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2. Extremes of summer Arctic sea ice reduction investigated with a rare event algorithm

Author

Sauer, Jerome, Demaeyer, Jonathan, Zappa, Giuseppe, Massonnet, François, and Ragone, Francesco

Subjects
Physics - Atmospheric and Oceanic Physics
Abstract

Various studies identified possible drivers of extremes of Arctic sea ice reduction, such as observed in the summers of 2007 and 2012, including preconditioning, local feedback mechanisms, oceanic heat transport and the synoptic- and large-scale atmospheric circulations. However, a robust quantitative statistical analysis of extremes of sea ice reduction is hindered by the small number of events that can be sampled in observations and numerical simulations with computationally expensive climate models. Recent studies tackled the problem of sampling climate extremes by using rare event algorithms, i.e., computational techniques developed in statistical physics to reduce the computational cost required to sample rare events in numerical simulations. Here we apply a rare event algorithm to ensemble simulations with the intermediate complexity coupled climate model PlaSim-LSG to investigate extreme negative summer pan-Arctic sea ice area anomalies under pre-industrial greenhouse gas conditions. Owing to the algorithm, we estimate return times of extremes orders of magnitude larger than feasible with direct sampling, and we compute statistically significant composite maps of dynamical quantities conditional on the occurrence of these extremes. We find that extremely low sea ice summers in PlaSim-LSG are associated with preconditioning through the winter sea ice-ocean state, with enhanced downward longwave radiation due to an anomalously moist and warm spring Arctic atmosphere and with enhanced downward sensible heat fluxes during the spring-summer transition. As a consequence of these three processes, the sea ice-albedo feedback becomes active in spring and leads to an amplification of pre-existing sea ice area anomalies during summer.

Published
2023

10. Antarctica and the Southern Ocean

Author

Abrahamsen, E Povl, Barreira, Sandra, Bitz, Cecilia M, Butler, Amy, Clem, Kyle R, Colwell, Steve, Coy, Lawrence, de Laat, Jos, du Plessis, Marcel D, Fogt, Ryan L, Fricker, Helen Amanda, Fyfe, John, Gardner, Alex S, Gille, Sarah T, Gorte, Tessa, Gregor, L, Hobbs, Will, Johnson, Bryan, Keenan, Eric, Keller, Linda M, Kramarova, Natalya A, Lazzara, Matthew A, Lenaerts, Jan TM, Lieser, Jan L, Liu, Hongxing, Long, Craig S, Maclennan, Michelle, Massom, Robert A, Massonnet, François, Mazloff, Matthew R, Mikolajczyk, David, Narayanan, A, Nash, Eric R, Newman, Paul A, Petropavlovskikh, Irina, Pitts, Michael, Queste, Bastien Y, Reid, Phillip, Roquet, F, Santee, Michelle L, Strahan, Susan, Swart, Sebastiann, and Wang, Lei

Subjects
Astronomical and Space Sciences, Atmospheric Sciences, Physical Geography and Environmental Geoscience, Meteorology & Atmospheric Sciences
Published
2020

11. Antarctic Sea Ice Area in CMIP6

Author

Roach, Lettie A, Dörr, Jakob, Holmes, Caroline R, Massonnet, François, Blockley, Edward W, Notz, Dirk, Rackow, Thomas, Raphael, Marilyn N, O'Farrell, Siobhan P, Bailey, David A, and Bitz, Cecilia M

Subjects
Climate Action, sea ice, CMIP6, Antarctica, climate models, Southern Ocean, model evaluation, Meteorology & Atmospheric Sciences
Abstract

Fully coupled climate models have long shown a wide range of Antarctic sea ice states and evolution over the satellite era. Here, we present a high-level evaluation of Antarctic sea ice in 40 models from the most recent phase of the Coupled Model Intercomparison Project (CMIP6). Many models capture key characteristics of the mean seasonal cycle of sea ice area (SIA), but some simulate implausible historical mean states compared to satellite observations, leading to large intermodel spread. Summer SIA is consistently biased low across the ensemble. Compared to the previous model generation (CMIP5), the intermodel spread in winter and summer SIA has reduced, and the regional distribution of sea ice concentration has improved. Over 1979–2018, many models simulate strong negative trends in SIA concurrently with stronger-than-observed trends in global mean surface temperature (GMST). By the end of the 21st century, models project clear differences in sea ice between forcing scenarios.

