[{"language":[{"iso":"eng"}],"doi":"10.1016/j.cpc.2018.09.020","quality_controlled":"1","external_id":{"arxiv":["1808.03824"]},"main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/1808.03824"}],"oa":1,"publication_identifier":{"issn":["0010-4655"]},"month":"03","volume":236,"date_created":"2021-07-16T08:53:01Z","date_updated":"2021-08-09T12:37:16Z","author":[{"first_name":"Venkat","last_name":"Kapil","full_name":"Kapil, Venkat"},{"first_name":"Mariana","last_name":"Rossi","full_name":"Rossi, Mariana"},{"last_name":"Marsalek","first_name":"Ondrej","full_name":"Marsalek, Ondrej"},{"last_name":"Petraglia","first_name":"Riccardo","full_name":"Petraglia, Riccardo"},{"first_name":"Yair","last_name":"Litman","full_name":"Litman, Yair"},{"first_name":"Thomas","last_name":"Spura","full_name":"Spura, Thomas"},{"last_name":"Cheng","first_name":"Bingqing","orcid":"0000-0002-3584-9632","id":"cbe3cda4-d82c-11eb-8dc7-8ff94289fcc9","full_name":"Cheng, Bingqing"},{"last_name":"Cuzzocrea","first_name":"Alice","full_name":"Cuzzocrea, Alice"},{"first_name":"Robert H.","last_name":"Meißner","full_name":"Meißner, Robert H."},{"full_name":"Wilkins, David M.","first_name":"David M.","last_name":"Wilkins"},{"full_name":"Helfrecht, Benjamin A.","first_name":"Benjamin A.","last_name":"Helfrecht"},{"full_name":"Juda, Przemysław","first_name":"Przemysław","last_name":"Juda"},{"full_name":"Bienvenue, Sébastien P.","first_name":"Sébastien P.","last_name":"Bienvenue"},{"last_name":"Fang","first_name":"Wei","full_name":"Fang, Wei"},{"full_name":"Kessler, Jan","last_name":"Kessler","first_name":"Jan"},{"full_name":"Poltavsky, Igor","first_name":"Igor","last_name":"Poltavsky"},{"full_name":"Vandenbrande, Steven","last_name":"Vandenbrande","first_name":"Steven"},{"last_name":"Wieme","first_name":"Jelle","full_name":"Wieme, Jelle"},{"last_name":"Corminboeuf","first_name":"Clemence","full_name":"Corminboeuf, Clemence"},{"last_name":"Kühne","first_name":"Thomas D.","full_name":"Kühne, Thomas D."},{"full_name":"Manolopoulos, David E.","first_name":"David E.","last_name":"Manolopoulos"},{"first_name":"Thomas E.","last_name":"Markland","full_name":"Markland, Thomas E."},{"full_name":"Richardson, Jeremy O.","first_name":"Jeremy O.","last_name":"Richardson"},{"last_name":"Tkatchenko","first_name":"Alexandre","full_name":"Tkatchenko, Alexandre"},{"first_name":"Gareth A.","last_name":"Tribello","full_name":"Tribello, Gareth A."},{"first_name":"Veronique","last_name":"Van Speybroeck","full_name":"Van Speybroeck, Veronique"},{"last_name":"Ceriotti","first_name":"Michele","full_name":"Ceriotti, Michele"}],"publisher":"Elsevier","publication_status":"published","year":"2019","extern":"1","date_published":"2019-03-01T00:00:00Z","page":"214-223","article_type":"original","citation":{"apa":"Kapil, V., Rossi, M., Marsalek, O., Petraglia, R., Litman, Y., Spura, T., … Ceriotti, M. (2019). i-PI 2.0: A universal force engine for advanced molecular simulations. Computer Physics Communications. Elsevier. https://doi.org/10.1016/j.cpc.2018.09.020","ieee":"V. Kapil et al., “i-PI 2.0: A universal force engine for advanced molecular simulations,” Computer Physics Communications, vol. 236. Elsevier, pp. 214–223, 2019.","ista":"Kapil V, Rossi M, Marsalek O, Petraglia R, Litman Y, Spura T, Cheng B, Cuzzocrea A, Meißner RH, Wilkins DM, Helfrecht BA, Juda P, Bienvenue SP, Fang W, Kessler J, Poltavsky I, Vandenbrande S, Wieme J, Corminboeuf C, Kühne TD, Manolopoulos DE, Markland TE, Richardson JO, Tkatchenko A, Tribello GA, Van Speybroeck V, Ceriotti M. 2019. i-PI 2.0: A universal force engine for advanced molecular simulations. Computer Physics Communications. 