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The future Copernicus Imaging Microwave Radiometer (CIMR), funded by the European Commission and developed by the European Space Agency (ESA), will include a spaceborne radiometer able to provide the highest ground spatial resolution as of launch date for C- to Ka-bands, due to its large deployable mesh reflector able to produce images over a swath 2000 km wide. Because of side and grating lobes in the patterns, the antenna subsystem introduces distortions in the acquired data that result in a loss of radiometric accuracy caused by unwanted energy collected far from the antenna boresight. A candidate antenna pattern correction (APC) algorithm based on an iterative formulation that takes advantages of measurements belonging to the same swath was already proposed by the authors. As the antenna boresight moves closer to the edges of the swath, the antenna pattern (AP) senses regions not already observed, where the correction needs a guess or auxiliary out-of-swath information. This article evaluates the performance of the candidate APC algorithm according to various possible a priori assumptions. Eventually, an evaluation is performed using a timeseries derived from Special Sensor Microwave/Imager enhanced-resolution data. This was done to get a first assessment of the impact of past ancillary information on the APC process.

Recent updates in the use of 0.5-2 GHz microwave radiometry for remotely sensing Earth’s cryosphere are reported. These updates concern measurements and modeling of the spectral properties of brightness temperatures for geophysical regions such as ice sheets, sea ice, ice shelves, and others. The results are intended to support the continued development of 0.5-2 GHz passive microwave mission concepts for future deployment in space.

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.

Airborne 0.5–2 GHz brightness temperatures were collected along a transect of the Priestley Glacier, Northern Victoria Land, Antarctica that coincides with previously acquired 189–199 MHz depth sounding radar data from NASA’s Operation IceBridge (OIB). The measured brightness temperature spectra evolve from negative spectral gradients (brightness temperature decreases with frequency) over the inland ice sheet and upper reach of the outlet glacier toward positive spectral gradients in the central region of the glacier. The spectra then increase almost linearly with frequency over the floating portion of the glacier terminus. The positive spectral gradients are more similar to sea ice on the ocean as compared to the grounded interior ice sheet. Comparison with modeling studies at Ross Ice Shelf sites where physical temperature has been measured in boreholes shows that positive gradients are to be expected where glacier ice overlies a water base. Calculations of radar reflectivity support the assumption of patchy regions of basal water and help to resolve ambiguities associated with processes such as interface roughness and near-surface firn layering.

The rapid evolution of the effects observed in various areas of our planet related to climate change poses urgent questions about the knowledge of the state of the polar area and requires satellite acquisitions with fine spatial resolution and high accuracy to develop advanced products. The Copernicus Imaging Microwave Radiometer (CIMR) mission, based on a multifrequency microwave radiometer and designed to observe the ocean, sea ice, and Arctic environment, requires brightness temperature measurements with a total absolute uncertainty of 0.5 K and a spatial resolution of 5 km. This constraint demands very large reflectors with a gain value of tens of decibels. Mechanical constraints will be attained by using a mesh reflector, which guarantees the required resolution but with the drawback of a radiation pattern characterized by many grating lobes that contaminate the value of the brightness temperature associated with the boresight position. In this article, an antenna pattern correction (APC) is proposed to correct these effects. The algorithm takes advantage of an iterative formulation based on the Jacobi Method, providing a suitable correction that depends on the chosen spatial resolution. The APC algorithm was tested at both K- and Ka-bands with similar performance. Here, only the results from the latter are shown, as its antenna pattern is the most challenging among CIMR.

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.

Airborne 500–2000-MHz radiometric measurements recorded in high-latitude regions (portions of Greenland, Antarctica, and Northern Canada) are used to provide insight into the radio frequency interference (RFI) environment that can be expected for future radiometer missions operating in this frequency range. Statistics of the RFI environment are reported in terms of the likelihood of a specified bandwidth measurement containing RFI corruption. The results indicate that wideband radiometry from 500 to 2000 MHz is viable for science applications in the majority of the regions surveyed.

Arctic sea-ice thickness and salinity retrievals are simulated to explore the performance of nadir-observing microwave radiometry operating with up to 16 frequency channels in the 0.5–2-GHz frequency range. A radiative transfer model is used to create lookup tables of the circularly polarized thermal emissions of first-year (FY) and multiyear (MY) sea ice, and the performance of two distinct retrieval methods is examined. The first method retrieves only sea-ice thicknesses, while the second retrieves both ice thickness and ice salinity. Retrieval errors are simulated for both FY and MY sea ice as a function of ice thickness, salinity, and temperature to investigate the impact of radiometric uncertainty, the frequency channels used, and any errors in ancillary information. To gain further insight into Arctic scale retrieval performance, a simulated brightness temperature dataset is produced for Arctic sea ice for the period October 2020–March 2021 using sea-ice thicknesses from the SMOS-CryoSat-2 algorithm. Compared to existing sea-ice thickness retrievals obtained from 1.4-GHz microwave radiometers, the results demonstrate that 0.5–2-GHz radiometry can achieve higher sensitivity to a sea-ice thickness within the range 0.5–1.5 m for FY sea ice and enable the retrieval of multiple sea-ice parameters (thickness and salinity) simultaneously.

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.

Bistatic and multistatic radar observations are mostly conceived to exploit the signal phase, e.g., for interferometry, tomography, and ocean current applications. In these situations, the distance between the transmitting and receiving antennas (bistatic baseline) is generally small in order to, among other reasons, keep high the coherence between the backscattered (monostatic) and bistatic radar echoes. Less evidence can be found in the literature on the exploitation of the signal amplitude (i.e., the scattering coefficient) of monostatic observations combined with bistatic ones, thus implementing a multistatic observation. In this case, to increase the information content in the inverse problem (i.e., the retrieval of biogeophysical parameters), the observations to be combined must be sufficiently independent in order to improve the accuracy of the retrieval. This article aims at identifying suitable geometrical configurations of a passive satellite radar flying in convoy with an active spaceborne SAR at L-band. Few bistatic datasets exist to verify this concept experimentally, so that electromagnetic models can help understanding its potential in different fields. The applications foreseen in this article are the retrieval of soil moisture and vegetation biomass. A model-based investigation shows that retrieval performances can be improved by combining monostatic and bistatic measurements in geometric configurations requiring very large along track and across track baselines. In this way, the scattering mechanisms involved in the monostatic and bistatic geometry are sufficiently different so that their combination increases the retrieval performances with respect to a monostatic acquisition.