Published
2020

12. Moving Sea Ice Prediction Forward via Community Intercomparison

Author

Steele, Michael, Eicken, Hajo, Bhatt, Uma, Bieniek, Peter, Blanchard-Wrigglesworth, Ed, Wiggins, Helen, Turner-Bogren, Betsy, Hamilton, Lawrence, Little, Joseph, Massonnet, François, Meier, Walter N., Overland, James, Serreze, Mark, Stroeve, Julienne, Walsh, John, and Wang, Muyin

Published
2021

15. Year of Polar Prediction : A Focus on Antarctica

Author

Bromwich, David H., Werner, Kirstin, Casati, Barbara, Powers, Jordan G., Gorodetskaya, Irina V., Massonnet, Francois, Vitale, Vito, Heinrich, Victoria J., Liggett, Daniela, Arndt, Stefanie, Barja, Boris, Bazile, Eric, Carpentier, Scott, Carrasco, Jorge F., Choi, Taejin, Choi, Yonghan, Colwell, Steven R., Cordero, Raul R., Gervasi, Massimo, Haiden, Thomas, Hirasawa, Naohiko, Inoue, Jun, Jung, Thomas, Kalesse, Heike, Kim, Seong-Joong, Lazzara, Matthew A., Manning, Kevin W., Norris, Kimberley, Park, Sang-Jong, Reid, Phillip, Rigor, Ignatius, Rowe, Penny M., Schmithüsen, Holger, Seifert, Patric, Sun, Qizhen, Uttal, Taneil, Zannoni, Mario, and Zou, Xun

Published
2021

16. Impact of ocean vertical-mixing parameterization on Arctic sea ice and upper-ocean properties using the NEMO-SI3 model.

Author

Allende, Sofia, Treguier, Anne Marie, Lique, Camille, de Boyer Montégut, Clément, Massonnet, François, Fichefet, Thierry, and Barthélemy, Antoine

Subjects
ATMOSPHERIC boundary layer, MIXING height (Atmospheric chemistry), OCEANIC mixing, SURFACE temperature, PARAMETERIZATION
Abstract

We evaluate the vertical turbulent-kinetic-energy (TKE) mixing scheme of the NEMO-SI3 ocean–sea-ice model in sea-ice-covered regions of the Arctic Ocean. Specifically, we assess the parameters involved in TKE mixed-layer-penetration (MLP) parameterization. This ad hoc parameterization aims to capture processes that impact the ocean surface boundary layer, such as near-inertial oscillations, ocean swells, and waves, which are often not well represented in the default TKE scheme. We evaluate this parameterization for the first time in three regions of the Arctic Ocean: the Makarov, Eurasian, and Canada basins. We demonstrate the strong effect of the scaling parameter that accounts for the presence of sea ice. Our results confirm that TKE MLP must be scaled down below sea ice to avoid unrealistically deep mixed layers. The other parameters evaluated are the percentage of energy penetrating below the mixed layer and the length scale of its decay with depth. All these parameters affect mixed-layer depth and its seasonal cycle, surface temperature, and salinity, as well as underlying stratification. Shallow mixed layers are associated with stronger stratification and fresh surface anomalies, and deeper mixed layers correspond to weaker stratification and salty surface anomalies. Notably, we observe significant impacts on sea-ice thickness across the Arctic Ocean in two scenarios: when the scaling parameter due to sea ice is absent and when the TKE mixed-layer-penetration process vanishes. In the former case, we observe an increase of several meters in mixed-layer depth, along with a reduction in sea-ice thickness ranging from 30 to 40 cm, reflecting the impact of stronger mixing. Conversely, in the latter case, we notice that a shallower mixed layer is accompanied by a moderate increase in sea-ice thickness, ranging from 10 to 20 cm, as expected from weaker mixing. Additionally, interannual variability suggests that experiments incorporating a scaling parameter based on sea-ice concentration display an increased mixed-layer depth during periods of reduced sea ice, which is consistent with observed trends. These findings underscore the influence of enhanced ocean mixing, through specific parameterizations, on the physical properties of the upper ocean and sea ice. [ABSTRACT FROM AUTHOR]

