News
- Nov 2019 - Jan 2020: 5th Antarctic Campaign, with a lightning visit of the megadunes on the EAIIST traverse.
- Jul 2019: Second SMRT training at Waterloo University in Canada and 3 week visit at Environment Canada in Toronto.
- Mar 2019: Field trip in Sodankyla, Findland for SnowAAP experiment.
- Oct 2018: The spectral albedometer Autosolexs at Dome C has started to provide observations for the fifth season.
- Oct 2018: The Dessimination COST Harmosnow workshop in Budapest is gathering 80 people.
- June 2018: A side meeting at Polar 2018 on Antarctic precipitation and blowing snow. The presentations are online.
- Mai 2018: The surface melting dataset is up-to-date with the 2017-2018 season.
- Mar 2018: ”Snow Observations and Data Assimilation” in Bormio, Italy, March 12-16, 2018 is organised by Harmosnow.
- Feb 2018: After a very successful SMRT Training at Lautaret pass, the paper on the model is out and the website is open. A big step for the microwave community !
Publications
Selected publications:
- G. Picard, M. Sandells, H. Löwe, SMRT: An active / passive microwave radiative transfer model for snow with multiple microstructure and scattering formulations (v1.0), Geoscientific Model Development, 11, 2763-2788, doi:10.5194/gmd-11-2763-2018
- F. I., Adodo, F., Remy, and G. Picard, Seasonal variations of the backscattering coefficient measured by radar altimeters over the Antarctica Ice Sheet, The Cryosphere, doi:10.5194/tc-12-1767-2018, 2018
- Tuzet, F., Dumont, M., Lafaysse, M., Picard, G., Arnaud, L., Voisin, D., Lejeune, Y., Charrois, L., Nabat, P., and Samuel, M., A multi-layer physically-based snowpack model simulating direct and indirect radiative impacts of light-absorbing impurities in snow, The Cryosphere, 11, 2633-2653, doi:10.5194/tc-11-2633-2017, 2017
- M. Dumont, L. Arnaud, G. Picard, Q. Libois, Y. Lejeune, P. Nabat, D. Voisin, S. Morin, In situ continuous visible and near-infrared spectroscopy of an alpine snowpack, The Cryosphere, 11, 1091-1110, doi:10.5194/tc-11-1091-2017 2017
- G. Picard, Libois, Q., and Arnaud, L., Refinement of the ice absorption spectrum in the visible using radiance profile measurements in Antarctic snow, The Cryosphere, doi:10.5194/tc-2016-146, 2016
- G. Picard, L. Arnaud, J.-M. Panel, S. Morin, Design of a scanning laser meter for monitoring the spatio-temporal evolution of snow depth and its application in the Alps and in Antarctica, The Cryosphere, 10, 1495-1511,doi:10.5194/tc-10-1495-2016, 2016
Ongoing and past projects
ANR EAIIST, 2017 - 2020 (J. Savarino): East Antarctic International Ice Sheet Traverse- ESA S3 SNOW, 2017 - 2018
ANR ASUMA, 2015 - 2018 (V. Favier): Amélioration de la précision de l'estimation de bilan de masse de surface en Antarctique.
- Acceleration of Permafrost Thaw By Snow-Vegetation Interactions, BNP Paribas Fundation, 2015 - 2017 (F. Dominé)
- ESA Microsnow, 2015 - 2016
- ESA CRYOSMOS, 2015 - 2016
- CNES projects: SMOS, Antar-TS and GreenEdge
- ANR MONISNOW 2011-2016 (G. Picard): Monitoring Snow in a changing climate
- PNTS 2010-2012 (G. Picard): Detection of snowfall events using microwave observations
- LEFE/QUASPPER 2010-2012 (S. Morin): Quantitative assessment and modeling of snow physical properties
PICS 2008-2011 (G. Picard) : Programme International de Collaboration Scientifique with CARTEL, University of Sherbrooke, Canada- LEFE/CHARMANT 2008-2011 (G. Krinner): Regional change of the surface mass balance in Antarctica
- ANR/VANISH 2007-2011 (M. Fily): Vulnerability of the Antarctic ice sheet and its atmosphere
- PNTS 2006-2008 (G. Picard): Coupling between a snow evolution model and a microwave emission model in Antarctica
Post-doc, PhD and Master Students
Post-doc:- F. Larue (2018-)
- M. Lamare (2017-)
- O. Passalacqua (2018)
- M. Leduc-Leballeur (2012-2017)
- C. Vargel (supervised A. Royer (U. Sherbrooke) and G. Picard, 2017-2021)
- F. Tuzet (supervised with M. Dumont, 2016-2020)
- F. Adodo (supervised wtih F. Rémy (LEGOS), 2015-2018)
- M. Belke (supervised with F. Dominé (Takuvik, Québec) and G. Picard, 2015-2019)
- G. Vérin (supervised withM. Babin (Takuvik, Québec), 2014-2018)
- H. Fréville (supervised with E. Brun (CNRM-GAME), 2012-2015)
- Q. Libois (2011-2014)
- F. Dupont (supervised with M. Fily (LGGE) & A. Royer (U. Sherbrooke, Quebec), 2010-2013)
- N. Champollion (supervised with M. Fily (LGGE), 2009-2012)
- L. Brucker (supervised with M. Fily (LGGE), 2006-2009)
- R. Caneill (2017): Analysis of Elevation Maps Measured by Laser Scannering at Dome C, Antarctica. Investigation of Snow Accumulation Processes
- A. Lemoine (2017): Modeling microwave observations from snow properties in Antarctica
- N. Champollion (2009): Measuring snow specific surface area
- B. Montpetit (2008): Toward a finer resolution snow melt product (French)
- I. Gravaud (2008): Detection of precipitation events by passive microwave remote sensing in Antarctica(French)
- F. Cyr (2007): Modeled and observed snow melt (French)
Instruments
POSSSUM (Profile Of Snow Specific Surface Area Measurement Using SWIR reflectance) measures the specific surface area (SSA, a metrics of the grain size) profile in snow boreholes with a vertical resolution of one centimeter and down to depths of up to 20 m. POSSSUM measure the snow reflectance (albedo) in the short wave infrared (SWIR) at 1310nm to estimate the SSA. It takes max 1 hour to sample a 10 m deep hole! POSSSUM was tested and validated in the Alps (Arnaud et al. 2011) and was used in Antarctica in Dec 2009 for the first time.
