What is the surface mass balance of Antarctica? An intercomparison of regional climate model estimates
We compare the performance of five different regional climate models (RCMs) (COSMO-CLM2, HIRHAM5, MAR3.10, MetUM, and RACMO2.3p2), forced by ERA-Interim reanalysis, in simulating the near-surface climate and surface mass balance (SMB) of Antarctica. All models simulate Antarctic climate well when co...
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ftunivutrecht:oai:dspace.library.uu.nl:1874/416437 2023-07-23T04:14:37+02:00 What is the surface mass balance of Antarctica? An intercomparison of regional climate model estimates Mottram, Ruth H. Hansen, Nicolay Kittel, Christoph van Wessem, Melchior Agosta, Cécile Amory, Charles Boberg, F. van de Berg, Willem Jan Fettweis, Xavier Gossart, Alexandra van Lipzig, NPM van Meijgaard, E. Orr, Andrew Phillips, Tony Webster, Stuart Simonsen, S.B. Souverijns, Niels Sub Dynamics Meteorology Marine and Atmospheric Research 2021 application/pdf https://dspace.library.uu.nl/handle/1874/416437 en eng 1994-0416 https://dspace.library.uu.nl/handle/1874/416437 info:eu-repo/semantics/OpenAccess Article 2021 ftunivutrecht 2023-07-02T03:32:45Z We compare the performance of five different regional climate models (RCMs) (COSMO-CLM2, HIRHAM5, MAR3.10, MetUM, and RACMO2.3p2), forced by ERA-Interim reanalysis, in simulating the near-surface climate and surface mass balance (SMB) of Antarctica. All models simulate Antarctic climate well when compared with daily observed temperature and pressure, with nudged models matching daily observations slightly better than free-running models. The ensemble mean annual SMB over the Antarctic ice sheet (AIS) including ice shelves is 2329±94 Gt yr−1 over the common 1987–2015 period covered by all models. There is large interannual variability, consistent between models due to variability in the driving ERA-Interim reanalysis. Mean annual SMB is sensitive to the chosen period; over our 30-year climatological mean period (1980 to 2010), the ensemble mean is 2483 Gt yr−1. However, individual model estimates vary from 1961±70 to 2519±118 Gt yr−1. The largest spatial differences between model SMB estimates are in West Antarctica, the Antarctic Peninsula, and around the Transantarctic Mountains. We find no significant trend in Antarctic SMB over either period. Antarctic ice sheet (AIS) mass loss is currently equivalent to around 0.5 mm yr−1 of global mean sea level rise (Shepherd et al., 2020), but our results indicate some uncertainty in the SMB contribution based on RCMs. We compare modelled SMB with a large dataset of observations, which, though biased by undersampling, indicates that many of the biases in SMB are common between models. A drifting-snow scheme improves modelled SMB on ice sheet surface slopes with an elevation between 1000 and 2000 m, where strong katabatic winds form. Different ice masks have a substantial impact on the integrated total SMB and along with model resolution are factored into our analysis. Targeting undersampled regions with high precipitation for observational campaigns will be key to improving future estimates of SMB in Antarctica. Article in Journal/Newspaper Antarc* Antarctic Antarctic Peninsula Antarctica Ice Sheet Ice Shelves West Antarctica Utrecht University Repository Antarctic Antarctic Peninsula The Antarctic Transantarctic Mountains West Antarctica |
institution |
Open Polar |
collection |
Utrecht University Repository |
op_collection_id |
ftunivutrecht |
language |
English |
description |
