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10 results for “ice cliffs”
Model outputs to "Langtang Ice Cliff Modelling Study"
<p>This dataset contains all the model results of our study "Supraglacial ice cliffs can substantially increase the mass loss of debris-covered glaciers".</p> <p>The zip-file contains one main folder: "Cliffmodel_Results" (produced using the 3D-backwasting ice cliff model from Buri et al., 2016b, Buri & Pellicciotti, 2018).</p> <p>More raw data upon request.</p> <p> </p> <p><strong>Folder structure of "Langtang_IceCliffModellingStudy.7z":</strong></p> <p>───Cliffmodel_Results<br> ├───LangshishaGlacier<br> │ ├───Output_Cliffs_Langshisha2014_A_3m<br> │ ├───Output_Cliffs_Langshisha2014_B_3m<br> │ ├───Output_Cliffs_Langshisha2014_C_3m<br> │ ├───Output_Cliffs_Langshisha2014_D_3m<br> │ ├───Output_Cliffs_Langshisha2014_E_3m<br> │ ├───Output_Cliffs_Langshisha2014_F_3m<br> │ ├───Output_Cliffs_Langshisha2014_G_3m<br> │ └───Output_Cliffs_Langshisha2014_H_3m<br> ├───LangtangGlacier<br> │ ├───Output_Cliffs_Langtang2014_A_3m<br> │ ├───Output_Cliffs_Langtang2014_B_3m<br> │ ├───Output_Cliffs_Langtang2014_C_3m<br> │ ├───Output_Cliffs_Langtang2014_D_3m<br> │ ├───Output_Cliffs_Langtang2014_E_3m<br> │ ├───Output_Cliffs_Langtang2014_F_3m<br> │ ├───Output_Cliffs_Langtang2014_G_3m<br> │ ├───Output_Cliffs_Langtang2014_H_3m<br> │ ├───Output_Cliffs_Langtang2014_I_3m<br> │ ├───Output_Cliffs_Langtang2014_J_3m<br> │ ├───Output_Cliffs_Langtang2014_K_3m<br> │ ├───Output_Cliffs_Langtang2014_L_3m<br> │ ├───Output_Cliffs_Langtang2014_M_3m<br> │ ├───Output_Cliffs_Langtang2014_N_3m<br> │ ├───Output_Cliffs_Langtang2014_O_3m<br> │ ├───Output_Cliffs_Langtang2014_P_3m<br> │ ├───Output_Cliffs_Langtang2014_Q_3m<br> │ ├───Output_Cliffs_Langtang2014_R_3m<br> │ ├───Output_Cliffs_Langtang2014_S_3m<br> │ └───Output_Cliffs_Langtang2014_T_3m<br> ├───LirungGlacier<br> │ ├───Output_Cliffs_Lirung2014_A_3m<br> │ │ └───intermediateOutput<br> │ └───Output_Cliffs_Lirung2014_B_3m<br> │ └───intermediateOutput<br> └───ShalbachumGlacier<br> ├───Output_Cliffs_Shalbachum2014_A_3m<br> │ └───intermediateOutput<br> ├───Output_Cliffs_Shalbachum2014_B_3m<br> │ └───intermediateOutput<br> ├───Output_Cliffs_Shalbachum2014_C_3m<br> │ └───intermediateOutput<br> ├───Output_Cliffs_Shalbachum2014_D_3m<br> │ └───intermediateOutput<br> └───Output_Cliffs_Shalbachum2014_E_3m<br> └───intermediateOutput<br> </p> <p> </p> <p><strong>File structure within Cliffmodel_Results \ <GLACIERNAME> \ Output_Cliffs_<GLACIERNAME>2014_A_3m:</strong></p> <p><em>DC_Fluxes_ts<TIMESTEP1>to<TIMESTEP2>_Cliffs_<GLACIERNAME>2014_3m_ls.rda</em></p> <p>→List of 10 matrices for each energy balance flux with average diurnal cycle (rows) and cliff (columns) for specific model period </p> <p><em>geom_ts<TIMESTEP1>_Cliffs_Lirung2014_A_3m.txt</em></p> <p>→Characteristics (Elevation,Slope,Aspect,x,y,ID,VsI,VsL,Vd) for each pixel of all cliffs (specific ID) for specific model period </p> <p><em>MODELSETTINGS_GSM_<GLACIERNAME>_<GLACIERSECTOR>_22Aug_Cliffs_<GLACIER>2014.txt</em></p> <p>→Details on all modelsettings</p> <p><em>PC_Melt_ts<TIMESTEP1>to<TIMESTEP2>_Cliffs_<GLACIERNAME>2014_3m.txt</em></p> <p>→Melt values for each cliff (columns) and timestep (rows) for specific model period </p> <p><em>PC_Stats_ts<TIMESTEP1>to<TIMESTEP2>_Cliffs_<GLACIERNAME>2014_3m.txt</em></p> <p>→Summary statistics for each cliff (rows) for specific model period </p> <p><em>perPx_DC_Fluxes_ts<TIMESTEP1>to<TIMESTEP2>_Cliffs_<GLACIERNAME>2014_3m_ls.rda</em></p> <p>→List of list with per pixel diurnal cycle and standard deviation of each energy flux for specific model period </p> <p><em>SD_Fluxes_ts<TIMESTEP1>to<TIMESTEP2>_Cliffs_<GLACIERNAME>2014_3m_ls.rda</em></p> <p>→List of 10 matrices for each energy balance flux with standard deviation for each hour of the day (rows) and cliff (columns) for specific model period </p> <p><em>Stats_MeanFluxes_tts<TIMESTEP1>to<TIMESTEP2>_Cliffs_<GLACIERNAME>2014_3m.txt</em></p> <p>→Mean energy fluxes per timestep (rows) averaged over all ice cliffs</p> <p><em>Stats_NonGriddedData_ts<TIMESTEP1>to<TIMESTEP2>_Cliffs_<GLACIERNAME>2014_3m.txt</em></p> <p>→Statistics of non-distributed parameters averaged over all cliffs per timestep (rows)</p>
Data and scripts for 'Sub-seasonal variability of supraglacial ice cliff melt rates and associated processes from time-lapse photogrammetry'
