Evaluation of coastal Antarctic precipitation in LMDz6 global atmospheric model using ground-based radar observations

In the current context of climate change in the poles, one of the objectives of the APRES3 (Antarctic Precipitation Remote Sensing from Surface and Space) project was to characterize the vertical structure of precipitation in order to better simulate it. Precipitation simulated by models in Antarcti...

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Published in:Arctic and Antarctic Research
Main Authors: F. Lemonnier, A. Chemison, G. Krinner, J.-B. Madeleine, C. Claud, C. Genthon
Format: Article in Journal/Newspaper
Language:English
Published: Государственный научный центр Российской Федерации Арктический и антарктический научно-исследовательский институт 2021
Subjects:
Online Access:https://www.aaresearch.science/jour/article/view/352
https://doi.org/10.30758/0555-2648-2021-67-2-147-164
id ftjaaresearch:oai:oai.aari.elpub.ru:article/352
record_format openpolar
institution Open Polar
collection Arctic and Antarctic Research
op_collection_id ftjaaresearch
language English
topic polar climate modeling
General Circulation Model evaluation
numerical dissipation evaluation
spellingShingle polar climate modeling
General Circulation Model evaluation
numerical dissipation evaluation
F. Lemonnier
A. Chemison
G. Krinner
J.-B. Madeleine
C. Claud
C. Genthon
Evaluation of coastal Antarctic precipitation in LMDz6 global atmospheric model using ground-based radar observations
topic_facet polar climate modeling
General Circulation Model evaluation
numerical dissipation evaluation
description In the current context of climate change in the poles, one of the objectives of the APRES3 (Antarctic Precipitation Remote Sensing from Surface and Space) project was to characterize the vertical structure of precipitation in order to better simulate it. Precipitation simulated by models in Antarctica is currently very widespread and it overestimates the data. Sensitivity studies have been conducted using a global climate model and compared to the observations obtained at the Dumont d’Urville coast station, obtained by a Micro Rain Radar (MRR). The LMDz/IPSL general circulation model, with zoomed configuration over Dumont d’Urville, has been considered for this study. A sensitivity study was conducted on the physical and numerical parameters of the LMDz model with the aim of estimating their contribution to the precipitation simulation. Sensitivity experiments revealed that changes in the sedimentation and sublimation parameters do not significantly impact precipitation rate. However, dissipation of the LMDz model, which is a numerical process that dissipates spatially excessive energy and keeps the model stable, impacts precipitation indirectly but very strongly. A suitable adjustment of the dissipation reduces significantly precipitation over Antarctic peripheral area, thus providing a simulated profile in better agreement with the MRR observations. In the current context of climate change in the poles, one of the objectives of the APRES3 (Antarctic Precipitation Remote Sensing from Surface and Space) project was to characterize the vertical structure of precipitation in order to better simulate it. Precipitation simulated by models in Antarctica is currently very widespread and it overestimates the data. Sensitivity studies have been conducted using a global climate model and compared to the observations obtained at the Dumont d’Urville coast station, obtained by a Micro Rain Radar (MRR). The LMDz/IPSL general circulation model, with zoomed configuration over Dumont d’Urville, has been considered for this ...
