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Academic literature on the topic 'Glace de mer – Arctique, Océan'
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Journal articles on the topic "Glace de mer – Arctique, Océan"
Eegeesiak, Okalik. "L’océan Arctique et la glace de mer sont notre Nuna." Chronique ONU 54, no. 2 (2017): 49–51. http://dx.doi.org/10.18356/aae2d19a-fr.
Full textMsadek, Rym, Gilles Garric, Sara Fleury, Florent Garnier, Lauriane Batté, and Mitchell Bushuk. "Prévoir les variations saisonnières de la glace de mer arctique et leurs impacts sur le climat." La Météorologie, no. 111 (2020): 024. http://dx.doi.org/10.37053/lameteorologie-2020-0089.
Full textDissertations / Theses on the topic "Glace de mer – Arctique, Océan"
Randall, Kevin. "La glace de mer arctique : Source ou puits d'oxyde nitreux?" Thesis, Université Laval, 2010. http://www.theses.ulaval.ca/2010/27428/27428.pdf.
Full textNitrous oxide (N2O) is a greenhouse gas which also plays a role in stratospheric ozone depletion. The objective of this study was to demonstrate the presence of N2O in Arctic sea ice, and to quantify the impact of this potential source to the atmosphere. Bulk concentrations of N2O in the bottom 10 cm of the sea ice and in the underlying surface waters were measured in the Beaufort Sea from March to April 2008. Our sea ice measurements revealed low N2O bulk concentrations with N2O being consistently undersaturated with respect to the underlying surface water (ca. 40% saturation) and the atmosphere (ca. 30% saturation). The most plausible mechanism to explain the low N2O sea ice concentrations is a loss of N2O via brine rejection during sea ice formation in autumn and winter. Sea ice could thus act as a source of N2O via brine rejection during sea ice formation in autumn and winter.
Chevallier, Matthieu. "Prévisibilité saisonnière de la glace de mer de l'océan Arctique." Thesis, Paris Est, 2012. http://www.theses.fr/2012PEST1117/document.
Full textSea ice experiences some major changes in the early 21st century. The recent decline of the summer Arctic sea ice extent, reaching an all-time record low in September 2012, has woken renewed interest in this remote marine area. Sea ice seasonal forecasting is a challenge of operational oceanography that could benefit to several stakeholders : fishing, energy, research, tourism. Moreover, sea ice is a boundary condition of the atmosphere. As such, as tropical sea surface temperature, it may drive some atmosphere seasonal predictability. The goal of this PhD work was to set up a dedicated Arctic sea ice seasonal forecasting system, using CNRM-CM5.1 coupled climate model. We address the initialization strategy, the creation and the evaluation of the hindcasts (or re-forecasts). In contrast to sea ice concentration, very few thickness data are available over the whole Arctic ocean. In order to initialize sea ice and the ocean dynamically and thermodynamically, we used the ocean-sea ice component of CNRM-CM5.1, named NEMO-GELATO, in forced mode. The initialization run is a forced simulation driven by ERA-Interim forcing over the period 1990-2010. Corrections based on satellite data and in-situ measurements leads to skilful simulation of the ocean and sea ice mean state and interannual variability. Sea ice thickness seems overall underestimated, based on the most recent estimates. Some characteristics of sea ice inherent predictability are then addressed. A diagnostic potential predictability study allowed us to identify two regimes of predictability using sea ice volume and the ice thickness distribution. The first one is the 'persistence regime', for winter sea ice area. March sea ice area is potentially predictable up to 3 months in advance using simple persistence, and surface covered by thin ice to a lesser extent. The second one is the 'memory regime', for summer sea ice area. September sea ice area is potentially predictable up to 6 months in advance using volume and to a greater extent the area covered by relatively thick ice. These results suggest that a comprehensive winter volume and thickness initialization could improve the summer forecasts. Summer and winter seasonal hindcasts shows very encouraging skills, in terms of raw and detrended anomalies. These skills suggest a predicatibility from initial conditions besides predictability due to the trend. Summer forecasts analysis shows that the volume and the ice thickess distribution explains a high fraction of the variance of predicted sea ice extent, which confirms the existence of the 'memory regime'. Winter forecasts also suggest the 'persistence regime'. A regional investigation of the winter hindcast helps precising the role of the ocean in the forecasts, and shows to what extent our system predictions could be used operationally, especially in the Barents Sea
Germe, Agathe. "Variabilité de la glace de mer en mer du Groenland : liens avec les forçages atmosphériques et océaniques à l'échelle interannuelle." Paris 6, 2010. http://www.theses.fr/2010PA066629.
Full textChevallier, Matthieu, and Matthieu Chevallier. "Prévisibilité saisonnière de la glace de mer de l'océan Arctique." Phd thesis, Université Paris-Est, 2012. http://pastel.archives-ouvertes.fr/pastel-00806125.
Full textMaksimovich, Elena. "L' impact des conditions météorologiques sur la variabilité de démarrage de la fonte sur la glace de mer en Arctique centrale." Paris 6, 2012. http://www.theses.fr/2012PA066033.
