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Ice shelves are important parts of the cryosphere that influence ice sheet dynamics and mass loss. The internal temperatures of ice shelves are currently known only from a few borehole sites or from glaciological models. Microwave radiometry in the 0.4–2.5 GHz range is capable of receiving thermal emissions from deep within an ice shelf and thereby providing information on internal temperatures. This letter reports modeling studies of the brightness temperature of the Ross Ice Shelf (RIS) from 0.4 to 2.5 GHz that provide insight into the potential of microwave radiometers for measuring ice shelf internal properties.

Microwave brightness temperatures observed in Antarctica at 89 GHz from the advanced microwave sounding unit B (AMSU-B) point out an exceptional decrease of 57 K at Dome Fuji ($77.31^{\circ} \text{S}$,$39.70^{\circ} \text{E}$) during the 2019–2020 summer. The grain size index (GSI) based on 89 and 150 GHz from AMSU-B and independent observations at 89 GHz from the advanced microwave scanning radiometer 2 (AMSR-2) also show concurrent unusual values. To explain such event, a theoretical analysis was carried out by means of a radiative transfer model. We explore the sensitivity of brightness temperature to surface snow properties focusing on December, just before the decrease, and April, at its end. Results confirm that this variation is mainly related to an increase in snow grain size. A decrease in snow density is also involved as suggested by the increase in brightness temperature at 1.4 GHz from soil moisture and ocean salinity (SMOS) and in the polarization ratio at 36 GHz from AMSR-2. Extreme values observed at multiple frequencies, as well as peculiar atmospheric conditions explored in a previous study, confirm the uniqueness of this event at least on decennial scale.

Since 2004 ESA has supported the Domex experiment to monitor the emission of the East Antarctic Plateau at Dome C to verify and assess the calibration and stability of SMOS L1 products. The region has been monitored from monthly to yearly scale. This work focuses on the absolute calibration methodology developed for the Domex experiment and its improvements along the experiment's life. The calibrated dataset consisting of almost nine years of brightness temperatures is discussed here. Results were compared with the other L-band datasets over Dome-C, such as SMOS, SMAP and DOMECair 2013.

This paper is a preliminary study of estimation of Antarctica Dome-C ice sheet properties using 0.5-2 GHz Ultra Wide Band Software Defined Radiometer (UWBRAD). The estimated ice sheet parameters include the vertical temperature profile and stochastic parameters that describe the density fluctuations within the ice column. The borehole measured temperature profile is used as a prior. The inversion uses regularization to incorporate both the prior borehole measurement and the UWBRAD data in the cost function. A hybrid model that use both cloud and partially-coherent models is chosen for this study as the forward model [1]. Since the partially-coherent model has a long computation time, a neural network is trained to replace the hybrid forward model and this neural network is used in the inversion. A genetic algorithm inversion scheme is used.

Measurements of the 500–2000-MHz brightness temperature spectra of Antarctica acquired under the Ice Sheet and Sea Ice Ultrawideband Microwave Airborne eXperiment (ISSIUMAX) are reported. These data sets support the remote sensing of ice sheet properties, in particular information on the temperature profile within the ice sheet. The Ultrawideband Software-Defined Microwave Radiometer (UWBRAD) was installed on a Twin Otter aircraft, and measurements were collected on coastal areas and the interior of East Antarctica in November and December 2018. UWBRAD 500–2000-MHz brightness temperature measurements along a 1000-km path over the ice sheet are compared in this letter to forward model simulations for these locations and confirm the expected sensitivities to ice sheet parameters.

Radiometric and radar data from NASA’s Soil Moisture Active Passive (SMAP) satellite are presented in a study of the Ross Ice Shelf, Antarctica. L-band brightness temperature (TB) patterns compare favorably to the outflow patterns from East and West Antarctica. CoolerTBis associated with the broad outflow from West Antarctic ice streams and the outflow from narrow outlet glaciers that drain East Antarctica. Aside from outlet glacier discharges, ice from East Antarctica is thinner and radiometrically warmer than that from West Antarctica.TBis stable across the ice shelf over the 6-year period of observations (1-2 K standard deviation). Over shorter times, surface melt events cause pre- and post-meltTBto vary by as much as 5 K in vertical polarization. Radar measurements highlight areas where backscatter is strong from melt related ice lenses and ice layers, consistent with a corresponding decrease inTB. TheTBpolarization ratio on the ice shelf is approximately 1.13 and decreases from the West Antarctic grounding line towards the East Antarctic outlet glaciers. The backscatter polarization ratio increases by several dB from West to East Antarctica, indicating a decreasing influence of volume scatter toward East Antarctica. The decreasingTBpolarization ratio indicates a diminishing role of firn layering on the depth-integrated emission. There is a negative correlation between warming brightness temperature and thinning. An explanation for this observation is that the relatively warm ice shelf has a relatively shallow (500 m or less) penetration depth leading to a warm physical temperature bias.

