[{"type":"journal_article","main_file_link":[{"url":"https://doi.org/10.1016/j.rse.2020.112201","open_access":"1"}],"intvolume":"       253","citation":{"ista":"Kneib M, Miles ES, Jola S, Buri P, Herreid S, Bhattacharya A, Watson CS, Bolch T, Quincey D, Pellicciotti F. 2021. Mapping ice cliffs on debris-covered glaciers using multispectral satellite images. Remote Sensing of Environment. 253(2), 112201.","apa":"Kneib, M., Miles, E. S., Jola, S., Buri, P., Herreid, S., Bhattacharya, A., … Pellicciotti, F. (2021). Mapping ice cliffs on debris-covered glaciers using multispectral satellite images. <i>Remote Sensing of Environment</i>. Elsevier. <a href=\"https://doi.org/10.1016/j.rse.2020.112201\">https://doi.org/10.1016/j.rse.2020.112201</a>","chicago":"Kneib, M., E.S. Miles, S. Jola, P. Buri, S. Herreid, A. Bhattacharya, C.S. Watson, T. Bolch, D. Quincey, and Francesca Pellicciotti. “Mapping Ice Cliffs on Debris-Covered Glaciers Using Multispectral Satellite Images.” <i>Remote Sensing of Environment</i>. Elsevier, 2021. <a href=\"https://doi.org/10.1016/j.rse.2020.112201\">https://doi.org/10.1016/j.rse.2020.112201</a>.","short":"M. Kneib, E.S. Miles, S. Jola, P. Buri, S. Herreid, A. Bhattacharya, C.S. Watson, T. Bolch, D. Quincey, F. Pellicciotti, Remote Sensing of Environment 253 (2021).","mla":"Kneib, M., et al. “Mapping Ice Cliffs on Debris-Covered Glaciers Using Multispectral Satellite Images.” <i>Remote Sensing of Environment</i>, vol. 253, no. 2, 112201, Elsevier, 2021, doi:<a href=\"https://doi.org/10.1016/j.rse.2020.112201\">10.1016/j.rse.2020.112201</a>.","ama":"Kneib M, Miles ES, Jola S, et al. Mapping ice cliffs on debris-covered glaciers using multispectral satellite images. <i>Remote Sensing of Environment</i>. 2021;253(2). doi:<a href=\"https://doi.org/10.1016/j.rse.2020.112201\">10.1016/j.rse.2020.112201</a>","ieee":"M. Kneib <i>et al.</i>, “Mapping ice cliffs on debris-covered glaciers using multispectral satellite images,” <i>Remote Sensing of Environment</i>, vol. 253, no. 2. Elsevier, 2021."},"status":"public","date_published":"2021-02-01T00:00:00Z","article_number":"112201","day":"01","scopus_import":"1","extern":"1","quality_controlled":"1","language":[{"iso":"eng"}],"volume":253,"abstract":[{"lang":"eng","text":"Ice cliffs play a key role in the mass balance of debris-covered glaciers, but assessing their importance is limited by a lack of datasets on their distribution and evolution at scales larger than an individual glacier. These datasets are often derived using operator-biased and time-consuming manual delineation approaches, despite the recent emergence of semi-automatic mapping methods. These methods have used elevation or multispectral data, but the varying slope and mixed spectral signal of these dynamic features makes the transferability of these approaches particularly challenging. We develop three semi-automated and objective new approaches, based on the Spectral Curvature and Linear Spectral Unmixing of multispectral images, to map these features at a glacier to regional scale. The transferability of each method is assessed by applying it to three sites in the Himalaya, where debris-covered glaciers are widespread, with varying lithologic, glaciological and climatic settings, and encompassing different periods of the melt season. We develop the new methods keeping in mind the wide range of remote sensing platforms currently in use, and focus in particular on two products: we apply the three approaches at each site to near-contemporaneous atmospherically-corrected Pléiades (2 m resolution) and Sentinel-2 (10 m resolution) images and assess the effects of spatial and spectral resolution on the results. We find that the Spectral Curvature method works best for the high spatial resolution, four band Pléaides images, while a modification of the Linear Spectral Unmixing using the scaling factor of the unmixing is best for the coarser spatial resolution, but additional spectral information of Sentinel-2 products. In both cases ice cliffs are mapped with a Dice coefficient higher than 0.48. Comparison of the Pléiades results with other existing methods shows that the Spectral Curvature approach performs better and is more robust than any other existing automated or semi-automated approaches. Both methods outline a high number of small, sometimes shallow-sloping and thinly debris-covered ice patches that differ from our traditional understanding of cliffs but may have non-negligible impact on the mass balance of debris-covered glaciers. Overall these results pave the way for large scale efforts of ice cliff mapping that can enable inclusion of these features in debris-covered glacier melt models, as well as allow the generation of multiple datasets to study processes of cliff formation, evolution and decline."