Spatiotemporal variability of air temperature biases in regional climate models over the Greenland ice sheet
Regional climate models (RCMs) are fundamental tools in understanding and quantifying the contribution of the Greenland ice sheet to sea-level rise. We perform an extensive evaluation of the daily air temperature simulated by two RCMs, MARv3.12 and RACMO $2.3\text{p}2$, and a global atmospheric rean...
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Cambridge University Press
2025-01-01
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| Series: | Journal of Glaciology |
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| Online Access: | https://www.cambridge.org/core/product/identifier/S0022143025000383/type/journal_article |
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| author | Federico Covi Regine Hock Åsa Rennermalm Xavier Fettweis Brice Noël |
| author_facet | Federico Covi Regine Hock Åsa Rennermalm Xavier Fettweis Brice Noël |
| author_sort | Federico Covi |
| collection | DOAJ |
| description | Regional climate models (RCMs) are fundamental tools in understanding and quantifying the contribution of the Greenland ice sheet to sea-level rise. We perform an extensive evaluation of the daily air temperature simulated by two RCMs, MARv3.12 and RACMO
$2.3\text{p}2$, and a global atmospheric reanalysis, ERA5, at 35 locations across the ice sheet over the period 1995–2020. We compare model results to weather station data from two climate networks, focusing on the spatial and temporal variability in mean biases (MBs). All three models perform well at low elevations (<1500 m a.s.l.) with an MB of 0.16∘C (MAR),
$0.36^{\circ}\mathrm{C}$ (RACMO) and
$0.41^{\circ}\mathrm{C}$ (ERA5), while warm biases (>1.70
$^{\circ}\mathrm{C}$) are found at high elevations (>1500 m a.s.l.). Temperature biases exhibit a strong seasonality, being more pronounced during winter and much smaller during summer ranging from
$0.11^{\circ}\mathrm{C}$ to
$0.59^{\circ}\mathrm{C}$. No interannual variability is found in the biases of all three datasets. Daily variability within each month is captured well by both climate models and the reanalysis at most locations. Finally, all three models perform overall better in the ablation zone during summer, i.e. where and when considerable melt production occurs. |
| format | Article |
| id | doaj-art-c497b34fc1094916ba717d9541986155 |
| institution | DOAJ |
| issn | 0022-1430 1727-5652 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Cambridge University Press |
| record_format | Article |
| series | Journal of Glaciology |
| spelling | doaj-art-c497b34fc1094916ba717d95419861552025-08-20T03:05:49ZengCambridge University PressJournal of Glaciology0022-14301727-56522025-01-017110.1017/jog.2025.38Spatiotemporal variability of air temperature biases in regional climate models over the Greenland ice sheetFederico Covi0https://orcid.org/0000-0002-0775-4345Regine Hock1Åsa Rennermalm2https://orcid.org/0000-0002-2470-7444Xavier Fettweis3https://orcid.org/0000-0002-4140-3813Brice Noël4British Antarctic Survey, Cambridge, United Kingdom Geophysical Institute, University of Alaska Fairbanks, Fairbanks, AK, USA Department of Geosciences, University of Oslo, Oslo, NorwayGeophysical Institute, University of Alaska Fairbanks, Fairbanks, AK, USA Department of Geosciences, University of Oslo, Oslo, NorwayDepartment of Geography, Rutgers, The State University of New Jersey, New Brunswick, NJ, USADepartment of Geography, University of Liège, Liège, BelgiumDepartment of Geography, University of Liège, Liège, BelgiumRegional climate models (RCMs) are fundamental tools in understanding and quantifying the contribution of the Greenland ice sheet to sea-level rise. We perform an extensive evaluation of the daily air temperature simulated by two RCMs, MARv3.12 and RACMO $2.3\text{p}2$, and a global atmospheric reanalysis, ERA5, at 35 locations across the ice sheet over the period 1995–2020. We compare model results to weather station data from two climate networks, focusing on the spatial and temporal variability in mean biases (MBs). All three models perform well at low elevations (<1500 m a.s.l.) with an MB of 0.16∘C (MAR), $0.36^{\circ}\mathrm{C}$ (RACMO) and $0.41^{\circ}\mathrm{C}$ (ERA5), while warm biases (>1.70 $^{\circ}\mathrm{C}$) are found at high elevations (>1500 m a.s.l.). Temperature biases exhibit a strong seasonality, being more pronounced during winter and much smaller during summer ranging from $0.11^{\circ}\mathrm{C}$ to $0.59^{\circ}\mathrm{C}$. No interannual variability is found in the biases of all three datasets. Daily variability within each month is captured well by both climate models and the reanalysis at most locations. Finally, all three models perform overall better in the ablation zone during summer, i.e. where and when considerable melt production occurs.https://www.cambridge.org/core/product/identifier/S0022143025000383/type/journal_articleClimate changeglacier meteorologyice-sheet mass balance |
| spellingShingle | Federico Covi Regine Hock Åsa Rennermalm Xavier Fettweis Brice Noël Spatiotemporal variability of air temperature biases in regional climate models over the Greenland ice sheet Journal of Glaciology Climate change glacier meteorology ice-sheet mass balance |
| title | Spatiotemporal variability of air temperature biases in regional climate models over the Greenland ice sheet |
| title_full | Spatiotemporal variability of air temperature biases in regional climate models over the Greenland ice sheet |
| title_fullStr | Spatiotemporal variability of air temperature biases in regional climate models over the Greenland ice sheet |
| title_full_unstemmed | Spatiotemporal variability of air temperature biases in regional climate models over the Greenland ice sheet |
| title_short | Spatiotemporal variability of air temperature biases in regional climate models over the Greenland ice sheet |
| title_sort | spatiotemporal variability of air temperature biases in regional climate models over the greenland ice sheet |
| topic | Climate change glacier meteorology ice-sheet mass balance |
| url | https://www.cambridge.org/core/product/identifier/S0022143025000383/type/journal_article |
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