format Article in Journal/Newspaper
author F. Lemonnier
A. Chemison
G. Krinner
J.-B. Madeleine
C. Claud
C. Genthon
author_facet F. Lemonnier
A. Chemison
G. Krinner
J.-B. Madeleine
C. Claud
C. Genthon
author_sort F. Lemonnier
title Evaluation of coastal Antarctic precipitation in LMDz6 global atmospheric model using ground-based radar observations
title_short Evaluation of coastal Antarctic precipitation in LMDz6 global atmospheric model using ground-based radar observations
title_full Evaluation of coastal Antarctic precipitation in LMDz6 global atmospheric model using ground-based radar observations
title_fullStr Evaluation of coastal Antarctic precipitation in LMDz6 global atmospheric model using ground-based radar observations
title_full_unstemmed Evaluation of coastal Antarctic precipitation in LMDz6 global atmospheric model using ground-based radar observations
title_sort evaluation of coastal antarctic precipitation in lmdz6 global atmospheric model using ground-based radar observations
publisher Государственный научный центр Российской Федерации Арктический и антарктический научно-исследовательский институт
publishDate 2021
url https://www.aaresearch.science/jour/article/view/352
https://doi.org/10.30758/0555-2648-2021-67-2-147-164
genre Antarc*
Antarctic
Antarctica
Arctic
The Cryosphere
genre_facet Antarc*
Antarctic
Antarctica
Arctic
The Cryosphere
op_source Arctic and Antarctic Research; Том 67, № 2 (2021); 147-164
Проблемы Арктики и Антарктики; Том 67, № 2 (2021); 147-164
2618-6713
0555-2648
10.30758/0555-2648-2021-67-2
op_relation https://www.aaresearch.science/jour/article/view/352/200
Church J.A., Clark P.U., Cazenave A., Gregory J.M., Jevrejeva S., Levermann A., Merrifield M. A., Milne G.A., Nerem, R.S., Nunn P. D., Payne A., Pfeffer W.T., Stammer D., Unnikrishnan A.S. Sea-level rise by 2100. Science. 2013, 342: 1445–1445.
Shepherd A., Ivins E., Rignot E., Smith B., Van Den Broeke M., Velicogna I., Whitehouse P., Briggs K., Joughin I., Krinner G., Nowicki S., Payne T., Scambos T., Schlegel N., Geruo A., Agosta C., Ahlstrøm A., Babonis G., Barletta V., . Wouters B. Mass balance of the Antarctic Ice Sheet from 1992 to 2017. Nature. 2018, 558: 219–222.
Das I., Bell R.E., Scambos T.A., Wolovick M., Creyts T.T., Studinger M., Frearson N., Nicolas J.P., Lenaerts J.T., van den Broeke M.R. Influence of persistent wind scour on the surface mass balance of Antarctica. Nature Geoscience. 2013, 6 (5): 367–371.
Palerme C., Kay J., Genthon C., L’Ecuyer T., Wood N., Claud C. How much snow falls on the Antarctic ice sheet? The Cryosphere. 2014, 8: 1577–1587.
Souverijns N., Gossart A., Lhermitte S., Gorodetskaya I.V., Grazioli J., Berne A., Duran-Alarcon C., Boudevillain B., Genthon C., Scarchilli C., van Lipzig N.P.M. Evaluation of the CloudSat surface snowfall product over Antarctica using ground-based precipitation radars. The Cryosphere. 2018, 12: 3775–3789. https://doi.org/10.5194/tc-12-3775-2018.
Lemonnier F., Madeleine J., Claud C., Genthon C., Durán-Alarcón C., Palerme C., Berne A., Souverijns N., van Lipzig N., Gorodetskaya I., L’Ecuyer T., Wood N. Evaluation of CloudSat snowfall rate profiles by a comparison with in-situ micro rain radars observations in East Antarctica. The Cryosphere. 2019, 13 (3): 943–954.
Palerme C., Claud C., Wood N., L’Ecuyer T., Genthon C. How does ground clutter affect CloudSat snowfall retrievals over ice sheets? IEEE Geoscience And Remote Sensing Letters. 2019, 16: 342–346.
Eisen O., Frezzotti M., Genthon C., Isaksson E., Magand O., van den Broeke M.R., Dixon D.A., Ekaykin A., Holmlund P., Kameda T., Karlof L., Kaspari S., Lipenkov V.Y., Oerter H., Takahashi S., Vaughan D.G. Ground-based measurements of spatial and temporal variability of snow accumulation in East Antarctica. Reviews of Geophysics. 2008, 46(RG2001), doi:10.1029/2006RG000218.
Taylor K.E., Stouffer R.J., Meehl G.A. An overview of CMIP5 and the experiment design. Bulletin of the American Meteorological Society. 2012, 93: 485–498.
Krinner G., Guicherd B., Ox K., Genthon C., Magand O. Influence of oceanic boundary conditions in simulations of Antarctic climate and surface mass balance change during the coming century. Journal of Climate. 2008, 21: 938–962.
Palerme C., Genthon C., Claud C., Kay J.E., Wood N.B., L’Ecuyer T. Evaluation of current and projected Antarctic precipitation in CMIP5 models. Climate Dynamics. 2017, 48: 225–239.