}],"_id":"12590","issue":"2","article_processing_charge":"No","publication":"Remote Sensing of Environment","publication_status":"published","publisher":"Elsevier","oa":1,"author":[{"full_name":"Kneib, M.","first_name":"M.","last_name":"Kneib"},{"first_name":"E.S.","full_name":"Miles, E.S.","last_name":"Miles"},{"first_name":"S.","full_name":"Jola, S.","last_name":"Jola"},{"last_name":"Buri","first_name":"P.","full_name":"Buri, P."},{"last_name":"Herreid","first_name":"S.","full_name":"Herreid, S."},{"last_name":"Bhattacharya","first_name":"A.","full_name":"Bhattacharya, A."},{"full_name":"Watson, C.S.","first_name":"C.S.","last_name":"Watson"},{"last_name":"Bolch","first_name":"T.","full_name":"Bolch, T."},{"last_name":"Quincey","full_name":"Quincey, D.","first_name":"D."},{"first_name":"Francesca","full_name":"Pellicciotti, Francesca","last_name":"Pellicciotti","id":"b28f055a-81ea-11ed-b70c-a9fe7f7b0e70"}],"title":"Mapping ice cliffs on debris-covered glaciers using multispectral satellite images","oa_version":"Published Version","doi":"10.1016/j.rse.2020.112201","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","keyword":["Computers in Earth Sciences","Geology","Soil Science"],"date_created":"2023-02-20T08:12:00Z","date_updated":"2023-02-28T12:53:46Z","publication_identifier":{"issn":["0034-4257"]},"article_type":"original","year":"2021","month":"02"},{"publisher":"Elsevier","type":"journal_article","intvolume":"       186","title":"Object-based analysis of unmanned aerial vehicle imagery to map and characterise surface features on a debris-covered glacier","author":[{"first_name":"P.D.A.","full_name":"Kraaijenbrink, P.D.A.","last_name":"Kraaijenbrink"},{"full_name":"Shea, J.M.","first_name":"J.M.","last_name":"Shea"},{"id":"b28f055a-81ea-11ed-b70c-a9fe7f7b0e70","last_name":"Pellicciotti","full_name":"Pellicciotti, Francesca","first_name":"Francesca"},{"last_name":"Jong","first_name":"S.M. de","full_name":"Jong, S.M. de"},{"full_name":"Immerzeel, W.W.","first_name":"W.W.","last_name":"Immerzeel"}],"citation":{"ista":"Kraaijenbrink PDA, Shea JM, Pellicciotti F, Jong SM de, Immerzeel WW. 2016. Object-based analysis of unmanned aerial vehicle imagery to map and characterise surface features on a debris-covered glacier. Remote Sensing of Environment. 186, 581–595.","apa":"Kraaijenbrink, P. D. A., Shea, J. M., Pellicciotti, F., Jong, S. M. de, &#38; Immerzeel, W. W. (2016). Object-based analysis of unmanned aerial vehicle imagery to map and characterise surface features on a debris-covered glacier. <i>Remote Sensing of Environment</i>. Elsevier. <a href=\"https://doi.org/10.1016/j.rse.2016.09.013\">https://doi.org/10.1016/j.rse.2016.09.013</a>","mla":"Kraaijenbrink, P. D. A., et al. “Object-Based Analysis of Unmanned Aerial Vehicle Imagery to Map and Characterise Surface Features on a Debris-Covered Glacier.” <i>Remote Sensing of Environment</i>, vol. 186, Elsevier, 2016, pp. 581–95, doi:<a href=\"https://doi.org/10.1016/j.rse.2016.09.013\">10.1016/j.rse.2016.09.013</a>.","short":"P.D.A. Kraaijenbrink, J.M. Shea, F. Pellicciotti, S.M. de Jong, W.W. Immerzeel, Remote Sensing of Environment 186 (2016) 581–595.","chicago":"Kraaijenbrink, P.D.A., J.M. Shea, Francesca Pellicciotti, S.M. de Jong, and W.W. Immerzeel. “Object-Based Analysis of Unmanned Aerial Vehicle Imagery to Map and Characterise Surface Features on a Debris-Covered Glacier.” <i>Remote Sensing of Environment</i>. Elsevier, 2016. <a href=\"https://doi.org/10.1016/j.rse.2016.09.013\">https://doi.org/10.1016/j.rse.2016.09.013</a>.","ieee":"P. D. A. Kraaijenbrink, J. M. Shea, F. Pellicciotti, S. M. de Jong, and W. W. Immerzeel, “Object-based analysis of unmanned aerial vehicle imagery to map and characterise surface features on a debris-covered glacier,” <i>Remote Sensing of Environment</i>, vol. 186. Elsevier, pp. 581–595, 2016.","ama":"Kraaijenbrink PDA, Shea JM, Pellicciotti F, Jong SM de, Immerzeel WW. Object-based analysis of unmanned aerial vehicle imagery to map and characterise surface features on a debris-covered glacier. <i>Remote Sensing of Environment</i>. 