236, 214–223.","ama":"Kapil V, Rossi M, Marsalek O, et al. i-PI 2.0: A universal force engine for advanced molecular simulations. Computer Physics Communications. 2019;236:214-223. doi:10.1016/j.cpc.2018.09.020","chicago":"Kapil, Venkat, Mariana Rossi, Ondrej Marsalek, Riccardo Petraglia, Yair Litman, Thomas Spura, Bingqing Cheng, et al. “I-PI 2.0: A Universal Force Engine for Advanced Molecular Simulations.” Computer Physics Communications. Elsevier, 2019. https://doi.org/10.1016/j.cpc.2018.09.020.","short":"V. Kapil, M. Rossi, O. Marsalek, R. Petraglia, Y. Litman, T. Spura, B. Cheng, A. Cuzzocrea, R.H. Meißner, D.M. Wilkins, B.A. Helfrecht, P. Juda, S.P. Bienvenue, W. Fang, J. Kessler, I. Poltavsky, S. Vandenbrande, J. Wieme, C. Corminboeuf, T.D. Kühne, D.E. Manolopoulos, T.E. Markland, J.O. Richardson, A. Tkatchenko, G.A. Tribello, V. Van Speybroeck, M. Ceriotti, Computer Physics Communications 236 (2019) 214–223.","mla":"Kapil, Venkat, et al. “I-PI 2.0: A Universal Force Engine for Advanced Molecular Simulations.” Computer Physics Communications, vol. 236, Elsevier, 2019, pp. 214–23, doi:10.1016/j.cpc.2018.09.020."},"publication":"Computer Physics Communications","article_processing_charge":"No","day":"01","scopus_import":"1","oa_version":"Preprint","intvolume":" 236","status":"public","title":"i-PI 2.0: A universal force engine for advanced molecular simulations","_id":"9677","user_id":"6785fbc1-c503-11eb-8a32-93094b40e1cf","abstract":[{"text":"Progress in the atomic-scale modeling of matter over the past decade has been tremendous. This progress has been brought about by improvements in methods for evaluating interatomic forces that work by either solving the electronic structure problem explicitly, or by computing accurate approximations of the solution and by the development of techniques that use the Born–Oppenheimer (BO) forces to move the atoms on the BO potential energy surface. As a consequence of these developments it is now possible to identify stable or metastable states, to sample configurations consistent with the appropriate thermodynamic ensemble, and to estimate the kinetics of reactions and phase transitions. All too often, however, progress is slowed down by the bottleneck associated with implementing new optimization algorithms and/or sampling techniques into the many existing electronic-structure and empirical-potential codes. To address this problem, we are thus releasing a new version of the i-PI software. This piece of software is an easily extensible framework for implementing advanced atomistic simulation techniques using interatomic potentials and forces calculated by an external driver code. While the original version of the code (Ceriotti et al., 2014) was developed with a focus on path integral molecular dynamics techniques, this second release of i-PI not only includes several new advanced path integral methods, but also offers other classes of algorithms. In other words, i-PI is moving towards becoming a universal force engine that is both modular and tightly coupled to the driver codes that evaluate the potential energy surface and its derivatives.","lang":"eng"}],"type":"journal_article"},{"article_processing_charge":"No","day":"14","scopus_import":"1","date_published":"2019-01-14T00:00:00Z","page":"100-107","article_type":"original","citation":{"apa":"Giberti, F., Cheng, B., Tribello, G. A., & Ceriotti, M. (2019). Iterative unbiasing of quasi-equilibrium sampling. Journal of Chemical Theory and Computation. American Chemical Society. https://doi.org/10.1021/acs.jctc.9b00907","ieee":"F. Giberti, B. Cheng, G. A. Tribello, and M. Ceriotti, “Iterative unbiasing of quasi-equilibrium sampling,” Journal of Chemical Theory and Computation, vol. 16, no. 1. American Chemical Society, pp. 100–107, 2019.","ista":"Giberti F, Cheng B, Tribello GA, Ceriotti M. 2019. Iterative unbiasing of quasi-equilibrium sampling. Journal of Chemical Theory and Computation. 