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.

Ice sheet subsurface temperature is important for understanding glacier dynamics, yet existing methods to obtain the temperature of the ice sheet column are limited toin situsources at present. The ultrawideband software-defined microwave radiometer (UWBRAD) has been developed to investigate the remote sensing of ice sheet internal temperatures. UWBRAD measures brightness temperature spectra from 0.5 to 2 GHz using 12 subchannels and employs a sophisticated algorithm for detection and mitigation of radio frequency interference (RFI). The instrument was deployed during a flight over northwestern Greenland in September 2017 and acquired the first wideband low-frequency brightness temperature spectra over the ice sheet and coastal regions. The results reveal strong spatial and spectral variations that correlate well with internal ice sheet temperature information. In this article, the section of the flight path ranging from the Camp Century to NEEM to NGRIP boreholes is used for subsurface temperature estimation. A “partially coherent” forward model is applied along with a Robin model for the temperature profile and a two-scale model of ice sheet density variations to describe measured brightness temperatures. Using this model, vertical temperature profiles are retrieved along the flight path using a sequential Bayesian estimator; borehole measurements at the three campsites are used to obtain Bayesian priors. The retrieved temperature profiles show reasonable behaviors and demonstrate the potential of ultrawideband microwave radiometry for remotely sensing internal ice sheet temperatures.

The launch of L-band passive microwave radiometer satellites in the last decade (SMOS, Aquarius, and SMAP) started a new era in Earth Observation at low frequency. On the trails of these missions, recent studies showed that microwave radiometers operating at even lower frequencies (P-band) can provide new information for cryospheric and ocean science and improve the current understanding of Earth processes. In particular, experimental airborne campaigns were conducted in both Artic and Antarctica, within the NASA's UWBRAD project, by using a wide band radiometer operating in the range 0.5-2 GHz, aimed at investigating the temperature profiles of ice sheets and the sea ice thickness. By leveraging the results of UWBRAD system, a new mission concept was proposed to ESA Earth Explorer 10 and 11 (called CryoRad) and NASA EVI-6 (called PolarRad) featuring a spacebome 0.4-2 GHz nadir-looking microwave radiometer for the monitoring of polar regions. Even though the main goals of all these sensors are related to observables such as soil moisture, ocean salinity, and geophysical parameters of the cryosphere, all of them suffer from the emission due the atmosphere. In the spectral range comprised between 0.5 and 2 GHz the atmosphere is considered almost transparent, being the major contributions to the emission due to the water vapor (in both physical phases) and to the molecular oxygen, however a clear assessment is still lacking in literature. The aim of this paper is to provide an accurate estimate of the atmospheric effect on measured TBfrom space at low frequency for different climate scenario by using a combination of in-situ data (i.e. radio-sounding) and microwave emission model.

Sea ice thickness and salinity are important quantities in understanding and forecasting the evolution of the cryosphere. However, the retrieval of multiple sea ice parameters through microwave remote sensing is a challenging task. In this study, the potential advantages of using a multi-channel wideband microwave radiometer are demonstrated through simulations of the retrieval of both sea ice thickness and salinity for multiple ice types and for different numbers of radiometer channels.

ESA's Soil Moisture and Ocean Salinity (SMOS) mission [1] has been in orbit for over 11 years, and its Microwave Imaging Radiometer with Aperture Synthesis (MIRAS) in two dimensions keeps being fully operational. This II-year long lifetime of SMOS, so far, has enabled the calibration and Level-1 processor team to improve the calibration procedures and the image reconstruction resulting in a new version of the Level-1 data processor, v724. To present the main performance features of this new version and the improvement in the calibration procedures constitute the main objective and content of this presentation.

In recent years, special attention has been paid, in microwave remote sensing from space, to extend observations to low frequencies (i.e lower than L band). Active mission at P-band (i.e. the ESA's Biomass mission based on SAR) will be launched in 2022 and missions based on low frequency microwave radiometer are proposed to both ESA and NASA. Because of the high penetration depth in ice, these sensors are particularly suitable for investigating parameters of the cryosphere. Nevertheless, in order to properly derive information on such geophysical parameters, there is the need to improve our knowledge of the interaction of electromagnetic waves and the different media. In this paper we present and discuss a first series of results obtained during a propagation measurement campaign carried out at the French–Italian Concordia research station during the summer campaign 2019-2020 in Antarctica in order to investigate on the electromagnetic properties of the Antarctic's firn in the frequency range 0.4-2 GHz. Specific instrumentation has been designed and assembled, essentially consisting of a transmitting unit and a receiving one, to be let down into two boreholes in the firn. Preliminary measurement results are presented and discussed.

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.

ESA's Soil Moisture and Ocean Salinity (SMOS) mission [1] has been in orbit for over 9 years, and its Microwave Imaging Radiometer with Aperture Synthesis (MIRAS) in two dimensions is working well. The data products are generated using version v620 of the Level-1 operational processor, a version which entered into operation in Spring 2015. During last year a comprehensive data set was processed using a new processor version v720 and the assessment of the results is expected to be completed by mid 2019. In parallel to this evaluation of v720, the following version v730 of the Level-1 processor of SMOS has been already produced. This latter version is intended for investigating the capability to reduce Radio Frequency Interferences (RFI) by applying image processing techniques. This paper describes the major features and status of the two mentioned versions of the SMOS Level-1 processor, and importantly, aims at updating the remote sensing community on those aspects of the SMOS mission.

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.

The Ultra- Wideband Software Defined Microwave Radiometer (UWBRAD) was developed at The Ohio State University to provide nadiral brightness temperatures measurements of ice sheets primarily but also other geophysical media in the spectral range 0.5-2 GHz. During its deployment in Greenland in September 2017, UWBRAD acquired data over the ice sheets but also over open ocean. This paper focuses on the analysis of these ocean datasets in order to show the potential of using 0.5-2 GHz microwave radiometry to retrieve sea surface salinity.

The Ultra-Wideband Software Defined Microwave Radiometer (UWBRAD) measures scene brightness temperatures from 0.5-2 GHz. UWBRAD was deployed in a September 2017 airborne campaign in Greenland, and observed brightness temperatures of the ice sheet as well as sea ice, the ocean surface, and land regions during the transit to and from Calgary, Canada (the aircraft base of operations). This presentation will review the campaign and datasets collected. Spectral features of thermal emissions from the ice sheet and other geophysical regions are also examined to obtain insight into the utility of 0.5-2 GHz thermal emission measurements for remote sensing applications.