2016;186:581-595. doi:<a href=\"https://doi.org/10.1016/j.rse.2016.09.013\">10.1016/j.rse.2016.09.013</a>"},"oa_version":"None","status":"public","doi":"10.1016/j.rse.2016.09.013","day":"01","page":"581-595","date_published":"2016-12-01T00:00:00Z","extern":"1","scopus_import":"1","language":[{"iso":"eng"}],"quality_controlled":"1","date_created":"2023-02-20T08:14:35Z","keyword":["Computers in Earth Sciences","Geology","Soil Science"],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_updated":"2023-02-24T11:31:58Z","abstract":[{"text":"Debris-covered glaciers in the Himalaya may have spatially-averaged rates of surface height change that are similar to those observed on bare-ice glaciers, despite the insulating effects of thick debris. Spatially heterogeneous melt patterns caused by the development and evolution of ice cliffs and supraglacial pond systems result in substantial mass losses over time. However, mechanisms controlling the formation and survival of cliffs and ponds remain largely unknown. To study the distribution and characteristics of these surface features we deploy an unmanned aerial vehicle (UAV) over a stretch of the debris-covered Langtang Glacier, Nepal. Acquired images are processed into high-resolution orthomosaics and elevation models with the Structure from Motion (SfM) photogrammetry algorithm. Ice cliffs and ponds are classified using object-based image analysis (OBIA) and their morphology and spatial distribution are analysed and evaluated using object, pixel and point cloud approaches. Results show that ice cliffs are predominantly north-facing, and larger ice cliffs are generally coupled with supraglacial ponds, which may affect their evolution considerably. The spatial distribution of ice cliffs indicates that they are more likely to form in areas where high strain rates are expected. The spatial configuration of ponds over the entire tongue reveals high pond density near confluences, possibly due to closure of conduits via transverse compression. We conclude that the combination of OBIA and UAV imagery is a valuable tool in the semi-automatic and objective analysis of surface features on debris-covered glaciers. The technique may also have potential for upscaling to the use of spaceborne imagery, and the use of UAV-derived point clouds to analyse ice cliff undercuts is promising.","lang":"eng"}],"volume":186,"article_type":"original","publication_identifier":{"issn":["0034-4257"]},"_id":"12614","year":"2016","article_processing_charge":"No","month":"12","publication":"Remote Sensing of Environment","publication_status":"published"},{"year":"2014","publication_identifier":{"issn":["0034-4257"]},"article_type":"original","month":"07","date_updated":"2023-02-24T08:32:39Z","date_created":"2023-02-20T08:16:56Z","keyword":["Computers in Earth Sciences","Geology","Soil Science"],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","oa_version":"None","title":"High-resolution monitoring of Himalayan glacier dynamics using unmanned aerial vehicles","author":[{"first_name":"W.W.","full_name":"Immerzeel, W.W.","last_name":"Immerzeel"},{"first_name":"P.D.A.","full_name":"Kraaijenbrink, P.D.A.","last_name":"Kraaijenbrink"},{"last_name":"Shea","full_name":"Shea, J.M.","first_name":"J.M."},{"last_name":"Shrestha","first_name":"A.B.","full_name":"Shrestha, A.B."