Roussel M.-L., Lemonnier F., Genthon C., Krinner G. Evaluating Antarctic precipitation in ERA5 and CMIP6 10 against CloudSat observations. The Cryosphere. 2020, 14: 2715–2727.
Grazioli J., Genthon C., Boudevillain B., Duran-Alarcon C., Del Guasta M., Jean-Baptiste M., Berne A. Measurements of precipitation in Dumont d’Urville, Adélie Land, East Antarctica. The Cryosphere. 2017, 11: 1797–1811.
Grazioli J., Madeleine J.-B., Gallée H., Forbes R. M., Genthon C., Krinner G., Berne A. Katabatic winds diminish precipitation contribution to the Antarctic ice mass balance. Proceedings of the National Academy of Sciences. 2017, 114: 10858–10863.
Durán-Alarcón C., Boudevillain B., Genthon C., Grazioli J., Souverijns N., van Lipzig N.P.M., Gorodetskaya I.V., Berne A. The vertical structure of precipitation at two stations in East Antarctica derived from micro rain radars. The Cryosphere. 2019, 13: 247–264.
Hourdin F., Rio C., Grandpeix J.-Y., Madeleine J.-B., Cheruy F., Rochetin N., Jam A., Musat I., Idelkadi A., Fairhead L., Foujols M.-A., Mellul L., Traore A.-K., Dufresne J.-L., Boucher O., Lefebvre M.-P., Millour E., Vignon E., Jouhaud J., Diallo F.B., Lott F., Gastineau G., Caubel A., Meurdesoif Y., Ghattas J. LMDZ6A: the atmospheric component of the IPSL climate model with improved and better tuned physics. Journal of Advances in Modeling Earth Systems. 2020, 12 (7): e2019MS001892.
Madeleine J.-B., Hourdin F., Grandpeix J.-Y., Rio C., Dufresne J.-L., Vignon E., Boucher O., Konsta D., Cheruy F., Musat I., Idelkadi A., Fairhead L., Millour E., Lefebvre M.-P., Mellul L., Rochetin N., Lemonnier F., Touzé-Peiffer L., Bonazzola M. Improved representation of clouds in the atmospheric component LMDZ6A of the IPSL-CM6A Earth System Model. Journal of Advances in Modeling Earth Systems. 2020, 12 (10): e2020MS002046.
Mlawer E.J., Taubman S.J., Brown P.D., Iacono M.J., Clough S.A. Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave. Journal of Geophysical Research: Atmospheres. 1997, 102: 16663–16682.
Zender C.S., Kiehl J. Sensitivity of climate simulations to radiative effects of tropical anvil structure. Journal of Geophysical Research: Atmospheres. 1997, 102: 23793–23803.
Heymsfield A.J., Donner L.J. A scheme for parameterizing ice-cloud water content in general circulation models. Journal of the Atmospheric Sciences. 1990, 47: 1865–1877.
Vignon E., Hourdin F., Genthon C., Gallée H., Bazile E., Lefebvre M.-P., Madeleine J.-B., Van de Wiel B.J. Antarctic boundary layer parametrization in a general circulation model: 1-D simulations facing summer observations at Dome C. Journal of Geophysical Research: Atmospheres. 2017, 122: 6818–6843.
Coindreau O., Hourdin F., Haeffelin M., Mathieu A., Rio C. Assessment of physical parameterizations using a global climate model with stretchable grid and nudging. Monthly weather review. 2007, 135: 1474–1489.
Maahn M., Kollias P. Improved Micro Rain Radar snow measurements using Doppler spectra post-processing. Atmos. Meas. Tech. 2012, 5: 2661– 2673.
Jablonowski C., Williamson D.L. The pros and cons of diffusion, filters and fixers in atmospheric general circulation models. In: Lauritzen P., Jablonowski C., Taylor M., Nair R. (eds) Numerical Techniques for Global Atmospheric Models. Lecture Notes in Computational Science and Engineering, vol 80. Springer, Berlin, Heidelberg, 2011: 381–493.
