Strange India All Strange Things About India and world


  • 1.

    Pritchard, H. D. Asia’s shrinking glaciers protect large populations from drought stress. Nature 569, 649–654 (2019).

    ADS 
    CAS 
    PubMed 

    Google Scholar 

  • 2.

    WCRP Global Sea Level Budget Group. Global sea-level budget 1993–present. Earth Syst. Sci. Data 10, 1551–1590 (2018).

    ADS 

    Google Scholar 

  • 3.

    Stoffel, M. & Huggel, C. Effects of climate change on mass movements in mountain environments. Prog. Phys. Geogr. 36, 421–439 (2012).

    Google Scholar 

  • 4.

    IPCC. IPCC Special Report on the Ocean and Cryosphere in a Changing Climate (eds Pörtner, H. O. et al.) (IPCC, 2019).

  • 5.

    Gardner, A. et al. A reconciled estimate of glacier contributions to sea level rise: 2003 to 2009. Science 340, 852–857 (2013).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 6.

    Nerem, R. S. et al. Climate-change-driven accelerated sea-level rise detected in the altimeter era. Proc. Natl Acad. Sci. USA 115, 2022–2025 (2018).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 7.

    IMBIE Team. Mass balance of the Greenland Ice Sheet from 1992 to 2018. Nature 579, 233–239 (2020).

    ADS 

    Google Scholar 

  • 8.

    IMBIE team. Mass balance of the Antarctic Ice Sheet from 1992 to 2017. Nature 558, 219–222 (2018).

    ADS 

    Google Scholar 

  • 9.

    Smith, B. et al. Pervasive ice sheet mass loss reflects competing ocean and atmosphere processes. Science 368, 1239–1242 (2020).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 10.

    Kääb, A., Berthier, E., Nuth, C., Gardelle, J. & Arnaud, Y. Contrasting patterns of early twenty-first-century glacier mass change in the Himalayas. Nature 488, 495–498 (2012).

    ADS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 11.

    Kulp, S. A. & Strauss, B. H. New elevation data triple estimates of global vulnerability to sea-level rise and coastal flooding. Nat. Commun. 10, 4844 (2019); author correction 10, 5752 (2019).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 12.

    Immerzeel, W. W. et al. Importance and vulnerability of the world’s water towers. Nature 577, 364–369 (2020).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 13.

    Marzeion, B., Cogley, J. G., Richter, K. & Parkes, D. Attribution of global glacier mass loss to anthropogenic and natural causes. Science 345, 919–921 (2014).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 14.

    Huss, M. & Hock, R. Global-scale hydrological response to future glacier mass loss. Nat. Clim. Chang. 8, 135–140 (2018).

    ADS 

    Google Scholar 

  • 15.

    IPCC. Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part B: Regional Aspects (Cambridge University Press, 2014).

  • 16.

    Cauvy-Fraunié, S. & Dangles, O. A global synthesis of biodiversity responses to glacier retreat. Nat. Ecol. Evol. 3, 1675–1685 (2019).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 17.

    World Glacier Monitoring Service (WGMS). Fluctuations of Glaciers Database https://wgms.ch/data_databaseversions/ (2019).

  • 18.

    Bamber, J. L., Westaway, R. M., Marzeion, B. & Wouters, B. The land ice contribution to sea level during the satellite era. Environ. Res. Lett. 13, 063008 (2018); corrigendum 13, 099502 (2018).

    ADS 

    Google Scholar 

  • 19.

    Wouters, B., Gardner, A. S. & Moholdt, G. Global glacier mass loss during the GRACE satellite mission (2002–2016). Front. Earth Sci. 7, 96 (2019).

    ADS 

    Google Scholar 

  • 20.

    Ciracì, E., Velicogna, I. & Swenson, S. Continuity of the mass loss of the world’s glaciers and ice caps from the GRACE and GRACE Follow-On missions. Geophys. Res. Lett. 47, 226 (2020).

    Google Scholar 

  • 21.

    Zemp, M. et al. Global glacier mass changes and their contributions to sea-level rise from 1961 to 2016. Nature 568, 382–386 (2019).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 22.

    RGI Consortium. Randolph Glacier Inventory – A Dataset of Global Glacier Outlines. Technical Report https://www.glims.org/RGI/00_rgi60_TechnicalNote.pdf (Global Land Ice Measurements from Space, 2017).

  • 23.

    Huss, M. Density assumptions for converting geodetic glacier volume change to mass change. Cryosphere 7, 877–887 (2013).

