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Omar Bellprat, Javier García-Serrano, Neven S. Fučkar, François Massonnet, Virginie Guemas, and Francisco J. Doblas-Reyes
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Louis-Philippe Caron, François Massonnet, Philip J. Klotzbach, Tom J. Philp, and Julienne Stroeve
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Louis-Philippe Caron, François Massonnet, Philip J. Klotzbach, Tom J. Philp, and Julienne Stroeve
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Jennifer V. Lukovich, Julienne C. Stroeve, Alex Crawford, Lawrence Hamilton, Michel Tsamados, Harry Heorton, and François Massonnet

Abstract

In this study the impact of extreme cyclones on Arctic sea ice in summer is investigated. Examined in particular are relative thermodynamic and dynamic contributions to sea ice volume budgets in the vicinity of Arctic summer cyclones in 2012 and 2016. Results from this investigation illustrate that sea ice loss in the vicinity of the cyclone trajectories during each year was associated with different dominant processes: thermodynamic processes (melting) in the Pacific sector of the Arctic in 2012, and both thermodynamic and dynamic processes in the Pacific sector of the Arctic in 2016. Comparison of both years further suggests that the Arctic minimum sea ice extent is influenced by not only the strength of the cyclone, but also by the timing and location relative to the sea ice edge. Located near the sea ice edge in early August in 2012, and over the central Arctic later in August in 2016, extreme cyclones contributed to comparable sea ice area (SIA) loss, yet enhanced sea ice volume loss in 2012 relative to 2016. Central to a characterization of extreme cyclone impacts on Arctic sea ice from the perspective of thermodynamic and dynamic processes, we present an index describing relative thermodynamic and dynamic contributions to sea ice volume changes. This index helps to quantify and improve our understanding of initial sea ice state and dynamical responses to cyclones in a rapidly warming Arctic, with implications for seasonal ice forecasting, marine navigation, coastal community infrastructure, and designation of protected and ecologically sensitive marine zones.

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Yong-Fei Zhang, Cecilia M. Bitz, Jeffrey L. Anderson, Nancy Collins, Jonathan Hendricks, Timothy Hoar, Kevin Raeder, and François Massonnet

Abstract

Simulating Arctic sea ice conditions up to the present and predicting them several months in advance has high stakeholder value, yet remains challenging. Advanced data assimilation (DA) methods combine real observations with model forecasts to produce sea ice reanalyses and accurate initial conditions for sea ice prediction. This study introduces a sea ice DA framework for a sea ice model with a parameterization of the ice thickness distribution by resolving multiple thickness categories. Specifically, the Los Alamos Sea Ice Model, version 5 (CICE5), is integrated with the Data Assimilation Research Testbed (DART). A series of perfect model observing system simulation experiments (OSSEs) are designed to explore DA algorithms within the ensemble Kalman filter (EnKF) and the relative importance of different observation types. This study demonstrates that assimilating sea ice concentration (SIC) observations can effectively remove SIC errors, with the error of total Arctic sea ice area reduced by about 60% annually. When the impact of SIC observations is strongly localized in space, the error of total volume is also modestly improved. The largest simulation improvements are produced when sea ice thickness (SIT) and SIC are jointly assimilated, with the error of total volume decreased by more than 70% annually. Assimilating multiyear sea ice concentration (MYI) can reduce error in total volume by more than 50%. Assimilating MYI produces modest improvements in snow depth (errors are reduced by around 16%), while assimilating SIC and SIT has no obvious influence on snow depth. This study also suggests that different observation types may need different localization distances to optimize DA performance.

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Neven S. Fučkar, François Massonnet, Virginie Guemas, Javier García-Serrano, Omar Bellprat, Mario Acosta, and Francisco J. Doblas-Reyes
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Juan C. Acosta Navarro, Pablo Ortega, Javier García-Serrano, Virginie Guemas, Etienne Tourigny, Rubén Cruz-García, François Massonnet, and Francisco J. Doblas-Reyes
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Ed Blockley, Martin Vancoppenolle, Elizabeth Hunke, Cecilia Bitz, Daniel Feltham, Jean-François Lemieux, Martin Losch, Eric Maisonnave, Dirk Notz, Pierre Rampal, Steffen Tietsche, Bruno Tremblay, Adrian Turner, François Massonnet, Einar Ólason, Andrew Roberts, Yevgeny Aksenov, Thierry Fichefet, Gilles Garric, Doroteaciro Iovino, Gurvan Madec, Clément Rousset, David Salas y Melia, and David Schroeder
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Helge F. Goessling, Thomas Jung, Stefanie Klebe, Jenny Baeseman, Peter Bauer, Peter Chen, Matthieu Chevallier, Randall Dole, Neil Gordon, Paolo Ruti, Alice Bradley, David H. Bromwich, Barbara Casati, Dmitry Chechin, Jonathan J. Day, François Massonnet, Brian Mills, Ian Renfrew, Gregory Smith, and Renee Tatusko
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David H. Bromwich, Kirstin Werner, Barbara Casati, Jordan G. Powers, Irina V. Gorodetskaya, François Massonnet, Vito Vitale, Victoria J. Heinrich, Daniela Liggett, Stefanie Arndt, Boris Barja, Eric Bazile, Scott Carpentier, Jorge F. Carrasco, Taejin Choi, Yonghan Choi, Steven R. Colwell, Raul R. Cordero, Massimo Gervasi, Thomas Haiden, Naohiko Hirasawa, Jun Inoue, Thomas Jung, Heike Kalesse, Seong-Joong Kim, Matthew A. Lazzara, Kevin W. Manning, Kimberley Norris, Sang-Jong Park, Phillip Reid, Ignatius Rigor, Penny M. Rowe, Holger Schmithüsen, Patric Seifert, Qizhen Sun, Taneil Uttal, Mario Zannoni, and Xun Zou

Abstract

The Year of Polar Prediction in the Southern Hemisphere (YOPP-SH) had a special observing period (SOP) that ran from 16 November 2018 to 15 February 2019, a period chosen to span the austral warm season months of greatest operational activity in the Antarctic. Some 2,200 additional radiosondes were launched during the 3-month SOP, roughly doubling the routine program, and the network of drifting buoys in the Southern Ocean was enhanced. An evaluation of global model forecasts during the SOP and using its data has confirmed that extratropical Southern Hemisphere forecast skill lags behind that in the Northern Hemisphere with the contrast being greatest between the southern and northern polar regions. Reflecting the application of the SOP data, early results from observing system experiments show that the additional radiosondes yield the greatest forecast improvement for deep cyclones near the Antarctic coast. The SOP data have been applied to provide insights on an atmospheric river event during the YOPP-SH SOP that presented a challenging forecast and that impacted southern South America and the Antarctic Peninsula. YOPP-SH data have also been applied in determinations that seasonal predictions by coupled atmosphere–ocean–sea ice models struggle to capture the spatial and temporal characteristics of the Antarctic sea ice minimum. Education, outreach, and communication activities have supported the YOPP-SH SOP efforts. Based on the success of this Antarctic summer YOPP-SH SOP, a winter YOPP-SH SOP is being organized to support explorations of Antarctic atmospheric predictability in the austral cold season when the southern sea ice cover is rapidly expanding.

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