Simulating seasonally and spatially varying snow cover brightness temperature using HUT snow emission model and retrieval of a microwave effective grain size Juha Lemmetyinen a, ⁎, Chris Derksen b , Peter Toose b , Martin Proksch c,d , Jouni Pulliainen a , Anna Kontu a , Kimmo Rautiainen a , Jaakko Seppänen e , Martti Hallikainen e a Finnish Meteorological Institute, Arctic Research, Erik Palménin aukio 1, 00560 Helsinki, Finland b Environment Canada, Climate Research Division, 4905 Dufferin Street, M3H 5T4 Toronto, Ontario, Canada c WSL Institute for Snow and Avalanche Research SLF, Flüelastrasse 11, CH-7260 Davos Dorf, Switzerland d Institute for Meteorology and Geophysics IMGI, University of Innsbruck, Innrain 52f, 6020 Innsbruck, Austria e Aalto University, Department of Radio Science and Engineering, Otakaari 5A, Espoo, Finland abstract article info Article history: Received 24 April 2014 Received in revised form 5 September 2014 Accepted 11 September 2014 Available online xxxx Keywords: Snow water equivalent Passive microwave The Helsinki University of Technology (HUT) snow emission model forms the basis of the European Space Agency's GlobSnow snow water equivalent (SWE) product (Takala et al., 2011). The model applies a semi- empirical radiative transfer calculation to account for the interaction of the snow medium with microwaves; separate components are applied to account for vegetation, the atmosphere, and emission from the ground surface. For the retrieval of SWE, an innovative method is used to account for spatial and temporal variability in snow conditions by retrieving an effective parameter describing the scattering behavior of microwaves in the snow (a proxy indicator of the microwave effective snow grain size). In this study, the influence of differing snow conditions, as well as varying land cover, on the retrieved microwave effective snow grain size was analyzed. Passive microwave measurements were acquired using tower-based, mobile sled-based and airborne radiometers in a mixed forest environment near Sodankylä, Finland. Forward simulations at the tower site over an entire winter period showed that the use of an empirical relation to modify the classical in situ measured grain size produced HUT model bias errors less than 6 K on average at 19 and 37 GHz from a ~20–80 cm deep boreal snowpack. Model simulations for airborne and sled-based observations showed that using a simplified 2-layer representation of the snowpack improves simulation biases and RMSE, although modification of the measured grain size was again necessary to achieve these results, regardless of the layering configuration. The microwave effective grain size retrieved from HUT predictions was closely related to a simple average grain size measured in situ, both in terms of magnitude and temporal trend. This is an important finding as the retrieval scheme of Takala et al. (2011) relies on the microwave effective grain size to retain a degree of physical basis for values to be generally applicable over larger areas, which is challenging because this free parameter also accounts for errors unrelated to the effective snow grain size (i.e. vegetation, soil conditions, scene heterogeneity, etc.). © 2014 Elsevier Inc. All rights reserved. 1. Introduction Snow cover properties can be monitored on a regional or hemi- spherical scale by means of manual or automated point-wise measure- ments through the application of appropriate interpolation techniques (e.g. Brasnett, 1999). However, in higher latitudes snow measurement networks are very sparse, affecting the accuracy of these methods (Atkinson & Kelly, 1997). Satellite microwave radiometry has the poten- tial to provide additional value due to the spatial and temporal coverage of satellite measurements. In-addition, relative to data collected in visible wavelengths, microwave remote sensors have the added benefit of improved cloud penetration, and are not dependent on solar illumi- nation, making microwave radiometry particularly suitable for high lat- itude regions. Retrieval of snow water equivalent (SWE) from passive microwave observations dates back over three decades to initial studies made using the first operational radiometers in space (Foster et al., 1980; Künzi et al., 1982; Rango, Chang, & Foster, 1979; Tiuri & Hallikainen, 1981). The basic hypotheses presented in these first studies are still retained in several currently operational SWE retrieval algorithms (Goodison & Walker, 1995; Kelly, 2009; Takala et al., 2011). The algorithms are based on the scattering of microwave radiation in the snow medium; radiation from the ground surface is attenuated, Remote Sensing of Environment 156 (2015) 71–95 ⁎ Corresponding author. Tel.: +358 407303663. E-mail address: juha.lemmetyinen@fmi.fi (J. Lemmetyinen). http://dx.doi.org/10.1016/j.rse.2014.09.016 0034-4257/© 2014 Elsevier Inc. All rights reserved. Contents lists available at ScienceDirect Remote Sensing of Environment journal homepage: www.elsevier.com/locate/rse