    ADS 

    Google Scholar 

  • 24.

    Ablain, M. et al. Uncertainty in satellite estimates of global mean sea-level changes, trend and acceleration. Earth Syst. Sci. Data 11, 1189–1202 (2019).

    ADS 

    Google Scholar 

  • 25.

    Velicogna, I. et al. Continuity of ice sheet mass loss in Greenland and Antarctica from the GRACE and GRACE Follow-On missions. Geophys. Res. Lett. 47, L11501 (2020).

    Google Scholar 

  • 26.

    Larsen, C. F. et al. Surface melt dominates Alaska glacier mass balance. Geophys. Res. Lett. 42, 5902–5908 (2015).

    ADS 

    Google Scholar 

  • 27.

    Blazquez, A. et al. Exploring the uncertainty in GRACE estimates of the mass redistributions at the Earth surface: implications for the global water and sea level budgets. Geophys. J. Int. 215, 415–430 (2018).

    ADS 

    Google Scholar 

  • 28.

    Shean, D. E. et al. A systematic, regional assessment of High Mountain Asia glacier mass balance. Front. Earth Sci. 7, 363 (2020).

    ADS 

    Google Scholar 

  • 29.

    Braun, M. H. et al. Constraining glacier elevation and mass changes in South America. Nat. Clim. Chang. (2019).

  • 30.

    Dehecq, A. et al. Elevation changes inferred from TanDEM-X data over the Mont-Blanc area: impact of the X-band interferometric bias. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 9, 3870–3882 (2016).

    ADS 

    Google Scholar 

  • 31.

    Sandberg Sørensen, L. et al. 25 years of elevation changes of the Greenland Ice Sheet from ERS, Envisat, and CryoSat-2 radar altimetry. Earth Planet. Sci. Lett. 495, 234–241 (2018).

    ADS 

    Google Scholar 

  • 32.

    Bevis, M. et al. Accelerating changes in ice mass within Greenland, and the ice sheet’s sensitivity to atmospheric forcing. Proc. Natl Acad. Sci. USA 116, 1934–1939 (2019).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 33.

    Garreaud, R. D. et al. The Central Chile Mega Drought (2010–2018): a climate dynamics perspective. Int. J. Climatol. 40, 421–439 (2020).

    Google Scholar 

  • 34.

    Raper, S. C. B. & Braithwaite, R. J. Low sea level rise projections from mountain glaciers and icecaps under global warming. Nature 439, 311–313 (2006).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 35.

    Parkes, D. & Marzeion, B. Twentieth-century contribution to sea-level rise from uncharted glaciers. Nature 563, 551–554 (2018).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 36.

    Becker, J. J. et al. Global bathymetry and elevation data at 30 arc seconds resolution: SRTM30_PLUS. Mar. Geod. 32, 355–371 (2009).

    Google Scholar 

  • 37.

    Tielidze, L. G. & Wheate, R. D. The Greater Caucasus glacier inventory (Russia, Georgia and Azerbaijan). Cryosphere 12, 81–94 (2018).

    ADS 

    Google Scholar 

  • 38.

    Dunse, T. et al. Glacier-surge mechanisms promoted by a hydro-thermodynamic feedback to summer melt. Cryosphere 9, 197–215 (2015).

    ADS 

    Google Scholar 

  • 39.

    McMillan, M. et al. Rapid dynamic activation of a marine-based Arctic ice cap: ice cap dynamic activation. Geophys. Res. Lett. 41, 8902–8909 (2014).

    ADS 

    Google Scholar 

  • 40.

    Nuth, C. et al. Dynamic vulnerability revealed in the collapse of an Arctic tidewater glacier. Sci. Rep. 9, 5541 (2019).

    ADS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 41.

    Howat, I. M., Negrete, A. & Smith, B. E. The Greenland Ice Mapping Project (GIMP) land classification and surface elevation data sets. Cryosphere 8, 1509–1518 (2014).

    ADS 

    Google Scholar 

  • 42.

    Fretwell, P. et al. Bedmap2: improved ice bed, surface and thickness datasets for Antarctica. Cryosphere 7, 375–393 (2013).

    ADS 

    Google Scholar 

  • 43.

    NASA/METI/AIST/Japan Spacesystems & U.S./Japan ASTER Science Team. ASTER Level 1A Data Set – Reconstructed, Unprocessed Instrument Data. 2001, NASA EOSDIS Land Processes DAAC, 2001); https://doi.org/10.5067/ASTER/AST_L1A.003.

