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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.

The NDSA technique, proposed for estimating the IWV (Integrated Water Vapor) through a tropospheric radio link, operates by transmitting two sinusoidal signals at K band and gauging their reception power. This enables the estimation of IWV based on the different signals’attenuation. In 2018, an instrument prototype was finalized for the first measurement campaign, showcasing the NDSA method. In this paper we describe the improved version of the instrument, used for a second campaign in 2022, the procedures for its characterization and generation of data, and some of the campaign outcomes.

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.

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.

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 Normalized Differential Spectral Attenuation technique (NDSA) has been proposed as a method for measuring Integrated Water Vapor (IWV) by means of attenuation measurements in the Ku-/K-band along tropospheric microwave links. After a first measurement campaign aimed at demonstrating the NDSA method, a second field experiment has been carried out from August 1 to November 30, 2022. The transmitter was placed on the top of Monte Gomito (44.1277° lat, 10.6434° lon, 1892 meters a.s.l.) and the receiver on the roof of the Department of Information Engineering of the University of Florence (43.7985° lat, 11.2528° lon, 50 meters a.s.l.). The resulting radio link length was 61.15 km. Four ground weather stations of the regional weather service were selected among those available. The purpose is comparing the IWV estimates provided by NDSA measurements with the ground point data of air temperature, air humidity, barometric pressure, and rainfall.

Recent applications of passive L-band observations from space are summarized for ocean, land surface and cryosphere applications. The main limitation of the measurements performed by the current generation of sensors is the spatial resolution. The need of a mission ensuring the continuation of L-band measurements from space with high spatial resolution (10-15 km) is discussed.

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.

Active microwave remote sensing data at different frequencies can provide crucial information on crop morphology and conditions, thus effectively supporting agronomic management at different scales. Despite the ever-increasing availability of spaceborne platforms and the extensive research developed throughout more than two decades, some knowledge gaps still await to be filled toward operational use, dealing with SAR backscatter response to crop-specific features and seasonal dynamics, including the effects of agronomic practices. In this work, we used variance-based global sensitivity analysis (GSA) as a quantitative framework for investigating the sensitivity of X-band backscattering to agronomic and morphological features typical of two different crops maize and rice. To this end, we jointly exploited empirical data on crop status and growth, high-resolution TerraSAR-X (TSX) data, and microwave radiative transfer model (RTM) simulations. Phenology-informed simulations allowed us to quantify the contributions of different scattering mechanisms for the two crops under varying observation setups, to assess the sensitivity of X-band backscattering to morphostructural crop biophysical parameters (BPs) (and their interactions), and to evaluate the effects of crop biomass on backscatter across growth stages. In particular, multidimensional GSA outputs accounting for model input correlations through Shapley effects provided a comprehensive suite of information on the relative proportion of total backscatter variance explained by a range of parameters and a quantitative description of the different behavior in vertical and horizontal polarization (changing throughout plant growth) in paddy rice, and the mixed contribution of canopy density and leaf angle distribution (depending on the incident angle) in maize.

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.

Measurement of water vapor (WV) in the lower troposphere on a continuous temporal basis would improve our knowledge of the atmospheric dynamics and the performance of numerical weather prediction models. In recent studies, a new measurement concept, the normalized differential spectral attenuation (NDSA) approach, was proposed. It is based on measurements of differential attenuation at 18.8 and 19.2 GHz performed along a tropospheric radio link. While NDSA measurement at a fixed elevation angle provides information on integrated WV (IWV), measurements at different elevation angles allow to retrieve the vertical WV content profile. A prototype NDSA demonstrator, which consists of two units, a synthesized transmitter and a software-defined radio receiver, has been designed and implemented. The system was accurately characterized through several laboratory tests, and then a first experimental campaign was conducted at fixed elevation angle along a ground-to-ground radio link. Obtained results confirm the sensitivity of the NDSA measurements to the IWV along such link with a good agreement with the existing ground-based and satellite data products.

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 knowledge of the water vapor (WV) distribution in the Earth's atmosphere is of great importance for weather prediction. Meteorological models, in particular, the so-called limited area models, can assimilate humidity measurements, increasing the reliability of the simulated atmospheric dynamics. An important improvement can be achieved, for instance, if we are able to provide the total column with a sufficient precision and accuracy. In this paper, the novel normalized differential spectral attenuation (NDSA) approach is applied to retrieve the vertical profile of WV-and thus the total column-from measurements of differential attenuation signals at microwaves. A forward model (FM) has been used to simulate the ray-tracing of a microwave signal from a transmitter to a receiver in the atmosphere by using the 3-D atmospheric parameters as provided by a numerical weather prediction (NWP) model. From the NDSA measurement, the integrated WV (IWV) content can be directly derived. A further retrieval code is able to invert the measurements of IWV along the path length, providing the vertical humidity profile, which is directly related to the total vertical column assimilated by weather prediction models. In this paper, we show that the values of the total column can be retrieved with a precision and accuracy up to about 0.6% and 2.1%, respectively, which could have a positive impact on NWP models at short time scale.