Published
2024
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21. The Year of Polar Prediction in the Southern Hemisphere (YOPP-SH)

Author

Bromwich, David H., Werner, Kirstin, Casati, Barbara, Powers, Jordan G., Gorodetskaya, Irina V., Massonnet, François, Vitale, Vito, Heinrich, Victoria J., Liggett, Daniela, Arndt, Stefanie, Barja, Boris, Bazile, Eric, Carpentier, Scott, Carrasco, Jorge F., Choi, Taejin, Choi, Yonghan, Colwell, Steven R., Cordero, Raul R., Gervasi, Massimo, Haiden, Thomas, Hirasawa, Naohiko, Inoue, Jun, Jung, Thomas, Kalesse, Heike, Kim, Seong-Joong, Lazzara, Matthew A., Manning, Kevin W., Norris, Kimberley, Park, Sang-Jong, Reid, Phillip, Rigor, Ignatius, Rowe, Penny M., Schmithüsen, Holger, Seifert, Patric, Sun, Qizhen, Uttal, Taneil, Zannoni, Mario, and Zou, Xun

Published
2020

22. The Future of Sea Ice Modeling : Where Do We Go from Here?

Author

Blockley, Ed, Vancoppenolle, Martin, Hunke, Elizabeth, Bitz, Cecilia, Feltham, Daniel, Lemieux, Jean-François, Losch, Martin, Maisonnave, Eric, Notz, Dirk, Rampal, Pierre, Tietsche, Steffen, Tremblay, Bruno, Turner, Adrian, Massonnet, François, Ólason, Einar, Roberts, Andrew, Aksenov, Yevgeny, Fichefet, Thierry, Garric, Gilles, Iovino, Doroteaciro, Madec, Gurvan, Rousset, Clément, Salas y Melia, David, and Schroeder, David