},{"first_name":"Francesca","full_name":"Pellicciotti, Francesca","last_name":"Pellicciotti","id":"b28f055a-81ea-11ed-b70c-a9fe7f7b0e70"},{"full_name":"Bierkens, M.F.P.","first_name":"M.F.P.","last_name":"Bierkens"},{"full_name":"de Jong, S.M.","first_name":"S.M.","last_name":"de Jong"}],"page":"93-103","doi":"10.1016/j.rse.2014.04.025","publisher":"Elsevier","_id":"12636","publication_status":"published","publication":"Remote Sensing of Environment","article_processing_charge":"No","issue":"7","language":[{"iso":"eng"}],"quality_controlled":"1","extern":"1","scopus_import":"1","abstract":[{"lang":"eng","text":"Himalayan glacier tongues are commonly debris covered and they are an important source of melt water. However, they remain relatively unstudied because of the inaccessibility of the terrain and the difficulties in field work caused by the thick debris mantles. Observations of debris-covered glaciers are therefore scarce and airborne remote sensing may bridge the gap between scarce field observations and coarse resolution space-borne remote sensing. In this study we deploy an Unmanned Aerial Vehicle (UAV) before and after the melt and monsoon season (May and October 2013) over the debris-covered tongue of the Lirung Glacier in Nepal. Based on stereo-imaging and the structure for motion algorithm we derive highly detailed ortho-mosaics and digital elevation models (DEMs), which we geometrically correct using differential GPS observations collected in the field. Based on DEM differencing and manual feature tracking we derive the mass loss and the surface velocity of the glacier at a high spatial accuracy. On average, mass loss is limited and the surface velocity is very small. However, the spatial variability of melt rates is very high, and ice cliffs and supra-glacial ponds show mass losses that can be an order of magnitude higher than the average. We suggest that future research should focus on the interaction between supra-glacial ponds, ice cliffs and englacial hydrology to further understand the dynamics of debris-covered glaciers. Finally, we conclude that UAV deployment has large potential in glaciology and it may revolutionize methods currently applied in studying glacier surface features."}],"volume":150,"citation":{"ista":"Immerzeel WW, Kraaijenbrink PDA, Shea JM, Shrestha AB, Pellicciotti F, Bierkens MFP, de Jong SM. 2014. High-resolution monitoring of Himalayan glacier dynamics using unmanned aerial vehicles. Remote Sensing of Environment. 150(7), 93–103.","apa":"Immerzeel, W. W., Kraaijenbrink, P. D. A., Shea, J. M., Shrestha, A. B., Pellicciotti, F., Bierkens, M. F. P., &#38; de Jong, S. M. (2014). High-resolution monitoring of Himalayan glacier dynamics using unmanned aerial vehicles. <i>Remote Sensing of Environment</i>. Elsevier. <a href=\"https://doi.org/10.1016/j.rse.2014.04.025\">https://doi.org/10.1016/j.rse.2014.04.025</a>","chicago":"Immerzeel, W.W., P.D.A. Kraaijenbrink, J.M. Shea, A.B. Shrestha, Francesca Pellicciotti, M.F.P. Bierkens, and S.M. de Jong. “High-Resolution Monitoring of Himalayan Glacier Dynamics Using Unmanned Aerial Vehicles.” <i>Remote Sensing of Environment</i>. Elsevier, 2014. <a href=\"https://doi.org/10.1016/j.rse.2014.04.025\">https://doi.org/10.1016/j.rse.2014.04.025</a>.","short":"W.W. Immerzeel, P.D.A. Kraaijenbrink, J.M. Shea, A.B. Shrestha, F. Pellicciotti, M.F.P. Bierkens, S.M. de Jong, Remote Sensing of Environment 150 (2014) 93–103.","mla":"Immerzeel, W. W., et al. “High-Resolution Monitoring of Himalayan Glacier Dynamics Using Unmanned Aerial Vehicles.” <i>Remote Sensing of Environment</i>, vol. 150, no. 7, Elsevier, 2014, pp. 93–103, doi:<a href=\"https://doi.org/10.1016/j.rse.2014.04.025\">10.1016/j.rse.2014.04.025</a>.","ama":"Immerzeel WW, Kraaijenbrink PDA, Shea JM, et al. High-resolution monitoring of Himalayan glacier dynamics using unmanned aerial vehicles. <i>Remote Sensing of Environment</i>. 2014;150(7):93-103. doi:<a href=\"https://doi.org/10.1016/j.rse.2014.04.025\">10.1016/j.rse.2014.04.025</a>","ieee":"W. W. Immerzeel <i>et al.</i>, “High-resolution monitoring of Himalayan glacier dynamics using unmanned aerial vehicles,” <i>Remote Sensing of Environment</i>, vol. 150, no. 7. Elsevier, pp. 93–103, 2014."},"day":"01","date_published":"2014-07-01T00:00:00Z","status":"public","type":"journal_article","intvolume":"       150"},{"main_file_link":[{"url":"https://doi.org/10.1029/2012JD017795","open_access":"1"}],"type":"journal_article","intvolume":"       117","citation":{"ista":"Reid TD, Carenzo M, Pellicciotti F, Brock BW. 2012. Including debris cover effects in a distributed model of glacier ablation. Journal of Geophysical Research: Atmospheres. 