skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.


Title: Variable-resolution CESM2 over Antarctica (ANTSI): Monthly outputs used for evaluation.
Included are outputs from an AMIP-style (data-driven ocean and sea ice) simulation of Variable-Resolution CESM2 from 1979-2015. Resolution is 1° globally with a refined 0.25° resolution over the Southern Ocean as well over the Antarctic ice sheet. Outputs are at a monthly timescale, and include those variables relevant for evaluation. Each netcdf file ends with several relevant tags to indicate <source>.<output deisgnator>.<variable>.<time period>.nc. Atmospheric variables are labeled with "cam" whereas ice sheet variables are labeled with "clm2". clm2.h0.SNOW.198901-199812.nc cam.h1.Q.198901-199812.nc Variables are described for CESM2 (see NCAR documentation for clm and cam) Variables included for cam include FLDS, FLNS, CLDICE, CLDLIQ, LHFLX, PRECC, PRECL, PRECSC, PS,Q, SHFLX, U, V, Z3 Variables included for clm2 include FIRA, FIRE, FLDS, FSDS, FSH, QICE, QRUNOFF, QSNOMELT, QSOIL, RAIN, SNOW. Calculation of surface mass balance (SMB) from these fields is explained in Datta et al., 2023: Datta RT; Herrington A; Lenaerts JTM; Schneider DP; Trusel L; Yin Z; Dunmire D (Sep 2023) Evaluating the impact of enhanced horizontal resolution over the Antarctic domain using a variable-resolution Earth system model. The Cryosphere, 17 (9) , 3847-3866. https://doi.org/10.5194/tc-17-3847-2023  more » « less
Award ID(s):
1952199
PAR ID:
10542114
Author(s) / Creator(s):
Publisher / Repository:
Zenodo
Date Published:
Subject(s) / Keyword(s):
variable-resolution CESM2, earth systems model, Antarctica, surface mass balance, precipitation
Format(s):
Medium: X Size: 27GB
Size(s):
27GB
Right(s):
Creative Commons Attribution 4.0 International; Open Access
Institution:
University of Colorado Boulder
Sponsoring Org:
National Science Foundation
More Like this
  1. ; ; ; ; ; ; ; (, Texas Data Repository)
    <p><b> Introduction </b> <br> The National Science Foundations Center for Oldest Ice Exploration (<a href="https://www.coldex.org">NSF COLDEX</a>) is a Science and Technology Center working to extend the record of atmospheric gases, temperature and ice sheet history to greater than 1 million years. As part of this effort, NSF COLDEX has been searching for a site for a continuous ice core extending through the mid-Pleistocene transition. Two seasons of airborne survey were conducted from South Pole Station across the southern flank of Dome A. </p> <p><b> 2023-2024 Field Season </b> <br> In the 2023-2024 field season (CXA2), and using a BT-67 Basler, NSF COLDEX conducted 17 flights from South Pole Station toward the southern flank of Dome C. Three test flights were conducted from McMurdo Station. Instrumentation included the <a href="https://doi.org/10.18738/T8/J38CO5">60 MHz MARFA ice penetrating radar </a> from the University of Texas Institute for Geophysics, a <a href="https://doi.org/10.1109/IGARSS53475.2024.10640448">UHF ice penetrating radar </a> from the Center for Remote Sensing and Integrated Systems; an GT-2 Gravimeter, and LD-90 laser altimeter and an G-823 Magnetometer. </p> <p><b> Basal specularity content </b> <br> These basal specularity content were derived from comparing 1D and 2D focused MARFA data (<a href="http://doi.org/10.1109/TGRS.2007.897416">Peters et al., 2007</a>). By comparing bed echo strengths for different focusing apertures, and accounting for the ranges and angles involved, we can derive the "specularity content" of the bed echo, a proxy for small scale bed roughness and a good indicator for subglacial water pressure in regions of distributed subglacial water (<a href="https://doi.org/10.1109/LGRS.2014.2337878">Schroeder et al., 2014, IEEE GRSL </a>, <a href="https://doi.org/10.1016/j.epsl.2019.115961">Dow et al., 2019, EPSL </a>) and smooth deforming bed material (<a href="http://doi.org/10.1002/2014GL061645">Schroeder et al., 2014, GRL</a>, <a href="http://dx.doi/org/10.1098/rsta.2014.0297">Young et al., 2016, PTRS</a>. Specularity data are inherently noisy, so these products have been smoothed with a 1 km filter.</p> 
    more » « less
  2. ; ; ; ; ; ; ; ; ; ; et al (, Texas Data Repository)
