Supplementary data for: "Historical glacier change on Svalbard predicts doubling of mass loss by 2100"

Supplementary datasets for: Geyman, E.C., van Pelt, W.J.J., Maloof, A.C., Faste Aas, H., and Kohler, J., 2022. "Historical glacier change on Svalbard predicts doubling of mass loss by 2100." Nature. Abstract: The melting of glaciers and ice caps accounts for about one-third of current sea-level rise, exceeding the mass loss from the more voluminous Greenland or Antarctic Ice Sheets. The Arctic archipelago of Svalbard, which hosts spatial climate gradients that are larger than the expected temporal climate shifts over the next century, is a natural laboratory to constrain the climate sensitivity of glaciers and predict their response to future warming. Here we link historical and modern glacier observations to predict that twenty-first century glacier thinning rates will more than double those from 1936 to 2010. Making use of an archive of historical aerial imagery from 1936 and 1938, we use structure-from-motion photogrammetry to reconstruct the three-dimensional geometry of 1,594 glaciers across Svalbard. We compare these reconstructions to modern ice elevation data to derive the spatial pattern of mass balance over a more than 70-year timespan, enabling us to see through the noise of annual and decadal variability to quantify how variables such as temperature and precipitation control ice loss. We find a robust temperature dependence of melt rates, whereby a 1°C rise in mean summer temperature corresponds to a decrease in area-normalized mass balance of -0.28 m yr-1 of water equivalent. Finally, we design a space-for-time substitution8 to combine our historical glacier observations with climate projections and make first-order predictions of twenty-first century glacier change across Svalbard. Dataset description: This dataset contains the digital elevation models (DEMs), elevation change maps, point clouds, orthophotos, and vector outlines of glacier extents based on the Norwegian Polar Institute's collection of 5,507 high-oblique aerial images captured over Svalbard in 1936/1938. The photographs were analyzed through structure-from-motion (SfM) photogrammetry to generate 3D models. We also provide an .xlsx spreadsheet containing glacier-by-glacier statistics of ice loss and climate fields. Note that all of the raster and point cloud files listed below have been georeferenced in Metashape using the ground control points (GCPs) illustrated in Main Text, Fig. 2e, but have not undergone the co-registration and bias-correction following the methods of Nuth & Kaab (2011), which was done on a glacier-by-glacier basis. However, the glacier change budgets in the .xlsx file [#5 below] do reflect the values from the glacier-by-glacier co-registered and bias-corrected DEMs. See below for descriptions of each dataset (each number below corresponds to a different zipped folder). ------------------------------------------------------------------------------------- Svalbard-wide datasets [all georeferenced Svalbard-wide datasets are in the coordinate system UTM 33N]: 1. Svalbard-wide 1936 DEM (20 m and 50 m resolution) [georeferenced .tif file] 2. Svalbard-wide 1936 orthophotomosaic (20 m resolution) [georeferenced .tif file] 3. Svalbard-wide dh (1936-2010) (20 m and 50 m resolution) [georeferenced .tif file] 4. Shapefile of 1936 glacier extents [ESRI .shp file] 5. Glacier-by-glacier statistics [.xlsx file] ------------------------------------------------------------------------------------- Regional-datasets: Due to file size limitations, the high-resolution (5 m) datasets are split into the 8 regions illustrated in Main Text, Fig. 2d: Zone 1 - South Spitsbergen Zone 2 - Barentsoya-Edgeoya Zone 3 - Austfonna Zone 4 - Vestfonna Zone 5 - Northeast Spitsbergen Zone 6 - Central Spitsbergen Zone 7 - Northwest Spitsbergen Zone 8 - North Spitsbergen 6. Regional 1936 DEMs (5 m resolution) [georeferenced .tif files] 7. Regional dh (1936-2010) (5 m resolution) [georeferenced .tif files] 8. Local 1936 orthomosaics (5 m resolution) [georeferenced .tif files] 9. Unprocessed point clouds [.laz files]. These files represent the raw 3D point clouds (x,y,z) generated in Agisoft Metashape for each of the 17 local models described in Extended Data Figure 3. 10. Thumbnail-sized copies of the 5,507 historical aerial images (1936 and 1938) analyzed in this study, along with a .csv file labeling the approximate location of each photograph.