117(D18), D18105.","apa":"Reid, T. D., Carenzo, M., Pellicciotti, F., &#38; Brock, B. W. (2012). Including debris cover effects in a distributed model of glacier ablation. <i>Journal of Geophysical Research: Atmospheres</i>. American Geophysical Union. <a href=\"https://doi.org/10.1029/2012jd017795\">https://doi.org/10.1029/2012jd017795</a>","chicago":"Reid, T. D., M. Carenzo, Francesca Pellicciotti, and B. W. Brock. “Including Debris Cover Effects in a Distributed Model of Glacier Ablation.” <i>Journal of Geophysical Research: Atmospheres</i>. American Geophysical Union, 2012. <a href=\"https://doi.org/10.1029/2012jd017795\">https://doi.org/10.1029/2012jd017795</a>.","short":"T.D. Reid, M. Carenzo, F. Pellicciotti, B.W. Brock, Journal of Geophysical Research: Atmospheres 117 (2012).","mla":"Reid, T. D., et al. “Including Debris Cover Effects in a Distributed Model of Glacier Ablation.” <i>Journal of Geophysical Research: Atmospheres</i>, vol. 117, no. D18, D18105, American Geophysical Union, 2012, doi:<a href=\"https://doi.org/10.1029/2012jd017795\">10.1029/2012jd017795</a>.","ama":"Reid TD, Carenzo M, Pellicciotti F, Brock BW. Including debris cover effects in a distributed model of glacier ablation. <i>Journal of Geophysical Research: Atmospheres</i>. 2012;117(D18). doi:<a href=\"https://doi.org/10.1029/2012jd017795\">10.1029/2012jd017795</a>","ieee":"T. D. Reid, M. Carenzo, F. Pellicciotti, and B. W. Brock, “Including debris cover effects in a distributed model of glacier ablation,” <i>Journal of Geophysical Research: Atmospheres</i>, vol. 117, no. D18. American Geophysical Union, 2012."},"article_number":"D18105","day":"27","date_published":"2012-09-27T00:00:00Z","status":"public","language":[{"iso":"eng"}],"quality_controlled":"1","extern":"1","scopus_import":"1","abstract":[{"lang":"eng","text":"Distributed glacier melt models generally assume that the glacier surface consists of bare exposed ice and snow. In reality, many glaciers are wholly or partially covered in layers of debris that tend to suppress ablation rates. In this paper, an existing physically based point model for the ablation of debris-covered ice is incorporated in a distributed melt model and applied to Haut Glacier d'Arolla, Switzerland, which has three large patches of debris cover on its surface. The model is based on a 10 m resolution digital elevation model (DEM) of the area; each glacier pixel in the DEM is defined as either bare or debris-covered ice, and may be covered in snow that must be melted off before ice ablation is assumed to occur. Each debris-covered pixel is assigned a debris thickness value using probability distributions based on over 1000 manual thickness measurements. Locally observed meteorological data are used to run energy balance calculations in every pixel, using an approach suitable for snow, bare ice or debris-covered ice as appropriate. The use of the debris model significantly reduces the total ablation in the debris-covered areas, however the precise reduction is sensitive to the temperature extrapolation used in the model distribution because air near the debris surface tends to be slightly warmer than over bare ice. Overall results suggest that the debris patches, which cover 10% of the glacierized area, reduce total runoff from the glacierized part of the basin by up to 7%."}],"volume":117,"_id":"12648","publication":"Journal of Geophysical Research: Atmospheres","publication_status":"published","article_processing_charge":"No","issue":"D18","oa":1,"publisher":"American Geophysical Union","oa_version":"Published Version","title":"Including debris cover effects in a distributed model of glacier ablation","author":[{"last_name":"Reid","full_name":"Reid, T. D.","first_name":"T. D."},{"last_name":"Carenzo","first_name":"M.","full_name":"Carenzo, M."},{"id":"b28f055a-81ea-11ed-b70c-a9fe7f7b0e70","last_name":"Pellicciotti","full_name":"Pellicciotti, Francesca","first_name":"Francesca"},{"last_name":"Brock","first_name":"B. W.","full_name":"Brock, B. W."