Within the framework of European Space Agency (ESA) activities, several campaigns were carried out in the last decade with the purpose of exploiting the capabilities of multifrequency synthetic aperture radar (SAR) data to retrieve snow information. This article presents the results obtained from the ESA SnowSAR airborne campaigns, carried out between 2011 and 2013 on boreal forest, tundra and alpine environments, selected as representative of different snow regimes. The aim of this study was to assess the capability of X- and Ku-bands SAR in retrieving the snow parameters, namely snow depth (SD) and snow water equivalent (SWE). The retrieval was based on machine learning (ML) techniques and, in particular, of artificial neural networks (ANNs). ANNs have been selected among other ML approaches since they are capable to offer a good compromise between retrieval accuracy and computational cost. Two approaches were evaluated, the first based on the experimental data (data driven) and the second based on data simulated by the dense medium radiative transfer (DMRT). The data driven algorithm was trained on half of the SnowSAR dataset and validated on the remaining half. The validation resulted in a correlation coefficient$R \simeq 0.77$between estimated and target SD, a root-mean-square error (RMSE)$\simeq 13$cm, and bias = 0.03 cm. ANN algorithms specific for each test site were also implemented, obtaining more accurate results, and the robustness of the data driven approach was evaluated over time and space. The algorithm trained with DMRT simulations and tested on the experimental dataset was able to estimate the target parameter (SWE in this case) with$R =0.74$, RMSE = 34.8 mm, and bias = 1.8 mm. The model driven approach had the twofold advantage of reducing the amount ofin situdata required for training the algorithm and of extending the algorithm exportability to other test sites.

The Snow Microwave Radiative Transfer (SMRT) model was initially developed to explore the sensitivity of microwave scattering to snow microstructure for active and passive remote sensing applications. Here, we discuss the modular design of SMRT that has enabled its rapid extension by the community. SMRT can now represent a layered medium consisting of snow, land ice, lake ice and/or sea ice overlying a substrate of soil, water or parameterized by reflectivity. A time-dependent radiative transfer solution method has also been added to allow for low resolution mode altimetry applications. We illustrate the use of SMRT to simulate brightness temperature for snow on lake ice, backscatter for snow on soil and altimeter waveforms for snow on sea ice.

Vertical ice sheet temperature profiles are affected by processes such as snow accumulation rates, geothermal effects, the properties of the ground over which the ice column is sitting. These internal ice sheet temperatures and their variations both with depth and location are crucial in understanding ice sheet evolution. The temperature profile in depth plays an important role in influencing stress-strain relationships in the ice sheet volume, and therefore impacts ice sheet dynamics including deformation and flow across the ice sheet base. There are currently no instruments for remote sensing the entire vertical ice sheet temperature profile. Most current information about the depth and spatial variation in ice sheet temperatures comes from borehole measurements [1].

Advances in RFI detection and filtering have promoted the design of wide-bandwidth radiometers that operate outside the traditional protected radiometry bands. Wideband operation requires the use of components without well-matched impedances, producing multiple reflections within a system that may impact the calibration process. Operating over large bandwidths also exposes the system to unknown and possibly high power RF signals that can damage components, requiring the use of protective devices that can increase loss and reflections further. UWBRAD is an ultrawideband radiometer designed to operate from 500-2000 MHz that has successfully flown three missions to the polar regions of Earth (Greenland and Antarctica). This paper reviews the calibration methods, challenges, and RFI environments encountered in these missions with consequences and lessons for future wideband radiometers.

An ultrawideband radiometer was used to measure microwave brightness temperature spectra over Arctic sea ice in the Lincoln Sea near the north coast of Greenland. Spectra over the range of 0.5-2 GHz were compared to thermal infrared images collected during the airborne campaign and also compared to nearly concurrent Sentinel-1 C-band synthetic aperture radar (SAR) data. Based on those comparisons, spectral signatures were associated with thick multiyear ice and thin ice. A radiative transfer (RT) model consisting of a homogeneous slab of sea ice bounded by sea water and air was then used to invert the spectra for sea ice thickness and salinity. Inferred thicknesses were consistent with ice thickness climatology for ice floes in the Lincoln Sea. Salinities are higher than expected which may be a consequence of neglecting surface and volume scattering contributions in the models.

