Analyzing and modeling the SMOS spatial variations in the East Antarctic Plateau

Macelloni, Giovanni; Leduc-Leballeur, Marion; Brogioni, Marco; Ritz, Catherine; Picard, Ghislain

doi:10.1016/j.rse.2016.02.037

Cited by 25 publications

(22 citation statements)

References 53 publications

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“…The presence of snow largely affects the diurnal cycle of LST, for which current state-of-the-art models show some limitations. Recent results have also shown the potential for monitoring internal temperature of the ice sheet in Antarctica [123,124] using SMOS data. EOs can provide reliable information of LST over snow and ice in clear-sky conditions [125].…”

Section: Permanent Snow and Icementioning

confidence: 99%

Satellite and In Situ Observations for Advancing Global Earth Surface Modelling: A Review

et al. 2018

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In this paper, we review the use of satellite-based remote sensing in combination with in situ data to inform Earth surface modelling. This involves verification and optimization methods that can handle both random and systematic errors and result in effective model improvement for both surface monitoring and prediction applications. The reasons for diverse remote sensing data and products include (i) their complementary areal and temporal coverage, (ii) their diverse and covariant information content, and (iii) their ability to complement in situ observations, which are often sparse and only locally representative. To improve our understanding of the complex behavior of the Earth system at the surface and sub-surface, we need large volumes of data from high-resolution modelling and remote sensing, since the Earth surface exhibits a high degree of heterogeneity and discontinuities in space and time. The spatial and temporal variability of the biosphere, hydrosphere, cryosphere and anthroposphere calls for an increased use of Earth observation (EO) data attaining volumes previously considered prohibitive. We review data availability and discuss recent examples where satellite remote sensing is used to infer observable surface quantities directly or indirectly, with particular emphasis on key parameters necessary for weather and climate prediction. Coordinated high-resolution remote-sensing and modelling/assimilation capabilities for the Earth surface are required to support an international application-focused effort.

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Section: Permanent Snow and Icementioning

confidence: 99%

Satellite and In Situ Observations for Advancing Global Earth Surface Modelling: A Review

et al. 2018

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“…In terms of the future applications of GNSS‐R to monitoring the Antarctic ice sheet, it may be possible to deduce properties of Antarctic snow and ice by combining these observations with those from passive L‐band instruments, such as SMOS (e.g., Macelloni et al, ), and at other microwave frequencies, such as K u ‐band from CryoSat‐2.…”

Section: Discussionmentioning

confidence: 99%

Independent DEM of Antarctica Using GNSS‐R Data From TechDemoSat‐1

Cartwright

Clarizia

Cipollini

et al. 2018

Geophysical Research Letters

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The first digital elevation model (DEM) of the Antarctic ice sheet derived from Global Navigation Satellite Systems-Reflectometry (GNSS-R) data from the UK TechDemoSat-1 satellite is presented. This is obtained using 32 months of data from the mission. This opportunistic and inexpensive method is shown to produce encouraging results from the technology demonstration platform of TechDemoSat-1, with median bias under 18 m and root-mean-square difference under 91 m when compared to the CryoSat-2 1-km DEM v1.0. Discrepancies between the two data sets are explored along with possible causes of such differences and potential improvements to further optimize this technique for future GNSS-R missions.Plain Language Summary Obtaining measurements of the Antarctic ice sheet is critical for understanding the effects that climate change might be having on it and its potential future contribution to rising sea levels. The only practical way to do this is by using satellite data, and this has been done successfully previously from the CryoSat-2 satellite, which carries a radar altimeter. However, due to its orbit, it cannot measure an area near the South Pole. Here we demonstrate that measurements of the Antarctic ice sheet, including the vicinity of the South Pole, can be made by taking advantage of GPS signals that bounce off the ice sheet surface. The data are obtained from the UK's TechDemoSat-1 mission, which carries a simple low-cost receiver to pick up the reflected GPS signals. The results from this demonstration mission (which was not designed to survey ice sheets) are promising, showing the potential of this approach for measuring the ice sheet in the future with a dedicated satellite mission.

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“…Englacial temperature profiles have been derived from satellite and airborne passive detection of high frequency L-band microwave radiation (~1.4 GHz; Macelloni et al, 2019Macelloni et al, , 2016Passalacqua et al, 2018); data primarily collected to investigate soil moisture and ocean salinity (Kerr et al, 2010). These wavelengths have very low absorption in ice and low scattering by particles (e.g.…”

Section: Microwave Emissivitymentioning

confidence: 99%

“…Macelloni et al (2019) derived englacial temperature profiles for the Antarctic ice sheet from 2-year averaged vertical-polarised (V) radiation collected at the "Brewster angle" (57.1° ±2.6°; the angle of incidence at which the radiation is perfectly transmitted through the air-snow interface with no reflection, minimising the influence of surface or shallow sub-surface effects). The corrected intensity (brightness temperature, TB) correlates with the surface temperature of the ice, but is also affected by the ice sheet thickness (a largely inverse correlation), density profile, and grain size (Macelloni et al, 2016). As such, the ice sheet's thermal structure at depth could be estimated by comparing the observed TB and a simulated TB derived through microwave emissivity modelling, including one-dimensional modelling of the ice sheet's temperature profile.…”

Section: Microwave Emissivitymentioning

confidence: 99%

Geothermal heat flow in Antarctica: current and future directions

Burton‐Johnson

Dziadek

Martín

2020

Preprint

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Abstract. Antarctic geothermal heat flow (GHF) affects the temperature of the ice sheet, determining its ability to slide and internally deform, as well as the behaviour of the continental crust. However, GHF remains poorly constrained, with few and sparse local, borehole-derived estimates, and large discrepancies in the magnitude and distribution of existing continent-scale estimates from geophysical models. We review the methods to extract GHF, compile borehole and probe-derived estimates from measured temperature profiles, and recommend the following future directions: 1) Obtain more borehole-derived estimates from the subglacial bedrock and englacial temperature profiles. 2) Estimate GHF beneath the interior of the East Antarctic Ice Sheet (the region most sensitive to GHF variation) via long-wavelength microwave emissivity. 3) Estimate GHF from inverse glaciological modelling, constrained by evidence for basal melting. 4) Revise geophysically-derived GHF estimates using a combination of Curie depth, seismic, and thermal isostasy models. 5) Integrate in these geophysical approaches a more accurate model of the structure and distribution of heat production elements within the crust, and considering heterogeneities in the underlying mantle. And 6) continue international interdisciplinary communication and data access.

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Analyzing and modeling the SMOS spatial variations in the East Antarctic Plateau

Cited by 25 publications

References 53 publications

Satellite and In Situ Observations for Advancing Global Earth Surface Modelling: A Review

Satellite and In Situ Observations for Advancing Global Earth Surface Modelling: A Review

Independent DEM of Antarctica Using GNSS‐R Data From TechDemoSat‐1

Geothermal heat flow in Antarctica: current and future directions

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