}],"doi":"10.1029/2012jd017795","date_updated":"2023-02-20T10:57:31Z","date_created":"2023-02-20T08:17:57Z","keyword":["Paleontology","Space and Planetary Science","Earth and Planetary Sciences (miscellaneous)","Atmospheric Science","Earth-Surface Processes","Geochemistry and Petrology","Soil Science","Water Science and Technology","Ecology","Aquatic Science","Forestry","Oceanography","Geophysics"],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","year":"2012","article_type":"original","publication_identifier":{"issn":["0148-0227"]},"month":"09"},{"date_updated":"2024-10-14T12:01:08Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_created":"2023-02-20T08:18:14Z","keyword":["Paleontology","Space and Planetary Science","Earth and Planetary Sciences (miscellaneous)","Atmospheric Science","Earth-Surface Processes","Geochemistry and Petrology","Soil Science","Water Science and Technology","Ecology","Aquatic Science","Forestry","Oceanography","Geophysics"],"year":"2011","article_type":"original","publication_identifier":{"issn":["0148-0227"]},"month":"12","publisher":"American Geophysical Union","oa":1,"oa_version":"Published Version","author":[{"last_name":"Petersen","first_name":"L.","full_name":"Petersen, L."},{"orcid":"0000-0002-5554-8087","id":"b28f055a-81ea-11ed-b70c-a9fe7f7b0e70","last_name":"Pellicciotti","full_name":"Pellicciotti, Francesca","first_name":"Francesca"}],"title":"Spatial and temporal variability of air temperature on a melting glacier: Atmospheric controls, extrapolation methods and their effect on melt modeling, Juncal Norte Glacier, Chile","doi":"10.1029/2011jd015842","quality_controlled":"1","language":[{"iso":"eng"}],"scopus_import":"1","extern":"1","volume":116,"abstract":[{"text":"Temperature data from three Automatic Weather Stations and twelve Temperature Loggers are used to investigate the spatiotemporal variability of temperature over a glacier, its main atmospheric controls, the suitability of extrapolation techniques and their effect on melt modeling. We use data collected on Juncal Norte Glacier, central Chile, during one ablation season. We examine temporal and spatial variability in lapse rates (LRs), together with alternative statistical interpolation methods. The main control over the glacier thermal regime is the development of a katabatic boundary layer (KBL). Katabatic wind occurs at night and in the morning and is eroded in the afternoon. LRs reveal strong diurnal variability, with steeper LRs during the day when the katabatic wind weakens and shallower LRs during the night and morning. We suggest that temporally variable LRs should be used to account for the observed change. They tend to be steeper than equivalent constant LRs, and therefore result in a reduction in simulated melt compared to use of constant LRs when extrapolating from lower to higher elevations. In addition to the temporal variability, the temperature-elevation relationship varies also in space. Differences are evident between local LRs and including such variability in melt modeling affects melt simulations. Extrapolation methods based on the spatial variability of the observations after removal of the elevation trend, such as Inverse Distance Weighting or Kriging, do not seem necessary for simulations of gridded temperature data over a glacier.","lang":"eng"}],"_id":"12651","publication_status":"published","publication":"Journal of Geophysical Research: Atmospheres","issue":"D23","article_processing_charge":"No","main_file_link":[{"url":"https://doi.org/10.1029/2011JD01584","open_access":"1"}],"type":"journal_article","intvolume":"       116","citation":{"apa":"Petersen, L., &#38; Pellicciotti, F. (2011). Spatial and temporal variability of air temperature on a melting glacier: Atmospheric controls, extrapolation methods and their effect on melt modeling, Juncal Norte Glacier, Chile. <i>Journal of Geophysical Research: Atmospheres</i>. American Geophysical Union. <a href=\"https://doi.org/10.1029/2011jd015842\">https://doi.org/10.1029/2011jd015842</a>","ista":"Petersen L, Pellicciotti F. 2011. Spatial and temporal variability of air temperature on a melting glacier: Atmospheric controls, extrapolation methods and their effect on melt modeling, Juncal Norte Glacier, Chile. Journal of Geophysical Research: Atmospheres. 