Spiga A., Guerlet S., Millour E., Indurain M., Meurdesoif Y., Cabanes S., Dubos T., Leconte J., Boissinot A., Lebonnois S., Sylvestre M., Fouchet T. Global climate modeling of Saturn’s atmosphere. Part II: multi-annual high-resolution dynamical simulations. Icarus, Elsevier. 2020, 335: 113377. 10.1016/j.icarus.2019.07.011. hal-02278447.
https://www.aaresearch.science/jour/article/view/352
doi:10.30758/0555-2648-2021-67-2-147-164
op_rights Authors retain the copyright of their papers without restriction and grant the Arctic and Antarctic Research (Russia) journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License.
Авторы, публикующиеся в данном Журнале, сохраняют авторские права на свое произведение и предоставляют Журналу право публикации на условиях лицензии Creative Commons Attribution International 4.0 CC-BY, которая позволяет неограниченно использовать произведения при условии указания авторства и ссылки на оригинальную публикацию в Журнале.
op_doi https://doi.org/10.30758/0555-2648-2021-67-2-147-16410.30758/0555-2648-2021-67-210.5194/tc-12-3775-201810.1029/2006RG00021810.1016/j.icarus.2019.07.011.
container_title Arctic and Antarctic Research
container_volume 67
container_issue 2
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spelling ftjaaresearch:oai:oai.aari.elpub.ru:article/352 2024-09-15T17:44:35+00:00 Evaluation of coastal Antarctic precipitation in LMDz6 global atmospheric model using ground-based radar observations F. Lemonnier A. Chemison G. Krinner J.-B. Madeleine C. Claud C. Genthon 2021-07-09 application/pdf https://www.aaresearch.science/jour/article/view/352 https://doi.org/10.30758/0555-2648-2021-67-2-147-164 eng eng Государственный научный центр Российской Федерации Арктический и антарктический научно-исследовательский институт https://www.aaresearch.science/jour/article/view/352/200 Church J.A., Clark P.U., Cazenave A., Gregory J.M., Jevrejeva S., Levermann A., Merrifield M. A., Milne G.A., Nerem, R.S., Nunn P. D., Payne A., Pfeffer W.T., Stammer D., Unnikrishnan A.S. Sea-level rise by 2100. Science. 2013, 342: 1445–1445. Shepherd A., Ivins E., Rignot E., Smith B., Van Den Broeke M., Velicogna I., Whitehouse P., Briggs K., Joughin I., Krinner G., Nowicki S., Payne T., Scambos T., Schlegel N., Geruo A., Agosta C., Ahlstrøm A., Babonis G., Barletta V., . Wouters B. Mass balance of the Antarctic Ice Sheet from 1992 to 2017. Nature. 2018, 558: 219–222. Das I., Bell R.E., Scambos T.A., Wolovick M., Creyts T.T., Studinger M., Frearson N., Nicolas J.P., Lenaerts J.T., van den Broeke M.R. Influence of persistent wind scour on the surface mass balance of Antarctica. Nature Geoscience. 2013, 6 (5): 367–371. Palerme C., Kay J., Genthon C., L’Ecuyer T., Wood N., Claud C. How much snow falls on the Antarctic ice sheet? The Cryosphere. 2014, 8: 1577–1587. Souverijns N., Gossart A., Lhermitte S., Gorodetskaya I.V., Grazioli J., Berne A., Duran-Alarcon C., Boudevillain B., Genthon C., Scarchilli C., van Lipzig N.P.M. Evaluation of the CloudSat surface snowfall product over Antarctica using ground-based precipitation radars. The Cryosphere. 2018, 12: 3775–3789. https://doi.org/10.5194/tc-12-3775-2018. Lemonnier F., Madeleine J., Claud C., Genthon C., Durán-Alarcón C., Palerme C., Berne A., Souverijns N., van Lipzig N., Gorodetskaya I., L’Ecuyer T., Wood N. Evaluation of CloudSat snowfall rate profiles by a comparison with in-situ micro rain radars observations in East Antarctica. The Cryosphere. 2019, 13 (3): 943–954. Palerme C., Claud C., Wood N., L’Ecuyer T., Genthon C. How does ground clutter affect CloudSat snowfall retrievals over ice sheets? IEEE Geoscience And Remote Sensing Letters. 2019, 16: 342–346. Eisen O., Frezzotti M., Genthon C., Isaksson E., Magand O., van den Broeke M.R., Dixon D.A., Ekaykin A., Holmlund P., Kameda T., Karlof L., Kaspari S., Lipenkov V.Y., Oerter H., Takahashi S., Vaughan D.G. Ground-based measurements of spatial and temporal variability of snow accumulation in East Antarctica. Reviews of Geophysics. 