Estimation of the Antarctic surface mass balance using the regional climate model MAR (1979–2015) and identification of dominant processes
<p>The Antarctic ice sheet mass balance is a major component of the sea level budget and results from the difference of two fluxes of a similar magnitude: ice flow discharging in the ocean and net snow accumulation on the ice sheet surface, i.e. the surface mass balance (SMB). Separately model...
| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2019-01-01
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| Series: | The Cryosphere |
| Online Access: | https://www.the-cryosphere.net/13/281/2019/tc-13-281-2019.pdf |
| _version_ | 1818509681749917696 |
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| author | C. Agosta C. Agosta C. Agosta C. Amory C. Kittel A. Orsi V. Favier H. Gallée M. R. van den Broeke J. T. M. Lenaerts J. T. M. Lenaerts J. M. van Wessem W. J. van de Berg X. Fettweis |
| author_facet | C. Agosta C. Agosta C. Agosta C. Amory C. Kittel A. Orsi V. Favier H. Gallée M. R. van den Broeke J. T. M. Lenaerts J. T. M. Lenaerts J. M. van Wessem W. J. van de Berg X. Fettweis |
| author_sort | C. Agosta |
| collection | DOAJ |
| description | <p>The Antarctic ice sheet mass balance is a major component of the sea level
budget and results from the difference of two fluxes of a similar magnitude:
ice flow discharging in the ocean and net snow accumulation on the ice sheet
surface, i.e. the surface mass balance (SMB). Separately modelling ice
dynamics and SMB is the only way to project future trends.
In addition, mass balance studies frequently use regional climate models
(RCMs) outputs as an alternative to observed fields because SMB observations
are particularly scarce on the ice sheet. Here we evaluate new simulations of
the polar RCM MAR forced by three reanalyses, ERA-Interim, JRA-55, and MERRA-2,
for the period 1979–2015, and we compare MAR results to the last outputs of
the RCM RACMO2 forced by ERA-Interim. We show that MAR and RACMO2 perform
similarly well in simulating coast-to-plateau SMB gradients, and we find no
significant differences in their simulated SMB when integrated over the ice
sheet or its major basins. More importantly, we outline and quantify missing
or underestimated processes in both RCMs. Along stake transects, we show that
both models accumulate too much snow on crests, and not enough snow in
valleys, as a result of drifting snow transport fluxes not included in MAR
and probably underestimated in RACMO2 by a factor of 3. Our results tend
to confirm that drifting snow transport and sublimation fluxes are much
larger than previous model-based estimates and need to be better resolved and
constrained in climate models. Sublimation of precipitating particles in
low-level atmospheric layers is responsible for the significantly lower
snowfall rates in MAR than in RACMO2 in katabatic channels at the ice sheet
margins. Atmospheric sublimation in MAR represents 363 <span class="inline-formula">Gt</span> <span class="inline-formula">yr<sup>−1</sup></span> over the grounded ice sheet for the year 2015, which is 16 %
of the simulated snowfall loaded at the ground. This estimate is consistent
with a recent study based on precipitation radar observations and is more
than twice as much as simulated in RACMO2 because of different time
residence of precipitating particles in the atmosphere. The remaining spatial
differences in snowfall between MAR and RACMO2 are attributed to differences
in advection of precipitation with snowfall particles being likely advected too
far inland in MAR.</p> |
| first_indexed | 2024-12-10T22:48:43Z |
| format | Article |
| id | doaj.art-85ac8d38c6ae4927831899c19fc31f36 |
| institution | Directory Open Access Journal |
| issn | 1994-0416 1994-0424 |
| language | English |
| last_indexed | 2024-12-10T22:48:43Z |
| publishDate | 2019-01-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | The Cryosphere |
| spelling | doaj.art-85ac8d38c6ae4927831899c19fc31f362022-12-22T01:30:30ZengCopernicus PublicationsThe Cryosphere1994-04161994-04242019-01-011328129610.5194/tc-13-281-2019Estimation of the Antarctic surface mass balance using the regional climate model MAR (1979–2015) and identification of dominant processesC. Agosta0C. Agosta1C. Agosta2C. Amory3C. Kittel4A. Orsi5V. Favier6H. Gallée7M. R. van den Broeke8J. T. M. Lenaerts9J. T. M. Lenaerts10J. M. van Wessem11W. J. van de Berg12X. Fettweis13F.R.S.-FNRS, Laboratory of Climatology, Department of Geography, University of Liège, 4000 Liège, BelgiumLaboratoire des Sciences du Climat et de l'Environnement (IPSL/CEA-CNRS-UVSQ UMR8212), CEA Saclay, 91190 Gif-sur-Yvette, FranceUniversité Grenoble Alpes, CNRS, Institut des Géosciences de l'Environnement, 38000, Grenoble, FranceF.R.S.-FNRS, Laboratory of Climatology, Department of Geography, University of Liège, 4000 Liège, BelgiumF.R.S.