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Magand, O.; Picard, G.; Brucker, L.; Fily, M.; Genthon, C. (2008). Snow melting bias in microwave mapping of Antarctic snow accumulation. TCD, 2(2), 255–273.
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. (2005). The International Trans-Antarctic Scientific Expedition (ITASE): an overview. Annals of glaciology, 41, 180–185.
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Fily,M., O. Magand, C. Genthon, G. Picard, L. Brucker, G. Krinner. (2008). POTENTIAL ERRORS IN SNOW ACCUMULATION DATA SETS IN EAST ANTARCTICA.
Abstract: SCAR meeting, St Petersburg, July 2008
Programme: 454
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Krinner, G.; Guicherd, B.; Ox, K.; Genthon, C.; Magand, O. (2008). Influence of Oceanic Boundary Conditions in Simulations of Antarctic Climate and Surface Mass Balance Change during the Coming Century. Journal of climate, 21(5), 938–962.
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Schlosser, E; Oerter, H; Masson-Delmotte, V; Reijmer, C, 2008. (2008). Atmospheric influence on the deuterium excess signal in polar firn: implications for ice-core interpretation. JOURNAL OF GLACIOLOGY, 54 (184):117-124 2008.
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. (2011). Modeling time series of microwave brightness temperature at Dome C, Antarctica, using vertically resolved snow temperature and microstructure measurements
. Journal of Glaciology, 57(201), 171–182.
Abstract: Time series of observed microwave brightness temperatures at Dome C, East Antarctic plateau, were modeled over 27 months with a multilayer microwave emission model based on dense-medium radiative transfer theory. The modeled time series of brightness temperature at 18.7 and 36.5 GHz were compared with Advanced Microwave Scanning Radiometer-EOS observations. The model uses in situ high-resolution vertical profiles of temperature, snow density and grain size. The snow grain-size profile was derived from near-infrared (NIR) reflectance photography of a snow pit wall in the range 850-1100 nm. To establish the snow grain-size profile, from the NIR reflectance and the specific surface area of snow, two empirical relationships and a theoretical relationship were considered. In all cases, the modeled brightness temperatures were overestimated, and the grain-size profile had to be scaled to increase the scattering by snow grains. Using a scaling factor and a constant snow grain size below 3 m depth (i.e. below the image-derived snow pit grain-size profile), brightness temperatures were explained with a root-mean-square error close to 1 K. Most of this error is due to an overestimation of the predicted brightness temperature in summer at 36.5 GHz.
Programme: 454
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Brucker Ludovic, Picard Ghislain, Fily Michel, . (2010). Snow grain-size profiles deduced from microwave snow emissivities in Antarctica
. Journal Of Glaciology, 56(197), 514–526.
Abstract: Spaceborne microwave radiometers are an attractive tool for observing Antarctic climate because their measurements are related to the snow temperature. However, the conversion from microwave emission to snow temperature is not simple and strongly depends on the emissivity through S snow properties. This difficulty in predicting the snow property profile for Antarctic conditions is the main bottleneck in the retrieval of accurate climate information from microwave radiometers. We attempt to explain the vertically polarized emissivity at 19.3 and 37 GHz derived from brightness temperatures acquired by the Special Sensor Microwave/Imager (SSM/I) and physical temperature from the ERA-40 re-analysis. In Antarctica the snow emissivities at 19.3 and 37 GHz are nearly equal although a decrease with frequency is expected. To explain this, we consider various profiles of snow grain size and density and predict their emissivity using a dense-medium radiative transfer (DMRT) model. The results show that the emissivities cannot be explained by constant profiles of grain size and density. Heterogeneous snowpacks need to be considered. We first test random variations of snow density and grain radius with depth and then monotonic and continuous variations in the snow grain radius. In both cases, we show that an overall increase of the snow grain radius with depth is required to match the observed emissivity in Antarctica. In addition, two parameters characterizing the snow grain profiles are retrieved and compared with (1) in situ measurements of grain size at various locations in East Antarctica, (2) grain size estimated using visible spaceborne radiometers and (3) a semi-empirical relationship for grain growth.
Programme: 454
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. (2009). Polar firn air reveals large-scale impact of anthropogenic mercury emissions during the 1970s.
. Proceedings of the National Academy of Sciences of the United States of America, 106(38), 16114–9.
Abstract: Mercury (Hg) is an extremely toxic pollutant, and its biogeochemical cycle has been perturbed by anthropogenic emissions during recent centuries. In the atmosphere, gaseous elemental mercury (GEM; Hg degrees ) is the predominant form of mercury (up to 95%). Here we report the evolution of atmospheric levels of GEM in mid- to high-northern latitudes inferred from the interstitial air of firn (perennial snowpack) at Summit, Greenland. GEM concentrations increased rapidly after World War II from approximately 1.5 ng m(-3) reaching a maximum of approximately 3 ng m(-3) around 1970 and decreased until stabilizing at approximately 1.7 ng m(-3) around 1995. This reconstruction reproduces real-time measurements available from the Arctic since 1995 and exhibits the same general trend observed in Europe since 1990. Anthropogenic emissions caused a two-fold rise in boreal atmospheric GEM concentrations before the 1970s, which likely contributed to higher deposition of mercury in both industrialized and remotes areas. Once deposited, this toxin becomes available for methylation and, subsequently, the contamination of ecosystems. Implementation of air pollution regulations, however, enabled a large-scale decline in atmospheric mercury levels during the 1980s. The results shown here suggest that potential increases in emissions in the coming decades could have a similar large-scale impact on atmospheric Hg levels.
Keywords: Air, Air Pollutants, Air Pollutants: analysis, Air Pollution, Air Pollution: analysis, Air: analysis, Algorithms, Arctic Regions, Atmosphere, Atmosphere: analysis, Ecosystem, Environmental Monitoring, Environmental Monitoring: methods, Gases, Gases: analysis, Greenland, Humans, Kinetics, Mercury, Mercury: analysis, Monte Carlo Method, Snow, Snow: chemistry, Time Factors,
Programme: 454
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Houssais M.N. & Herbaut C. (2003). Variability of the ice export through Fram Strait in 1993-98 : the winter 1994-95 anomaly. Polar research, 22, 99–106.
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L'heveder B. & Houssais M.N. (2001). Investigating the variability of the Arctic sea ice thickness in response to a stochastic thermodynamic atmospheric forcing. Climate dynamics, 17, 107–125.
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