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19 results for “Surface mass balance”
Dataset for "Remapping of Greenland ice sheet surface mass balance anomalies for large ensemble sea-level change projections"
<p>This dataset is used to reproduce the results presented in the following publication:</p> <p>Goelzer, H., Noel, B. P. Y., Edwards, T. L., Fettweis, X., Gregory, J. M., Lipscomb, W. H., van de Wal, R. S. W., and van den Broeke, M. R.: Remapping of Greenland ice sheet surface mass balance anomalies for large ensemble sea-level change projections, The Cryosphere Discuss., https://doi.org/10.5194/tc-2019-188, in review, 2019.</p> <p> </p>
MARv3.10 outputs: What is the Surface Mass Balance of Antarctica? An Intercomparison of Regional Climate Model Estimates
<p>MARv3.10 outputs used in:</p> <p><em>Mottram, R., Hansen, N., Kittel, C., van Wessem, M., Agosta, C., Amory, C., Boberg, F., van de Berg, W. J., Fettweis, X., Gossart, A., van Lipzig, N. P. M., van Meijgaard, E., Orr, A., Phillips, T., Webster, S., Simonsen, S. B., and Souverijns, N.: What is the Surface Mass Balance of Antarctica? An Intercomparison of Regional Climate Model Estimates, The Cryosphere Discuss. [preprint], https://doi.org/10.5194/tc-2019-333, accepted, 2020.</em></p> <ul> <li>MARv3.10 forced by ERA-Interim outputs with monthly values of SMB and components (kg m<sup>-2</sup> month<sup>-1</sup>), and (near-) surface temperature (°C) over the Antarctic ice sheet (1981--2018)</li> <li>Grid file used in MAR simulation</li> </ul> <p>Be carreful that the unit metadata in the netcdf files from SMB and its components are uncorrect. <strong>Values are in kg m<sup>-2</sup> month<sup>-1</sup></strong> instead of kg m<sup>-2</sup> day<sup>-1</sup>.<br> <br> If you need other variables or output frequencies from MAR, write me (c2kittel@gmail.com) and I will be glad to help you. I will also be happy to share the scripts I have developed to analyse the outputs and make the figures in this paper if needed. Please cite the paper if you use these MAR outputs. However, note that these outputs are now considered as deprecated since new outputs using a more recent model version (MARv3.11) and forcing (ERA5) have been published (see Kittel et al., 2021: https://tc.copernicus.org/articles/15/1215/2021/).<br> <br> Data usage notice:</p> <p>If you use any of these results, please acknowledge the work of the people involved in producing them. Acknowledgements should have language similar to the below that contained informations related to MAR. In order to document MAR scientific impact and enable ongoing support of the model, users are likely encouraged to contact C. Kittel and C. Agosta to add their works in the list of MAR-related publications. </p> <p>"We thank the MAR team which make available the model outputs, as well agencies (F.R.S - FNRS, CÉCI, and the Walloon Region) that provided computational resources for MAR simulations."</p> <p>You should also refer to and cite the following paper:</p> <p><em>Mottram, R., Hansen, N., Kittel, C., van Wessem, M., Agosta, C., Amory, C., Boberg, F., van de Berg, W. J., Fettweis, X., Gossart, A., van Lipzig, N. P. M., van Meijgaard, E., Orr, A., Phillips, T., Webster, S., Simonsen, S. B., and Souverijns, N.: What is the Surface Mass Balance of Antarctica? An Intercomparison of Regional Climate Model Estimates, The Cryosphere Discuss. [preprint], https://doi.org/10.5194/tc-2019-333, accepted, 2020.</em></p>
Downscaled surface mass balance in Antarctica: impacts of subsurface processes and large-scale atmospheric circulation
<p>Here is the surface mass balance calculated from a offline subsurface model, that is used in the paper Downscaled surface mass balance in Antarctica: impacts of subsurface processes and large-scale atmospheric circulation.<br> More data are available by contacting nichsen@space.dtu.dk</p>
Monthly accumulated sublimation and yearly accumulated surface mass balance (SMB) components RACMO model simulations for Antarctica on 27km grid for 2000-2012