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.

The ultrawideband software-defined microwave radiometer is a 500–2000-MHz radiometer developed to probe temperatures inside ice sheets. Given the instrument’s operation outside of protected portions of the spectrum, radio frequency interference (RFI) is a significant concern, and the instrument is designed to facilitate RFI detection and filtering. This paper analyzes the design and operation of the radiometer, the accuracy and stability of the brightness temperatures it produces, and the RFI analyses of the results acquired in its debut flight over northern Canada and Greenland in September 2016.

An ultra-wideband radiometer has been developed to measure subsurface properties of the cryosphere including ice sheets and sea ice. The radiometer measures brightness temperature spectra from 0.5 to 2 GHz using 12 channels, each of which measures scene brightness temperatures over an ~88-MHz bandwidth resolved into 0.24-MHz intervals. The instrument was flown over northwestern Greenland in September 2016 and acquired the first, wideband, low-frequency brightness temperature spectra over the ice sheet and coastal region. The results reveal strong spatial and spectral variations that correlate well with the physical properties of the surface encountered along the flight path, which started over ocean, then passed the rock near the coast, and then up onto the ablation, wet, percolation, and dry snow zones of the interior ice sheet. In particular, strong spectral responses in percolation and dry snow zones are observed and plausibly explained by varying the distribution of horizontal density layers and isolated icy bodies in the upper portion of the firn. The success of the airborne deployment of the instrument and subsequent implementation of algorithms to limit radio frequency interference in unprotected bands is motivating continued airborne investigations as well as stimulating research into the feasibility of a spaceborne instrument.

The Ultra-Wideband Microwave Radiometer is a novel pseudo-correlation radiometer design measuring scene brightness temperatures from 0.5-2 GHz created under NASA's Instrument Incubator Program. This document analyzes the design and operation of the radiometer, the accuracy and stability of the brightness temperatures it produces, and presents initial results from a field campaign conducted in Greenland in September 2016.

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.

There is a long-stranding need of reliable space-borne observations on snow mass. Current satellite sensors and data products are largely unable to meet requirements presented in particular by numerical prediction and watershed management. Consequently, several concept studies have been initiated to address these specific needs, outlining possibilities for future space sensors focusing on retrieval of snow mass and other characteristics of the terrestrial cryosphere. The results of these of-going mission concept studies are presented and discussed. Several possible sensor options are presented, which would address diverse needs on either hemispheric or regional scales.

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.

This work aims at defining applications, products and user requirements, as well as the hardware and ground processing design of a companion satellite mission which shall carry aboard a “passive” radar working in tandem with the Argentinian L-band radar developed by CONAE and denoted as SAOCOM. The primary objective (i.e., science driver) of the SAOCOM companion satellite mission (SAOCOM-CS) is forest tomography, which will be carried out by exploiting small baselines between active and passive systems (order of km) changing with time. Conversely, this paper summarizes the investigation carried out for different bistatic radar configurations that are characterized by much larger spatial baselines (up to hundreds of km) and bistatic angles with very large components both in azimuth and in elevation. Soil moisture and vegetation biomass retrieval takes advantage from the combined exploitation of monostatic and bistatic measurements. The retrieval ambiguity related to target azimuthal anisotropy could also be reduced by bistatic observations, like in the case of the ocean surface. The bistatic system shall collect data with suitable directions and polarizations. The expected performances of a multistatic system have been predicted using electromagnetic models.

This paper will investigate the effect of layered snow in alpine regions on microwave emission at Ku and Ka bands, using both experimental data and model simulations. A multilayer dense-media radiative transfer model (DMRT), was implemented under the quasi-crystalline approximation (ML-QCA), to account for the effects of snow layers on the emission from dry snow covers. The model then evaluated the sensitivity of two microwave indices, based on frequency and polarization combinations, to snow parameters. Model simulations were compared to radiometric dual frequency/polarization measurements of snow covers, collected during long-term experiments carried out over three winter seasons between 2007 and 2011 in the Eastern Italian Alps. This comparison has the twofold purpose of validating the model with experimental data and verifying the influence of snow layering on microwave emission and related frequency and polarization indices. The wide variations in snow characteristics over several winter seasons allowed for an extended validation of the model, which was demonstrated to account for the complex stratigraphy (up to 15 layers) of snow. The measured brightness temperatures at Ku and Ka bands were compared to those simulated through the multi (ML-QCA) and single-layer (SL-QCA) models, by using the observed snow parameters as inputs. In the case of SL, we used the average value of all layers weighted for the layer thickness. The results showed that the ML-QCA model was better correlated to the radiometric measurements than the SL-QCA. A direct comparison of measured and simulated data showed that the slope of correlation for the single-layer ranged between 0.4 and 0.5, with determination coefficient lower than 0.3; whereas the slope in the multi-layer approach ranged between 0.7 and 1.0, with determination coefficients between 0.51 and 0.75 and Root Mean Square Error (RMSE) between 11K and 15K.

The Ultra-wideband Software Defined Radiometer (UWBRAD) for ice sheet internal temperature sensing is designed to provide observations of ice sheet brightness temperatures from 500-2000 MHz. This presentation reports on current status of the instrument development, experimental results obtained to date, and plans for a September 2016 airborne deployment over Greenland.

Antarctica is a very unique continent, completely covered by thousands of meter of ice and firn. Therefore its microwave signature is different from any other place on Earth. Although the emission at low microwave frequency of the East Antarctic plateau is temporally stable for long periods, especially at V polarization and for incidence angles close to the Brewster one, a detailed analysis of satellite and ground based L-band measurements revealed that changes in the characteristics of snow surface can have an appreciable effect on the emission at H polarization. This work is focused on analyzing the temporal variations of the brightness temperature and on linking it to their primary causes. Ground measurements and model simulations indicate that, when strong wind event take place, they could swipe away the first weak layers of snow, exposing the more dense ones. This superficial change can cause a variation of the overall snowpack emission which causes the brightness temperature at H pol to decrease appreciably. On the contrary, the accumulation and densification processes make the Tb to increase.

