04 May 2023
 | 04 May 2023
Status: this preprint is open for discussion.

Evaluating Snow Microwave Radiative Transfer (SMRT) model emissivities using observations of Arctic tundra snow

Kirsty Wivell, Stuart Fox, Melody Sandells, Chawn Harlow, Richard Essery, and Nick Rutter

Abstract. Improved modelling of snow emissivity is needed to improve the assimilation of surface-sensitive atmospheric sounding observations from satellites in polar regions for Numerical Weather Prediction (NWP). This paper evaluates emissivity simulated with the Snow Microwave Radiative Transfer (SMRT) model using observations of Arctic tundra snow, at frequencies between 89 and 243 GHz. Measurements of snow correlation length, density and layer thickness were used as input to SMRT, and an optimization routine was used to assess the impact of each parameter on simulations of emissivity when compared to a set of Lambertian emissivity spectra, retrieved from observations of tundra snow from three flights of the Facility for Airborne Atmospheric Measurements (FAAM) aircraft. Probability distributions returned by the optimization routine demonstrate parameter uncertainties and the sensitivity of simulations to the different snow parameters. Results showed that SMRT was capable of reproducing a range of observed emissivities between 89 and 243 GHz. Varying correlation length alone allowed SMRT to capture much of the variability in the emissivity spectra, however, overall RMSE (and MAE) decreased from 0.029 (0.018) to 0.013 (0.0078) when the thickness of the snow layers was also varied. When all three parameters were varied simulations were similarly sensitive to both correlation length and density, although the influence of density was most evident when comparing spectra from snowpacks with and without surface snow. Simulations were most sensitive to surface snow and wind slab parameters, while sensitivity to depth hoar depended on the thickness and scattering strength of layers above, demonstrating the importance of representing all three parameters for multi-layer snowpacks when modelling emissivity spectra. This work demonstrates the ability of SMRT to simulate snow emissivity at these frequencies, and is a key step in progress towards modelling emissivity for data assimilation in NWP.

Kirsty Wivell et al.

Status: open (until 29 Jun 2023)

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  • RC1: 'Comment on egusphere-2023-878', Anonymous Referee #1, 26 May 2023 reply

Kirsty Wivell et al.

Data sets

Emissivity spectra retrieved from airborne observations collected during the MACSSIMIZE field campaign Kirsty Wivell, Stuart Fox, and Chawn Harlow

Kirsty Wivell et al.


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Short summary
Satellite microwave observations improve weather forecasts, but to use these observations in the Arctic, snow emission must be known. This study uses airborne and in situ snow observations to validate emissivity simulations for two- and three-layer snowpacks, at key frequencies for weather prediction. We assess the impact of thickness, grain size and density in key snow layers, which will help inform development of physical snow models that provide input snow profiles to emissivity simulations.