Response of L-Band brightness temperatures to freeze/thaw and snow dynamics in a prairie environment from ground-based radiometer measurements

Abstract:The present study demonstrates the successful use of the high sensitivity of L-band brightness temperatures to snow liquid water in the retrieval of snow liquid water from multi-angular L-band brightness temperatures. The emission model employed was developed from parts of the "microwave emission model of layered snowpacks" (MEMLS), coupled with components adopted from the "L-band microwave emission of the biosphere" (L-MEB) model. Two types of snow liquid water retrievals were performed based on L-band brightness temperatures measured over (i) areas with a metal reflector placed on the ground ("reflector area"-T B,R ), and (ii) natural snow-covered ground ("natural area"-T B,N ). The reliable representation of temporal variations of snow liquid water is demonstrated for both types of the aforementioned quasi-simultaneous retrievals. This is verified by the fact that both types of snow liquid water retrievals indicate a dry snowpack throughout the "cold winter period" with frozen ground and air temperatures well below freezing, and synchronously respond to snowpack moisture variations during the "early spring period". The robust and reliable performance of snow liquid water retrieved from T B,R , together with their level of detail, suggest the use of these retrievals as "references" to assess the meaningfulness of the snow liquid water retrievals based on T B,N . It is noteworthy that the latter retrievals are achieved in a two-step retrieval procedure using exclusively L-band brightness temperatures, without the need for in-situ measurements, such as ground permittivity ε G and snow mass-density ρ S . The latter two are estimated in the first retrieval-step employing the well-established two-parameter (ρ S , ε G ) retrieval scheme designed for dry snow conditions and explored in the companion paper that is included in this special issue in terms of its sensitivity with respect to disturbative melting effects. The two-step retrieval approach proposed and investigated here, opens up the possibility of using airborne or spaceborne L-band radiometry to estimate (ρ S , ε G ) and additionally snow liquid water as a new passive L-band data product.

mentioning

confidence: 79%

Snow Wetness Retrieved from L-Band Radiometry

Naderpour

Schwank

2018

“…Theoretically, the study areas can be extended to the globe, and a long-time series F/T record can also be built using observations within the life span of AMSR2 and MODIS. However, impacts on F/T transitions from factors, for instance, snow, vegetation, topography, etc., are challenges faced by remote sensing observations [38]. The influence of land cover is weakness of the approach proposed here.…”

Section: High-resolution F/t Mapsmentioning

confidence: 98%

High-Resolution Mapping of Freeze/Thaw Status in China via Fusion of MODIS and AMSR2 Data

Zhao

Shi

et al. 2017

Transition of freeze/thaw (F/T) affects land-atmospheric interactions and other biospheric dynamics. Global F/T statuses are normally monitored using microwave remote sensing, but at coarse resolutions (e.g., 25 km). Integration of coarse microwave remote sensing data with finer satellite products represents an opportunity to further enhance our ability to map F/T statuses regionally and globally. Here, we implemented and tested an approach to generate daily F/T status maps at a 5-km spatial resolution through the fusion of passive microwave data from AMSR2 and land surface temperature products from MODIS, using China as our study area for the year 2013 and 2014. Moreover, possible influences from elevation, vegetation, seasonality, etc., were also analyzed, as such analysis provides a direction to improve the approach. Overall, our freeze/thaw maps agreed well with ground reference observations, with an accuracy of~86.6%. The new F/T maps helped to identify regions subject to frequent F/T transitions through the year, such as the Qinghai-Tibetan Plateau, Xinjiang, Gansu, Heilongjiang, Jilin, and Liaoning Province. This study indicates that the combination of AMSR2 and MODIS observations provides an effective method to obtain finer F/T maps (5-km or lower) for extensive regions. The finer F/T maps improve our knowledge of the F/T state detected by satellite remote sensing, and have a wide range of applications in regional studies considering land surface heterogeneity and models (e.g., community land models).

“…As a consequence, emerging microwave remote sensing techniques have focused on obtaining global-scale information on parameters, such as snow cover [3][4][5], vegetation optical depth [6,7], ground freeze/thaw states [8][9][10], and soil moisture [11][12][13]. The availability of these recently observable state parameters improves forecasts of climate scenarios and the optimization of corresponding mitigation strategies.…”

Section: Introductionmentioning

confidence: 99%

Snow Density and Ground Permittivity Retrieved from L-Band Radiometry: Melting Effects

Schwank

Naderpour

2018

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.