Recent warming trends of the Greenland ice sheet documented by historical firn and ice temperature observations and machine learning

  1. Vandecrux, Baptiste
  2. Fausto, Robert S.
  3. Box, Jason E.
  4. Covi, Federico
  5. Hock, Regine
  6. Rennermalm, Åsa K.
  7. Heilig, Achim
  8. Abermann, Jakob
  9. van As, Dirk
  10. Bjerre, Elisa
  11. Fettweis, Xavier
  12. Smeets, Paul C. J. P.
  13. Kuipers Munneke, Peter
  14. van den Broeke, Michiel R.
  15. Brils, Max
  16. Langen, Peter L.
  17. Mottram, Ruth
  18. Ahlstrøm, Andreas P.

Download
tc-18-609-2024.pdf 6,98MB
WeightNameValue
1000 Titel
  • Recent warming trends of the Greenland ice sheet documented by historical firn and ice temperature observations and machine learning
1000 Autor/in
  1. Vandecrux, Baptiste |
  2. Fausto, Robert S. |
  3. Box, Jason E. |
  4. Covi, Federico |
  5. Hock, Regine |
  6. Rennermalm, Åsa K. |
  7. Heilig, Achim |
  8. Abermann, Jakob |
  9. van As, Dirk |
  10. Bjerre, Elisa |
  11. Fettweis, Xavier |
  12. Smeets, Paul C. J. P. |
  13. Kuipers Munneke, Peter |
  14. van den Broeke, Michiel R. |
  15. Brils, Max |
  16. Langen, Peter L. |
  17. Mottram, Ruth |
  18. Ahlstrøm, Andreas P. |
1000 Verlag
  • Copernicus Publications
1000 Erscheinungsjahr 2024
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2024-02-12
1000 Erschienen in
1000 Quellenangabe
  • 18(2):609-631
1000 Copyrightjahr
  • 2024
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.5194/tc-18-609-2024 |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • <jats:p>Abstract. Surface melt on the Greenland ice sheet has been increasing in intensity and extent over the last decades due to Arctic atmospheric warming. Surface melt depends on the surface energy balance, which includes the atmospheric forcing but also the thermal budget of the snow, firn and ice near the ice sheet surface. The temperature of the ice sheet subsurface has been used as an indicator of the thermal state of the ice sheet's surface. Here, we present a compilation of 4612 measurements of firn and ice temperature at 10 m below the surface (T10 m) across the ice sheet, spanning from 1912 to 2022. The measurements are either instantaneous or monthly averages. We train an artificial neural network model (ANN) on 4597 of these point observations, weighted by their relative representativity, and use it to reconstruct T10 m over the entire Greenland ice sheet for the period 1950–2022 at a monthly timescale. We use 10-year averages and mean annual values of air temperature and snowfall from the ERA5 reanalysis dataset as model input. The ANN indicates a Greenland-wide positive trend of T10 m at 0.2 ∘C per decade during the 1950–2022 period, with a cooling during 1950–1985 (−0.4 ∘C per decade) followed by a warming during 1985–2022 (+0.7 ∘ per decade). Regional climate models HIRHAM5, RACMO2.3p2 and MARv3.12 show mixed results compared to the observational T10 m dataset, with mean differences ranging from −0.4 ∘C (HIRHAM) to 1.2 ∘C (MAR) and root mean squared differences ranging from 2.8 ∘C (HIRHAM) to 4.7 ∘C (MAR). The observation-based ANN also reveals