    <p>NSF COLDEX performed two airborne campaigns from South Pole Station over the Southern Flank of Dome A and 2022-23 and 2023-24, searching for a potential site of a continuous ice core that could sample the mid-Pleistocene transition. Ice thickness data extracted from the MARFA radar system has allow for a new understanding of this region.</p> <p>Here we generate crustal scale maps of ice thickness, bed elevation, specularity content, subglacial RMS deviation and fractional basal ice thickness with 1 km sampling, and 10 km resolution. We include both masked and unmasked grids.</p> <p> The projection is in the SCAR standard ESPG:3031 polar stereographic projection with true scale at 71˚S.</p> <p>These geotiffs were generated using performed using GMT6.5 (<a href="https://doi.org/10.1029/2019GC008515">Wessel et al., 2019</a>) using the pygmt interface, by binning the raw data to 2.5 km cells, and using the <a href="https://github.com/sakov/nn-c"> nnbathy </a> program to apply natural neighbor interpolation to 1 km sampling. A 10 km Gaussian filter - representing typical lines spacings - was applied and then a mask was applied for all locations where the nearest data point was further than 8 km. </p> Ice thickness, bed elevation and RMS deviation @ 400 m length scale (<a href="http://dx.doi.org/10.1029/2000JE001429">roughness</a>) data includes the following datasets: <ul> <li> UTIG/CRESIS <a href="https://doi.org/10.18738/T8/J38CO5">NSF COLDEX Airborne MARFA data</a></li> <li> British Antarctic Survey <a href="https://doi.org/10.5285/0f6f5a45-d8af-4511-a264-b0b35ee34af6">AGAP-North</a></li> <li> LDEO <a href="https://doi.org/10.1594/IEDA/317765"> AGAP-South </a></li> <li> British Antarctic Survey <a href="https://doi.org/10.5270/esa-8ffoo3e">Polargap</a></li> <li> UTIG Support Office for Airborne Research <a href="https://doi.org/10.15784/601588">Pensacola-Pole Transect (PPT) </a></li> <li> NASA/CReSIS <a href="https://doi.org/10.5067/GDQ0CUCVTE2Q"> 2016 and 2018 Operation Ice Bridge </a> </li> <li> ICECAP/PRIC <a href="https://doi.org/10.15784/601437"> SPICECAP Titan Dome Survey </a> </ul> <p>Specularity content (<a href="https://doi.org/10.1109/LGRS.2014.2337878">Schroeder et al. 2014</a>) is compiled from <a href="https://doi.org/10.18738/T8/KHUT1U"> Young et al. 2025a </a> and <a href="https://doi.org/10.18738/T8/6T5JS6"> Young et al. 2025b</a>.</p> <p>Basal ice fractional thickness is complied from manual interpretation by Vega Gonzàlez, Yan and Singh. </p> <p>Code to generated these grids can be found at <a href="https://github.com/smudog/COLDEX_dichotomy_paper_2025"> at github.com </a></p> 
    more » « less
  3. ; (, Zenodo)
    Annual or summer (JJA)  mean variables from two CESM2-CISM2 simulations: 'F09' uses the f09 grid for the atmosphere and land components, 'ARCTIC' uses the variable-resolution arctic grid. Three periods - piControl, 1pctCO2 and 4xext are included.  CAM variables: CLDTOT, PHIS, PS, T, TGCLDLWP, TREFHT, Z3 CLM variables: EFLX_LH_TOT, FGR, FIRA, FLDS, FSDS, FSH, FSM, FSR, PCT_LANDUNIT, QFLX_EVAP_TOT, QICE_MELT, QRUNOFF, QSNOMELT, RAIN, SNOW CISM variables: iarea, ice_sheet_mask, ivol, thk, total_bmb_flux, total_calving_flux, total_smb_flux POP variables: MOC CICE variables: aice, hi 
    more » « less
  4. ; ; ; ; ; ; (, The Cryosphere)
    Abstract. Earth system models are essential tools for understandingthe impacts of a warming world, particularly on the contribution of polarice sheets to sea level change. However, current models lack full couplingof the ice sheets to the ocean and are typically run at a coarse resolution(1∘ grid spacing or coarser). Coarse spatial resolution isparticularly a problem over Antarctica, where sub-grid-scale orography iswell-known to influence precipitation fields, and glacier models requirehigh-resolution atmospheric inputs. This resolution limitation has beenpartially addressed by regional climate models (RCMs), which must be forcedat their lateral and ocean surface boundaries by (usually coarser) globalatmospheric datasets, However, RCMs fail to capture the two-way couplingbetween the regional domain and the global climate system. Conversely,running high-spatial-resolution models globally is