Abstract

Natural snow, one of the most important components of the cryosphere, is fundamentally a layered medium. In forward simulation and retrieval, a single-layer effective microstructure parameter is widely used to represent the emission of multiple-layer snowpacks. However, in most cases, this parameter is fitted instead of calculated based on a physical theory. The uncertainty under different frequencies, polarizations, and snow conditions is uncertain. In this study, we explored different methods to reduce the layered snow properties to a set of single-layer values that can reproduce the same brightness temperature (TB) signal. A validated microwave emission model of layered snowpack (MEMLS) was used as the modelling tool. Multiple-layer snow TB from the snow’s surface was compared with the bulk TB of single-layer snow. The methods were tested using snow profile samples from the locally validated and global snow process model simulations, which follow the natural snow’s characteristics. The results showed that there are two factors that play critical roles in the stability of the bulk TB error, the single-layer effective microstructure parameter, and the reflectivity at the air–snow and snow–soil boundaries. It is important to use the same boundary reflectivity as the multiple-layer snow case calculated using the snow density at the topmost and bottommost layers instead of the average density. Afterwards, a mass-weighted average snow microstructure parameter can be used to calculate the volume scattering coefficient at 10.65 to 23.8 GHz. At 36.5 and 89 GHz, the effective microstructure parameter needs to be retrieved based on the product of the snow layer transmissivity. For thick snow, a cut-off threshold of 1/e is suggested to be used to include only the surface layers within the microwave penetration depth. The optimal method provides a root mean squared error of bulk TB of less than 5 K at 10.65 to 36.5 GHz and less than 10 K at 89 GHz for snow depths up to 130 cm.

Highlights

  • Introduction5% of the precipitation in the world reaches the ground in the form of snowfall [1]

  • Seasonal snow cover is an important component of the cryosphere

  • In order to improve the understanding of TB Error, the snow depth is presented in thick gray lines

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Summary

Introduction

5% of the precipitation in the world reaches the ground in the form of snowfall [1]. Each snowfall event accumulates a new amount of fresh snow over the old snow, which results in a naturally layered snow profile of vertical inhomogeneity. Snow particles undergo a complex metamorphism process, where the particle size increases and the particle shape changes. The snow microstructure governs many snow physical properties and the radiative transfer properties for remote sensing at visible, near-infrared, and microwave bands [2,3,4,5]. The snow microstructure parameters, for example, the geometric grain size, specific surface area, and autocorrelation function, are measurable using different instruments [6,7,8], when it comes to the remote sensing signal simulation or Remote Sens.

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