16(1), 100–107.","ama":"Giberti F, Cheng B, Tribello GA, Ceriotti M. Iterative unbiasing of quasi-equilibrium sampling. Journal of Chemical Theory and Computation. 2019;16(1):100-107. doi:10.1021/acs.jctc.9b00907","chicago":"Giberti, F., Bingqing Cheng, G. A. Tribello, and M. Ceriotti. “Iterative Unbiasing of Quasi-Equilibrium Sampling.” Journal of Chemical Theory and Computation. American Chemical Society, 2019. https://doi.org/10.1021/acs.jctc.9b00907.","short":"F. Giberti, B. Cheng, G.A. Tribello, M. Ceriotti, Journal of Chemical Theory and Computation 16 (2019) 100–107.","mla":"Giberti, F., et al. “Iterative Unbiasing of Quasi-Equilibrium Sampling.” Journal of Chemical Theory and Computation, vol. 16, no. 1, American Chemical Society, 2019, pp. 100–07, doi:10.1021/acs.jctc.9b00907."},"publication":"Journal of Chemical Theory and Computation","issue":"1","abstract":[{"lang":"eng","text":"Atomistic modeling of phase transitions, chemical reactions, or other rare events that involve overcoming high free energy barriers usually entails prohibitively long simulation times. Introducing a bias potential as a function of an appropriately chosen set of collective variables can significantly accelerate the exploration of phase space, albeit at the price of distorting the distribution of microstates. Efficient reweighting to recover the unbiased distribution can be nontrivial when employing adaptive sampling techniques such as metadynamics, variationally enhanced sampling, or parallel bias metadynamics, in which the system evolves in a quasi-equilibrium manner under a time-dependent bias. We introduce an iterative unbiasing scheme that makes efficient use of all the trajectory data and that does not require the distribution to be evaluated on a grid. The method can thus be used even when the bias has a high dimensionality. We benchmark this approach against some of the existing schemes on model systems with different complexity and dimensionality."}],"type":"journal_article","oa_version":"Preprint","intvolume":" 16","title":"Iterative unbiasing of quasi-equilibrium sampling","status":"public","user_id":"6785fbc1-c503-11eb-8a32-93094b40e1cf","_id":"9680","publication_identifier":{"issn":["1549-9618"],"eissn":["1549-9626"]},"month":"01","language":[{"iso":"eng"}],"doi":"10.1021/acs.jctc.9b00907","quality_controlled":"1","oa":1,"main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/1911.01140"}],"external_id":{"pmid":["31743021"],"arxiv":["1911.01140"]},"extern":"1","volume":16,"date_updated":"2021-08-09T12:37:37Z","date_created":"2021-07-19T06:56:45Z","author":[{"last_name":"Giberti","first_name":"F.","full_name":"Giberti, F."},{"full_name":"Cheng, Bingqing","first_name":"Bingqing","last_name":"Cheng","id":"cbe3cda4-d82c-11eb-8dc7-8ff94289fcc9","orcid":"0000-0002-3584-9632"},{"first_name":"G. A.","last_name":"Tribello","full_name":"Tribello, G. A."},{"first_name":"M.","last_name":"Ceriotti","full_name":"Ceriotti, M."