Intercomparison of Electromagnetic Models for Passive Microwave Remote Sensing of Snow

Electromagnetic models can be used for understanding the interaction between electromagnetic waves and matter, interpreting experimental data, and retrieving geophysical parameters. Comparing the results of different snow models, when driven with the same set of input parameters, can benefit remote sensing of snow. Microwave brightness temperatures of snow at 19 and 37 GHz for six different classes of snow (prairie, tundra, taiga, alpine, maritime, and ephemeral) are simulated by means of four different electromagnetic models: the Helsinki University of Technology snow emission model, the microwave emission model of layered snowpacks, a dense-medium radiative-transfer theory model, and a strong fluctuation theory model. The frequency behavior of the extinction coefficients obtained with the different models between 5 and 90 GHz is also studied. The four models are also driven with inputs derived from snow-pit data, and the outputs are compared with ground-based measurements of brightness temperatures at 18.7 and 36.5 GHz. Significant differences among the brightness temperatures and the extinction coefficients simulated with the four models in the cases of the six classes of snow are observed. Moreover, no particular model is found to be able to systematically reproduce all of the experimental data. The results highlight the need to more closely examine the relationships relating mean grain size and correlation length, introduce multiple layers in each model, and to perform controlled laboratory measurements on materials with well-known electromagnetic properties in order to improve the understanding of the causes of the observed differences and to improve model performance