We compare the performance of five different regional climate models (RCMs) (COSMO-CLM2, HIRHAM5, MAR3.10, MetUM, and RACMO2.3p2), forced by ERA-Interim reanalysis, in simulating the near-surface climate and surface mass balance (SMB) of Antarctica. All models simulate Antarctic climate well when compared with daily observed temperature and pressure, with nudged models matching daily observations slightly better than free-running models. The ensemble mean annual SMB over the Antarctic ice sheet (AIS) including ice shelves is 2329±94 Gt yr−1 over the common 1987–2015 period covered by all models. There is large interannual variability, consistent between models due to variability in the driving ERA-Interim reanalysis. Mean annual SMB is sensitive to the chosen period; over our 30-year climatological mean period (1980 to 2010), the ensemble mean is 2483 Gt yr−1. However, individual model estimates vary from 1961±70 to 2519±118 Gt yr−1. The largest spatial differences between model SMB estimates are in West Antarctica, the Antarctic Peninsula, and around the Transantarctic Mountains. We find no significant trend in Antarctic SMB over either period. Antarctic ice sheet (AIS) mass loss is currently equivalent to around 0.5 mm yr−1 of global mean sea level rise (Shepherd et al., 2020), but our results indicate some uncertainty in the SMB contribution based on RCMs. We compare modelled SMB with a large dataset of observations, which, though biased by undersampling, indicates that many of the biases in SMB are common between models. A drifting-snow scheme improves modelled SMB on ice sheet surface slopes with an elevation between 1000 and 2000 m, where strong katabatic winds form. Different ice masks have a substantial impact on the integrated total SMB and along with model resolution are factored into our analysis. Targeting undersampled regions with high precipitation for observational campaigns will be key to improving future estimates of SMB in Antarctica. |
author2 |
Sub Dynamics Meteorology Marine and Atmospheric Research |
format |
Article in Journal/Newspaper |
author |
Mottram, Ruth H. Hansen, Nicolay Kittel, Christoph van Wessem, Melchior Agosta, Cécile Amory, Charles Boberg, F. van de Berg, Willem Jan Fettweis, Xavier Gossart, Alexandra van Lipzig, NPM van Meijgaard, E. Orr, Andrew Phillips, Tony Webster, Stuart Simonsen, S.B. Souverijns, Niels |
spellingShingle |
Mottram, Ruth H. Hansen, Nicolay Kittel, Christoph van Wessem, Melchior Agosta, Cécile Amory, Charles Boberg, F. van de Berg, Willem Jan Fettweis, Xavier Gossart, Alexandra van Lipzig, NPM van Meijgaard, E. Orr, Andrew Phillips, Tony Webster, Stuart Simonsen, S.B. Souverijns, Niels What is the surface mass balance of Antarctica? An intercomparison of regional climate model estimates |
author_facet |
Mottram, Ruth H. Hansen, Nicolay Kittel, Christoph van Wessem, Melchior Agosta, Cécile Amory, Charles Boberg, F. van de Berg, Willem Jan Fettweis, Xavier Gossart, Alexandra van Lipzig, NPM van Meijgaard, E. Orr, Andrew Phillips, Tony Webster, Stuart Simonsen, S.B. Souverijns, Niels |
author_sort |
Mottram, Ruth H. |
title |
What is the surface mass balance of Antarctica? An intercomparison of regional climate model estimates |
title_short |
What is the surface mass balance of Antarctica? An intercomparison of regional climate model estimates |
title_full |
What is the surface mass balance of Antarctica? An intercomparison of regional climate model estimates |
title_fullStr |
What is the surface mass balance of Antarctica? An intercomparison of regional climate model estimates |
title_full_unstemmed |
What is the surface mass balance of Antarctica? An intercomparison of regional climate model estimates |
title_sort |
what is the surface mass balance of antarctica? an intercomparison of regional climate model estimates |
publishDate |
2021 |
url |
https://dspace.library.uu.nl/handle/1874/416437 |
geographic |
Antarctic Antarctic Peninsula The Antarctic Transantarctic Mountains West Antarctica |
geographic_facet |
Antarctic Antarctic Peninsula The Antarctic Transantarctic Mountains West Antarctica |
genre |
Antarc* Antarctic Antarctic Peninsula Antarctica Ice Sheet Ice Shelves West Antarctica |
genre_facet |
Antarc* Antarctic Antarctic Peninsula Antarctica Ice Sheet Ice Shelves West Antarctica |
op_relation |
1994-0416 https://dspace.library.uu.nl/handle/1874/416437 |
op_rights |
info:eu-repo/semantics/OpenAccess |
_version_ |
1772186145286782976 |