}],"publisher":"American Chemical Society","publication_status":"published","pmid":1,"year":"2019"},{"article_type":"original","page":"6754-6772","publication":"Water Resources Research","citation":{"ieee":"M. Girona‐Mata, E. S. Miles, S. Ragettli, and F. Pellicciotti, “High‐resolution snowline delineation from Landsat imagery to infer snow cover controls in a Himalayan catchment,” Water Resources Research, vol. 55, no. 8. American Geophysical Union, pp. 6754–6772, 2019.","apa":"Girona‐Mata, M., Miles, E. S., Ragettli, S., & Pellicciotti, F. (2019). High‐resolution snowline delineation from Landsat imagery to infer snow cover controls in a Himalayan catchment. Water Resources Research. American Geophysical Union. https://doi.org/10.1029/2019wr024935","ista":"Girona‐Mata M, Miles ES, Ragettli S, Pellicciotti F. 2019. High‐resolution snowline delineation from Landsat imagery to infer snow cover controls in a Himalayan catchment. Water Resources Research. 55(8), 6754–6772.","ama":"Girona‐Mata M, Miles ES, Ragettli S, Pellicciotti F. High‐resolution snowline delineation from Landsat imagery to infer snow cover controls in a Himalayan catchment. Water Resources Research. 2019;55(8):6754-6772. doi:10.1029/2019wr024935","chicago":"Girona‐Mata, Marc, Evan S. Miles, Silvan Ragettli, and Francesca Pellicciotti. “High‐resolution Snowline Delineation from Landsat Imagery to Infer Snow Cover Controls in a Himalayan Catchment.” Water Resources Research. American Geophysical Union, 2019. https://doi.org/10.1029/2019wr024935.","short":"M. Girona‐Mata, E.S. Miles, S. Ragettli, F. Pellicciotti, Water Resources Research 55 (2019) 6754–6772.","mla":"Girona‐Mata, Marc, et al. “High‐resolution Snowline Delineation from Landsat Imagery to Infer Snow Cover Controls in a Himalayan Catchment.” Water Resources Research, vol. 55, no. 8, American Geophysical Union, 2019, pp. 6754–72, doi:10.1029/2019wr024935."},"date_published":"2019-08-01T00:00:00Z","keyword":["Water Science and Technology"],"scopus_import":"1","day":"01","article_processing_charge":"No","title":"High‐resolution snowline delineation from Landsat imagery to infer snow cover controls in a Himalayan catchment","status":"public","intvolume":" 55","_id":"12600","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","oa_version":"Published Version","type":"journal_article","abstract":[{"text":"The snow cover dynamics of High Mountain Asia are usually assessed at spatial resolutions of 250 m or greater, but this scale is too coarse to clearly represent the rugged topography common to the region. Higher-resolution measurement of snow-covered area often results in biased sampling due to cloud cover and deep shadows. We therefore develop a Normalized Difference Snow Index-based workflow to delineate snow lines from Landsat Thematic Mapper/Enhanced Thematic Mapper+ imagery and apply it to the upper Langtang Valley in Nepal, processing 194 scenes spanning 1999 to 2013. For each scene, we determine the spatial distribution of snow line altitudes (SLAs) with respect to aspect and across six subcatchments. Our results show that the mean SLA exhibits distinct seasonal behavior based on aspect and subcatchment position. We find that SLA dynamics respond to spatial and seasonal trade-offs in precipitation, temperature, and solar radiation, which act as primary controls. We identify two SLA spatial gradients, which we attribute to the effect of spatially variable precipitation. Our results also reveal that aspect-related SLA differences vary seasonally and are influenced by solar radiation. In terms of seasonal dominant controls, we demonstrate that the snow line is controlled by snow precipitation in winter, melt in premonsoon, a combination of both in postmonsoon, and temperature in monsoon, explaining to a large extent the spatial and seasonal variability of the SLA in the upper Langtang Valley. We conclude that while SLA and snow-covered area are complementary metrics, the SLA has a strong potential for understanding local-scale snow cover dynamics and their controlling