  • 44.

    Porter, C. et al. ArcticDEM (Harvard Dataverse, 2018); https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/OHHUKH.

  • 45.

    Howat, I. M., Porter, C., Smith, B. E., Noh, M.-J. & Morin, P. The reference elevation model of Antarctica. Cryosphere 13, 665–674 (2019).

    ADS 

    Google Scholar 

  • 46.

    Rizzoli, P. et al. Generation and performance assessment of the global TanDEM-X digital elevation model. ISPRS J. Photogramm. Remote Sens. 132, 119–139 (2017).

    ADS 

    Google Scholar 

  • 47.

    Vassilaki, D. I. & Stamos, A. A. TanDEM-X DEM: comparative performance review employing LIDAR data and DSMs. ISPRS J. Photogramm. Remote Sens. 160, 33–50 (2020).

    Google Scholar 

  • 48.

    Nuth, C. & Kääb, A. Co-registration and bias corrections of satellite elevation data sets for quantifying glacier thickness change. Cryosphere 5, 271–290 (2011).

    ADS 

    Google Scholar 

  • 49.

    Rupnik, E., Daakir, M. & Pierrot Deseilligny, M. MicMac – a free, open-source solution for photogrammetry. Open Geospat. Data Softw. Stand. 2, 14 (2017).

    Google Scholar 

  • 50.

    Girod, L., Nuth, C., Kääb, A., McNabb, R. & Galland, O. MMASTER: improved ASTER DEMs for elevation change monitoring. Remote Sens. 9, 704 (2017).

    Google Scholar 

  • 51.

    Wales, D. J. & Doye, J. P. K. Global optimization by basin-hopping and the lowest energy structures of Lennard–Jones clusters containing up to 110 atoms. J. Phys. Chem. A 101, 5111–5116 (1997).

    CAS 

    Google Scholar 

  • 52.

    Noh, M.-J. & Howat, I. M. The surface extraction from TIN based Search-space Minimization (SETSM) algorithm. ISPRS J. Photogramm. Remote Sens. 129, 55–76 (2017).

    ADS 

    Google Scholar 

  • 53.

    Dussaillant, I. et al. Two decades of glacier mass loss along the Andes. Nat. Geosci. 12, 802–808 (2019); author correction 13, 711 (2020).

    ADS 
    CAS 

    Google Scholar 

  • 54.

    Brun, F., Berthier, E., Wagnon, P., Kääb, A. & Treichler, D. A spatially resolved estimate of High Mountain Asia glacier mass balances, 2000–2016. Nat. Geosci. 10, 668–673 (2017); author correction 11, 543 (2018).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 55.

    Toutin, T. Three-dimensional topographic mapping with ASTER stereo data in rugged topography. IEEE Trans. Geosci. Remote Sens. 40, 2241–2247 (2002).

    ADS 

    Google Scholar 

  • 56.

    Lacroix, P. Landslides triggered by the Gorkha earthquake in the Langtang valley, volumes and initiation processes. Earth Planets Space 68, 1–10 (2016).

    Google Scholar 

  • 57.

    Shean, D. E. et al. An automated, open-source pipeline for mass production of digital elevation models (DEMs) from very-high-resolution commercial stereo satellite imagery. ISPRS J. Photogramm. Remote Sens. 116, 101–117 (2016).

    ADS 

    Google Scholar 

  • 58.

    Höhle, J. & Höhle, M. Accuracy assessment of digital elevation models by means of robust statistical methods. ISPRS J. Photogramm. Remote Sens. 64, 398–406 (2009).

    ADS 

    Google Scholar 

  • 59.

    Williams, C. K. I. & Rasmussen, C. E. Gaussian Processes for Machine Learning Vol. 2 (MIT Press, 2006).

  • 60.

    Schiefer, E., Menounos, B. & Wheate, R. Recent volume loss of British Columbian glaciers, Canada. Geophys. Res. Lett. (2007).

  • 61.

    Nuimura, T., Fujita, K., Yamaguchi, S. & Sharma, R. R. Elevation changes of glaciers revealed by multitemporal digital elevation models calibrated by GPS survey in the Khumbu region, Nepal Himalaya, 1992–2008. J. Glaciol. 58, 648–656 (2012).

    ADS 

    Google Scholar 

  • 62.

    Willis, M. J., Melkonian, A. K., Pritchard, M. E. & Rivera, A. Ice loss from the Southern Patagonian Ice Field, South America, between 2000 and 2012. Geophys. Res. Lett. 39, L17501 (2012).