Different researches were addressed to the assessment of the boreal forest environment using active microwave remote sensing. Some of these activities were also devoted to estimate the ground parameters under the forest (i.e. soil moisture, snow mass) and, in order to understand the complex mechanisms which govern the radar backscattering, different electromagnetic models were developed for simulating the boreal scenario. An improvement of these models, for better characterizing the sparse forests, also considered the effect of shadow induced by the trees. Besides the computation of the attenuation caused by shadow on ground backscattering, the first needed parameter was the quantification of the percentage of the pixel affected by shadow. The estimation of this parameter can be obtained from high resolution optical images which are not always available at global scale. An alternative semi- empirical method based on 3D CAD modelling and ancillary information, which allow to quantify the amount of the shaded area is presented in the paper. Different forest profiles, height and densities and different geometry of observation were considered, and semi-empirical relationships between shadow area extension and these parameters were founded. The effect of electromagnetic shadowing was also quantified by performing model simulations. Finally a validation of the method was achieved by using high-resolution data collected from optical sensors in a forested area of Finland.

Recent studies, which were carried out within the framework of ESA's CoReH2O Phase-A mission, demonstrated that multi-frequency SAR data are able to quantify the amount of snow mass on land or glaciers (SWE). On the other hand the presence of forest has a significant impact on the propagation of the radar signal, depending on its structure, biomass, water content and cover fraction. In particular for dense forest, scattering of vegetation strongly hides the signal from snow and, consequently, compromises the sensitivity to snow parameters. A method for the compensation of the vegetation effect for the SWE retrieval in boreal forests is presented in this research. The procedure is based on the possibility to separate the scattering contribution from soil and vegetation from the data itself using ancillary information. The compensation follow through the estimation of the direct scattering from vegetation by using a minimization technique. Moreover, using a time series of backscatter images, this method is able to monitor the evolution of soil and vegetation status changes along the season, and improve the quality of the SWE retrieval algorithm.

This paper aims at identifying suitable geometrical configurations of a passive satellite radar flying in convoy with an active spaceborne SAR. The work has been performed in the frame of the SAOCOM-CS scientific investigations. It is a small satellite that ESA is conceiving to fly in convoy with the Argentinian SAOCOM 1B to acquire bistatic radar data at L-band. The applications foreseen in the paper are the retrieval of soil moisture and crop biomass. It is shown by a model based investigation that retrieval performances can be improved by combining monostatic and bistatic measurements in geometric configurations requiring very high along track and across track baselines.

This paper investigates the algorithms that are used to predict the full polarimetric bistatic normalized radar cross-section of rough surfaces. These include small perturbation method (SPM), the physical optics (PO) approach, the small slope approximation (SSA) and the integration equation method (IEM) and its derivatives improved IEM and advanced IEM. The methods are then compared to ground truth values obtained from multiple Monte Carlo runs a numerical Method of Moments (MOM) code using the same surface statistics. Effects of using band-limited exponential instead of a true exponential correlation function for surface statistics are also explored. Mean L1-norm error values integrated over the hemisphere are given between AIEM and MOM and SSA and MOM.

In this paper, the effects of multilayer structure of snowpack and its temporal evolution on backscattering are investigated by model simulations. The study is focused on layering structures of dry snow that may represent a risk of avalanches in Alpine regions. The implemented model has been validated using X-band Cosmo SkyMed (CSK ®) acquisitions collected in the winters between 2009 and 2013 on a test area located in the Eastern part of the Italian Alps, and corresponding direct measurements of the main snow parameters. After the validation, the models are applied to simulate the backscattering from snow profiles typical of snow covers characterized by a high risk of avalanches.

Winter season backscatter (σ°) evolution of snow covered lake ice was observed by ground-based University of Waterloo X-(9.6 GHz) and Ku-band (17.2 GHz) scatterometers (UW-SCAT) during the winter of 2010-11. The UW-SCAT post-processing procedure allowed for the observation of σ° at the surface (snow/ice interface, ice types) and the ice volume. Observations indicated that: (1) σ° associated with the development of tubular bubbles within the ice volume causes double-bounce of the signal and high returns at X- and Ku-bands; (2) ice types at the surface (grey ice) composed of high density spherical micro-bubbles result in σ° increases at both X- and Ku-bands; and (3) the removal of snow overlying ice results in a drop in Ku-band σ° up to 5.5 dB, exhibiting sensitivity to snow water equivalent.

Since the SMOS satellite launch in 2009, its L-band radiometer data have been analyzed in depth by scientists worldwide and have resulted in significant steps forward in different disciplines. As primary objectives of the mission, the main research focus has been related to soil moisture and ocean salinity. However, the availability of a complete long-term, all-weather time-series of calibrated global brightness temperature data has enabled much broader research investigations on other topics such as the Cryosphere. SMOS data collected over central of Antarctica were also analyzed and whereas Tb is in general very stable in time it presents some intriguing spatial variations which are not yet fully explained. Using electromagnetic model simulations, and ancillary data for describing the physical parameters of the ice sheet, the observed variability and features in SMOS data are reproduced and explained.

The mean power of the reflected Global Navigation Satellite System (GNSS) signals acquired by a GNSS-Reflectometry (GNSS-R) receiver can be modeled through the integral bistatic radar equation by weighting the contributions of all scatterers on the surface by the system impulse response. The geophysical properties of the scattering surface affect the magnitude of the reflected navigation signals through the bistatic scattering coefficient which, in case the observed surface is land, is a function of the soil dielectric properties, surface roughness, and vegetation cover. In this paper, the GNSS-R signal simulator developed in the framework of the Land MOnitoring with Navigation signal (LEiMON) Project, supported by European Space Agency, is presented. The simulator is able to predict the power reflected by land, taking as input the system and observation parameters, as well as the land surface parameters. The latter are used to simulate both the coherent and the incoherent scattering, taking advantage of widely used theoretical models of bistatic scattering from bare soils and vegetated surfaces. First, the geometrical formulation is discussed, and then, the problem of polarization mismatch due to real antennas at circular polarization is faced following the polarization synthesis approach. Finally, a comparison with some experimental data collected during the LEiMON campaign is presented. The simulations display the same trend of the experimental data, thus showing that the simulator can be used as an efficient tool for the interpretation of GNSS-R measurements.