116(D23), D23109.","ieee":"L. Petersen and F. Pellicciotti, “Spatial and temporal variability of air temperature on a melting glacier: Atmospheric controls, extrapolation methods and their effect on melt modeling, Juncal Norte Glacier, Chile,” <i>Journal of Geophysical Research: Atmospheres</i>, vol. 116, no. D23. American Geophysical Union, 2011.","ama":"Petersen L, Pellicciotti F. Spatial and temporal variability of air temperature on a melting glacier: Atmospheric controls, extrapolation methods and their effect on melt modeling, Juncal Norte Glacier, Chile. <i>Journal of Geophysical Research: Atmospheres</i>. 2011;116(D23). doi:<a href=\"https://doi.org/10.1029/2011jd015842\">10.1029/2011jd015842</a>","mla":"Petersen, L., and Francesca Pellicciotti. “Spatial and Temporal Variability of Air Temperature on a Melting Glacier: Atmospheric Controls, Extrapolation Methods and Their Effect on Melt Modeling, Juncal Norte Glacier, Chile.” <i>Journal of Geophysical Research: Atmospheres</i>, vol. 116, no. D23, D23109, American Geophysical Union, 2011, doi:<a href=\"https://doi.org/10.1029/2011jd015842\">10.1029/2011jd015842</a>.","short":"L. Petersen, F. Pellicciotti, Journal of Geophysical Research: Atmospheres 116 (2011).","chicago":"Petersen, L., and Francesca Pellicciotti. “Spatial and Temporal Variability of Air Temperature on a Melting Glacier: Atmospheric Controls, Extrapolation Methods and Their Effect on Melt Modeling, Juncal Norte Glacier, Chile.” <i>Journal of Geophysical Research: Atmospheres</i>. American Geophysical Union, 2011. <a href=\"https://doi.org/10.1029/2011jd015842\">https://doi.org/10.1029/2011jd015842</a>."},"date_published":"2011-12-16T00:00:00Z","day":"16","article_number":"D23109","status":"public"},{"_id":"12658","article_processing_charge":"No","issue":"D3","publication_status":"published","publication":"Journal of Geophysical Research: Atmospheres","extern":"1","scopus_import":"1","language":[{"iso":"eng"}],"quality_controlled":"1","abstract":[{"lang":"eng","text":"[1] During the ablation period 2001 a glaciometeorological experiment was carried out on Haut Glacier d'Arolla, Switzerland. Five meteorological stations were installed on the glacier, and one permanent automatic weather station in the glacier foreland. The altitudes of the stations ranged between 2500 and 3000 m a.s.l., and they were in operation from end of May to beginning of September 2001. The spatial arrangement of the stations and temporal duration of the measurements generated a unique data set enabling the analysis of the spatial and temporal variability of the meteorological variables across an alpine glacier. All measurements were taken at a nominal height of 2 m, and hourly averages were derived for the analysis. The wind regime was dominated by the glacier wind (mean value 2.8 m s−1) but due to erosion by the synoptic gradient wind, occasionally the wind would blow up the valley. A slight decrease in mean 2 m air temperatures with altitude was found, however the 2 m air temperature gradient varied greatly and frequently changed its sign. Mean relative humidity was 71% and exhibited limited spatial variation. Mean incoming shortwave radiation and albedo both generally increased with elevation. The different components of shortwave radiation are quantified with a parameterization scheme. Resulting spatial variations are mainly due to horizon obstruction and reflections from surrounding slopes, i.e., topography. The effect of clouds accounts for a loss of 30% of the extraterrestrial flux. Albedos derived from a Landsat TM image of 30 July show remarkably constant values, in the range 0.49 to 0.50, across snow covered parts of the glacier, while albedo is highly spatially variable below the zone of continuous snow cover. These results are verified with ground measurements and compared with parameterized albedo. Mean longwave radiative fluxes decreased with elevation due to lower air temperatures and the effect of upper hemisphere slopes. It is shown through parameterization that this effect would even be more pronounced without the effect of clouds. Results are discussed with respect to a similar study which has been carried out on Pasterze Glacier (Austria). The presented algorithms for interpolating, parameterizing and simulating variables and parameters in alpine regions are integrated in the software package AMUNDSEN which is freely available to be adapted and further developed by the community."