    ADS 

    Google Scholar 

  • 63.

    Pedregosa, F. et al. Scikit-learn: machine learning in Python. J. Mach. Learn. Res. 12, 2825–2830 (2011).

    MathSciNet 
    MATH 

    Google Scholar 

  • 64.

    Zwally, H. J., Schutz, R., Hancock, D. & Dimarzio, J. GLAS/ICESat L2 Global Land Surface Altimetry Data (HDF5), Version 34 (NASA Snow and Ice Data Center, 2014); https://nsidc.org/data/GLAH14.

  • 65.

    Alexandrov, O., McMichael, S. & Beyer., R. A. IceBridge DMS L3 Ames Stereo Pipeline Photogrammetric DEM, Version 1 (accessed 1 June 2019); https://nsidc.org/data/IODEM3/versions/1.

  • 66.

    Larsen, C. IceBridge UAF Lidar Scanner L1B Geolocated Surface Elevation Triplets, Version 1 (accessed 20 February 2020); https://nsidc.org/data/ILAKS1B/versions/1.

  • 67.

    Beyer, R. A., Alexandrov, O. & McMichael, S. The Ames Stereo Pipeline: NASA’s open source software for deriving and processing terrain data. Earth Space Sci. 5, 537–548 (2018).

    ADS 

    Google Scholar 

  • 68.

    Harding, D. J. ICESat waveform measurements of within-footprint topographic relief and vegetation vertical structure. Geophys. Res. Lett. 32, L21S10 (2005).

    Google Scholar 

  • 69.

    Gardelle, J., Berthier, E. & Arnaud, Y. Impact of resolution and radar penetration on glacier elevation changes computed from DEM differencing. J. Glaciol. 58, 419–422 (2012).

    ADS 

    Google Scholar 

  • 70.

    McNabb, R., Nuth, C., Kääb, A. & Girod, L. Sensitivity of glacier volume change estimation to DEM void interpolation. Cryosphere 13, 895–910 (2019).

    ADS 

    Google Scholar 

  • 71.

    Cressie, N. A. C. Statistics for Spatial Data Vol. 4, 613–617 (Wiley, 1993).

  • 72.

    Rolstad, C., Haug, T. & Denby, B. Spatially integrated geodetic glacier mass balance and its uncertainty based on geostatistical analysis: application to the western Svartisen ice cap, Norway. J. Glaciol. 55, 666–680 (2009).

    ADS 

    Google Scholar 

  • 73.

    Dehecq, A. et al. Automated processing of declassified KH-9 Hexagon satellite images for global elevation change analysis since the 1970s. Front. Earth Sci. 8, 566802 (2020).

    Google Scholar 

  • 74.

    Menounos, B. et al. Heterogeneous changes in western North American glaciers linked to decadal variability in zonal wind strength. Geophys. Res. Lett. 46, 200–209 (2018).

    ADS 

    Google Scholar 

  • 75.

    Howat, I. M., Smith, B. E., Joughin, I. & Scambos, T. A. Rates of southeast Greenland ice volume loss from combined ICESat and ASTER observations. Geophys. Res. Lett. 35, L17505 (2008).

    ADS 

    Google Scholar 

  • 76.

    Wang, D. & Kääb, A. Modeling glacier elevation change from DEM time series. Remote Sens. 7, 10117–10142 (2015).

    ADS 

    Google Scholar 

  • 77.

    Cogley, J. G. & Adams, W. P. Mass balance of glaciers other than the ice sheets. J. Glaciol. 44, 315–325 (1998).

    ADS 
    CAS 

    Google Scholar 

  • 78.

    Journel, A. G. & Huijbregts, C. J. Mining Geostatistics Vol. 600 (Academic Press, 1978).

  • 79.

    Webster, R. & Oliver, M. A. Geostatistics for Environmental Scientists (John Wiley & Sons, 2007).

  • 80.

    Gräler, B., Pebesma, E. & Heuvelink, G. Spatio-temporal interpolation using gstat. R J. 8, 204 (2016).

    Google Scholar 

  • 81.

    Mälicke, M. & Schneider, H. D. Scikit-GStat 0.2.6: A Scipy Flavored Geostatistical Analysis Toolbox Written in Python (2019); https://zenodo.org/record/3531816#.YFsJ737Le00.

  • 82.

    Dussaillant, I., Berthier, E. & Brun, F. Geodetic mass balance of the Northern Patagonian Icefield from 2000 to 2012 using two independent methods. Front. Earth Sci. 6, 8 (2018).