2008, 46(RG2001), doi:10.1029/2006RG000218. Taylor K.E., Stouffer R.J., Meehl G.A. An overview of CMIP5 and the experiment design. Bulletin of the American Meteorological Society. 2012, 93: 485–498. Krinner G., Guicherd B., Ox K., Genthon C., Magand O. Influence of oceanic boundary conditions in simulations of Antarctic climate and surface mass balance change during the coming century. Journal of Climate. 2008, 21: 938–962. Palerme C., Genthon C., Claud C., Kay J.E., Wood N.B., L’Ecuyer T. Evaluation of current and projected Antarctic precipitation in CMIP5 models. Climate Dynamics. 2017, 48: 225–239. Roussel M.-L., Lemonnier F., Genthon C., Krinner G. Evaluating Antarctic precipitation in ERA5 and CMIP6 10 against CloudSat observations. The Cryosphere. 2020, 14: 2715–2727. Grazioli J., Genthon C., Boudevillain B., Duran-Alarcon C., Del Guasta M., Jean-Baptiste M., Berne A. Measurements of precipitation in Dumont d’Urville, Adélie Land, East Antarctica. The Cryosphere. 2017, 11: 1797–1811. Grazioli J., Madeleine J.-B., Gallée H., Forbes R. M., Genthon C., Krinner G., Berne A. Katabatic winds diminish precipitation contribution to the Antarctic ice mass balance. Proceedings of the National Academy of Sciences. 2017, 114: 10858–10863. Durán-Alarcón C., Boudevillain B., Genthon C., Grazioli J., Souverijns N., van Lipzig N.P.M., Gorodetskaya I.V., Berne A. The vertical structure of precipitation at two stations in East Antarctica derived from micro rain radars. The Cryosphere. 2019, 13: 247–264. Hourdin F., Rio C., Grandpeix J.-Y., Madeleine J.-B., Cheruy F., Rochetin N., Jam A., Musat I., Idelkadi A., Fairhead L., Foujols M.-A., Mellul L., Traore A.-K., Dufresne J.-L., Boucher O., Lefebvre M.-P., Millour E., Vignon E., Jouhaud J., Diallo F.B., Lott F., Gastineau G., Caubel A., Meurdesoif Y., Ghattas J. LMDZ6A: the atmospheric component of the IPSL climate model with improved and better tuned physics. Journal of Advances in Modeling Earth Systems. 2020, 12 (7): e2019MS001892. Madeleine J.-B., Hourdin F., Grandpeix J.-Y., Rio C., Dufresne J.-L., Vignon E., Boucher O., Konsta D., Cheruy F., Musat I., Idelkadi A., Fairhead L., Millour E., Lefebvre M.-P., Mellul L., Rochetin N., Lemonnier F., Touzé-Peiffer L., Bonazzola M. Improved representation of clouds in the atmospheric component LMDZ6A of the IPSL-CM6A Earth System Model. Journal of Advances in Modeling Earth Systems. 2020, 12 (10): e2020MS002046. Mlawer E.J., Taubman S.J., Brown P.D., Iacono M.J., Clough S.A. Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave. Journal of Geophysical Research: Atmospheres. 1997, 102: 16663–16682. Zender C.S., Kiehl J. Sensitivity of climate simulations to radiative effects of tropical anvil structure. Journal of Geophysical Research: Atmospheres. 1997, 102: 23793–23803. Heymsfield A.J., Donner L.J. A scheme for parameterizing ice-cloud water content in general circulation models. Journal of the Atmospheric Sciences. 1990, 47: 1865–1877. Vignon E., Hourdin F., Genthon C., Gallée H., Bazile E., Lefebvre M.-P., Madeleine J.-B., Van de Wiel B.J. Antarctic boundary layer parametrization in a general circulation model: 1-D simulations facing summer observations at Dome C. Journal of Geophysical Research: Atmospheres. 2017, 122: 6818–6843. Coindreau O., Hourdin F., Haeffelin M., Mathieu A., Rio C. Assessment of physical parameterizations using a global climate model with stretchable grid and nudging. Monthly weather review. 