an underestimation of the subsurface warming trends in climate models for the bare-ice and dry-snow areas. The subsurface warming brings the Greenland ice sheet surface closer to the melting point, reducing the amount of energy input required for melting. Our compilation documents the response of the ice sheet subsurface to atmospheric warming and will enable further improvements of models used for ice sheet mass loss assessment and reduce the uncertainty in projections. </jats:p>
1000 Liste der Beteiligten
  1. https://frl.publisso.de/adhoc/uri/VmFuZGVjcnV4LCBCYXB0aXN0ZQ==|https://frl.publisso.de/adhoc/uri/RmF1c3RvLCBSb2JlcnTCoFMu|https://frl.publisso.de/adhoc/uri/Qm94LCBKYXNvbsKgRS4=|https://frl.publisso.de/adhoc/uri/Q292aSwgRmVkZXJpY28=|https://frl.publisso.de/adhoc/uri/SG9jaywgUmVnaW5l|https://frl.publisso.de/adhoc/uri/UmVubmVybWFsbSwgw4VzYcKgSy4=|https://frl.publisso.de/adhoc/uri/SGVpbGlnLCBBY2hpbQ==|https://frl.publisso.de/adhoc/uri/QWJlcm1hbm4sIEpha29i|https://frl.publisso.de/adhoc/uri/dmFuwqBBcywgRGlyaw==|https://frl.publisso.de/adhoc/uri/QmplcnJlLCBFbGlzYQ==|https://frl.publisso.de/adhoc/uri/RmV0dHdlaXMsIFhhdmllcg==|https://frl.publisso.de/adhoc/uri/U21lZXRzLCBQYXVswqBDLsKgSi7CoFAu|https://frl.publisso.de/adhoc/uri/S3VpcGVyc8KgTXVubmVrZSwgUGV0ZXI=|https://frl.publisso.de/adhoc/uri/dmFuwqBkZW7CoEJyb2VrZSwgTWljaGllbMKgUi4=|https://frl.publisso.de/adhoc/uri/QnJpbHMsIE1heA==|https://frl.publisso.de/adhoc/uri/TGFuZ2VuLCBQZXRlcsKgTC4=|https://frl.publisso.de/adhoc/uri/TW90dHJhbSwgUnV0aA==|https://frl.publisso.de/adhoc/uri/QWhsc3Ryw7htLCBBbmRyZWFzwqBQLg==
1000 Hinweis
  • DeepGreen-ID: 0b72599f0f7f43be916abd9834b72adb ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search)
1000 Label
1000 Förderer
  1. Austrian Science Fund |
  2. National Science Foundation |
  3. Netherlands Earth System Science Centre |
  4. Aarhus Universitet |
  5. Deutsche Forschungsgemeinschaft |
1000 Fördernummer
  1. -
  2. -
  3. -
  4. -
  5. -
1000 Förderprogramm
  1. -
  2. -
  3. -
  4. -
  5. -
1000 Dateien
1000 Förderung
  1. 1000 joinedFunding-child
    1000 Förderer Austrian Science Fund |
    1000 Förderprogramm -
    1000 Fördernummer -
  2. 1000 joinedFunding-child
    1000 Förderer National Science Foundation |
    1000 Förderprogramm -
    1000 Fördernummer -
  3. 1000 joinedFunding-child
    1000 Förderer Netherlands Earth System Science Centre |
    1000 Förderprogramm -
    1000 Fördernummer -
  4. 1000 joinedFunding-child
    1000 Förderer Aarhus Universitet |
    1000 Förderprogramm -
    1000 Fördernummer -
  5. 1000 joinedFunding-child
    1000 Förderer Deutsche Forschungsgemeinschaft |
    1000 Förderprogramm -
    1000 Fördernummer -
1000 Objektart article
1000 Beschrieben durch
1000 @id frl:6480104.rdf
1000 Erstellt am 2024-05-23T12:16:07.337+0200
1000 Erstellt von 322
1000 beschreibt frl:6480104
1000 Zuletzt bearbeitet 2024-05-27T10:48:55.096+0200
1000 Objekt bearb. Mon May 27 10:48:55 CEST 2024
1000 Vgl. frl:6480104
1000 Oai Id
  1. oai:frl.publisso.de:frl:6480104 |
1000 Sichtbarkeit Metadaten public
1000 Sichtbarkeit Daten public
1000 Gegenstand von

View source