Abstract
The L-band radiometry data and in-situ ground and snow measurements performed during the 2016/2017 winter campaign at the Davos-Laret remote sensing field laboratory are presented and discussed. An improved version of the procedure for the computation of L-band brightness temperatures from ELBARA radiometer raw data is introduced. This procedure includes a thorough explanation of the calibration and filtering including a refined radio frequency interference (RFI) mitigation approach. This new mitigation approach not only performs better than conventional “normality” tests (kurtosis and skewness) but also allows for the quantification of measurement uncertainty introduced by non-thermal noise contributions. The brightness temperatures of natural snow covered areas and areas with a reflector beneath the snow are simulated for varying amounts of snow liquid water content distributed across the snow profile. Both measured and simulated brightness temperatures emanating from natural snow covered areas and areas with a reflector beneath the snow reveal noticeable sensitivity with respect to snow liquid water. This indicates the possibility of estimating snow liquid water using L-band radiometry. It is also shown that distinct daily increases in brightness temperatures measured over the areas with the reflector placed on the ground indicate the onset of the snow melting season, also known as “early-spring snow”.
Highlights
Microwave remote sensing is preeminently suitable to achieve quantitative estimates of large-scale terrestrial state parameters
The present work is to be seen as the scientific basis for upcoming research on L-band remote sensing applied to the retrieval of ground freeze/thaw state and snow volume properties, such as mass density and liquid water content
As part of ETH L-band radiometer (ELBARA)-II’s raw data processing to achieve calibrated brightness temperatures, a refined radio frequency interference (RFI) mitigation approach is suggested based on fitting a Gaussian model to the distribution of measured raw-data voltage samples
Summary
Microwave remote sensing is preeminently suitable to achieve quantitative estimates of large-scale terrestrial state parameters. The development of radiative transfer models with the aforementioned features necessitates the development and operation of field laboratories allowing for comprehensive, synchronous and collocated in-situ and near-distance remote sensing measurements. Such field laboratories, dedicated to the development of methods to optimally exploit microwave remote sensing of the Cryosphere, are still rare today. It is of value for the development of a new retrieval approach for the estimation of snow liquid water-column from passive L-band radiometry. Using Synthetic Aperture Radar (SAR) techniques, 3D backscatter maps of the site are made indicating parameters such as radiation penetration depth and snow water equivalent of dry snow
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