Published
2020

25. Predicting September Arctic Sea Ice: A Multi-Model Seasonal Skill Comparison

Author

Bushuk, Mitchell, Ali, Sahara, Bailey, David A, Bao, Qing, Batté, Lauriane, Bhatt, Uma S, Blanchard-Wrigglesworth, Edward, Blockley, Ed, Cawley, Gavin, Chi, Junhwa, Counillon, François, Coulombe, Philippe Goulet, Cullather, Richard I, Diebold, Francis X, Dirkson, Arlan, Exarchou, Eleftheria, Göbel, Maximilian, Gregory, William, Guemas, Virginie, Hamilton, Lawrence, He, Bian, Horvath, Sean, Ionita, Monica, Kay, Jennifer E, Kim, Eliot, Kimura, Noriaki, Kondrashov, Dmitri, Labe, Zachary M, Lee, WooSung, Lee, Younjoo J, Li, Cuihua, Li, Xuewei, Lin, Yongcheng, Liu, Yanyun, Maslowski, Wieslaw, Massonnet, François, Meier, Walter N, Merryfield, William J, Myint, Hannah, Navarro, Juan C Acosta, Petty, Alek, Qiao, Fangli, Schröder, David, Schweiger, Axel, Shu, Qi, Sigmond, Michael, Steele, Michael, Stroeve, Julienne, Sun, Nico, Tietsche, Steffen, Tsamados, Michel, Wang, Keguang, Wang, Jianwu, Wang, Wanqiu, Wang, Yiguo, Wang, Yun, Williams, James, Yang, Qinghua, Yuan, Xiaojun, Zhang, Jinlun, Zhang, Yongfei, Bushuk, Mitchell, Ali, Sahara, Bailey, David A, Bao, Qing, Batté, Lauriane, Bhatt, Uma S, Blanchard-Wrigglesworth, Edward, Blockley, Ed, Cawley, Gavin, Chi, Junhwa, Counillon, François, Coulombe, Philippe Goulet, Cullather, Richard I, Diebold, Francis X, Dirkson, Arlan, Exarchou, Eleftheria, Göbel, Maximilian, Gregory, William, Guemas, Virginie, Hamilton, Lawrence, He, Bian, Horvath, Sean, Ionita, Monica, Kay, Jennifer E, Kim, Eliot, Kimura, Noriaki, Kondrashov, Dmitri, Labe, Zachary M, Lee, WooSung, Lee, Younjoo J, Li, Cuihua, Li, Xuewei, Lin, Yongcheng, Liu, Yanyun, Maslowski, Wieslaw, Massonnet, François, Meier, Walter N, Merryfield, William J, Myint, Hannah, Navarro, Juan C Acosta, Petty, Alek, Qiao, Fangli, Schröder, David, Schweiger, Axel, Shu, Qi, Sigmond, Michael, Steele, Michael, Stroeve, Julienne, Sun, Nico, Tietsche, Steffen, Tsamados, Michel, Wang, Keguang, Wang, Jianwu, Wang, Wanqiu, Wang, Yiguo, Wang, Yun, Williams, James, Yang, Qinghua, Yuan, Xiaojun, Zhang, Jinlun, and Zhang, Yongfei

Abstract

Abstract This study quantifies the state-of-the-art in the rapidly growing field of seasonal Arctic sea ice prediction. A novel multi-model dataset of retrospective seasonal predictions of September Arctic sea ice is created and analyzed, consisting of community contributions from 17 statistical models and 17 dynamical models. Prediction skill is compared over the period 2001–2020 for predictions of Pan-Arctic sea ice extent (SIE), regional SIE, and local sea ice concentration (SIC) initialized on June 1, July 1, August 1, and September 1. This diverse set of statistical and dynamical models can individually predict linearly detrended Pan-Arctic SIE anomalies with skill, and a multi-model median prediction has correlation coefficients of 0.79, 0.86, 0.92, and 0.99 at these respective initialization times. Regional SIE predictions have similar skill to Pan-Arctic predictions in the Alaskan and Siberian regions, whereas regional skill is lower in the Canadian, Atlantic, and Central Arctic sectors. The skill of dynamical and statistical models is generally comparable for Pan-Arctic SIE, whereas dynamical models outperform their statistical counterparts for regional and local predictions. The prediction systems are found to provide the most value added relative to basic reference forecasts in the extreme SIE years of 1996, 2007, and 2012. SIE prediction errors do not show clear trends over time, suggesting that there has been minimal change in inherent sea ice predictability over the satellite era. Overall, this study demonstrates that there are bright prospects for skillful operational predictions of September sea ice at least three months in advance.

Published
2024

27. The role of atmospheric conditions in the Antarctic sea ice extent summer minima.

Author

Mezzina, Bianca, Goosse, Hugues, Klein, François, Barthélemy, Antoine, and Massonnet, François

Subjects
ATMOSPHERIC circulation, WEATHER, SPRING, ANTARCTIC ice, WINTER
Abstract