<p>This repository contains three zipped elements used in the study <em>Sub-seasonal variability of supraglacial ice cliff melt rates and associated processes from time-lapse photogrammetry (</em>https://doi.org/10.5194/tc-2022-81):</p> <p>1. The time-lapse DEMs (original and flow-corrected), orthomosaics (not flow-corrected) and cliff outlines (original and flow-corrected) of the 24K and Langtang survey areas used in this study. The spatial resolution is the same as used in the analysis. These zipped files also contain a .csv file (time_selection.csv) indicating for each index (indicated in the file name) the serial date number in days (date origin January 0, 0000).</p> <p>2. The R and Python scripts (Scripts_final.zip) used to process the DEMs and orthomosaics from the time-lapse images as well as the script to calculate the slope-perpendicular melt. These scripts come with .csv and .txt files that serve as template for the required input data format.</p>
Ngozumpa Glacier Gokyo ice cliffs photographic surface model
<p>Data files of a photographic surface model of three ice cliffs exposed on the surface of the Ngozumpa Glacier ( 27°57′N, 85°42′E), Nepal, near the village of Gokyo.</p> <p>Details of how the data were produced:</p> <ul> <li>1160 full resolution JPEG images were used to make the difgital surface model (DSM)</li> <li>Photos were taken using Nikon D5000 with 100mm Tamron macro lens on 4th April 2016</li> <li>7 ground control points (GCPs) within the captured scene were used to scale and georeference the DSM</li> <li>GCPs were measured using a Trimble XH6000 with Tornado antenna as rover and a Trimble Geo7X with Zephyr antenna as a local base station</li> <li>Agisoft Photoscan (v1.26) was used to make the DSM using a SfM-MVS workflow</li> <li>Point pairs appearing in only one image pair and havoing a reprojection error grreater than 0.5 pixels were removed</li> <li>Model optimization was done using default parameters of f, b1, b2, cx, cy, k1-4, p1 and p2 and, as the lens distortion plot showed no extreme skewing or distortion, these optimization settings were accepted.</li> <li>The dense point cloud was generated using the ‘High’ quality setting with ‘Aggressive’ point filtering.</li> <li>The dense point cloud was then used directly to generate the DSM and orthomosaic at resolutions of 0.046 and 0.023 m respectively.</li> </ul> <p>Description of files:</p> <ul> <li><strong>GokyoIceCliffs_POINTCLOUD.txt:</strong> dense point cloud including the whole scene covered by the photographs. Format: x,y,z, text file, WGS 84 / UTM zone 45N.</li> <li><strong>GokyoIceCliffs_DSM_0.04.tif:</strong> 0.046 m resolution digital terrain model derived from the dense point cloud covering the area of interest including the 3 sampled ice cliffs. Format: TIFF WGS 84 / UTM zone 45N.</li> <li><strong>GokyoIceCliffs_ORTHO_0.04.tif: </strong>0.023 m resolution orthophoto covering the area of interest including the 3 sampled ice cliffs. Format: TIFF WGS 84 / UTM zone 45N.</li> </ul> <p> </p>
Data for 'Controls on Ice Cliff Distribution and Characteristics on Debris-Covered Glaciers'
<p>This dataset contains ice cliff, pond, debris, glacier and crevasse zone outlines (as shapefiles) derived for the study 'Controls on Ice Cliff Distribution and Characteristics on Debris-Covered Glaciers'.</p> <p>They were outlined from 14 Pléiades multi-spectral images (see Methods and tables in corresponding manuscript and SI) acquired at the dates indicated in the corresponding folder names.</p> <p>The majority of the Pléiades stereo-pairs used were provided by Etienne Berthier via the Pléiades Glacier Observatory (PGO) initiative of the French Space Agency (CNES). The remaining images were acquired through the CNES ISIS Programme. </p>
McMurdo Dry Valleys Garwood Ice Cliff Meteorological Station Monthly Averages, 2012-
 As part of the Long Term Ecological Research in the McMurdo Dry Valleys of Antarctica, meteorological data was collected from various locations throughout Beacon, Taylor, Wright and Victoria Valleys. These files contain averages derived from data for the Garwood Ice Cliff meteorology station. This station reported data for about a year, during 2011. On January 10, 2012 the station was being transferred to the custody of the MCM LTER program by Joe Levy (UT), completing of the handover on the Austral summer of 2014. The GAFM station was moved ~5 m from its original site in 2013 (out of the stream bed). GAFM no longer used, dismantled.