In this paper, a multilayer version of the Dense Medium Radiative Transfer (DMRT) model has been implemented for the active remote sensing. The effects of multilayer structure of snowpack and its temporal evolution on backscattering have been investigated. The study has been focused on the effect of layering structure of snowpack typical of the Alpine regions. The ground measurements used as model inputs have been collected on the Italian Alps during the 2009–2010 winter season.

In recent decades, with the development of low-frequency missions such as SMOS and Aquarius, which have a large antenna, the need has arisen to find stable areas for the external calibration of L-band radiometers. “Cold sky” and “calm ocean” are routinely used as low reference temperatures, and Antarctica, in particular the East Antarctic Plateau, has been investigated in recent years as a potential candidate for higher reference temperatures. The reason for this interest lies in its geographical location (it can be seen several times a day by polar-orbiting satellites), as well as in the size, structure, spatial homogeneity, and thermal stability of this area. In particular the area of Dome-C, where the Italian-French base is located, was monitored in the past years using ground based radiometer and satellite data. Data acquired in new experiment, started in 2012, are described in the present study together to an analysis of SMOS data collected in the same area. The results pointed out that the brightness temperature over that region is very stable both in space and time and have individuated a large area able to contain several footprints of space-borne radiometers and thus is suitable for cross calibration between the sensors.

In preparation for the CoReH2O satellite mission, one of the three missions selected for scientific and technical feasibility studies within the Earth Explorer Programme of the ESA, experimental and theoretical studies have been under way in order to improve methods for the retrieval of snow physical properties from SAR data. The aim of this paper is to investigate the impact of vegetation in the retrieval of snow parameters from microwave backscattering measurements. A RTT model capable of simulating scattering from a snow-covered vegetated terrain was developed and implemented. A sensitivity analysis to snow and vegetation parameters was carried out thus a comparison with real SAR data is presented in the paper.

The analysis of the relationships between FI & SPD and SWE/SD was carried out using experimental data and simulations obtained using the DMRT-QCA Multilayer model. The comparison of experimental results and model analyses made it possible to investigate the polarizing effect of snow layering and to better assess the sensitivity of FI and SPD to the snow accumulation.

Monitoring of snow cover is crucial to the study of global climate changes for water resource management, as well as for flood and avalanche risk prevention. The sensitivity to snow characteristics of X-band backscattering of COSMO-SkyMed mission has been analyzed in the framework of experimental and model activities. X-band data have been found to contribute to the retrieval of the snow water equivalent (SWE), provided that the snow cover is characterized by a snow depth (SD) of roughly 60-70 cm (SWE >; 100-150 mm) and with relatively large crystal dimensions. Subsequently, an algorithm for retrieving SD or SWE has been developed and tested with experimental data collected on several ground stations.

In recent years, there has been growing interest on the part of the remote sensing community in using the Antarctic area for calibrating and validating data of low-frequency satellite-borne microwave radiometers. In particular, the East Antarctic Plateau appears to be suited for this purpose. The reasons for this interest are the size, structure, spatial homogeneity, and thermal stability of this area. This is particularly interesting for low-frequency microwave radiometers since, due to the low extinction of dry snow, the upper ice-sheet layer is almost transparent and the brightness temperature variability is therefore extremely small. In the context of calibration and validation activities of the European Space Agency's Soil Moisture and Ocean Salinity (SMOS) satellite, an experiment called DOMEX-2, which included radiometric L-band measurements, was carried out at the Italian-French base of Concordia located at Dome C in the East Antarctic Plateau from December 2008 to December 2010. Ground measurements (i.e., snow temperature at different depths, snow structure, meteorological data, etc.) were also collected during the experiment. This paper presents information on the experimental campaign, the characteristics of the radiometric measurements, and the main results. A comparison with SMOS data is also presented.

With the development of new low frequency satellite radiometers the characterization of the emission of the East Antarctic plateau become important for cal/val purposes. Also, the availability of further data open new horizons in the understanding of the climate processes of the continent. In this work we analyze the spatial homogeneity and the temporal stability of the east Antarctic plateau at C- and L-band by using a the modified absolute distance metric. Finally we were able to detect some promise areas in the Ridge and Dome C region which seems to be spatially homogeneous and temporally stable.

Monitoring of snow cover is crucial in water resource management and hydrological risk prevention. Experiments have shown the ability of C-band SAR in mapping the extent of wet snow. But, detection of dry snow at this frequency is difficult due to the high transmissivity of the snowpack. A model sensitivity study, corroborated by experimental data, has demonstrated that COSMO-Skymed X-band data can give significant information for generating maps of SWE for snow depth higher than about 50-60 cm.

Electromagnetic models, able to simulate scattering from vegetation, are widely used in the remote sensing community in order to interpret space-borne or air-borne SAR data and to develop algorithms capable to derive from them bio-physical quantities (i.e. biomass, tree height, etc.). Most of the models consider the vegetation as an ensemble of simple elements (cylinders, discs) for representing the different parts which compose the plant (e.g. trunk, branches, leaves, etc.). Specific analytical models able to describe the scattering form this elements were developed in the past but theirs validity ranges in terms of frequency or elements dimensions were not yet fully investigated. A comparison between analytical models and a numerical full wave model for cylinders, elliptical and spherical discs at different frequencies in the 1.5 - 20 GHz range is presented here.

The backscattering coefficient variations of Cosmo-SkyMed and TerraSAR-X SAR sensors have been investigated. When possible, the data of the two sensors have been compared and a quantitative analysis was carried out. The comparison of SAR data has been also performed taking into account the temporal variations, in order to quantify potential changes of surface parameters. A series of both Cosmo-SkyMed (CSK) and TerraSAR-X (TSX) images were collected on both mountain and agricultural areas. The potentials of X-band backscattering in estimating hydrological parameters of the surface were investigated.

The work presented in this paper has been carried out with the aim of interpreting the data of a GNSS Reflectometer (GNSS-R) over land. The problem involves the analysis of bistatic scattering of the incoming signal collected around the specular direction. This requires to model the coherent component associated to the mean surface but at the same time the diffuse incoherent component due to roughness at wavelength scale. In presence of vegetation, both components will be affected, the former mainly because of the canopy attenuation and the latter for the combined effect of attenuation and volume scattering. The paper reviews the problem and presents the approach followed to develop a simulator of GNSS-R data over land, aiming to support potential applications of GNSS-R for soil moisture and biomass retrieval.