Understanding the variability of Antarctic sea ice is still a challenge. After decades of modest growth, an unprecedented minimum in the sea ice extent (SIE) was registered in summer 2017, and, following years of anomalously low SIE, a new record was established in early 2022. These two memorable minima have received great attention as single cases, but a comprehensive analysis of summer SIE minima is currently lacking. Indeed, other similar events are present in the observational record, although they are minor compared to the most recent ones, and a full analysis of all summer SIE minima is essential to separate potential common drivers from event-specific dynamics in order to ultimately improve our understanding of the Antarctic sea ice and climate variability. In this work, we examine sea ice and atmospheric conditions during and before all summer SIE minima over the satellite period up to 2022. We use observations and reanalysis data and compare our main findings with results from an ocean–sea ice model (NEMO–LIM) driven by prescribed atmospheric fields from ERA5. Examining SIE and sea ice concentration (SIC) anomalies, we find that the main contributors to the summer minima are the Ross and Weddell sectors. However, the two regions play different roles, and the variability of the Ross Sea explains most of the minima, with typical negative SIE anomalies about twice as large as the ones in the Weddell Sea. Furthermore, the distribution of SIC anomalies is also different: in the Weddell Sea, they exhibit a dipolar structure, with increased SIC next to the continent and decreased SIC at the sea ice margin, while the Ross Sea displays a more homogenous decrease. We also examine the role of wintertime sea ice conditions before the summer SIE minima and find mixed results depending on the period: the winter conditions are relevant in the most recent events, after 2017, but they are marginal for previous years. Next, we consider the influence of the atmosphere on the SIE minima, which is shown to play a major role: after analyzing the anomalous atmospheric circulation during the preceding spring, we find that different large-scale anomalies can lead to similar regional prevailing winds that drive the summer minima. Specifically, the SIE minima are generally associated with dominant northwesterly anomalous winds in the Weddell Sea, while a southwesterly anomalous flow prevails in the Ross Sea. Finally, we investigate the relative contribution of dynamic (e.g., ice transport) and thermodynamic (e.g., local melting) processes to the summer minima. Our results indicate that the exceptional sea ice loss in both the Ross and Weddell sectors is dominated at the large scale by thermodynamic processes, while dynamics are also present but with a minor role. [ABSTRACT FROM AUTHOR]

Published
2024
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28. Advances in machine learning techniques can assist across a variety of stages in sea ice applications

Author

Eayrs, Clare, primary, Lee, Won Sang, additional, Jin, Emilia, additional, Lemieux, Jean-François, additional, Massonnet, François, additional, Vancoppenolle, Martin, additional, Zampieri, Lorenzo, additional, Bennetts, Luke G., additional, Blockley, Ed, additional, Chung, Eui-Seok, additional, Fraser, Alexander D., additional, Ham, Yoo-geun, additional, Im, Jungho, additional, Kim, Baek-min, additional, Kim, Beong-Hoon, additional, Kim, Jinsuk, additional, Kim, Joo-Hong, additional, Kim, Seong-Joong, additional, Kim, Seung Hee, additional, Korosov, Anton, additional, Lee, Choon-Ki, additional, Lee, Donghyuck, additional, Lee, Hyun-Ju, additional, Lee, Jeong-Gil, additional, Lee, Jiyeon, additional, Na, Jisung, additional, Park, In-woo, additional, Park, Jikang, additional, Wang, Xianwei, additional, Xu, Shiming, additional, and Yun, Sukyoung, additional

Published
2024
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29. EXPLAINING EXTREME EVENTS OF 2017 : From A Climate Perspective

