Abstract
Ground permittivity and snow density retrievals for the “snow-free period”, “cold winter period”, and “early spring period” are performed using the experimental L-band radiometry data from the winter 2016/2017 campaign at the Davos-Laret Remote Sensing Field Laboratory. The performance of the single-angle and multi-angle two-parameter retrieval algorithms employed during each of the aforementioned three periods is assessed using in-situ measured ground permittivity and snow density. Additionally, a synthetic sensitivity analysis is conducted that studies melting effects on the retrievals in the form of two types of “geophysical noise” (snow liquid water and footprint-dependent ground permittivity). Experimental and synthetic analyses show that both types of investigated “geophysical noise” noticeably disturb the retrievals and result in an increased correlation between them. The strength of this correlation is successfully used as a quality-indicator flag for the purpose of filtering out highly correlated ground permittivity and snow density retrievals. It is demonstrated that this filtering significantly improves the accuracy of both ground permittivity and snow density retrievals compared to corresponding reference in-situ data. Experimental and synthetic retrievals are performed in retrieval modes RM = “H”, “V”, and “HV”, where brightness temperatures from polarizations p = H, p = V, or both p = H and V are used, respectively, in the retrieval procedure. Our analysis shows that retrievals for RM = “V” are predominantly least prone to the investigated “geophysical noise”. The presented experimental results indicate that retrievals match in-situ observations best for the “snow-free period” and the “cold winter period” when “geophysical noise” is at minimum.
Highlights
Microwave remote sensing can provide necessary information on Cryosphere state parameters by quantifying radiation, heat, and mass fluxes through the terrestrial surface layer [1,2], which are determinative for exchange rates of water between land and atmosphere
This work extends the analysis of retrieval approaches with respect to the sensitivity of multi-angle retrievals PRM = ρSRM, εRGM to “melting effects” that occur in the snowpack and the underlying ground
It should be recalled that the aforementioned “geophysical noise” sources are essentially caused by digressions from the assumptions of a dry snowpack over a homogeneous ground in the retrieval algorithm based on “LS—MEMLS”
Summary
Microwave remote sensing can provide necessary information on Cryosphere state parameters by quantifying radiation, heat, and mass fluxes through the terrestrial surface layer [1,2], which are determinative for exchange rates of water between land and atmosphere. The central theme of the research presented here is the tackling of the latter two issues This is seen as a continuation of a series of recent research [29,30,31] on the application of passive L-band data to gain remote information on snow mass-density and the permittivity of the underlying ground used, for instance, to characterize freeze/thaw states. It should be noted that the sensitivity of retrievals with respect to specific types of “geophysical noise”, held to be most relevant during warmer winter periods, has not been explored to date This includes, in particular, liquid snow water and the spatial heterogeneity of ground permittivity, both of which were identified as the prominent sources of “geophysical noise” that reduced retrieval quality for melting phases that were observed during the prior mentioned FMI-ARC campaign [31].
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