2007, 135: 1474–1489. Maahn M., Kollias P. Improved Micro Rain Radar snow measurements using Doppler spectra post-processing. Atmos. Meas. Tech. 2012, 5: 2661– 2673. Jablonowski C., Williamson D.L. The pros and cons of diffusion, filters and fixers in atmospheric general circulation models. In: Lauritzen P., Jablonowski C., Taylor M., Nair R. (eds) Numerical Techniques for Global Atmospheric Models. Lecture Notes in Computational Science and Engineering, vol 80. Springer, Berlin, Heidelberg, 2011: 381–493. Spiga A., Guerlet S., Millour E., Indurain M., Meurdesoif Y., Cabanes S., Dubos T., Leconte J., Boissinot A., Lebonnois S., Sylvestre M., Fouchet T. Global climate modeling of Saturn’s atmosphere. Part II: multi-annual high-resolution dynamical simulations. Icarus, Elsevier. 2020, 335: 113377. 10.1016/j.icarus.2019.07.011. hal-02278447. https://www.aaresearch.science/jour/article/view/352 doi:10.30758/0555-2648-2021-67-2-147-164 Authors retain the copyright of their papers without restriction and grant the Arctic and Antarctic Research (Russia) journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License. Авторы, публикующиеся в данном Журнале, сохраняют авторские права на свое произведение и предоставляют Журналу право публикации на условиях лицензии Creative Commons Attribution International 4.0 CC-BY, которая позволяет неограниченно использовать произведения при условии указания авторства и ссылки на оригинальную публикацию в Журнале. Arctic and Antarctic Research; Том 67, № 2 (2021); 147-164 Проблемы Арктики и Антарктики; Том 67, № 2 (2021); 147-164 2618-6713 0555-2648 10.30758/0555-2648-2021-67-2 polar climate modeling General Circulation Model evaluation numerical dissipation evaluation info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion 2021 ftjaaresearch https://doi.org/10.30758/0555-2648-2021-67-2-147-16410.30758/0555-2648-2021-67-210.5194/tc-12-3775-201810.1029/2006RG00021810.1016/j.icarus.2019.07.011. 2024-07-25T23:30:58Z In the current context of climate change in the poles, one of the objectives of the APRES3 (Antarctic Precipitation Remote Sensing from Surface and Space) project was to characterize the vertical structure of precipitation in order to better simulate it. Precipitation simulated by models in Antarctica is currently very widespread and it overestimates the data. Sensitivity studies have been conducted using a global climate model and compared to the observations obtained at the Dumont d’Urville coast station, obtained by a Micro Rain Radar (MRR). The LMDz/IPSL general circulation model, with zoomed configuration over Dumont d’Urville, has been considered for this study. A sensitivity study was conducted on the physical and numerical parameters of the LMDz model with the aim of estimating their contribution to the precipitation simulation. Sensitivity experiments revealed that changes in the sedimentation and sublimation parameters do not significantly impact precipitation rate. However, dissipation of the LMDz model, which is a numerical process that dissipates spatially excessive energy and keeps the model stable, impacts precipitation indirectly but very strongly. A suitable adjustment of the dissipation reduces significantly precipitation over Antarctic peripheral area, thus providing a simulated profile in better agreement with the MRR observations. In the current context of climate change in the poles, one of the objectives of the APRES3 (Antarctic Precipitation Remote Sensing from Surface and Space) project was to characterize the vertical structure of precipitation in order to better simulate it. Precipitation simulated by models in Antarctica is currently very widespread and it overestimates the data. Sensitivity studies have been conducted using a global climate model and compared to the observations obtained at the Dumont d’Urville coast station, obtained by a Micro Rain Radar (MRR). The LMDz/IPSL general circulation model, with zoomed configuration over Dumont d’Urville, has been considered for this ... Article in Journal/Newspaper Antarc* Antarctic Antarctica Arctic The Cryosphere Arctic and Antarctic Research Arctic and Antarctic Research 67 2 147 164