McMurdo Dry Valleys Garwood Ice Cliff Meteorological Station Measurements, 2012-
   As part of the Long Term Ecological Research in the McMurdo Dry Valleys of Antarctica, meteorological data was collected from various locations throughout Beacon, Taylor, Wright and Victoria Valleys. These files contain data for the Garwood Ice Cliff meteorology  station. This station reported data for about a year, during 2011. On January 10, 2012 the station was being transferred to the custody of the MCM LTER program by Joe Levy (UT), completing of the handover on the Austral summer of 2014. The GAFM station was moved ~5 m from its original site in 2013 (out of the stream bed).     The Garwood ice cliff met station ceased operations in 2013.   Â
McMurdo Dry Valleys Garwood Ice Cliff Meteorological Station Daily Averages, 2012-
As part of the Long Term Ecological Research in the McMurdo Dry Valleys of Antarctica, meteorological data was collected from various locations throughout Beacon, Taylor, Wright and Victoria Valleys. These files contain data for the Garwood Ice Cliff meteorology station. This station reported data for about a year, during 2011. On January 10, 2012 the station was being transferred to the custody of the MCM LTER program by Joe Levy (UT), completing of the handover on the Austral summer of 2014. The GAFM station was moved ~5 m from its original site in 2013 (out of the stream bed).
Data Products associated with "Stream hydrology controls on ice cliff evolution and survival on debris-covered glaciers"
<p>Data products from the study "Stream hydrology controls on ice cliff evolution and survival on debris-covered glaciers," by Petersen et al, submitted September 2023 to Earth Surface Dynamics.</p>
STREAMICE code and inputs for "The West Antarctic Ice Sheet may not be vulnerable to Marine Ice Cliff Instability during the 21st Century"
<p>This repository contains all inputs and code to carry out the STREAMICE calving experiments run for the manuscript "The West Antarctic Ice Sheet may not be vulnerable to Marine Ice Cliff Instability during the 21st Century" using the modelling framework MITgcm.</p> <p>MITgcm-front_retreat/ contains a branch of the MITgcm code that enables calving front advance and retreat in the STREAMICE model, and is a branch of checkpoint 68d. Please see https://github.com/MITgcm/MITgcm/blob/master/LICENSE.txt for the MITgcm open source license detail.</p> <p>code/ contains experiment-specific code for the runs detailed in the manuscript</p> <p>input_fwd/ contains all binary and parameter input files for the runs detailed in the manuscript</p> <p>archer_scripts/ contains shell scripts written for the ARCHER2 UK supercomputer to demonstrate how the model is compiled</p> <p> </p> <p> </p>
Supporting videos of (ice cliffs of) Lirung glacier
<p>Supplementary material for: <strong><em>Using 3D turbulence-resolving simulations to understand the impact of surface properties on the energy balance of a debris-covered glacier, </em></strong>PNJ Bonekamp, CC van Heerwaarden, JF Steiner and WW Immerzeel, submitted to The Cryosphere.</p> <p>List of movies: <br> Icecliff_movie_qt.gif: specific moisture at ice cliff<br> Icecliff_movie_th.gif : potential temperature at ice cliff<br> Icecliff_movie_UV.gif: wind speed at ice cliff<br> Movie_conductiveflux.gif: the conductive heat flux at the surface<br> vertical_cross_movie_q.gif: specific moisture along the xz cross section<br> vertical_cross_movie_thl.gif: potential temperature along the xz cross section<br> vertical_cross_movie_UV.gif: wind speed along the xz cross section</p>
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