<p>Monthly accumulated (denoted monthlyS) sublimation components and yearly accumulated (denoted yearlyS) surface mass balance (SMB) components for Antarctica (ANT) on 27 km horizontal grid produced by RACMO model are presented in this dataset for the year 2000-2012. The dataset consists of data from three simulations named, NODRIFT, Rp3, and RpNew. NODRIFT represents the run with no blowing snow sublimation, Rp3 corresponds to version of the blowing snow model with simplifications, RpNew corresponds to the advanced version with new updates to the blowing snow model in RACMO. Details of the simulations can be found in the associated paper : <a title="Contribution of blowing snow sublimation to the surface mass balance of Antarctica" href="https://doi.org/10.5194/egusphere-2024-116" target="_blank" rel="noopener">https://doi.org/10.5194/egusphere-2024-116</a>. The data includes yealy accumulated SMB components including SMB, snow melt, refreezing, precipiation, runoff, blowing snow erosion, surface sublimation, and blowing snow sublimation, the data also includes yearly averaged (denoted yearlyA) . Furthermore, the data includes monthly accumulated sublimation components of surface sublimation (subl), and blowing snow sublimation (suds). </p>
Antarctic surface mass balance with the regional climate model MAR (1979–2015)
<p>Outputs of the regional climate model MAR v3.6.41 for Antarctica, resolution 35km + source code</p> <p>===========================================</p> <p>Cécile Agosta, 23 Jan 2019 </p> <p>cecile.agosta@gmail.com</p> <p>===========================================</p> <p>Grid specifications are given in MAR-ant35km-grid.nc (projection : EPSG 3031).</p> <p>* State variables are averages of daily means:</p> <p> TT > temperature (°C)</p> <p> ZZ > height above sea level (m)</p> <p> UU, VV > x-wind and y-wind in the stereographic grid (m s-1)</p> <p> UV > wind speed (m s-1)</p> <p>State variables ending with z (e.g. UUz) are interpolated on fixed altitude levels above the ground.</p> <p>State variables ending with p (e.g. UUp) are interpolated on fixed pressure levels.</p> <p>* SMB components are summed: kg m-2 month-1 for montly files, kg m-2 year-1 for annual files, kg m-2 year-1 for clim files</p> <p> snf > snowfall</p> <p> rnf > rainfall</p> <p> rof > run-off</p> <p> sbl > sublimation/condensation</p> <p> smb = snf + rnf - sbl - rof</p> <p> mlt > snowmelt</p> <p> rfz > refreezing</p> <p>If you use this data, please cite the final accepted version of this article:</p> <p>Agosta C., Amory C., Kittel C., Orsi A., Favier V., Gallée H., van den Broeke M.R., Lenaerts J.T., van Wessem J.M., & Fettweis X. (in review, 2018). Estimation of the Antarctic surface mass balance using MAR (1979-2015) and identification of dominant processes. <em>The Cryosphere Discussions</em>, 1–22, <a href="https://doi.org/10.5194/tc-2018-76">doi:10.5194/tc-2018-76</a>.</p> <p>Please contact me if you need other outputs (variables/daily or hourly time steps)</p>
Greenland monthly surface mass balance 1840-2012
<p>This surface mass balance (SMB) product is based on Box (2013), with refinements described by Schlegel et al. (2016), Appendix. It includes monthly estimates of accumulation and melt, as well as estimates for SMB error for the historical period (1960-2012).</p> <p>It is the results of a calibration of observational data to regional climate model (RCM) output, in this case RACMO2.3 (Noël et al., 2016). The calibration for temperature (T) and SMB components is based on a 53-year overlap period (1960-2012). Note that the overlap period for the calibration of snow accumulation rate is shorter, since ice core data availability drops after 1999. Calibration is made using linear regression coefficients for 5 km grid cells that match the average of the reconstruction to RACMO2.3. The RACMO2.3 output are resampled and reprojected from the native 0.1 deg (~10 km) grid to a 5 km grid better resolving areas where sharp gradients occur, especially near the ice margin where mass fluxes are largest. </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>
Surface mass balance of the Monte Sarmiento Massif (2000-2022), Tierra del Fuego, Chile.