mechanisms.","lang":"eng"}],"issue":"8","quality_controlled":"1","oa":1,"main_file_link":[{"url":"https://doi.org/10.1029/2019WR024935","open_access":"1"}],"language":[{"iso":"eng"}],"doi":"10.1029/2019wr024935","month":"08","publication_identifier":{"issn":["0043-1397"],"eissn":["1944-7973"]},"publication_status":"published","publisher":"American Geophysical Union","year":"2019","date_updated":"2023-02-28T12:14:18Z","date_created":"2023-02-20T08:12:59Z","volume":55,"author":[{"first_name":"Marc","last_name":"Girona‐Mata","full_name":"Girona‐Mata, Marc"},{"full_name":"Miles, Evan S.","first_name":"Evan S.","last_name":"Miles"},{"first_name":"Silvan","last_name":"Ragettli","full_name":"Ragettli, Silvan"},{"id":"b28f055a-81ea-11ed-b70c-a9fe7f7b0e70","last_name":"Pellicciotti","first_name":"Francesca","full_name":"Pellicciotti, Francesca"}],"extern":"1"},{"publication_identifier":{"issn":["2296-6463"]},"month":"06","language":[{"iso":"eng"}],"doi":"10.3389/feart.2019.00143","quality_controlled":"1","oa":1,"main_file_link":[{"open_access":"1","url":"https://doi.org/10.3389/feart.2019.00143"}],"extern":"1","article_number":"143","volume":7,"date_created":"2023-02-20T08:13:08Z","date_updated":"2023-02-28T12:04:48Z","author":[{"last_name":"Wijngaard","first_name":"René R.","full_name":"Wijngaard, René R."},{"full_name":"Steiner, Jakob F.","last_name":"Steiner","first_name":"Jakob F."},{"full_name":"Kraaijenbrink, Philip D. A.","first_name":"Philip D. A.","last_name":"Kraaijenbrink"},{"full_name":"Klug, Christoph","first_name":"Christoph","last_name":"Klug"},{"first_name":"Surendra","last_name":"Adhikari","full_name":"Adhikari, Surendra"},{"full_name":"Banerjee, Argha","first_name":"Argha","last_name":"Banerjee"},{"id":"b28f055a-81ea-11ed-b70c-a9fe7f7b0e70","last_name":"Pellicciotti","first_name":"Francesca","full_name":"Pellicciotti, Francesca"},{"first_name":"Ludovicus P. H.","last_name":"van Beek","full_name":"van Beek, Ludovicus P. H."},{"last_name":"Bierkens","first_name":"Marc F. P.","full_name":"Bierkens, Marc F. P."},{"first_name":"Arthur F.","last_name":"Lutz","full_name":"Lutz, Arthur F."},{"full_name":"Immerzeel, Walter W.","last_name":"Immerzeel","first_name":"Walter W."}],"publisher":"Frontiers Media","publication_status":"published","year":"2019","article_processing_charge":"No","day":"04","scopus_import":"1","date_published":"2019-06-04T00:00:00Z","article_type":"original","citation":{"short":"R.R. Wijngaard, J.F. Steiner, P.D.A. Kraaijenbrink, C. Klug, S. Adhikari, A. Banerjee, F. Pellicciotti, L.P.H. van Beek, M.F.P. Bierkens, A.F. Lutz, W.W. Immerzeel, Frontiers in Earth Science 7 (2019).","mla":"Wijngaard, René R., et al. “Modeling the Response of the Langtang Glacier and the Hintereisferner to a Changing Climate since the Little Ice Age.” Frontiers in Earth Science, vol. 7, 143, Frontiers Media, 2019, doi:10.3389/feart.2019.00143.","chicago":"Wijngaard, René R., Jakob F. Steiner, Philip D. A. Kraaijenbrink, Christoph Klug, Surendra Adhikari, Argha Banerjee, Francesca Pellicciotti, et al. “Modeling the Response of the Langtang Glacier and the Hintereisferner to a Changing Climate since the Little Ice Age.” Frontiers in Earth Science. Frontiers Media, 2019. https://doi.org/10.3389/feart.2019.00143.","ama":"Wijngaard RR, Steiner JF, Kraaijenbrink PDA, et al. Modeling the response of the Langtang Glacier and the Hintereisferner to a changing climate since the Little Ice Age. Frontiers in Earth Science. 