本附属数据集对应论文：Geyman, E.C.、van Pelt, W.J.J.、Maloof, A.C.、Faste Aas, H. 与 Kohler, J. 于2022年发表于《Nature》的《Historical glacier change on Svalbard predicts doubling of mass loss by 2100》。
摘要：冰川与冰盖消融约占当前海平面上升总量的三分之一，其质量损失规模已超过体量更为庞大的格陵兰冰盖与南极冰盖。北极斯瓦尔巴群岛拥有远超未来一个世纪预期气候时间变化幅度的空间气候梯度，是约束冰川气候敏感性、预测其对未来变暖响应的天然实验室。本研究将历史与现代冰川观测数据相结合，预测21世纪冰川减薄速率将较1936至2010年提升一倍以上。研究依托1936年与1938年的历史航空影像档案，通过运动恢复结构（Structure-from-Motion, SfM）摄影测量法重建了斯瓦尔巴群岛1594条冰川的三维几何形态。将这些重建结果与现代冰面高程数据对比，我们得到了跨越70余年的冰川物质平衡空间分布模式，从而剔除年际与年代际变率的噪声，量化温度、降水等变量对冰体损失的调控作用。研究发现消融速率存在显著的温度依赖性：夏季平均气温每升高1℃，单位面积归一化物质平衡将减少0.28 米·年⁻¹ 水当量。最后，本研究采用空间替代时间法（space-for-time substitution）⁸，将历史冰川观测数据与气候预测模型相结合，首次对斯瓦尔巴群岛全域21世纪的冰川变化做出了一阶近似预测。

数据集说明：本数据集包含基于挪威极地研究所1936/1938年拍摄的5507张斯瓦尔巴群岛高倾斜航空影像集所生成的数字高程模型（Digital Elevation Model, DEM）、高程变化图、点云数据、正射影像以及冰川范围矢量轮廓文件。研究通过运动恢复结构摄影测量法对这些影像进行分析，生成了三维冰川模型。本数据集同时附带一份.xlsx格式表格，包含逐条冰川的冰体损失统计数据与气候场信息。需注意：下文列出的所有栅格与点云文件均已通过Agisoft Metashape，利用正文中图2e所示的地面控制点（Ground Control Points, GCPs）完成地理配准，但未按照Nuth & Kaab（2011）的方法进行逐冰川的配准与偏差校正。然而，.xlsx文件（即下文第5项）中的冰川变化预算值，均基于逐冰川配准并完成偏差校正的DEM计算得到。下文按编号对应各压缩文件夹，各数据集详情如下：
-------------------------------------------------------------------------------------
斯瓦尔巴群岛全域数据集 [所有地理配准的全域数据集均采用UTM 33N坐标系]：
1. 斯瓦尔巴群岛全域1936年数字高程模型（分辨率20 m与50 m）[地理配准.tif文件]
2. 斯瓦尔巴群岛全域1936年正射影像镶嵌图（分辨率20 m）[地理配准.tif文件]
3. 斯瓦尔巴群岛全域1936-2010年高程变化量（dh，分辨率20 m与50 m）[地理配准.tif文件]
4. 1936年冰川范围矢量文件 [ESRI .shp格式文件]
5. 逐条冰川统计数据 [.xlsx格式文件]
-------------------------------------------------------------------------------------
区域数据集：受文件大小限制，高分辨率（5 m）数据集被划分为正文中图2d所示的8个区域：
区域1——斯匹次卑尔根岛南部
区域2——巴伦支岛-埃奇岛
区域3——奥斯特夫纳冰川
区域4——韦斯特夫纳冰川
区域5——斯匹次卑尔根岛东北部
区域6——斯匹次卑尔根岛中部
区域7——斯匹次卑尔根岛西北部
区域8——斯匹次卑尔根岛北部
6. 区域级1936年数字高程模型（分辨率5 m）[地理配准.tif文件]
7. 区域级1936-2010年高程变化量（dh，分辨率5 m）[地理配准.tif文件]
8. 区域级1936年正射影像镶嵌图（分辨率5 m）[地理配准.tif文件]
9. 未处理点云数据 [.laz格式文件]。此类文件为本研究扩展数据图3中所述的17个局部模型在Agisoft Metashape中生成的原始三维（x,y,z）点云。
10. 本研究分析的5507张1936年与1938年历史航空影像的缩略图副本，以及一份标注每张照片大致拍摄位置的.csv格式文件。