<p>This dataset contains the climatological input and the modelled surface mass balance of the Monte Sarmiento Massif, Tierra del Fuego, calculated with four different surface mass balance models. The climatological input is calculated by statistically downscaling ERA5 reanalysis data to a weather station at Schiaparelli Glacier via Quantile Mapping. The precipitation is simulated with an orographic precipitation model. The four applied surface mass balance models are a) a positive degree day model (PDD), b) a simplified energy balance model with potential radiation (SEBGpot) and c) with actual radiation including cloud cover and shading (SEBG), and d) a coupled snowpack and ice surface energy and mass balance model (COSIPY).</p>
Dataset - "Ice core evidence for a 20th century increase in surface mass balance in coastal Dronning Maud Land, East Antarctica"
<p>We provide in this dataset the isotopic and ionic records from a 120 m-long ice core drilled at the summit of Derwael ice rise (70°14'44.88'' S, 26°20'5.64'' E) situated in coastal Dronning Maud Land, East Antarctica. Ions concentrations (Na<sup>+</sup>, MSA, Cl<sup>-</sup>, SO<sub>4</sub><sup>2-</sup> and NO<sub>3</sub><sup>-</sup>) and water stable isotopes (δ<sup>18</sup>O, δD and d-excess) are presented for the top 103 meters (corresponding to 1815 and the Tambora eruption) with a continuous record for the water stable isotopes and discontinuous sections for ions concentrations. A complementary database “Annual layer thicknesses and age-depth (oldest estimate) of Derwael Ice Rise (IC12), Dronning Maud Land, East Antarctica” with age model and annual layer thickness is available at https://doi.org/10.1594/PANGAEA.857574 and the companion paper is Philippe et al., 2016 (“Ice core evidence for a 20th century increase in surface mass balance in coastal Dronning Maud Land, East Antarctica”, https://doi.org/10.5194/tc-10-2501-2016).</p>
Fifty years of instrumental surface mass balance observations at Vostok Station, central Antarctica
<p>The database of snow buildup, density and accumulation rate values as observed at the accumulation-stake farms in the vicinity of Vostok station (central East Antarctica) since January 1970.</p> <p>The reference for the data: Ekaykin A.A., Lipenkov V.Ya., Tebenkova N.A. Fifty years of instrumental surface mass balance observations at Vostok Station, central Antarctica. - J. of Glaciology, 2023, 1–13. https://doi.org/10.1017/jog.2023.53.</p> <p> </p>
Nitrate δ15N values and surface mass balance reconstructions from East Antarctica
<p>Geographic information, surface mass balance (SMB) data, and sub-photic zone (>0.3 m) nitrate concentration and nitrogen isotopic composition (δ15NNO3) for 135 sites across East Antarctica. This database was used to examine and define the relationship between δ15NNO3 and SMB in Antarctica as part of the SCADI (Snow Core Accumulation from Delta-15N Isotopes) and EAIIST (East Antarctic International Ice Sheet Traverse) projects. Of these 135 sites, 92 are newly reported here while the other site data were previously published and are cited accordingly. Snow bearing nitrate was sampled from snow pits and firn/ice cores at different dates depending on the original scientific campaign, but predominately between 2010 and 2020, with the earliest sampling occurring in 2004. Nitrate was later extracted from the snow, concentrated, and analyzed for δ15NNO3. Surface mass balance data comes from a combination of previous ground-based observations (e.g., stakes, ice core data) and the output from Modèle Atmosphérique Régional version 3.6.4 with European Centre for Medium-Range Weather Forecasts “Interim” re-analysis data (ERA-interim) data, adjusted for observed model SMB biases. Elevation data were extracted from the Reference Elevation Model of Antarctica (REMA, <a href="https://doi.org/10.5194/tc-13-665-2019">https://doi.org/10.5194/tc-13-665-2019</a>).