POSSSUM pictures..., Poster at ISSW 2009 
ASSSAP 1 & 2 (Alpine/Arctic Snow Specific Surface Area) is a light-weight version of POSSSUM designed for the shallow snowpacks (max 2 m) usually found in Alpine and Arctic regions. ASSSAP uses exactly the same principle of measurement as POSSSUM and allows in addition measurements on snow samples like DUFISSS/IceCube. ASSSAP has extensively been used in Antarctica, Greenland, and in the Alps. During the Davos Intercomparison campaign we have confirmed that the accuracy is as good as other technique in sample mode (10%) and still very good in profile mode (15%). Considering that it takes 10 min to acquire a 1-m profile, ASSSAP is a very efficient method to get accurate SSA and sample the spatial variability.
RLS (Rugged Laser Scan ) is an automatic laserscan designed to work at Dome C, even in winter by -80°C. It scans an area of 150m2 every day and allow monitoring snow accumulation, roughness change, sastrugi dynamics and more. Four devices are currently built, RLS1 has been runnning Dome C since Jan 2015 (Picard et al. 2016). RLS2 was one season at Col du Porte for testing (Picard et al. 2016) and two seasons at Col du Lac Blanc to investigate sastrugi development in collaboration with F. Naaim, H. Bellot. RLS3 device has been running at Col de Porte in a clear-cut in a pine forest to investigate snow &s; vegetation interactions (M. Sicart). RLS4 is being deployed at Umuijaq in Canada in the framework of the Acceleration of Permafrost Thaw By Snow-Vegetation Interactions project (F. Dominé).
Autosolexs is an automatic multi-channel spectrometer with home-made high-accuracy cosine collectors. AutosolexsDMC has been running at Dome C since Dec 2012 (Libois et al. 2015, Picard et al. 2016, see also data). It is composed of two heads with up- and down-looking channels and fibers embedded in the snowpack. AutosolexsCdP is a similar device installed at Col de Porte in 2012-2013 and 2013-2014 (Dumont et al. 2017, see also data) and at Col du Lautaret (2016-2017) for the ANR EBONI (M. Dumont) and ESA S3 SNOW projects.- Solexs is an optical instrument to measure the profile of irradiance in snow that can be related to snow microstructure (Libois et al. 2014) and ice absorption (Picard et al. 2016) depending on the environment and spectral range. It allows very fast measurements which is interesting by itself to assess the spatial variability but also from a more quantitative point of view when exploited in complement to other micro-structure like SSA or density.
Models
- SMRT is a new generation microwave model to compute thermal emission and backscatter of snowpacks. Initiated in an ESA project on snow microstructure in 2015, it is nowaday a comprehensive framework to conduct simulations for a wide range of media and electromagnetic conditions. The model is highly modular allowing switching between different scattering theories, snow microstructure representation, ice permittivity formulations, radiative transfer solving methods, etc. The model is also highly extensible and fully open to community developments. The model is equipped with a rich ecosystem of tools and a comprehensive documentation to lower the learning barrier for beginners. SMRT has a website and is on github with a lot of introduction materials.
- DMRT-ML computes the thermal microwave emission of snowpacks, is now available as an open source software. It is based on the Dense Media Radiative Transfer theory. Please use it and contribute to improve this code! More information, documentation and download
- TARTES computes snow albedo and other optical properties in the visible/near infrared range. It is a great small piece of Python code that merges Kokhanovsky and Zege, (2004) theory and two-stream solution of the radiative transfer equation. For this public release, we improved the model code and prepared a comprehensive documentation to make TARTES as easy-to-use as possible by any snow scientists with or without (strong) snow optics expertise. More information, documentation and download. TARTES can also be used online to compute albedo.
Data
PAuto is a near-infrared time-lapse photography system installed at Dome C to monitor the surface. It is ideal to reveal the complexity of the accumulation, drift, post-deposition, and crystallation processes. Operating such a camera is quite challenging in Antarctica with extreme low temperatures. The set of daily picture used by Champollion et al. 2013, spanning November 2009 to February 2010 and from January 2011 to February 2013 is can be browsed and downloaded. More recent data are available upon request. Pauto has been move on the American tower in Jan 2017.
Surface melting occurs every summer on the coasts and shelves in Antarctica. The inter-annual variations of the melt duration or extent are important indicators of the coastal climate variations. Melt events are easily detected using microwave radiometer data that are available since 1979. We processed these data to extract every single melt events in Antarctica at a 25-km resolution and on a daily basis. This dataset is packaged in a convenient format and freely distributed and updated every year in October when the lastest SSM/I data are published by NSIDC. Download Melt data