-FNRS, Laboratory of Climatology, Department of Geography, University of Liège, 4000 Liège, BelgiumLaboratoire des Sciences du Climat et de l'Environnement (IPSL/CEA-CNRS-UVSQ UMR8212), CEA Saclay, 91190 Gif-sur-Yvette, FranceUniversité Grenoble Alpes, CNRS, Institut des Géosciences de l'Environnement, 38000, Grenoble, FranceUniversité Grenoble Alpes, CNRS, Institut des Géosciences de l'Environnement, 38000, Grenoble, FranceInstitute for Marine and Atmospheric Research Utrecht, Utrecht University, Utrecht, the NetherlandsInstitute for Marine and Atmospheric Research Utrecht, Utrecht University, Utrecht, the NetherlandsDepartment of Atmospheric and Oceanic Sciences, University of Colorado Boulder, Boulder, CO, USAInstitute for Marine and Atmospheric Research Utrecht, Utrecht University, Utrecht, the NetherlandsInstitute for Marine and Atmospheric Research Utrecht, Utrecht University, Utrecht, the NetherlandsF.R.S.-FNRS, Laboratory of Climatology, Department of Geography, University of Liège, 4000 Liège, Belgium<p>The Antarctic ice sheet mass balance is a major component of the sea level budget and results from the difference of two fluxes of a similar magnitude: ice flow discharging in the ocean and net snow accumulation on the ice sheet surface, i.e. the surface mass balance (SMB). Separately modelling ice dynamics and SMB is the only way to project future trends. In addition, mass balance studies frequently use regional climate models (RCMs) outputs as an alternative to observed fields because SMB observations are particularly scarce on the ice sheet. Here we evaluate new simulations of the polar RCM MAR forced by three reanalyses, ERA-Interim, JRA-55, and MERRA-2, for the period 1979–2015, and we compare MAR results to the last outputs of the RCM RACMO2 forced by ERA-Interim. We show that MAR and RACMO2 perform similarly well in simulating coast-to-plateau SMB gradients, and we find no significant differences in their simulated SMB when integrated over the ice sheet or its major basins. More importantly, we outline and quantify missing or underestimated processes in both RCMs. Along stake transects, we show that both models accumulate too much snow on crests, and not enough snow in valleys, as a result of drifting snow transport fluxes not included in MAR and probably underestimated in RACMO2 by a factor of 3. Our results tend to confirm that drifting snow transport and sublimation fluxes are much larger than previous model-based estimates and need to be better resolved and constrained in climate models. Sublimation of precipitating particles in low-level atmospheric layers is responsible for the significantly lower snowfall rates in MAR than in RACMO2 in katabatic channels at the ice sheet margins. Atmospheric sublimation in MAR represents 363 <span class="inline-formula">Gt</span> <span class="inline-formula">yr<sup>−1</sup></span> over the grounded ice sheet for the year 2015, which is 16 % of the simulated snowfall loaded at the ground. This estimate is consistent with a recent study based on precipitation radar observations and is more than twice as much as simulated in RACMO2 because of different time residence of precipitating particles in the atmosphere. The remaining spatial differences in snowfall between MAR and RACMO2 are attributed to differences in advection of precipitation with snowfall particles being likely advected too far inland in MAR.</p>https://www.the-cryosphere.net/13/281/2019/tc-13-281-2019.pdf |
| spellingShingle | C. Agosta C. Agosta C. Agosta C. Amory C. Kittel A. Orsi V. Favier H. Gallée M. R. van den Broeke J. T. M. Lenaerts J. T. M. Lenaerts J. M. van Wessem W. J. van de Berg X. Fettweis Estimation of the Antarctic surface mass balance using the regional climate model MAR (1979–2015) and identification of dominant processes The Cryosphere |
| title | Estimation of the Antarctic surface mass balance using the regional climate model MAR (1979–2015) and identification of dominant processes |
| title_full | Estimation of the Antarctic surface mass balance using the regional climate model MAR (1979–2015) and identification of dominant processes |
| title_fullStr | Estimation of the Antarctic surface mass balance using the regional climate model MAR (1979–2015) and identification of dominant processes |
| title_full_unstemmed | Estimation of the Antarctic surface mass balance using the regional climate model MAR (1979–2015) and identification of dominant processes |
| title_short | Estimation of the Antarctic surface mass balance using the regional climate model MAR (1979–2015) and identification of dominant processes |
| title_sort | estimation of the antarctic surface mass balance using the regional climate model mar 1979 2015 and identification of dominant processes |
| url | https://www.the-cryosphere.net/13/281/2019/tc-13-281-2019.pdf |
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