A Case Study of Using a Multilayered Thermodynamical Snow Model for Radiance Assimilation

A microwave radiance assimilation (RA) scheme for the retrieval of snow physical state variables requires a snowpack physical model (SM) coupled to a radiative transfer model. In order to assimilate microwave brightness temperatures (Tbs) at horizontal polarization (h-pol), an SM capable of resolvin...

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Bibliographic Details
Published in:IEEE transactions on geoscience and remote sensing 2011-08, Vol.49 (8), p.2828-2837
Main Authors: Toure, A. M., Goita, K., Royer, R., Kim, E. J., Durand, M., Margulis, S. A., Huizhong Lu
Format: Article
Language:English
Subjects:
Applied geophysics
Assimilation
Azimuth
Data models
Earth sciences
Earth, ocean, space
Exact sciences and technology
Geophysics
Grain size
Ice
Internal geophysics
melt-refreeze crusts
Predictive models
radiance
Snow
snowpack model (SM)
Temperature measurement
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Summary:A microwave radiance assimilation (RA) scheme for the retrieval of snow physical state variables requires a snowpack physical model (SM) coupled to a radiative transfer model. In order to assimilate microwave brightness temperatures (Tbs) at horizontal polarization (h-pol), an SM capable of resolving melt-refreeze crusts is required. To date, it has not been shown whether an RA scheme is tractable with the large number of state variables present in such an SM or whether melt-refreeze crust densities can be estimated. In this paper, an RA scheme is presented using the CROCUS SM which is capable of resolving melt-refreeze crusts. We assimilated both vertical (v) and horizontal (h) Tbs at 18.7 and 36.5 GHz. We found that assimilating Tb at both h-pol and vertical polarization (v-pol) into CROCUS dramatically improved snow depth estimates, with a bias of 1.4 cm compared to -7.3 cm reported by previous studies. Assimilation of both h-pol and v-pol led to more accurate results than assimilation of v-pol alone. The snow water equivalent (SWE) bias of the RA scheme was 0.4 cm, while the bias of the SWE estimated by an empirical retrieval algorithm was -2.9 cm. Characterization of melt-refreeze crusts via an RA scheme is demonstrated here for the first time; the RA scheme correctly identified the location of melt-refreeze crusts observed in situ.
ISSN:0196-2892
1558-0644
DOI:10.1109/TGRS.2011.2118761