Articles | Volume 18, issue 2
https://doi.org/10.5194/os-18-483-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/os-18-483-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
08 Apr 2022
Research article |
| 08 Apr 2022
| 08 Apr 2022
Untangling the mistral and seasonal atmospheric forcing driving deep convection in the Gulf of Lion: 2012–2013
LMD/IPSL, École Polytechnique, Institut Polytechnique de Paris, ENS, PSL Research University, Sorbonne Université, CNRS, Palaiseau, France
Yonatan Givon
Department of Earth and Planetary Sciences, Weizmann Institute of Science, Rehovot, Israel
Romain Pennel
LMD/IPSL, École Polytechnique, Institut Polytechnique de Paris, ENS, PSL Research University, Sorbonne Université, CNRS, Palaiseau, France
Shira Raveh-Rubin
Department of Earth and Planetary Sciences, Weizmann Institute of Science, Rehovot, Israel
Philippe Drobinski
LMD/IPSL, École Polytechnique, Institut Polytechnique de Paris, ENS, PSL Research University, Sorbonne Université, CNRS, Palaiseau, France
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Deep convection in the Gulf of Lion is an important ocean mixing process in the western Mediterranean Sea that aids the general circulation of the Mediterranean Sea and promotes the local marine biology. By studying the fractal-ness of deep convection, we can determine which of the three periods: before, during, or after deep convection are the least predictable. The results show that the period following deep convection is the most difficult to replicate rather than deep convection itself.
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Deep convection in the Gulf of Lion is an important ocean mixing process in the western Mediterranean Sea that aids the general circulation of the Mediterranean Sea and promotes the local marine biology. By studying the fractal-ness of deep convection, we can determine which of the three periods: before, during, or after deep convection are the least predictable. The results show that the period following deep convection is the most difficult to replicate rather than deep convection itself.
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Raphaël Rousseau-Rizzi, Shira Raveh-Rubin, Jennifer L. Catto, Alice Portal, Yonatan Givon, and Olivia Martius
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Alice Portal, Shira Raveh-Rubin, Jennifer L. Catto, Yonatan Givon, and Olivia Martius
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Sylvain Mailler, Sotirios Mallios, Arineh Cholakian, Vassilis Amiridis, Laurent Menut, and Romain Pennel
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Laurent Menut, Bertrand Bessagnet, Arineh Cholakian, Guillaume Siour, Sylvain Mailler, and Romain Pennel
Geosci. Model Dev., 17, 3645–3665, https://doi.org/10.5194/gmd-17-3645-2024, https://doi.org/10.5194/gmd-17-3645-2024, 2024
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Yonatan Givon, Or Hess, Emmanouil Flaounas, Jennifer Louise Catto, Michael Sprenger, and Shira Raveh-Rubin
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Daniel A. Knopf, Joseph C. Charnawskas, Peiwen Wang, Benny Wong, Jay M. Tomlin, Kevin A. Jankowski, Matthew Fraund, Daniel P. Veghte, Swarup China, Alexander Laskin, Ryan C. Moffet, Mary K. Gilles, Josephine Y. Aller, Matthew A. Marcus, Shira Raveh-Rubin, and Jian Wang
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Assaf Hochman, Francesco Marra, Gabriele Messori, Joaquim G. Pinto, Shira Raveh-Rubin, Yizhak Yosef, and Georgios Zittis
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Emmanouil Flaounas, Silvio Davolio, Shira Raveh-Rubin, Florian Pantillon, Mario Marcello Miglietta, Miguel Angel Gaertner, Maria Hatzaki, Victor Homar, Samira Khodayar, Gerasimos Korres, Vassiliki Kotroni, Jonilda Kushta, Marco Reale, and Didier Ricard
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Jay M. Tomlin, Kevin A. Jankowski, Daniel P. Veghte, Swarup China, Peiwen Wang, Matthew Fraund, Johannes Weis, Guangjie Zheng, Yang Wang, Felipe Rivera-Adorno, Shira Raveh-Rubin, Daniel A. Knopf, Jian Wang, Mary K. Gilles, Ryan C. Moffet, and Alexander Laskin
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Laurent Menut, Bertrand Bessagnet, Régis Briant, Arineh Cholakian, Florian Couvidat, Sylvain Mailler, Romain Pennel, Guillaume Siour, Paolo Tuccella, Solène Turquety, and Myrto Valari
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The CHIMERE chemistry-transport model is presented in its new version, V2020r1. Many changes are proposed compared to the previous version. These include online modeling, new parameterizations for aerosols, new emissions schemes, a new parameter file format, the subgrid-scale variability of urban concentrations and new transport schemes.
Yonatan Givon, Douglas Keller Jr., Vered Silverman, Romain Pennel, Philippe Drobinski, and Shira Raveh-Rubin
Weather Clim. Dynam., 2, 609–630, https://doi.org/10.5194/wcd-2-609-2021, https://doi.org/10.5194/wcd-2-609-2021, 2021
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Mistral wind is a renowned phenomenon in the Mediterranean, yet its large-scale controlling mechanisms have not been systematically mapped. Here, using a new mistral database for 1981–2016, the upper-tropospheric flow patterns are classified by a self-organizing map algorithm, resulting in 16 distinct patterns related to Rossby wave life cycles. Each pattern has unique surface impact, having implications to understanding mistral predictability, air–sea interaction and their future projections.
Sylvain Mailler, Romain Pennel, Laurent Menut, and Mathieu Lachâtre
Geosci. Model Dev., 14, 2221–2233, https://doi.org/10.5194/gmd-14-2221-2021, https://doi.org/10.5194/gmd-14-2221-2021, 2021
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Representing the advection of thin polluted plumes in numerical models is a challenging task since these models usually tend to excessively diffuse these plumes in the vertical direction. This numerical diffusion process is the cause of major difficulties in representing such dense and thin polluted plumes in numerical models. We propose here, and test in an academic framework, a novel method to solve this problem through the use of an antidiffusive advection scheme in the vertical direction.
Naama Reicher, Carsten Budke, Lukas Eickhoff, Shira Raveh-Rubin, Ifat Kaplan-Ashiri, Thomas Koop, and Yinon Rudich
Atmos. Chem. Phys., 19, 11143–11158, https://doi.org/10.5194/acp-19-11143-2019, https://doi.org/10.5194/acp-19-11143-2019, 2019
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We characterized size-segregated airborne ice-nucleating particles (INPs) during dust storm events in the eastern Mediterranean. We found that particle size can predict its activity, and in general, larger particles are better INPs. The activity of supermicron particles dominated by desert mineral dust was similar between the different dust events regardless of the high variability of the geographic source desert and atmospheric journey.
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Short summary
The mistral winds are believed to be the primary source of cooling of the Gulf of Lion, leading to deep convection in the region, a process that mixes the ocean column from the seafloor to the sea surface. However, we have found that seasonal atmospheric changes also significantly cool the Gulf of Lion waters to cause deep convection, rather than mistral winds being the sole source, contributing roughly two-thirds of the required cooling, with the mistral winds contributing the final third.
The mistral winds are believed to be the primary source of cooling of the Gulf of Lion, leading...