Full textTiming of spring Snow Melt Onset (SMO) on Arctic sea ice strongly affects the heat accumulation in snow and ice during the short melt season. This summertime heat uptake is quasi-linearly and inversely proportional to the remnant ice volume by the end of the melt season. On top of sea ice SMO timing, as well as its interannual and regional variations are controlled by surface heat fluxes. Anomalously early (delayed) SMO is due to large and early (weak and retarded) heat accumulation within the snowpack. Satellite passive microwave (SSM/I) observations show that the \textit{apparent} Melt Onset (MO) varies by 20-30 days interannually and over 25-50 km distance. These apparent MO records appear to be a complex blend of SMO on sea ice and sea ice opening due to divergent ice drift. We extracted SMO out of the apparent MO record using sea ice concentration data. Applying 20-year ERA Interim reanalysis of radiative and turbulent surface heat fluxes we examined how well the heat fluxes reflect the variations in SMO. Anomalies of heat fluxes in the pre-melt period explained a significant portion of the interannual and spatial variations in SMO within the central Arctic. The main term was the downward longwave radiation locally accounting for up to 90\% of the temporal SMO variations. The role of the latent and sensible heat fluxes in earlier/later SMO was not to bring more/less heat to the surface but to reduce/enhance the surface heat loss. Solar radiation alone was not an important factor for SMO timing. Anomalies in surface fluxes were examined also in relation to meteorological conditions. 20-year MO and SMO trends are towards earlier spring melt in the central Arctic Ocean
Guerreiro, Kévin. "Amélioration des estimations d'épaisseur de glace de mer arctique par altimétrie spatiale." Thesis, Toulouse 3, 2017. http://www.theses.fr/2017TOU30277.
Full textSatellite observations have shown that the arctic sea ice extent has strongly decreased during the last 40 years, with a clear increase of the shrinking since the 90's. While the mechanisms responsible for this accelerated shrinking are relatively well known, sea ice models do not clearly reproduce the observed extent variations. This inaccurate representation is generally attributed to a misunderstanding of the arctic system climate feedbacks. Among these feedbacks, we seek to study one of them in particular: the sea ice thinning. Sea ice thinning is generally associated with an earlier seasonal melt as well as an increase in sea ice export; both tend to accelerate the sea ice retreat. A good representation of sea ice thickness is therefore necessary to improve our understanding of the arctic sea ice extent variations observed during the last decades. Unlike sea ice extent data, there are currently no pan-Arctic sea ice thickness observations covering a large period (> 20 years). However, several studies have demonstrated the potential of satellite altimetry to retrieve sea ice thickness at a basin scale. To measure sea ice thickness from radar altimetry, the "freeboard" technique is generally employed. This methodology consists of estimating the thickness of the emerged sea ice (freeboard) from radar altimetry and then converting this measurement to sea ice thickness, using an equation for the hydrostatic equilibrium that exists between the snow covered sea ice and the ocean. The freeboard methodology has been applied to diverse altimetric missions (ERS-2, Envisat and CryoSat-2) since 1995 and should allow the retrieval of more than 20 years of pan-Arctic ice thickness. However, the previous estimates of sea ice thickness are data shorter than 6 years in duration. This absence of a long ice thickness time series is mostly due to the difficulty in providing continuity between the different altimetric missions (conventional altimetry/SAR altimetry) as well as to the uncertainties related to the freeboard-to-thickness conversion. In this context, this thesis makes an analysis of the freeboard inter-mission biases and improves the freeboard-to-thickness conversion in order to produce long term ice thickness estimates. To achieve these goals, a thorough analysis of the interaction between the radar signal and the sea ice parameters (snow, roughness, etc) is performed. The analysis of the radar signal physics over sea ice allows to derive the longest time series of arctic sea ice thickness ever established to this day (2002-2016). The analysis of this time series shows that sea ice has thinned from 0.013(± 0.09) m/year in average during the 2002-2016 period. The ice thinning is mainly attributed to the loss of perennial sea ice that occurred during the same period while the high uncertainty associated with this trend is associated to the important inter-annual variability of arctic sea ice thickness
Jardon, Fernanda. "Etude de processus dynamiques et thermodynamiques dans l'océan et la glace de mer régissant l'activité des polynies côtières Arctiques : le cas du Storfjorden." Paris 6, 2011. http://www.theses.fr/2011PA066093.
Full textLebrun, Marion. "De l'interaction entre banquise, lumière et phytoplancton arctique." Electronic Thesis or Diss., Sorbonne université, 2019. http://www.theses.fr/2019SORUS524.
Full textLarge weaknesses remain considering our understanding of the drivers of phytoplankton growth in Arctic sea ice zone, especially due to large uncertainties in the interactions between sea ice, light and phytoplankton.The aim of this PhD thesis is to better understand these interactions and to highlight the main uncertainties considering these interactions in Earth System Models. I first show that the ice-free period is mainly led by the solar irradiance cycle and by the ocean-atmosphere thermodynamic exchanges during summer. It is consequently projected to extend into fall in the future. Then, I evaluate the radiative transfer scheme in the ocean model NEMO, in arctic sea ice zone. I show that NEMO largely underestimates the transmitted shortwave radiation in ice-covered waters, especially due to the overestimation of the snow and the first level of the ocean attenuation. I finally define a diagnostic to describe available light seasonality in the sea ice zone and I study the impact of this diagnostic on simulated phytoplankton in the bio-geochemistry model PISCES. However, large uncertainties remain in the study of the relation between this diagnostic and the phytoplankton growth. This is especially due to the non-linearity between available light and phytoplankton growth and also due to the lake of knowledge about the phytoplankton physiology
Haarpaintner, Jörg. "Formation de saumures par production de glaces de mer dans Storfjorden, Svalbard, estimée à partir d'images ers-2 sar et de simples modèles de dérive et formation de glaces de mer." Versailles-St Quentin en Yvelines, 2001. http://www.theses.fr/2001VERSA003.
Full textHoussais, Marie-Noëlle. "Modelisation des interactions ocean-glace : application a la mer du groenland." Paris 6, 1987. http://www.theses.fr/1987PA066173.
Full textBooks on the topic "Glace de mer – Arctique, Océan"
Sophie, Bobbé, ed. Banquises: Les Inuit et l'infini arctique. Editions Autrement, 1999.
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