In Antarctica, the coastal and ice-shelves areas are affected by snowmelt during the austral summer. The length and extend of this melting period are key parameters in the study of climate and its interannual variations in these regions. Melting events have a significant impact on the microwave emissivity of the surface. Thus, satellite microwave observations can be used in order to provide useful information over the whole Antarctic coast and ice-shelves. Several studies exploited the 19 and 37 GHz long time series to retrieve snowmelt events. In this study, these algorithms previously developed have been used to detect melt from the Soil Moisture and Ocean Salinity (SMOS) satellite observations at 1.4 GHz. Snowmelt dataset was obtained from April 2010 and March 2017 with SMOS observations. Finally, the potential of combined low and high frequencies to provide a synergetic description of surface melting events in Antarctica have been highlighted.

Earth's cold regions are key elements of the planet's climate system: they have strong feedbacks with global change and they have a direct impact on human activities. Despite their importance, at present they are not adequately monitored by state-of-the-art instruments. In order to fill this gap, a dedicated spaceborne mission called Cryorad has been proposed in the framework of the ESA Earth Explorer 10 call. The mission would comprise a 0.4-2 GHz nadir-looking radiometer installed on a polar-orbit satellite. Scientific and technical studies are underway, as well as experimental campaigns in Greenland and Antarctica.

In Antarctica, the coastal and ice-shelves areas are affected by snowmelt during the austral summer. The length and extend of this melting period are key parameters in the study of climate and its interannual variations in these regions. Melting events have a significant impact on the microwave emissivity of the surface. Thus, satellite microwave observations can be use in order to provide useful information over the whole Antarctic coast and ice-shelves. Several studies exploited the 19- and 37-GHz long time series to retrieve snowmelt events. Due to the large penetration depth at L-band in regard of higher microwave frequencies, SMOS observations (1.4-GHz) could give additional information. In this study, the algorithms developed in these previous works are used to detect melt from the SMOS brightness temperature at horizontal polarization. Snowmelt product is obtained from July 2010 and June 2015 with SMOS observations.

A new space-borne mission based on a multi-channel microwave radiometer in the frequency range 0.5-2 GHz as been recently approved by the Italian Space Agency for a preliminary concept study. The innovative instrument will be devoted to the study of the Cryosphere and in particular on sea ice volume, ice sheet temperature and soil status. Scientific objectives and first mission concept are presented here and in depth discussed at the conference.

The internal ice sheet temperature is a key parameter for the understanding of the ice sheet dynamics which, at present, is available only from glaciological models or in the few boreholes where temperature has been measured. From the analysis of space-borne L-band data from SMOS, collected over Antarctica, it was proved that they are sensitive to the ice sheet temperature profile. In this paper it is demonstrated that starting from satellite data and using a combination of glaciological and microwave emission model it is possible to retrieve this important geophysical parameter at continental scale.

Two electromagnetic models were used to simulate snow emission at L-band from in situ measurements of snow properties collected at Dome C in Antarctica. Two different approaches were used: one based on the radiative transfer theory and the other on the wave approach. The soil moisture ocean salinity (SMOS) satellite observations performed at 1.4 GHz (21 cm) were used to check the validity of these models. Model results based on the wave approach were in good agreement with SMOS observations, particularly for incidence angles lower than 55°. Comparisons suggest that the wave approach is more suitable to simulate brightness temperature at L-band than the transfer radiative theory, because interference between the layers of the snowpack is better taken into account. The model based on the wave approach was then used to investigate several L-band characteristics at Dome C. The emission e-folding depth, i.e., 67% of the signal, was estimated at 250 m, and 99% of the signal emanated from the top 900 m. L-band brightness temperature is only slightly affected by seasonal variations in surface temperature, confirming the high temporal stability of snow emission at low frequency. Sensitivity tests showed that good knowledge of density variability in the snowpack is essential for accurate simulations in L-band.

The CAROLS L-band radiometer, which is built and designed as a copy of DTU EMIRAD II instrument will be used in conjunction with other airborne instruments (in particular the C-Band scatterometer STORM) in coordination with in situ field campaigns for futur SMOS CAL/VAL activities. A validation campaign with four flights was made over the South West of France and the Bay of Biscay (Atlantic Ocean) in September 2007. Different instrumented sites were over ocean and land surfaces were coverecd. Moreover, in order to qualify the radiometric data, different types of aircraft maneuvers were performed over ocean: circle flights, wing and nose wags. We present in this paper the first analysis of the data quality using these ocean measurements. We show a very good sensitivity of both channels.