Journal cover Journal topic
The Cryosphere An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

Journal metrics

  • IF value: 4.790 IF 4.790
  • IF 5-year value: 5.921 IF 5-year
    5.921
  • CiteScore value: 5.27 CiteScore
    5.27
  • SNIP value: 1.551 SNIP 1.551
  • IPP value: 5.08 IPP 5.08
  • SJR value: 3.016 SJR 3.016
  • Scimago H <br class='hide-on-tablet hide-on-mobile'>index value: 63 Scimago H
    index 63
  • h5-index value: 51 h5-index 51
Volume 10, issue 2
The Cryosphere, 10, 623–638, 2016
https://doi.org/10.5194/tc-10-623-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
The Cryosphere, 10, 623–638, 2016
https://doi.org/10.5194/tc-10-623-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 16 Mar 2016

Research article | 16 Mar 2016

Microwave snow emission modeling uncertainties in boreal and subarctic environments

Alexandre Roy1,2, Alain Royer1,2, Olivier St-Jean-Rondeau1,2, Benoit Montpetit1, Ghislain Picard3, Alex Mavrovic1, Nicolas Marchand1,2,3, and Alexandre Langlois1,2 Alexandre Roy et al.
  • 1Centre d'Applications et de Recherches en Télédétection (CARTEL), Université de Sherbrooke, 2500 boul. Université, Sherbrooke, J1K 2R1, QC, Canada
  • 2Centre d'études Nordiques, Québec, Canada
  • 3Université Grenoble Alpes – CNRS, LGGE UMR5183, 38041 Grenoble, France

Abstract. This study aims to better understand and quantify the uncertainties in microwave snow emission models using the Dense Media Radiative Theory Multi-Layer model (DMRT-ML) with in situ measurements of snow properties. We use surface-based radiometric measurements at 10.67, 19 and 37 GHz in boreal forest and subarctic environments and a new in situ data set of measurements of snow properties (profiles of density, snow grain size and temperature, soil characterization and ice lens detection) acquired in the James Bay and Umiujaq regions of Northern Québec, Canada. A snow excavation experiment – where snow was removed from the ground to measure the microwave emission of bare frozen ground – shows that small-scale spatial variability (less than 1 km) in the emission of frozen soil is small. Hence, in our case of boreal organic soil, variability in the emission of frozen soil has a small effect on snow-covered brightness temperature (TB). Grain size and density measurement errors can explain the errors at 37 GHz, while the sensitivity of TB at 19 GHz to snow increases during the winter because of the snow grain growth that leads to scattering. Furthermore, the inclusion of observed ice lenses in DMRT-ML leads to significant improvements in the simulations at horizontal polarization (H-pol) for the three frequencies (up to 20 K of root mean square error). However, representation of the spatial variability of TB remains poor at 10.67 and 19 GHz at H-pol given the spatial variability of ice lens characteristics and the difficulty in simulating snowpack stratigraphy related to the snow crust. The results also show that, in our study with the given forest characteristics, forest emission reflected by the snow-covered surface can increase the TB up to 40 K. The forest contribution varies with vegetation characteristics and a relationship between the downwelling contribution of vegetation and the proportion of pixels occupied by vegetation (trees) in fisheye pictures was found. We perform a comprehensive analysis of the components that contribute to the snow-covered microwave signal, which will help to develop DMRT-ML and to improve the required field measurements. The analysis shows that a better consideration of ice lenses and snow crusts is essential to improve TB simulations in boreal forest and subarctic environments.

Publications Copernicus
Download
Citation