Datasets on multiparameter glacier change dynamics for the Jankar Chhu Watershed, Lahaul Himalaya, India

Characterization of glacier changes in the surface area, terminus, equilibrium line altitude (ELA), elevation, and velocity was worked out for the Jankar Chhu Watershed (JCW) of Lahaul Himalaya using freely available satellite remote sensing data and the limited number of field observations. We studied changes using Corona (1971), Landsat (1993‒2017), Sentinel 2A (2016), the SRTM Digital Elevation Model (DEM; 2000), and the global TanDEM‒X DEM (2014). Our results showed that changes in glacier area (‒14.7 ± 4.3 km²), terminus (‒4.7 ± 0.4 m a¯¹), and ELA (~ 20 m rise) between 1971 and 2016 are smaller than previously reported. Glacier lake area increased by ~0.3 km² during 1971‒2016. An intricate pattern of mass changes across the JCW was observed, with surface lowering on an average of ‒0.7 ± 0.4 m a¯¹ which equates to a geodetic mass balance of ‒0.6 ± 0.4 m w.e. a¯¹ during 2000‒14. The computed glacier surface velocities (1971‒2017)  reveal nearly stagnant debris-covered ablation zone but the dynamically active main trunk. The present study provides valuable insights into the recent multiparameter glacier variations, which are of critical importance to assess the future glacier dynamics on a regional scale in areas like the present one.</p

Spatially heterogeneous glacier elevation change in the Jankar Chhu Watershed, Lahaul Himalaya, India derived using ASTER DEMs

This study investigates elevation change (dh) and geodetic mass budget of glaciers in the Jankar Chhu Watershed (JCW), Lahaul Himalaya, India, based on the difference in ASTER DEMs during 2002–2018. Glacier-wide spatially heterogeneous dh patterns were evaluated in the context of morphological and topographical settings. During 2002–2018, glaciers show a mean annual elevation change rate (dh/dt) of −0.38 ± 0.10 m a−1, resulting in a specific mass budget of −0.32 ± 0.09 m w.e.a−1, close to the previously reported estimates in western Himalaya. Nearly stagnant thick debris-covered tongue (>10% debris cover) characterized by melt hotspots exhibits maximum dh at up-glacier instead of the terminus. Debris-free glaciers (dh near the terminus. Spatially heterogeneous dh under varying debris cover is interpreted as an insulating effect of debris thickness as validated by field measurements. We suggest that elevation change of debris-covered glaciers cannot be generalized and glacier-wide spatially detailed mapping of dh is necessary to better understand the control of different surface morphology under warming climatic conditions in the western Himalayas. We present a spatially heterogeneous elevation change rate of 33 glaciers (150.9 km2) in the Jankar Chhu Watershed (JCW), Chandrabhaga basin, Western Himalaya based on the differences of ASTER digital elevation models (DEMs).We estimate the altitude-dependent elevation change of glaciers under varying debris thickness and surface morphology.Glaciers in the JCW show mean dh/dt of –0.38 ± 0.10 m a−1, resulting in a specific mass budget of –0.32 ± 0.09 m w.e.a−1, close to the previously reported estimates in western Himalaya.Debris-covered ice exhibits higher elevation change than debris-free ones.Thick debris-covered tongues show maximum surface lowering at up glaciers while debris-free tongue exhibits maximum lowering near the terminus.Debris thickness controls the altitude-wise spatial elevation change pattern in the JCW. We present a spatially heterogeneous elevation change rate of 33 glaciers (150.9 km2) in the Jankar Chhu Watershed (JCW), Chandrabhaga basin, Western Himalaya based on the differences of ASTER digital elevation models (DEMs). We estimate the altitude-dependent elevation change of glaciers under varying debris thickness and surface morphology. Glaciers in the JCW show mean dh/dt of –0.38 ± 0.10 m a−1, resulting in a specific mass budget of –0.32 ± 0.09 m w.e.a−1, close to the previously reported estimates in western Himalaya. Debris-covered ice exhibits higher elevation change than debris-free ones. Thick debris-covered tongues show maximum surface lowering at up glaciers while debris-free tongue exhibits maximum lowering near the terminus. Debris thickness controls the altitude-wise spatial elevation change pattern in the JCW.</p

