# Greenland Ice Sheet Holocene Ice Mass Loss Simulations and Climate Reconstructions #----------------------------------------------------------------------- # World Data Service for Paleoclimatology, Boulder # and # NOAA Paleoclimatology Program # National Centers for Environmental Information (NCEI) #----------------------------------------------------------------------- # Template Version 3.0 # Encoding: UTF-8 # NOTE: Please cite Publication, and Online_Resource and date accessed when using these data. # If there is no publication information, please cite Investigators, Title, and Online_Resource and date accessed. # # Online_Resource: https://www.ncdc.noaa.gov/paleo/study/30172 # Description: NOAA Landing Page # Online_Resource: https://www.ncei.noaa.gov/pub/data/paleo/gcmoutput/briner2020/briner2020-2100-ice-loss.txt # Description: NOAA location of the template # # Original_Source_URL: # Description: # # Description/Documentation lines begin with # # Data lines have no # # # Data Type: Paleoclimate Modeling # # Dataset DOI: # # Parameter_Keywords: other model #-------------------- # Contribution_Date # Date: 2020-07-20 #-------------------- # File_Last_Modified_Date # Date: 2020-07-20 #-------------------- # Title # Study_Name: Greenland Ice Sheet Holocene Ice Mass Loss Simulations and Climate Reconstructions #-------------------- # Investigators # Investigators: Briner, J.P.; Cuzzone, J.K.; Badgeley, J.A.; Steig, E.J.; Morlighem, M.; Schlegel, N.-J.; Larour, E. #-------------------- # Description_Notes_and_Keywords # Description: Greenland ice sheet mass loss simulations from an ensemble (n=9) spanning 12,000 years ago to 1850 CE. # It also includes Gt/yr data from an ensemble of simulations from 1850 to 2012 CE, and Gt/yr data from an ensemble of # simulations from 2000-2100 CE following representative concentration pathway climates as part of CMIP6/ISMIP6. # Gridded temperature and precipitation reconstructions for the past 20,000 years are also included in netCDF file format. # Greenland gridded temperature and precipitation reconstructions are from data assimilation of ice-core data and a transient climate model. # # Provided Keywords: ice sheet model, Holocene, Greenland Ice Sheet, Ice mass loss, mass loss rate, 2100, RCP, Paleoclimate, climate change # #-------------------- # Publication # Authors: Jason P. Briner, Joshua K. Cuzzone, Jessica A. Badgeley, Nicolás E. Young, Eric J. Steig, Mathieu Morlighem, Nicole-Jeanne Schlegel, Gregory J. Hakim, Joerg M. Schaefer, Jesse V. Johnson, Alia J. Lesnek, Elizabeth K. Thomas, Estelle Allan, Ole Bennike, Allison A. Cluett, Beata Csatho, Anne de Vernal, Jacob Downs, Eric Larour, Sophie Nowicki # Published_Date_or_Year: 2020-10-01 # Published_Title: Rate of mass loss from the Greenland Ice Sheet will exceed Holocene values this century # Journal_Name: Nature # Volume: 586 # Edition: # Issue: 7827 # Pages: 70-74 # Report_Number: # DOI: 10.1038/s41586-020-2742-6 # Online_Resource: https://www.nature.com/articles/s41586-020-2742-6 # Full_Citation: # Abstract: The Greenland Ice Sheet (GIS) is losing mass at a high rate. Given the short-term nature of the observational