    ADS 

    Google Scholar 

  • 83.

    Berthier, E., Scambos, T. A. & Shuman, C. A. Mass loss of Larsen B tributary glaciers (Antarctic Peninsula) unabated since 2002. Geophys. Res. Lett. 39, L13501 (2012).

    ADS 

    Google Scholar 

  • 84.

    Granshaw, F. D. & Fountain, A. G. Glacier change (1958–1998) in the North Cascades National Park Complex, Washington, USA. J. Glaciol. 52, 251–256 (2006).

    ADS 
    CAS 

    Google Scholar 

  • 85.

    Pfeffer, W. et al. The Randolph Glacier Inventory: a globally complete inventory of glaciers. J. Glaciol. 60, 537–552 (2014).

    ADS 

    Google Scholar 

  • 86.

    Rastner, P. et al. The first complete inventory of the local glaciers and ice caps on Greenland. Cryosphere 6, 1483–1495 (2012).

    ADS 

    Google Scholar 

  • 87.

    Bolch, T., Menounos, B. & Wheate, R. Landsat-based inventory of glaciers in western Canada, 1985–2005. Remote Sens. Environ. 114, 127–137 (2010).

    ADS 

    Google Scholar 

  • 88.

    Pelto, B. M., Menounos, B. & Marshall, S. J. Multi-year evaluation of airborne geodetic surveys to estimate seasonal mass balance, Columbia and Rocky Mountains, Canada. Cryosphere 13, 1709–1727 (2019).

    ADS 

    Google Scholar 

  • 89.

    Wagnon, P. et al. Seasonal and annual mass balances of Mera and Pokalde glaciers (Nepal Himalaya) since 2007. Cryosphere 7, 1769–1786 (2013).

    ADS 

    Google Scholar 

  • 90.

    Berthier, E., Schiefer, E., Clarke, G. K. C., Menounos, B. & Rémy, F. Contribution of Alaskan glaciers to sea-level rise derived from satellite imagery. Nat. Geosci. 3, 92–95 (2010).

    ADS 
    CAS 

    Google Scholar 

  • 91.

    Berthier, E., Cabot, V., Vincent, C. & Six, D. Decadal region-wide and glacier-wide mass balances derived from multi-temporal ASTER Satellite Digital Elevation Models. Validation over the Mont-Blanc area. Front. Earth Sci. 4, 63 (2016).

    ADS 

    Google Scholar 

  • 92.

    Glacier Monitoring Switzerland. Swiss Glacier Volume Change, Release 2018 (2018); https://doi.glamos.ch/data/volumechange/volumechange_2018_r2018.html.

  • 93.

    Bauder, A., Funk, M. & Huss, M. Ice-volume changes of selected glaciers in the Swiss Alps since the end of the 19th century. Ann. Glaciol. 46, 145–149 (2007).

    ADS 

    Google Scholar 

  • 94.

    Davaze, L., Rabatel, A., Dufour, A., Hugonnet, R. & Arnaud, Y. Region-wide annual glacier surface mass balance for the European Alps from 2000 to 2016. Front. Earth Sci. 8, 149 (2020).

    ADS 

    Google Scholar 

  • 95.

    Schuler, T. V. et al. Reconciling Svalbard Glacier mass balance. Front. Earth Sci. 8, 523646 (2020).

    Google Scholar 

  • 96.

    Aðalgeirsdóttir, G. et al. Glacier Changes in Iceland From ~1890 to 2019. Front. Earth Sci. 8, 520 (2020).

    ADS 

    Google Scholar 

  • 97.

    Hersbach, H. & Dee, D. ERA5 reanalysis is in production. ECMWF Newsl. 147, 5–6 (2016).

    Google Scholar 

  • 98.

    Skliris, N., Zika, J. D., Nurser, G., Josey, S. A. & Marsh, R. Global water cycle amplifying at less than the Clausius–Clapeyron rate. Sci. Rep. 6, 38752 (2016).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 99.

    Sakakibara, D., Sugiyama, S., Sawagaki, T., Marinsek, S. & Skvarca, P. Rapid retreat, acceleration and thinning of Glaciar Upsala, Southern Patagonia Icefield, initiated in 2008. Ann. Glaciol. 54, 131–138 (2013).

    ADS 

    Google Scholar 

  • 100.

    Farr, T. G. et al. The Shuttle Radar Topography Mission. Rev. Geophys. 45, RG2004 (2007).

    ADS 

    Google Scholar 



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