials should be addressed to Mohammad Salmani.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWoodroffe, S. 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Using proglacial-threshold lakes to constrain fluctuations of the Jakobshavn Isbr\u0026aelig; ice margin, western Greenland, during the Holocene. \u003cem\u003eQuaternary Science Reviews\u003c/em\u003e \u003cstrong\u003e29\u003c/strong\u003e, 3861\u0026ndash;3874 (2010).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-9125064/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9125064/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe Greenland Ice Sheet has retreated since its historical maximum position (generally during the Little Ice Age; LIA, ~1300-1850 CE), but the rate and spatial pattern of recession between the LIA maximum and the satellite era remain poorly constrained. Here, we reconstruct the first continuous Greenland‑wide maximum observable LIA ice extent to quantify margin change across three multi‑decadal periods. We find widespread retreat from the LIA to the 1980s (~ -13,800 km²; -132 km2 yr-1), near‑equilibrium conditions during 1980s-2000s ( ~1,000 km²; +33 km2 yr-1), and renewed retreat during 2000s-2022 ( ~ -11,800 km²; −577 km2 yr-1). Taken together, our analysis yields a cumulative ice loss of ~24,600 km² since the LIA and an approximately four-fold post‑2000 acceleration relative to earlier retreat. These results indicate a clear departure from post‑LIA adjustments captured by our reconstruction and provide a Greenland‑wide historical baseline for constraining and evaluating ice sheet models.\u003c/p\u003e","manuscriptTitle":"Nearly half of Greenland's post-Little Ice Age area loss occurred since 2000","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-20 10:57:34","doi":"10.21203/rs.3.rs-9125064/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"communications-earth-and-environment","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"commsenv","sideBox":"Learn more about [Communications Earth and Environment](https://www.nature.com/commsenv/)","snPcode":"","submissionUrl":"","title":"Communications Earth \u0026 Environment","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Communications Series","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"42244ecf-bd96-4285-818f-c404ec953c31","owner":[],"postedDate":"March 20th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":64562098,"name":"Earth and environmental sciences/Climate sciences/Cryospheric science"},{"id":64562099,"name":"Earth and environmental sciences/Solid Earth sciences/Geomorphology"},{"id":64562100,"name":"Earth and environmental sciences/Climate sciences/Palaeoclimate"},{"id":64562101,"name":"Earth and environmental sciences/Climate sciences/Climate change/Climate-change impacts"}],"tags":[],"updatedAt":"2026-05-03T06:11:01+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-20 10:57:34","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9125064","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9125064","identity":"rs-9125064","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}