The capability of COSMO-SkyMed in estimating vegetation biomass has been investigated in this paper. SAR data from COSMO-SkyMed were collected on two agricultural areas in Italy in 2010 at different dates during the vegetation cycle. The performances of X-band data have been compared with accurate ground truth measurements of soil and vegetation carried out simultaneously to satellite passes. Experimental data have been compared with model simulations obtained with a discrete element radiative transfer model. Moreover, an inversion algorithm, based on an Artificial Neural Network and trained by using AIEM and the radiative transfer model, has been applied to retrieve the plant water content of wheat and sunflower crops and to generate the corresponding plant water content maps.

The development of bi-continuous scattering model greatly enhanced the ability to model the snow scattering characteristics based on microstructure with most similarity to real snowpack. In this study, snow section images of snow microstructure were used to study the scattering characteristics of snow by using the reconstructed snow 3D microstructure. The equivalent grain size of the continuous random structure is derived by using stereological method. By combining with dense media radiative transfer equations, the snow backscattering is simulated. The polarimetric and frequency characteristics were studied.

Antarctica is an important part of the Earth ecosystem. Due to its temperature, mass of stored water (and related thermal inertia) and position, it influences the atmosphere and marine circulations. Despite of its importance, Antarctica is the most unexplored region of Earth. The knowledge about the Antarctic environment is very limited due to its impervious conditions which hamper the human exploration. In this context remote sensing techniques helps in filling the gap. As pointed out in some preliminary works [1][2], microwave brightness temperature data can be useful for estimating snow sub-surface and air temperature. The aim of this paper is to extend previous studies by using AWS and AMSR-E data collected daily for 6 years for estimating snow and air temperature over the East Antarctic plateau. We assessed that the snow sub-surface temperature can be estimated by using linear regressions with a R between satellite and ground data greater than 0.9 (the retrieval RMSE obtained is around IK), while the determination coefficient of the relationships between the air and brightness temperatures was found to be around 0.7 (the associated retrieval RMSE varies between 2K and 7K).

In recent years there is growing interest, on the part of the remote sensing community, in using the Antarctic area for calibrating and validating data of the low-frequency satellite-borne microwave radiometers. In particular, the East Antarctic Plateau appears to be suited for this purpose. The reason of this interest lies in the size, structure, spatial homogeneity and thermal stability of this area. This is particularly interesting for low-frequency microwave radiometers since, due to the low extinction of dry snow, the upper ice sheet layer is almost transparent and the brightness temperature variability is therefore extremely small. In preparation for the November 2009 launch of the ESA's SMOS satellite, an experiment called DOMEX, which included radiometric L-band measurements was started in the Austral summer 2009. Data acquired in the campaign confirmed the temporal stability of the site. Comparison between ground and satellite data at L-band are also presented here. Moreover multi-frequency analysis of data collected over this area is performed by using SMOS and AMSR-E data.

In this paper, temporal trends of brightness temperature and related microwave indexes from AMSR-E and SMOS satellites were analyzed. Datasets were collected on three forest areas characterized by different climatic conditions and tree species. The test plots are: a deciduous forest of Larix in China; an evergreen Spruce forest in Russia; the mixed "Foreste Casentinesi" in Central Italy. The availability of different frequencies allowed us to investigate various canopy and soil effects. At the higher frequencies, the frequency index is sensitive to the snow cycle, and the polarization index is sensitive to the leaf cycle. At L band, a clear decrease of emissivity, at both polarizations, is associated to the snow melting process.

Monitoring of snow cover is crucial to the study of global climate changes, for water resource management, as well flood and avalanche risk prevention. The sensitivity of X band backscattering of Cosmo-Skymed mission has been first exploited by using model simulation and experimental data. An algorithm for retrieving snow depth or snow water equivalent has been then developed and test with experimental data.

The detection of the land surface scattering of the signal radiated by navigation satellites may help estimating geophysical parameters such as soil moisture and vegetation biomass. In fact, the modulation of the GNSS signal and its frequency (L band) are particularly effective to sense vegetation attenuation and change of soil permittivity due to moisture. An experiment has been carried out in Italy using a GNSS reflectometer (GNSS-R) developed by STARLAB, mounted on top of a crane and looking toward a couple of agricultural fields by two downlooking antennas operating at right and left circular polarization. The data collected during the experiment have been interpreted by comparing them to the output of a theoretical simulator, with the purpose of interpreting from an electromagnetic point of view the scattering mechanisms involved in the experiment. A summary of the simulator main feature and some comparison results is presented in this paper.

The results of an experiment carried out in Italy for exploiting the capabilities of X-band SAR in the monitoring of soil and vegetation characteristics are summarized in this paper. Data from X-band Cosmo-Skymed mission have been collected in two agricultural areas and compared with C-band data of ENVISAT/ASAR and with ground truth measurements. In general, a certain sensitivity to vegetation biomass and to moisture of bare soils has been found.

When considering a bistatic system made up of GNSS satellites and a receiver, the power at the receiver is modeled taking into account the matched filtering of the incoming signal with the PRN code modulation and Doppler filtering. In this paper, the simulator developed in the framework of the LEIMON Project supported by ESA, will be presented. The simulator is able to predict the power reflected by land taking as input the system and observation parameters, as well as the land surface parameters. The earth surface (represented by bare and vegetated soils) leaves its signature through the bistatic scattering coefficient which has been modeled by means of well established electromagnetic theories applicable at L-band. Experimental data collected during the LEIMON campaign will be compared with simulated data.

In preparation of the satellite mission CoReH2O, one of the three missions selected for scientific and technical feasibility studies within the Earth Explorer Programme of the European Space Agency, experimental and theoretical studies started in order to investigate backscatter properties of snow covered terrain and improve the methods for retrieval of snow physical properties from SAR data. The aim of this paper is to investigate the impact of vegetation in the retrieval of snow parameters from backscattering measurements. First a radiative transfer model, able to simulating scattering from a vegetated snow-covered terrain was developed and implemented. Lastly, a sensitivity analysis on snow and vegetation parameters was conducted for coniferous forest. Results confirm that with increasing biomass the sensitivity to SWE strongly decreases. Moreover when biomass is in the 0-150 m3/ha range a procedure to correct the vegetation effect in the SWE retrieval algorithm is suggested.