2019;7. doi:10.3389/feart.2019.00143","ieee":"R. R. Wijngaard et al., “Modeling the response of the Langtang Glacier and the Hintereisferner to a changing climate since the Little Ice Age,” Frontiers in Earth Science, vol. 7. Frontiers Media, 2019.","apa":"Wijngaard, R. R., Steiner, J. F., Kraaijenbrink, P. D. A., Klug, C., Adhikari, S., Banerjee, A., … Immerzeel, W. W. (2019). Modeling the response of the Langtang Glacier and the Hintereisferner to a changing climate since the Little Ice Age. Frontiers in Earth Science. Frontiers Media. https://doi.org/10.3389/feart.2019.00143","ista":"Wijngaard RR, Steiner JF, Kraaijenbrink PDA, Klug C, Adhikari S, Banerjee A, Pellicciotti F, van Beek LPH, Bierkens MFP, Lutz AF, Immerzeel WW. 2019. Modeling the response of the Langtang Glacier and the Hintereisferner to a changing climate since the Little Ice Age. Frontiers in Earth Science. 7, 143."},"publication":"Frontiers in Earth Science","abstract":[{"text":"This study aims at developing and applying a spatially-distributed coupled glacier mass balance and ice-flow model to attribute the response of glaciers to natural and anthropogenic climate change. We focus on two glaciers with contrasting surface characteristics: a debris-covered glacier (Langtang Glacier in Nepal) and a clean-ice glacier (Hintereisferner in Austria). The model is applied from the end of the Little Ice Age (1850) to the present-day (2016) and is forced with four bias-corrected General Circulation Models (GCMs) from the historical experiment of the CMIP5 archive. The selected GCMs represent region-specific warm-dry, warm-wet, cold-dry, and cold-wet climate conditions. To isolate the effects of anthropogenic climate change on glacier mass balance and flow runs from these GCMs with and without further anthropogenic forcing after 1970 until 2016 are selected. The outcomes indicate that both glaciers experience the largest reduction in area and volume under warm climate conditions, whereas area and volume reductions are smaller under cold climate conditions. Simultaneously with changes in glacier area and volume, surface velocities generally decrease over time. Without further anthropogenic forcing the results reveal a 3% (9%) smaller decline in glacier area (volume) for the debris-covered glacier and a 18% (39%) smaller decline in glacier area (volume) for the clean-ice glacier. The difference in the magnitude between the two glaciers can mainly be attributed to differences in the response time of the glaciers, where the clean-ice glacier shows a much faster response to climate change. We conclude that the response of the two glaciers can mainly be attributed to anthropogenic climate change and that the impact is larger on the clean-ice glacier. The outcomes show that the model performs well under different climate conditions and that the developed approach can be used for regional-scale glacio-hydrological modeling.","lang":"eng"}],"type":"journal_article","oa_version":"Published Version","intvolume":" 7","title":"Modeling the response of the Langtang Glacier and the Hintereisferner to a changing climate since the Little Ice Age","status":"public","_id":"12602","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87"},{"publication":"Journal of Glaciology","citation":{"short":"J.F. STEINER, P. BURI, E.S. MILES, S. RAGETTLI, F. Pellicciotti, Journal of Glaciology 65 (2019) 617–632.","mla":"STEINER, JAKOB F., et al. “Supraglacial Ice Cliffs and Ponds on Debris-Covered Glaciers: Spatio-Temporal Distribution and Characteristics.” Journal of Glaciology, vol. 65, no. 252, Cambridge University Press, 2019, pp. 617–32, doi:10.1017/jog.2019.40.","chicago":"STEINER, JAKOB F., PASCAL BURI, EVAN S. MILES, SILVAN RAGETTLI, and Francesca Pellicciotti. “Supraglacial Ice Cliffs and Ponds on Debris-Covered Glaciers: Spatio-Temporal Distribution and Characteristics.” Journal of Glaciology. Cambridge University Press, 2019. https://doi.org/10.1017/jog.2019.40.","ama":"STEINER JF, BURI P, MILES ES, RAGETTLI S, Pellicciotti F. Supraglacial ice cliffs and ponds on debris-covered glaciers: Spatio-temporal distribution and characteristics. Journal of Glaciology. 