</p> <p>Also contains nitrate concentration and isotopic (δ15NNO3) data, ice density, and surface mass balance estimates from the ABN1314-103 ice core. This 103 m long core was drilled beginning on 07 January 2014 as one of three ice cores at Aurora Basin North, Antarctica (-71.17, 111.37, 2679 m.a.s.l), in the 2013-2014 field season. The age-depth model for ABN1314-103 was matched through ion profiles from an annually-resolved model (ALC01112018) originally developed for one of the other ABN cores through seasonal ion and water isotope cycles and constrained by volcanic horizons. Each 1 m segment of the core was weighed and measured for ice density calculations, and then sampled for nitrate at 0.33 m resolution. Nitrate concentrations were taken on melted ice aliquots with ion chromatography, while isotopic analysis was achieved through bacterial denitrification and MAT 253 mass spectrometry after concentrating with anionic resin. Using the density data and the age-depth model’s dates for the top and bottom of each 1 m core segment, we reconstructed a history of surface mass balance changes as recorded in ABN1314-103. Additionally, we also estimated the effect of upstream topographic changes on the ice core’s surface mass balance record through a ground penetrating radar transect that extended 11.5 km against the direction of glacial ice flow. The modern SMB changes along this upstream transect were linked to ABN1314-103 core depths by through the local horizontal ice flow rate (16.2 m a-1) and the core’s age-depth model, and included here for comparative analysis. </p>
Antarctic surface climate and surface mass balance in the Community Earth System Model version 2 (1850-2100) - AWS data
<p>This Antarctica AWS temperature and wind speed dataset was compiled by Alexandra Gossart and Niels Souverijns (<a href="https://doi.org/10.1175/JCLI-D-19-0030.1">https://doi.org/10.1175/JCLI-D-19-0030.1</a>).</p>
Ice thickness and surface velocities for the manuscritpt Mass balance and stability of ice tongues in the Western Ross Sea
<p>The data set contains:</p> <p>ICESat-2 derived point ice thickness for 9 ice tongues in csv format</p> <p>Surface average velocities derived from the ASF Vertex platform on demand HYP3 autoRIFT velocity product for 9 ice tongues.</p>
A Factor Two Difference in 21st-Century Greenland Ice Sheet Surface Mass Balance Projections from Three Regional Climate Models for a Strong Warming Scenario (SSP5-8.5)
<p>1km regridded Greenland Ice Sheet SMB / Runoff / Melt projection until 2100. Projections from MAR, RACMO, HIRHAM forced by CESM2 (SSP5-8.5).</p>
MAR-ERA5 reanalysis of the Arctic land ice surface mass balance between 1950 and 2020
<p>This archive provides monthly outputs of the surface mass balance variables over the Arctic land ice, as modeled by MAR forced by ERA5.</p><p>These outputs were produced as part of the publication "Maure, D., Kittel,C., Lambin, C., Delhasse, A. and Fettweis, X.: "Spatially heterogeneous effect of climate warming<br>on the Arctic land ice", The Cryosphere, accepted. (2023). The data comes from the 6km domains presented in Fig.1 of the study, reinterpolated to a single Pan-Arctic 6km grid.</p><p> </p><p>Contact: Damien Maure </p><p>damien.maure@uliege.be</p><p> </p><p>The MAR code is available at https://gitlab.com/Mar-Group/MARv3. The version used to generate this dataset is tagged as v3.11.5.</p><p>About the dataset:<br>It contains one file per year</p><p>MAR_arctic_ERA5_v1_<strong>*year*</strong>.nc</p><p>MAR311</p><p>SMB: surface mass balance<br>SF: snowfall<br>RF: rainfall<br>RU: runoff<br>ME: melt<br>SU: sublimation - deposition (positive values indicates mass losses through sublimation)<br>(units: mm we day)</p><p> </p><p> </p>