This work deals with mapping snow water equivalent as well as soil moisture at low resolution from multifrequency microwave radiometers. The algorithm developed and implemented in this work produces the spatial distribution at regional scale of snow depth (SD) and of soil moisture (SMC) of snow free areas by using the brightness temperatures of the Advanced Multifrequency Scanning Radiometer (AMSR-E).

In recent years there is growing interest, on the part of the remote sensing community, in using the Antarctic area, for calibrating and validating data of satellite-borne microwave radiometers. With a view to the launching of the ESA's SMOS satellite, which is a satellite designed to observe soil moisture over the Earth landmasses, salinity over the oceans and to provide observations over regions of ice and snow, an experimental activity called DOMEX-2 was started at Dome-C Antarctica. The main scientific objectives of this activity are to provide microwave data for SMOS satellite calibration and in particular: the continuous acquisition of a calibrated timeseries of microwave (L-band) and thermal Infrared (8-14micron) emission over an entire Austral annual cycle, the acquisition of a long time-series of snow measurements and the acquisition of relevant local atmospheric measurements from the local weather station. This paper is focusing on the preparation and installation of DOMEX-2 experiment and a preliminary analysis of data.

An operational algorithm to produce snow cover maps from remote sensing data in the Italian Alps has been implemented in the framework of the Italian national project PROSA to contribute timely information to civil protection from floods and landslides. The algorithm can generate maps in presence of cloud cover by combining optical data from MODIS and SAR data from ENVISAT/ASAR. It has been validated on a wide area in North Italy by comparing the algorithm output with ground measurements.

Experimental campaigns with airborne and satellite microwave sensors have been carried out on an agricultural area in Northern Italy with the main purpose of gathering a suitable set of data to validate two operational algorithms developed to retrieve soil moisture from passive and active microwave sensors at different spatial scales. The algorithms will be used in a pilot project based on the use of Earth observation data in forecasting and monitoring the risk of floods and landslides. Radiometric data have been collected with the airborne IFAC instruments and the AMSR-E, while ENVISAT/ASAR images have been acquired for high resolution estimate of soil moisture at field scale.

Long-term microwave and infrared radiometric measurements of snowpack were carried out with ground-based sensors in winter 2006-2007 and 2007-2008, together with conventional measurements of snow-cover profiles. The first experiment focused on the behavior of snow emission during the destructive and constructive metamorphisms. The second involved a correlation analysis of the small fluctuations related to diurnal solar cycle in order to obtain the time delay of microwave brightness temperatures Tb with respect to the snow surface temperature. From this analysis, it was possible to estimate an effective (weighed average) temperature and the thickness of the layer that mostly contributed to microwave emission at 19 and 37 GHz. The ratio of the brightness temperature to the effective temperature can be assumed to be an equivalent emissivity of the snowpack. Data collected in both years have been compared with simulations carried out using the advanced Institute of Applied Physics (IFAC) Radiative Advanced Dry Snow Emission (IRIDE) model driven by data collected on ground. The model is based on the advanced integral equation method to represent soil, coupled to a layer of dry snow whose electromagnetic properties are described by the dense medium radiative transfer theory with quasi-crystalline approximation applied to a medium (air) filled with sticky particles. Simulations performed by using ground data as inputs to the model have been found to be well in agreement with experimental data. Moreover, the comparison of model simulations with experimental data allowed one to understand some peculiar characteristics of microwave emission from the snowpack related to its physical conditions.

Microwave radiometric measurements of snow pack were carried out with ground based sensors in winter 2007-2008. Data collected on dry snow, showed small fluctuations related to diurnal solar cycle and presented a time delay of microwave brightness temperatures with respect to the snow surface temperature. The measurement of these delays, together with a correlation analysis of the brightness and physical temperature of snow, made it possible estimating the thickness of layers that mostly contributed to microwave emission at 19 and 37 GHz. Simulations performed with IRIDE model were consistent with experimental data.

The Antarctic plateau is a part of Antarctic extending for a few hundred kilometers around the South Pole with an average elevation close to 3000 m a.s.l.. This area provides unique opportunities for various scientific disciplines including Glaciology, Atmospheric and Earth Sciences. In this paper temporal and spatial variability of multi-frequency microwave emission from the East Antarctic plateau by using AMSR-E data collected from 2005 to 2007 is analyzed.

In this paper an overview of the main microwave characteristics observed on three forest areas selected in different areas worldwide is given. Microwave parameters were analyzed for a yearly cycle (2007-2008), paying particular attention to the seasonal variations forest leaf biomass, expressed as leaf area index (LAI), and climatic conditions. Some microwave indexes of polarization and frequencies are in good agreement with the seasonal variations of vegetation. The emission at C-band was found to be related to the moisture conditions of the area.

The possible contribution of bistatic radar measurements for bare soil moisture retrieval is investigated in this paper. A simulation study based on well-established electromagnetic models of rough surface scattering (both coherent and incoherent components) has been accomplished for this purpose. The retrieval accuracy has been evaluated by using both the Cramer–Rao lower bound and the error variance of a linear regression estimator, thus considering slightly different assumptions on retrieval conditions. Both methods have allowed us to identify the optimal system configurations in terms of observation directions, polarizations, and frequency. This identification has been carried out for single-polarization and multipolarization receivers and for the case in which bistatic measurements are complemented by monostatic ones, which are expected to be available through already-existing spaceborne synthetic aperture radars. The optimal systems have first been singled out by considering a Gaussian autocorrelation function (ACF) and a constant value of correlation length. Successively, the simulations for an exponential ACF and a variable correlation length have been analyzed, demonstrating that the results substantially remain the same. The comparison between the soil moisture estimation accuracy yielded by the optimal configurations and that provided by the standard monostatic radar has shown that a significant improvement in the quality of retrieval can be achieved by complementing bistatic and monostatic measurements.

The sensitivity of bistatic scattering coefficient sigmadeg to soil moisture (smc) is investigated on the whole upper half space by means of model simulations of the incoherent scattered fields. The achieved results, represented as maps of sigmadeg as a function of azimuth and zenith angles, are evaluated by means of a quality index which takes into consideration the effect of roughness on smc measurement.