Author

Herring, Stephanie C., Christidis, Nikolaos, Hoell, Andrew, Hoerling, Marty, Stott, Peter A., Owen, Rebecca, Vano, Julie A., Dettinger, Michael D., Cifelli, Rob, Curtis, David, Dufour, Alexis, Miller, Kathleen, Olsen, J. Rolf, Wilson, Anna M., Nerem, R. S., Fasullo, J., Hoell, Andrew, Perlwitz, Judith, Dewes, Candida, Wolter, Klaus, Rangwala, Imtiaz, Quan, Xiao-Wei, Eischeid, Jon, Wang, Hailan, Schubert, Siegfried D., Koster, Randal D., Chang, Yehui, Christidis, Nikolaos, Betts, Richard A., Stott, Peter A., de Abreu, Rafael C., Cunningham, Christopher, Rudorff, Conrado M., Rudorff, Natalia, Abatan, Abayomi A., Dong, Buwen, Lott, Fraser C., Tett, Simon F. B., Sparrow, Sarah N., Navarro, Juan C. Acosta, Ortega, Pablo, García-Serrano, Javier, Guemas, Virginie, Tourigny, Etienne, Cruz-García, Rubén, Massonnet, François, Doblas-Reyes, Francisco J., Kew, Sarah F., Philip, Sjoukje Y., van Oldenborgh, Geert Jan, Otto, Friederike E. L., Vautard, Robert, van der Schrier, Gerard, Funk, Chris, Hoell, Andrew, Nicholson, Sharon, Korecha, Diriba, Galu, Gideon, Artan, Guleid, Teshome, Fetene, Hailermariam, Kinfe, Segele, Zewdu, Harrison, Laura, Tadege, Abebe, Atheru, Zachary, Pomposi, Catherine, Pedreros, Diego, Rimi, Ruksana H., Haustein, Karsten, Barbour, Emily J., Allen, Myles R., Takahashi, Chiharu, Shiogama, Hideo, Imada, Yukiko, Kosaka, Yu, Mori, Masato, Arai, Miki, Kamae, Youichi, Watanabe, Masahiro, Min, Seung-Ki, Kim, Yeon-Hee, Park, In-Hong, Lee, Donghyun, Sparrow, Sarah, Wallom, David, Stone, Dáithí, Sun, Ying, Dong, Siyan, Zhang, Xuebin, Stott, Peter, Hu, Ting, Wang, Shanshan, Yuan, Xing, Wu, Renguang, Chen, Yang, Chen, Wei, Su, Qin, Luo, Feifei, Sparrow, Sarah, Tian, Fangxing, Dong, Buwen, Tett, Simon F. B., Lott, Fraser C., Wallom, David, Zhou, Chunlüe, Wang, Kaicun, Qi, Dan, Tan, Jianguo, Perkins-Kirkpatrick, S. E., King, A. D., Cougnon, E. A., Grose, M. R., Oliver, E. C. J., Holbrook, N. J., Lewis, S. C., Pourasghar, F., Hope, Pandora, Black, Mitchell T., Lim, Eun-Pa, Dowdy, Andrew, Wang, Guomin, Pepler, Acacia S., and Fawcett, Robert J. B.

Published
2019

36. An assessment of ten ocean reanalyses in the polar regions

Author

Uotila, Petteri, Goosse, Hugues, Haines, Keith, Chevallier, Matthieu, Barthélemy, Antoine, Bricaud, Clément, Carton, Jim, Fučkar, Neven, Garric, Gilles, Iovino, Doroteaciro, Kauker, Frank, Korhonen, Meri, Lien, Vidar S., Marnela, Marika, Massonnet, François, Mignac, Davi, Peterson, K. Andrew, Sadikni, Remon, Shi, Li, Tietsche, Steffen, Toyoda, Takahiro, Xie, Jiping, and Zhang, Zhaoru

Published
2019
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45. Contributors