}],"volume":109,"citation":{"ista":"Strasser U, Corripio J, Pellicciotti F, Burlando P, Brock B, Funk M. 2004. Spatial and temporal variability of meteorological variables at Haut Glacier d’Arolla (Switzerland) during the ablation season 2001: Measurements and simulations. Journal of Geophysical Research: Atmospheres. 109(D3), D03103.","apa":"Strasser, U., Corripio, J., Pellicciotti, F., Burlando, P., Brock, B., &#38; Funk, M. (2004). Spatial and temporal variability of meteorological variables at Haut Glacier d’Arolla (Switzerland) during the ablation season 2001: Measurements and simulations. <i>Journal of Geophysical Research: Atmospheres</i>. American Geophysical Union. <a href=\"https://doi.org/10.1029/2003jd003973\">https://doi.org/10.1029/2003jd003973</a>","chicago":"Strasser, Ulrich, Javier Corripio, Francesca Pellicciotti, Paolo Burlando, Ben Brock, and Martin Funk. “Spatial and Temporal Variability of Meteorological Variables at Haut Glacier d’Arolla (Switzerland) during the Ablation Season 2001: Measurements and Simulations.” <i>Journal of Geophysical Research: Atmospheres</i>. American Geophysical Union, 2004. <a href=\"https://doi.org/10.1029/2003jd003973\">https://doi.org/10.1029/2003jd003973</a>.","short":"U. Strasser, J. Corripio, F. Pellicciotti, P. Burlando, B. Brock, M. Funk, Journal of Geophysical Research: Atmospheres 109 (2004).","mla":"Strasser, Ulrich, et al. “Spatial and Temporal Variability of Meteorological Variables at Haut Glacier d’Arolla (Switzerland) during the Ablation Season 2001: Measurements and Simulations.” <i>Journal of Geophysical Research: Atmospheres</i>, vol. 109, no. D3, D03103, American Geophysical Union, 2004, doi:<a href=\"https://doi.org/10.1029/2003jd003973\">10.1029/2003jd003973</a>.","ama":"Strasser U, Corripio J, Pellicciotti F, Burlando P, Brock B, Funk M. Spatial and temporal variability of meteorological variables at Haut Glacier d’Arolla (Switzerland) during the ablation season 2001: Measurements and simulations. <i>Journal of Geophysical Research: Atmospheres</i>. 2004;109(D3). doi:<a href=\"https://doi.org/10.1029/2003jd003973\">10.1029/2003jd003973</a>","ieee":"U. Strasser, J. Corripio, F. Pellicciotti, P. Burlando, B. Brock, and M. Funk, “Spatial and temporal variability of meteorological variables at Haut Glacier d’Arolla (Switzerland) during the ablation season 2001: Measurements and simulations,” <i>Journal of Geophysical Research: Atmospheres</i>, vol. 109, no. D3. American Geophysical Union, 2004."},"status":"public","article_number":"D03103","day":"16","date_published":"2004-02-16T00:00:00Z","type":"journal_article","intvolume":"       109","publication_identifier":{"issn":["0148-0227"]},"article_type":"original","year":"2004","month":"02","keyword":["Paleontology","Space and Planetary Science","Earth and Planetary Sciences (miscellaneous)","Atmospheric Science","Earth-Surface Processes","Geochemistry and Petrology","Soil Science","Water Science and Technology","Ecology","Aquatic Science","Forestry","Oceanography","Geophysics"],"date_created":"2023-02-20T08:18:57Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_updated":"2023-02-20T08:40:21Z","title":"Spatial and temporal variability of meteorological variables at Haut Glacier d'Arolla (Switzerland) during the ablation season 2001: Measurements and simulations","author":[{"full_name":"Strasser, Ulrich","first_name":"Ulrich","last_name":"Strasser"},{"last_name":"Corripio","full_name":"Corripio, Javier","first_name":"Javier"},{"full_name":"Pellicciotti, Francesca","first_name":"Francesca","id":"b28f055a-81ea-11ed-b70c-a9fe7f7b0e70","last_name":"Pellicciotti"},{"last_name":"Burlando","first_name":"Paolo","full_name":"Burlando, Paolo"},{"full_name":"Brock, Ben","first_name":"Ben","last_name":"Brock"},{"last_name":"Funk","first_name":"Martin","full_name":"Funk, Martin"}],"oa_version":"None","doi":"10.1029/2003jd003973","publisher":"American Geophysical Union"}]