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8 results for “icefield”
Thickness map of the Patagonian Icefields
<p>Ice thickness field for the Patagonian icefields relying on mass-conservation approach, which assimilates both glacier retreat data as well as an abundant record of direct thickness measurements. The thickness map has a time stamp of 2000. This map is provided together with error estimates and the basal topography beneath the icefields based on c-SRTM (v2.1) (Farr, T. et al. The Shuttle Radar Topography Mission. Reviews of Geophysics 45 (2007), http://dx.doi.org/10.1029/2005RG000183.)</p>
Supplementary Data to journal publication on 'The Foundations of the Patagonian Icefields'
<p>Partitioning and comparison of ice discharge estimates from the the Patagonian Icefields comprising associated uncertainties. For further details please refer to the notes in the individual files and/or consult the associated publication entitled 'The Foundations of the Patagonian Icefields' published in Communications Earth & Environment.</p>
Ground Penetrating Radar survey of San Quintin glacier, Northern Patagonia Icefield
<p>Measured ice thickness, Residual Bedrock Reflection Power (BRP) and Internal Reflection Power (IRP) of San Quitin glacier, Northern Patagonia Icefield.</p> <p> </p> <p>Data for the preprint "Frontal collapse of San Quintín glacier (Northern Patagonia Icefield), the last piedmont glacier lobe in the Andes" in review for The Cryosphere (https://doi.org/10.5194/tc-2023-10)</p> <p> </p>
Ice speed and elevation change rate of the Patagonian icefields
<p>These are the dataset of ice speed magnitude, error, number of valid velocity maps and elevation change rate of the Patagonian icefields (PIs) presented in the study. Please refer the main text for further technical information or directly ask the corresponding author.</p> <p>gererated April 2020, M. Minowa<br> updated Septempber 2020, M. Minowa</p> <p>===================================================================</p> <p>1. Annual velocity magnitude<br> File name: PIs_mag_utm18n_yyyy.tif<br> Format: geotiff<br> Coordinates: utm 18 North <br> No data value: -9999</p> <p><br> 2. Number of valid velocity maps<br> File name: PIs_cnt_utm18n_yyyy.tif<br> Format: geotiff<br> Coordinates: utm 18 North </p> <p><br> 3. Annual velocity error<br> File name: PIs_er_utm18n_yyyy.tif<br> Format: geotiff<br> Coordinates: utm 18 North <br> No data value: -9999 </p> <p>4. Elevation change rate map between 2000 and 2019<br> File name: PIs_dhdt_utm18s_2000-2019.tif<br> Format: Geotiff<br> Coordinates: utm 18 South<br> No data value: -9999</p> <p>5. Number of valid DEMs<br> File name: PIs_dhdt_cnt_utm18s_2000-2019.tif<br> Format: Geotiff<br> Coordinates: utm 18 South<br> No data value: -9999</p> <p>6. Systematic error map in the elevation change rate<br> File name: PIs_dhdt_mu_utm18s_2000-2019.tif<br> Format: Geotiff<br> Coordinates: utm 18 South<br> No data value: -9999</p> <p>7. Random error map in the elevation change rate<br> File name: PIs_dhdt_sigma_utm18s_2000-2019.tif<br> Format: Geotiff<br> Coordinates: utm 18 South<br> No data value: -9999<br> </p>
Climatic mass balance of the Cordillera Darwin Icefield (2000-2023), Tierra del Fuego, Chile
<p>This dataset contains the annual averages of the climatological input and the modelled climatic mass balance of the Cordillera Darwin Icefield, Tierra del Fuego. The climatological input is calculated by statistically downscaling ERA5 reanalysis data to weather stations across the Cordillera Darwin via Quantile Mapping. The precipitation is simulated with an orographic precipitation model. Global radiation is simulated with a radiation model. The applied climatic mass balance model is the coupled snowpack and ice surface energy and mass balance model (COSIPY).</p>
Projected surface mass balance of the Juneau Icefield, Southeast Alaska (2030 to 2060, RCP8.5)
<p>This dataset contains the modelled projected surface mass balance of the Juneau Icefield in Southeast Alaska for two global climate models (GFDL-CM3 and NCAR-CCSM4) for the RCP8.5 emissions scenario from 2030 to 2060. The simulated surface mass balance was produced using COSIPY - a coupled snowpack and ice surface energy and mass balance model. The input climate data was originally dynamically downscaled in Lader et al., (2020, <em>J. Appl. Meteor. Climatol.)</em></p> <p>This data supplements the manuscript "<em>Surface mass balance modelling of the Juneau Icefield highlights the potential for rapid ice loss by the mid-21st century</em>" submitted to the Journal of Glaciology. </p>
Past surface mass balance of the Juneau Icefield, Southeast Alaska (1980 to 2019)
<p>This dataset contains the modelled past surface mass balance of the Juneau Icefield in Southeast Alaska for three models. A reanalysis model, CFSR from 1980 to 2019. And two global climate models (GFDL-CM3 and NCAR-CCSM4) from 1980 to 2010. The simulated surface mass balance was produced using COSIPY - a coupled snowpack and ice surface energy and mass balance model. The input climate data was originally dynamically downscaled in Lader et al., (2020, <em>J. Appl. Meteor. Climatol.)</em></p> <p>This data supplements the manuscript "<em>Surface mass balance modelling of the Juneau Icefield highlights the potential for rapid ice loss by the mid-21st century</em>" submitted to the Journal of Glaciology. </p>
Ice thickness and bed elevation of the Northern and Southern Patagonian Icefields
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