Author

Abhilash, S., primary, Ahn, Min-Seop, additional, Baethgen, Walter E., additional, Balsamo, Gianpaolo, additional, Bazo, Juan, additional, Brown, Barbara, additional, Brunet, Gilbert, additional, Buizza, Roberto, additional, Butler, Amy, additional, Casati, Barbara, additional, Chang, P., additional, Charlton-Perez, Andrew, additional, Chattopadhyay, Rajib, additional, Chevallier, Matthieu, additional, Coelho, Caio A.S., additional, de Perez, Erin Coughlan, additional, Cunningham, Christopher, additional, Dankers, Rutger, additional, DeFlorio, Michael, additional, DeGennaro, Matthew, additional, Destrooper, Mathieu, additional, Dirmeyer, Paul A., additional, Dolif, Giovanni, additional, Domeisen, Daniela I.V., additional, Duell, Robyn, additional, Dutra, Emanuel, additional, Ek, Michael B., additional, Ferranti, Laura, additional, Frederiksen, Jorgen, additional, Garfinkel, Chaim, additional, Gentine, Pierre, additional, Gerber, Edwin P., additional, Ghil, Michael, additional, Goessling, Helge, additional, Golding, Brian, additional, Groth, Andreas, additional, Guémas, Virginie, additional, Hitchcock, Peter, additional, Hudson, Debra, additional, Jones, Charles, additional, Joseph, Susmitha, additional, Jung, Thomas, additional, Kang, In-Sik, additional, Karpechko, Alexey Yu., additional, Kondrashov, Dmitri, additional, Krishna, Phani M., additional, Lavaysse, Christophe, additional, Lin, Hai, additional, Lowe, Rachel, additional, Marchezini, Victor, additional, Martiny, Nadège, additional, Massonnet, François, additional, Maycock, Amanda C., additional, Methven, John, additional, Mills, Brian, additional, Mittermaier, Marion, additional, Miura, Hiroaki, additional, Moron, Vincent, additional, Nakazawa, Tetsuo, additional, Nissan, Hannah, additional, Pattanaik, D.R., additional, Robbins, Joanne, additional, Robertson, Andrew W., additional, Roucou, Pascal, additional, Sahai, A.K., additional, Saravanan, R., additional, Sarmiento, Juan Pablo, additional, Siegert, Stefan, additional, Sigmond, Michael, additional, Silver, Amber, additional, Simpson, Isla, additional, Singh, Roop, additional, Son, Seok-Woo, additional, Stan, Cristiana, additional, Stephenson, David B., additional, Straus, David, additional, Subramanian, Aneesh, additional, Takaya, Yuhei, additional, Terra, Rafael, additional, Thomson, Madeleine C., additional, Tippett, Michael K., additional, Tompkins, Adrian M., additional, Toth, Zoltan, additional, Trajber, Rachel, additional, Vitart, Frédéric, additional, Wang, Lei, additional, Watkins, Andrew, additional, Wilson, Laurie, additional, and Woolnough, Steven J., additional

Published
2019
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48. Importance of atmospheric feedbacks in simulating the seasonal cycle of the Antarctic sea ice and its response to perturbations.

Author

Goosse, Hugues, primary, Allende Contador, Sofia, additional, Bitz, Cecilia M., additional, Blanchard-Wrigglesworth, Edward, additional, Eayrs, Clare, additional, Fichefet, Thierry, additional, Himmich, Kenza, additional, Huot, Pierre-Vincent, additional, Klein, François, additional, Marchi, Sylvain, additional, Massonnet, François, additional, Mezzina, Bianca, additional, Pelletier, Charles, additional, Roach, Lettie, additional, Vancoppenolle, Martin, additional, and van Lipzig, Nicole P.M., additional

Published
2023
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50. SIPN South: six years of coordinated seasonal Antarctic sea ice predictions

Author

Massonnet, François, primary, Barreira, Sandra, additional, Barthélemy, Antoine, additional, Bilbao, Roberto, additional, Blanchard-Wrigglesworth, Edward, additional, Blockley, Ed, additional, Bromwich, David H., additional, Bushuk, Mitchell, additional, Dong, Xiaoran, additional, Goessling, Helge F., additional, Hobbs, Will, additional, Iovino, Doroteaciro, additional, Lee, Woo-Sung, additional, Li, Cuihua, additional, Meier, Walter N., additional, Merryfield, William J., additional, Moreno-Chamarro, Eduardo, additional, Morioka, Yushi, additional, Li, Xuewei, additional, Niraula, Bimochan, additional, Petty, Alek, additional, Sanna, Antonella, additional, Scilingo, Mariana, additional, Shu, Qi, additional, Sigmond, Michael, additional, Sun, Nico, additional, Tietsche, Steffen, additional, Wu, Xingren, additional, Yang, Qinghua, additional, and Yuan, Xiaojun, additional

Published
2023
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