Effect of snow microstructure and subnivean water bodies on microwave radiometry of seasonal snow

Anna Kontu

Research output: ThesisDoctoral ThesisCollection of Articles


Remote sensing using microwave radiometry is an acknowledged method for monitoring various environmental processes in the cryosphere, atmosphere, soil, vegetation and oceans. Several decades long time series of spaceborne passive microwave observations can be used to detect trends relating to climate change, while present measurements provide information on the current state of the environment. Unlike optical wavelengths, microwaves are mostly insensitive to atmospheric and lighting conditions and are therefore suitable for monitoring seasonal snow in the Arctic. One of the major challenges in the utilization of spaceborne passive microwave observations for snow measurements is the poor spatial resolution of instruments. The interpretation of measurements over heterogeneous areas requires sophisticated microwave emission models relating the measured parameters to physical properties of snow, vegetation and the subnivean layer. Especially the high contrast in the electrical properties of soil and liquid water introduces inaccuracies in the retrieved parameters close to coastlines, lakes and wetlands, if the subnivean water bodies are not accounted for in the algorithm. The first focus point of this thesis is the modelling of brightness temperature of ice- and snow-covered water bodies and their differences from snow-covered forested and open land areas. Methods for modelling the microwave signatures of water bodies and for using that information in the retrieval of snow parameters from passive microwave measurements are presented in this thesis. The second focus point is the effect of snow microstructure on its microwave signature. Even small changes in the size of scattering particles, snow grains, modify the measured brightness temperature notably. The coupling of different modelled and measured snow microstructural parameters with a microwave snow emission model and the application of those parameters in the retrieval of snow parameters from remote sensing data are studied.
Translated title of the contributionLumen hienorakenteen ja lumen peittämien vesialueiden vaikutus lumen mikroaaltosäteilyyn
Original languageEnglish
QualificationDoctor's degree
Awarding Institution
  • Aalto University
  • Praks, Jaan, Supervising Professor
  • Pulliainen, Jouni, Thesis Advisor, External person
Print ISBNs978-952-60-7941-7, 978-952-336-050-1
Electronic ISBNs978-952-60-7942-4, 978-952-336-051-8
Publication statusPublished - 2018
MoE publication typeG5 Doctoral dissertation (article)


  • passive microwave remote sensing
  • snow cover
  • snow model


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