The retreat of mountain glaciers since the Little Ice Age: a spatially explicit global database

Most of the world’s mountain glaciers have been retreating for more than a century in response to climate change. Accurate, spatially explicit information on glacier retreat is pivotal to study the consequences of ice loss on both abiotic and biotic components of the environment. Here, we present a spatially explicit dataset showing positions of glacier fronts since the Little Ice Age (LIA) maxima. The dataset is based on multiple historical archival records including topographical maps; repeated photographs, paintings and aerial or satellite images with supplement of geochronology and our own field data. We provide ESRI shapefiles showing 728 past positions of 93 glacier fronts from all continents, except Antarctica, covering the period between the Little Ice Age maxima and the present. On average, the time series span the past 190 years. From 2 to 46 past positions per glacier are depicted (on average: 7.8). Past positions of the glaciers have been obtained mostly on the basis of the literature, provided in a separate file, complemented with information obtained from topographical maps, historical, aerial or satellite pictures, and with our own field data, dating the position of geomorphological elements in the landscape on the basis of measurements taken in the field, signals and marks reporting the ancient position of the glacier front, and additional approaches for dating older moraines (lichenometry, dendrochronology, radiocarbon chronology).NOTES TO THE DATABASE:Database structure:glacier: glacier nameGLIMS id: glacier id, according to the Global Land Ice Measurements from Space (GLIMS)dating: calculated (or estimated) dating for a given line. source: source followed to draw the lines. Notes to fields of the database:GLIMS id: the database version is glims_db_20200630 (downloaded on February 3rd 2021). Exceptions i) Maladeta: the glacier is not mapped in the GLIMS db, but it appears in the online viewer (https://www.glims.org/maps/glims); ii) Qamanaarsuup Sermia and Popocatepetl: the glacier is not mapped neither in the GLIMS db nor in the online viewer.dating: in the cases a reference is cited in this field, it refers to the source we followed to estimate the age of the moraine ridge / position, sometimes by analogy with surrounding glaciers (cf. main text).source: specifically, we used:1) Articles / theses / maps: one or more figures from a given source were georeferenced, and the lines were redrawn following the original maps;2) Satellite / orthophotogrammetric data: the glacier profile in the specific year was drawn interpreting the satellite / aerial images provided by the sources (i.e., Esri ArcGIS World Imagery, GN orthophotogrammetry, Google Earth, IGN orthophotogrammetry, Regional orthophotogrammetry - Lombardia, Regional orthophotogrammetry - Vallee d Aoste / Valle d Aosta);3) Databases: lines were used as provided by the sources (i.e., GlaRiskAlp, GLIMS, OpenData Trentino);4) unpublished data / field marks: the identification of the moraine / position occurred in the field or using sources not yet published.The complete description of methodologies has been published on this paper:Marta, S., R. S. Azzoni, D. Fugazza, Levan Tielidze, P. Chand, K. Sieron, P. Almond, R. Ambrosini, F. Anthelme, P. A. Gazitúa, R. Bhambri, A. Bonin, M. Caccianiga, S. Cauvy-Fraunié, J. L. C. Lievano, J. Clague, J. A. C. Rapre, O. Dangles, P. Deline, A. Eger, R. C. Encarnación, S. Erokhin, A. Franzetti, L. Gielly, Fabrizio Gili, M. Gobbi, A. Guerrieri, S. Hågvar, N. Khedim, R. Kinyanjui, E. Messager, M. A. Morales-Martínez, G. Peyre, F. Pittino, J. Poulenard, R. Seppi, M. C. Sharma, N. Urseitova, B. P. Weissling, Y. Yang, V. Zaginaev, A. Zimmer, G. A. Diolaiuti, A. Rabatel, and G. F. Ficetola. 2021. The Retreat of Mountain Glaciers since the Little Ice Age: a Spatially Explicit Database. Data 6:10.3390/data6100107. https://www.mdpi.com/2306-5729/6/10/107#When referring to this dataset, please cite the Marta et al. 2021 paper.</div