2019;65(252):617-632. doi:10.1017/jog.2019.40","apa":"STEINER, J. F., BURI, P., MILES, E. S., RAGETTLI, S., & Pellicciotti, F. (2019). Supraglacial ice cliffs and ponds on debris-covered glaciers: Spatio-temporal distribution and characteristics. Journal of Glaciology. Cambridge University Press. https://doi.org/10.1017/jog.2019.40","ieee":"J. F. STEINER, P. BURI, E. S. MILES, S. RAGETTLI, and F. Pellicciotti, “Supraglacial ice cliffs and ponds on debris-covered glaciers: Spatio-temporal distribution and characteristics,” Journal of Glaciology, vol. 65, no. 252. Cambridge University Press, pp. 617–632, 2019.","ista":"STEINER JF, BURI P, MILES ES, RAGETTLI S, Pellicciotti F. 2019. Supraglacial ice cliffs and ponds on debris-covered glaciers: Spatio-temporal distribution and characteristics. Journal of Glaciology. 65(252), 617–632."},"article_type":"original","page":"617-632","date_published":"2019-08-01T00:00:00Z","scopus_import":"1","day":"01","article_processing_charge":"No","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","_id":"12601","title":"Supraglacial ice cliffs and ponds on debris-covered glaciers: Spatio-temporal distribution and characteristics","status":"public","intvolume":" 65","oa_version":"Published Version","type":"journal_article","abstract":[{"lang":"eng","text":"Ice cliffs and ponds on debris-covered glaciers have received increased attention due to their role in amplifying local melt. However, very few studies have looked at these features on the catchment scale to determine their patterns and changes in space and time. We have compiled a detailed inventory of cliffs and ponds in the Langtang catchment, central Himalaya, from six high-resolution satellite orthoimages and DEMs between 2006 and 2015, and a historic orthophoto from 1974. Cliffs cover between 1.4% (± 0.4%) in the dry and 3.4% (± 0.9%) in the wet seasons and ponds between 0.6% (± 0.1%) and 1.6% (± 0.3%) of the total debris-covered tongues. We find large variations between seasons, as cliffs and ponds tend to grow in the wetter monsoon period, but there is no obvious trend in total area over the study period. The inventory further shows that cliffs are predominately north-facing irrespective of the glacier flow direction. Both cliffs and ponds appear in higher densities several hundred metres from the terminus in areas where tributaries reach the main glacier tongue. On the largest glacier in the catchment ~10% of all cliffs and ponds persisted over nearly a decade."}],"issue":"252","oa":1,"main_file_link":[{"url":"https://doi.org/10.1017/jog.2019.40","open_access":"1"}],"quality_controlled":"1","doi":"10.1017/jog.2019.40","language":[{"iso":"eng"}],"month":"08","publication_identifier":{"eissn":["1727-5652"],"issn":["0022-1430"]},"year":"2019","publication_status":"published","publisher":"Cambridge University Press","author":[{"last_name":"STEINER","first_name":"JAKOB F.","full_name":"STEINER, JAKOB F."},{"first_name":"PASCAL","last_name":"BURI","full_name":"BURI, PASCAL"},{"full_name":"MILES, EVAN S.","last_name":"MILES","first_name":"EVAN S."},{"last_name":"RAGETTLI","first_name":"SILVAN","full_name":"RAGETTLI, SILVAN"},{"full_name":"Pellicciotti, Francesca","id":"b28f055a-81ea-11ed-b70c-a9fe7f7b0e70","last_name":"Pellicciotti","first_name":"Francesca"}],"date_created":"2023-02-20T08:13:03Z","date_updated":"2023-02-28T12:11:07Z","volume":65,"extern":"1"}]