computationallyexpensive and can produce vast amounts of data. Alternatively, variable-resolution grids can retain the benefits of highresolution over a specified domain without the computational costs ofrunning at a high resolution globally. Here we evaluate a historicalsimulation of the Community Earth System Model version 2 (CESM2)implementing the spectral element (SE) numerical dynamical core (VR-CESM2)with an enhanced-horizontal-resolution (0.25∘) grid over theAntarctic Ice Sheet and the surrounding Southern Ocean; the rest of theglobal domain is on the standard 1∘ grid. We compare it to1∘ model runs of CESM2 using both the SE dynamical core and thestandard finite-volume (FV) dynamical core, both with identical physics andforcing, including prescribed sea surface temperatures (SSTs) and sea ice concentrations fromobservations. Our evaluation reveals both improvements and degradations inVR-CESM2 performance relative to the 1∘ CESM2. Surface massbalance estimates are slightly higher but within 1 standard deviation ofthe ensemble mean, except for over the Antarctic Peninsula, which isimpacted by better-resolved surface topography. Temperature and windestimates are improved over both the near surface and aloft, although theoverall correction of a cold bias (within the 1∘ CESM2 runs) hasresulted in temperatures which are too high over the interior of the icesheet. The major degradations include the enhancement of surface melt aswell as excessive cloud liquid water over the ocean, with resultant impactson the surface radiation budget. Despite these changes, VR-CESM2 is avaluable tool for the analysis of precipitation and surface mass balanceand thus constraining estimates of sea level rise associated with theAntarctic Ice Sheet. 
    more » « less
  5. ; ; ; ; ; ; ; (, Texas Data Repository)
    <p><b> Introduction </b> <br> The National Science Foundations Center for Oldest Ice Exploration (<a href="https://www.coldex.org">NSF COLDEX</a>) is a Science and Technology Center working to extend the record of atmospheric gases, temperature and ice sheet history to greater than 1 million years. As part of this effort, NSF COLDEX has been searching for a site for a continuous ice core extending through the mid-Pleistocene transition. Two seasons of airborne survey were conducted from South Pole Station across the southern flank of Dome A. </p> <p><b> 2022-2023 Field Season </b> <br> In the 2022-20223 field season (CXA1), and using a BT-67 Basler, NSF COLDEX conducted 13 full flights and one weather abort from South Pole Station toward the southern flank of Dome C; as well as 1 survey flight toward Hercules Dome in support of the Hercules Dome Drilling project. Three test flights were conducted from McMurdo Station. Instrumentation included the <a href="https://doi.org/10.18738/T8/J38CO5">60 MHz MARFA ice penetrating radar </a> from the University of Texas Institute for Geophysics, a <a href="https://doi.org/10.1109/IGARSS53475.2024.10640448">UHF ice penetrating radar </a> from the Center for Remote Sensing and Integrated Systems; an GT-2 Gravimeter, and LD-90 laser altimeter and an G-823 Magnetometer. </p> <p><b> Basal specularity content </b> <br> These basal specularity content were derived from comparing 1D and 2D focused MARFA data (<a href="http://doi.org/10.1109/TGRS.2007.897416">Peters et al., 2007</a>). By comparing bed echo strengths for different focusing apertures, and accounting for the ranges and angles involved, we can derive the "specularity content" of the bed echo, a proxy for small scale bed roughness and a good indicator for subglacial water pressure in regions of distributed subglacial water (<a href="https://doi.org/10.1109/LGRS.2014.2337878">Schroeder et al., 2014, IEEE GRSL </a>, <a href="https://doi.org/10.1016/j.epsl.2019.115961">Dow et al., 2019, EPSL </a>) and smooth deforming bed material (<a href="http://doi.org/10.1002/2014GL061645">Schroeder et al., 2014, GRL</a>, <a href="http://dx.doi/org/10.1098/rsta.2014.0297">Young et al., 2016, PTRS</a>. Specularity data are inherently noisy, so these products have been smoothed with a 1 km filter.</p> 
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Save / Share this Record
  • Send to Email