record, it is difficult to assess the historical importance of this mass-loss trend. Unlike records of greenhouse gas concentrations and global temperature, in which observations have been merged with palaeoclimate datasets, there are no comparably long records for rates of GIS mass change. Here we reveal unprecedented mass loss from the GIS this century, by placing contemporary and future rates of GIS mass loss within the context of the natural variability over the past 12,000 years. We force a high-resolution ice-sheet model with an ensemble of climate histories constrained by ice-core data. Our simulation domain covers southwestern Greenland, the mass change of which is dominated by surface mass balance. The results agree favourably with an independent chronology of the history of the GIS margin. The largest pre-industrial rates of mass loss (up to 6,000 billion tonnes per century) occurred in the early Holocene, and were similar to the contemporary (ad 2000-2018) rate of around 6,100 billion tonnes per century. Simulations of future mass loss from southwestern GIS, based on Representative Concentration Pathway (RCP) scenarios corresponding to low (RCP2.6) and high (RCP8.5) greenhouse gas concentration trajectories, predict mass loss of between 8,800 and 35,900 billion tonnes over the twenty-first century. These rates of GIS mass loss exceed the maximum rates over the past 12,000 years. Because rates of mass loss from the southwestern GIS scale linearly with the GIS as a whole, our results indicate, with high confidence, that the rate of mass loss from the GIS will exceed Holocene rates this century. #------------------ # Funding_Agency # Funding_Agency_Name: US National Science Foundation # Grant: 1504267 #------------------ # Site_Information # Site_Name: Greenland Ice Sheet # Location: North America>Greenland # Country: Greenland # Northernmost_Latitude: 87.16 # Southernmost_Latitude: 53.81 # Easternmost_Longitude: -3.75 # Westernmost_Longitude: -86.25 # Elevation: #------------------ # Data_Collection # Collection_Name: Briner2020-2100-IceLoss # Earliest_Year: 2000 # Most_Recent_Year: 2100 # Time_Unit: Year CE # Core_Length: # Notes: #------------------ # Chronology_Information # Chronology: # #---------------- # Variables # # Data variables follow are preceded by "##" in columns one and two. # Data line variables format: one per line, shortname-tab-variable components (what, material, error, units, seasonality, data type,detail, method, C or N for Character or Numeric data, free text) # ## age age, , , year Common Era, , paleoclimatic modeling, , ,N, ## sim1 ice mass loss, , , gigaton per year, ,paleoclimatic modeling,,,N, simulation 1; Access 1.3 8.5 ## sim2 ice mass loss, , , gigaton per year, ,paleoclimatic modeling,,,N, simulation 2; CNRM CM6 8.5 ## sim3 ice mass loss, , , gigaton per year, ,paleoclimatic modeling,,,N, simulation 3; CNRM ESM2 8.5 ## sim4 ice mass loss, , , gigaton per year, ,paleoclimatic modeling,,,N, simulation 4; NorESM1 8.5 ## sim5 ice mass loss, , , gigaton per year, ,paleoclimatic modeling,,,N, simulation 5; UKESM1 CM6 8.5 ## sim6 ice mass loss, , , gigaton per year, ,paleoclimatic