Continuous snow temperature profiles from the Snow Ice Mass Balance Apparatus (SIMBA) (level 1 Raw), Study of Precipitation, the Lower Atmosphere and Surface for Hydrometeorology (SPLASH), November 2022-June 2023
<p>Raw (Level 1) measurements from the Snow Ice Mass Balance Apparatus (SIMBA) deployed at the Avery Picnic site (~ 38°58.345' N, 106°59.811' W) during the Study of Precipitation, the Lower Atmosphere, and Surface for Hydrometeorology (SPLASH) campaign near Gothic, Colorado, from November 2021 through June 2023. The SIMBA, originally designed for observing the mass balance of sea ice, is comprised of a thermistor chain with 2 cm spacing (Jackson et al., 2013). This system was configured for terrestrial snowpack by the manufacturer, SAMS Enterprise, to the specifications for SPLASH. The chain was installed suspended from a tripod and fixed to a rigid plastic bar near in time to the onset of snowpack in November 2022. The lowest 10 cm of the chain were buried within the soil. The top of the chain reached approximately 180 cm above the soil surface and snow was permitted to accumulate around the chain throughout the winter of 2022-2023. In the files, negative values of the "height" vector are below the soil surface and positive levels are above, which may be either snow or air depending on the snow depth. The system also uses a low-power heating cycle to measure thermistor's temperature response time for aiding in determining material interfaces: see Jackson et al. (2013) for details. </p><p>There are several cautions to be aware of when using these data. The data has been ingested into daily netCDF and metadata (in attributes) have been provided but no quality control has been carried out on this raw version of the data set. From 1 November through 22 December 2022, the sensor obtained profiles every 10 min after which corruption of the configuration file reverted the profiles to every 6 hours (0, 6, 12, and 18 UTC). After 1 January a problem in the firmware caused the system to lose connection to the time-synching GPS network and therefore the clock drifted from January through June 2023 (the maximum potential time stamping error is likely < 81 sec). Finally, from 23 March through 4 April 2023, the depth of the snow at the location of the sensor was deeper than 180 cm and thus measurements in the upper part of the snowpack were not observed then.</p><p>Jackson, K., J. Wilkinson, T. Maksym, D. Meldrum, J. Beckers, C. Haas, and D. Mackenzie (2013) A novel and low-cost sea ice mass balance buoy. Journal of Atmosphere and Oceanic Technology, 30(11), 2676-2688, https://doi.org/10.1175/JTECH-D-13-00058.1.</p>
Using a multi-layer snow model for transient paleo studies: surface mass balance evolution during the Last Interglacial
<p>This archive provides source data of figures in the main text of the manuscript "Using a multi-layer snow model for transient paleo studies: surface mass balance evolution during the Last Interglacial".</p>
High Mountain Asia 2 m DEM, Surface Velocity, and Lagrangian Surface Mass Balance for Select Debris Covered Glaciers V001
This High Mountain Asia data set contains 2 m resolution digital elevation models (DEMs), surface velocities, surface mass balance (SMB) rates, and SMB uncertainties for six debris-covered glaciers in Nepal. SMB rate is estimated by applying a Lagrangian specification to DEMs derived from very-high-resolution optical stereo imagery acquired by Maxar Technologies satellites WorldView-1, WorldView-2, WorldView-3, and GeoEye-1. This data set was granted permission for public release on 1 March 2024 under the National Reconnaissance Office (NRO) Electro-Optical Commercial Layer (EOCL) program.
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