The Antarctic plateau is the highest part of the east Antarctic ice-cap that extends for several hundred kilometers with an average altitude of close to 3000 m a.s.l.. In this paper, we analyze the temporal variability of multi-frequency microwave emission from the area surrounding the Dome-C scientific station, using AMSR-E data collected throughout 2005 and 2006, and snow temperatures measured at different depths down to 10m below the surface. The brightness temperature variability is associated with the temperature fluctuation at different depths and a simple method was developed for inverting these relationships and for exploiting the possibility of retrieving the snow temperature profiles from satellite data.

In recent years there has been a growing interest on the part of the remote sensing community in exploiting the Antarctic area, in particular the plateau where the Dome-C base is located, for the calibration and validation of data from satellite-borne microwave radiometers. With a view to the launching of new low-frequency satellite sensors, an experimental activity was started at Dome-C . In this paper, the preparations relative to a new campaign, in particular the design and calibration strategy of a L-band microwave radiometer, are presented.

The Antarctic plateau that extends for several hundred kilometers with an average altitude of close to 3000 m a.s.l. is the highest part of the east Antarctic ice cap. This area provides unique opportunities for various scientific disciplines, including glaciology and atmospheric and earth sciences. In addition, there is growing interest in using the Antarctic plateau, for calibrating and validating data of satellite-borne microwave radiometers, thanks to the size, structure, and spatial homogeneity of this area, and the thermal stability of deeper snow layers. In this paper, we analyze the temporal and spatial variabilities of multifrequency microwave emission from the area surrounding the Dome-C scientific station using Advanced Microwave Scanning Radiometer data collected throughout 2005. Moreover, a multilayer coherent electromagnetic model is used for estimating the contribution of snow layers to emission at various frequencies. The results are consistent with the physical structure of the ice sheet and with its seasonal and spatial variations.

The importance of microwave sensors in monitoring snow parameters is well recognized. However, several problems are still open regarding the reliability of remote sensing for operational use. In 2002-2005 a series of ERS SAR and ENVISAT ASAR images were collected on the Italian Alps to monitor the temporal evolution of snow cover. In the same time a long sequence of multi-frequency radiometric data was collected with ground based sensors. The measurements confirmed the potential of microwave active and passive sensors in monitoring the extent of wet snow cover and in estimating the liquid water content of wet snow and the snow water equivalent of refrozen snow.

A research activity aiming to assess the potential of bistatic measurements of scattered radiation from the land surface is presented. The purpose is to identify the best configuration of a passive system measuring the signal originated by sources of opportunity, like GNSS or radars aboard a satellite. The preliminary result of the study consists of the validation of the electromagnetic model simulating bistatic scattering from bare soil, including the coherent component. A very preliminary sensitivity analysis to soil moisture is also presented.

Satellite data are the most suitable tools for monitoring time and spatial variations of snow covered areas and for studying snow characteristics on a global scale. Current knowledge of the microwave emission from the deep ice sheet in Antarctica is limited by the lack of low-frequency satellite sensors and by their inadequate knowledge of the physical effects governing microwave emission at wavelengths exceeding 5 cm. On the other hand, in addition to the interest related to climatic changes and to glaciological and hydrological applications, there is growing interest, on the part of the remote sensing community, in using the Antarctic and, in particular, the Dome-C plateau where the Concordia station is located, for calibrating and validating data of satellite-borne microwave and optical radiometers. This is because of the size, structure, spatial homogeneity, and thermal stability of this area. With a view to the future launches of two new low-frequency spaceborne sensors Soil Moisture and Ocean Salinity mission and Aquarius, an experiment was carried out at Dome-C, thanks to financial support from European Space Agency, aimed at evaluating the stability and the absolute value of the L- and C-band brightness temperature Tb. This paper presents a report on the experimental campaign, the characteristics of the radiometric measurements, and on the main results. The C-band Tb data indicated a diurnal cycle amplitude of a few kelvin. It was confirmed that this takes place as a consequence of observed variability in the physical temperature of the top 4 m of the snowpack around the mean surface value of -24degC. In contrast, the L-band data indicated extremely stable Tb values of 192.32 K (1sigma=0.18 K) and 190.77 K (1sigma=0.57 K) at thetas=45deg and thetas=56deg, respectively

Satellite data are the most suitable tools for monitoring time and spatial variations of snow covered areas and for studying snow characteristics on a global scale. Current knowledge of the microwave emission from the deep ice sheet in Antarctica is limited by the lack of low-frequency satellite sensors and by their inadequate knowledge of the physical effects governing microwave emission at wavelengths exceeding 5 cm. On the other hand, in addition to the interest related to climatic changes and to glaciological and hydrological applications, there is growing interest, on the part of the remote sensing community, in using the Antarctic and, in particular, the Dome-C plateau where the Concordia station is located, for calibrating and validating data of satellite-borne microwave and optical radiometers. This is because of the size, structure, spatial homogeneity, and thermal stability of this area. With a view to the future launches of two new low-frequency spaceborne sensors Soil Moisture and Ocean Salinity mission and Aquarius, an experiment was carried out at Dome-C, thanks to financial support from European Space Agency, aimed at evaluating the stability and the absolute value of the L- and C-band brightness temperature Tb. This paper presents a report on the experimental campaign, the characteristics of the radiometric measurements, and on the main results. The C-band Tb data indicated a diurnal cycle amplitude of a few kelvin. It was confirmed that this takes place as a consequence of observed variability in the physical temperature of the top 4 m of the snowpack around the mean surface value of -24°C. In contrast, the L-band data indicated extremely stable Tb values of 192.32 K (1σ = 0.18 K) and 190.77 K (1σ = 0.57 K) at 0 = 45° and θ = 56°, respectively.

A study of the melting cycle of snow was carried out by using ground-based microwave radiometers, which operated continuously 24 h/day from late March to mid-May in 2002 and from mid-February to early May in 2003. The experiment took place on the eastern Italian Alps and included micrometeorological and conventional snow measurements as well. The measurements confirmed the high sensitivity of microwave emission at 19 and 37 GHz to the melting-refreezing cycles of snow. Moreover, micrometeorological data made it possible to simulate snow density, temperature, and liquid water content through a hydrological snowpack model and provided additional insight into these processes. Simulations obtained with a two-layer electromagnetic model based on the strong fluctuation theory and driven by the output of the hydrological snowpack model were consistent with experimental data and allowed interpretation of both variation in microwave emission during the melting and refreezing phases and in discerning the contributions of the upper and lower layers of snow as well as of the underlying ground surface.