modeling,,,N, simulation 6; MIROC 8.5 ## sim7 ice mass loss, , , gigaton per year, ,paleoclimatic modeling,,,N, simulation 7; MIROC 2.6 ## sim8 ice mass loss, , , gigaton per year, ,paleoclimatic modeling,,,N, simulation 8; CNRM CM6 2.6 # #---------------- # Data: # Data lines follow (have no #) # Data line format - tab-delimited text, variable short name as header # Missing Values: # age sim1 sim2 sim3 sim4 sim5 sim6 sim7 sim8 2000 -43.8875 -43.8875 -43.8875 -43.8875 -43.8875 -43.8875 -43.8875 -43.8875 2001 -41.8737 -41.8737 -41.8737 -41.8737 -41.8737 -41.8737 -41.8737 -41.8737 2002 -75.1073 -75.1073 -75.1073 -75.1073 -75.1073 -75.1073 -75.1073 -75.1073 2003 -96.5911 -96.5911 -96.5911 -96.5911 -96.5911 -96.5911 -96.5911 -96.5911 2004 -73.2894 -73.2894 -73.2894 -73.2894 -73.2894 -73.2894 -73.2894 -73.2894 2005 -36.8097 -36.8097 -36.8097 -36.8097 -36.8097 -36.8097 -36.8097 -36.8097 2006 -60.084 -60.084 -60.084 -60.084 -60.084 -60.084 -60.084 -60.084 2007 -110.0852 -110.0852 -110.0852 -110.0852 -110.0852 -110.0852 -110.0852 -110.0852 2008 -96.5362 -96.5362 -96.5362 -96.5362 -96.5362 -96.5362 -96.5362 -96.5362 2009 -106.716 -106.716 -106.716 -106.716 -106.716 -106.716 -106.716 -106.716 2010 -149.705 -149.705 -149.705 -149.705 -149.705 -149.705 -149.705 -149.705 2011 -165.9638 -165.9638 -165.9638 -165.9638 -165.9638 -165.9638 -165.9638 -165.9638 2012 -148.295 -148.295 -148.295 -148.295 -148.295 -148.295 -148.295 -148.295 2013 -94.8367 -94.8367 -94.8367 -94.8367 -94.8367 -94.8367 -94.8367 -94.8367 2014 -79.6447 -79.6447 -79.6447 -79.6447 -79.6447 -79.6447 -79.6447 -79.6447 2015 -71.8617 -136.0363 -104.6643 -41.833 -163.535 -32.572 -14.6385 -151.9109 2016 -49.1799 -76.4141 -127.8918 -32.0657 -112.2757 -56.0822 -107.9911 -141.0128 2017 -3.651 -38.6316 -135.5913 -24.4788 -142.3534 -89.3291 -91.682 -84.5492 2018 -76.7858 -91.7704 -111.9104 -106.5069 -178.7073 -112.5438 -45.9178 -111.6826 2019 -83.0494 -80.8451 -56.8235 -161.6773 -126.8436 -114.3485 -111.6201 -149.5583 2020 -71.3408 -66.8302 -74.2396 -148.2704 -175.3554 -147.2312 -127.9639 -85.8945 2021 -117.5844 -138.3807 -129.8672 -114.4204 -165.9115 -154.693 -108.2651 -80.4794 2022 -121.3066 -142.7115 -163.6954 -69.7886 -130.9692 -119.6066 -60.9992 -124.8173 2023 -105.3644 -107.6501 -196.011 -24.9907 -213.0668 -98.7608 -89.7824 -125.9991 2024 -61.3105 -119.4438 -140.4255 -41.3052 -201.8034 -107.2476 -166.1428 -99.9731 2025 -23.4647 -108.8805 -100.3747 -41.2273 -151.1535 -138.4367 -66.1988 -85.6601 2026 -18.6602 -117.8529 -97.2452 -51.4512 -200.8398 -145.4494 -1.6065 -102.0344 2027 -43.7975 -103.515 -115.4903 -88.5705 -155.9713 -66.4614 -52.7374 -103.2955 2028 -110.4807 -70.7455 -95.92 -102.0269 -161.0414 -69.8491 -104.0928 -98.0177 2029 -101.2645 -72.7521 -99.4543 -128.7192 -220.4831 -117.6279 -121.1373 -24.3479 2030 -26.6644 -83.9986 -112.713 -90.7427 -171.2759 -49.2771 -85.0972 -52.3946 2031 -38.9181 -86.6957 -91.9309 -76.3323 -172.2521 -53.0776 -72.562 -58.1305 2032 -85.8739 -81.1977 -80.0286 -72.1688 -206.0451 -98.3084 -89.1225 -71.8009 2033 -58.1523 -143.444 -95.0655 -72.7521 -287.3368 -122.3482 -118.5815 -128.5099 2034 -82.0753 -91.3315 -113.5744 -115.1281 -285.0553 -139.8657 -167.3106 -85.8499 2035 -119.621 -66.9016 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-90.9885 -155.6705 -98.4275 2048 -84.7545 -167.9852 -166.241 -71.2449 -375.1894 -149.1675 -149.2003 -120.2191 2049 -120.6943 -186.0292 -142.4627 -112.2003 -298.2387 -148.9436 -157.4067 -65.3657 2050 -123.8443 -171.5685 -87.6946 -170.9894 -264.9362 -114.8619 -99.0555 -42.9051 2051 -72.7332 -103.7591 -142.8497 -161.9765 -195.455 -161.5718 -100.4601 -26.437 2052 -87.9438 -107.4114 -187.0924 -189.84 -177.1528 -139.4392 -144.6969 -59.9381 2053 -97.3288 -129.1163 -177.4564 -227.079 -319.9828 -90.307 -106.7332 -103.501 2054 -115.8735 -166.5806 -199.8015 -145.6216 -341.6223 -99.3555 -98.8714 -83.1933 2055 -92.6489 -195.9661 -212.4058 -117.124 -301.4053 -123.6436 -141.691 -105.4789 2056 -143.534 -128.0782 -141.918 -160.7901 -310.6602 -205.2974 -83.6659 -130.7536 2057 -205.582 -130.6976 -188.2972 -138.1398 -353.5557 -253.1526 -41.5018 -137.5475 2058 -175.2753 -155.1465 -259.8274 -76.4676 -369.1545 -229.1429 -31.7222 -109.1294 2059 -182.7022 -215.4934 -162.0793 -36.7293 -423.3048 -226.9692 -35.2443 -102.5478 2060 -266.8818 -237.1395 -96.1265 -50.0224 -428.9492 -218.3891 -67.2408 -129.4538 2061 -235.6085 -223.0713 -160.2626 -30.316 -317.2846 -173.167 -117.0625 -131.7515 2062 -142.2683 -254.5918 -272.6898 -113.2862 -350.0282 -167.5182 -89.6475 -138.4775 2063 -161.9984 -236.3994 -268.0621 -163.3013 -408.7721 -128.7659 -126.1672 -155.8411 2064 -126.4027 -235.8313 -218.3192 -132.0678 -399.4871 -143.152 -187.5071 -144.8191 2065 -148.6218 -269.9533 -222.0573 -83.3311 -383.7369 -229.052 -141.445 -128.1856 2066 -129.1606 -249.2121 -193.5423 -99.6457 -456.0239 -194.425 -147.7246 -101.4877 2067 -109.3313 -291.8492 -195.8002 -170.2323 -464.9005 -247.2243 -129.5761 -81.3236 2068 -117.0178 -310.1692 -260.6293 -194.8524 -385.1735 -254.681 -76.6183 -117.48 2069 -141.1774 -208.8428 -269.9871 -169.5454 -438.8956 -175.8031 -55.1639 -159.5926 2070 -176.3221 -199.64 -203.482 -109.1626 -502.5158 -132.31 -141.3873 -162.2631 2071 -258.0435 -222.192 -208.3641 -158.5213 -469.9769 -219.4183 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-23.7793 -97.1553 2084 -192.7448 -419.2371 -405.2969 -181.475 -723.764 -341.5169 -61.8466 -94.0122 2085 -243.7372 -455.6129 -345.7632 -172.2367 -681.844 -288.6759 -139.1002 -42.515 2086 -275.2994 -458.5878 -340.8311 -209.7736 -622.4299 -296.4683 -147.9347 -49.354 2087 -244.0995 -383.9914 -385.4602 -218.4109 -660.0729 -367.4536 -164.1814 -114.8656 2088 -229.3883 -380.6138 -424.6999 -309.7836 -740.9245 -447.723 -136.6405 -123.195 2089 -176.9635 -374.8157 -448.631 -256.3102 -755.7101 -350.9045 -64.1185 -90.2449 2090 -117.822 -433.1264 -453.709 -205.7038 -634.5719 -372.9924 -35.24 -72.9705 2091 -150.9842 -530.39 -385.5904 -241.4535 -726.0989 -474.127 -33.2247 -93.276 2092 -186.8879 -468.6963 -414.9937 -214.7673 -741.2439 -521.7904 20.0543 -102.7315 2093 -275.5569 -482.7711 -466.0701 -183.4555 -639.048 -377.6321 -7.112 -121.8227 2094 -354.4076 -580.2696 -444.6361 -229.0419 -782.4211 -278.4681 -45.5689 -154.6519 2095 -269.8893 -601.2296 -530.2459 -253.5311 -860.8199 -399.4278 -53.4848 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