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.

In this paper the methodology to retrieve the vertical profiles of water vapor starting from microwave measurements is discussed. The novel technique, is based on a microwave radio link and the measure of differential attenuation of two signals transmitted at closely spaced frequencies in the Ku-K band. The capability to gain insight about the water vapour distribution in atmosphere and the potential strong impact on the weather prediction chains is also discussed.

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.

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.

The measure of water vapor (WV) in the lowest part of the troposphere is a critical issue which, up to now, cannot be measured from space with sufficient accuracy. A novel technique, which is based on a microwave radio link and the measure of differential attenuation of two signals transmitted at closely spaced frequencies in the Ku-K band, has been recently proposed. In order to prove the potential of this technique a new low-cost microwave link has been designed and the first measurements will be performed by means of a ground-to-ground link. Instrument design and characteristics, as well as expected results are presented here.

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.

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.

We investigate the degree to which ultrahigh frequency radio emission can be used to estimate subsurface physical temperature in the polar ice sheets. We combine electromagnetic emission forward models with plausible models of depth-dependent physical properties in the ice sheet. Temperature models are parameterized with variables including accumulation rate, geothermal heat flux, and surface temperature. Scattering is parameterized using empirical observations of grain growth combined with measured densities. Electromagnetic absorption is modeled using dielectric dispersion processes and semiempirical models based on observations. Our models illustrate that information about East Antarctic ice sheet temperature from near the surface to near the base can be gleaned from ultrawideband radiometer data. Based on our modeling study, we illustrate an instrument concept to measure ice sheet temperature profiles comprising a novel ultrawideband radiometer.

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.

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 CoReH2O mission design is mature; there are two viable technical configurations, and the breadboards of key hardware components, such as the dual-polarized antenna array feeds and high power amplifiers have been built and tested. The baseline retrieval algorithm has been intensively tested using simulated and experimental data. The tests confirm that the threshold performance for SWE products can be met under a wide range of snow conditions. Data from further field campaigns by the airborne SnowSAR acquired Austria, Canada, and Alaska from November 2012 through April 2013 are being analysed to investigate retrieval performance over alpine, glacier and tundra terrains.

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.

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 COld REgions Hydrology High-resolution Observatory (CoReH2O) satellite mission was selected for detailed scientific and technical studies within the Earth Explorer Programme of ESA. The sensor is a dual frequency SAR, operating at 17.2 GHz and 9.6 GHz, VV and VH polarizations The mission will deliver spatially distributed snow and ice observations to improve the representation of the croysphere in hydrological and climate models. Primary parameters are the extent and water equivalent (SWE) of the snow pack and snow accumulation on glaciers. Scientific preparations of the mission include the development and testing of algorithms for retrieval of snow parameters, studies on synergy of CoReH2O-type snow products with passive microwave measurements, the assimilation of satellite snow data in process models, and field experiments. Performance of retrievals for snow extent and SWE was tested with simulated and experimental data, including Ku- and X-band SAR images of the airborne SnowSAR system.

Snow extent and water equivalent (SWE) on land and snow accumulation on glaciers are the main parameters to be delivered by the Cold Regions Hydrology High-resolution Observatory (CoReH2O) satellite. Detailed scientific and technical studies for the mission are going on within the Earth Explorer Programme of ESA. The CoReH2O sensor is a dual frequency SAR, operating at 17.2 and 9.6 GHz, VV and VH polarizations. A main task for mission preparation is the development and validation of algorithms for retrieval of snow parameters. A constrained minimization approach is proposed for SWE retrieval, matching backscatter computed with a radiative transfer model and measurements in the four SAR channels by iterating for SWE and snow grain size. The algorithm was validated with simulated and measured backscatter data. The tests confirm the feasibility of the retrieval approach and help to quantify the requirements for statistical background information which is needed for constraining the solution.

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.

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).

We present in this paper an empirical approach for the characterization of the internal layering of dry snow masses by means of GNSS-R. A forward model has been designed for reconstructing reflected waveforms given a dry snow profile and geometry (elevation and elevation-rate), as a sum of multiple responses from different layers. To extract the internal information, Fourier transforms of time series of waveforms are computed to generate lag-holograms. The frequency stripes that appear are related to the depths of the contributing snow layers. The same analysis has been done with real data, showing with agreement with the models.

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.

The COld REgions Hydrology High-resolution Observatory (CoReH2O) satellite mission has been selected for detailed scientific and technical studies within the ESA Living Planet Programme. The mission addresses the need for distributed snow and ice observations to improve the representation of the cryosphere in climate models and the prediction of the water cycle. The sensor is a dual frequency SAR, operating at 17.2 GHz and 9.6 GHz, VV and VH polarizations. This configuration enables the decomposition of the scattering signal for retrieving snow mass (SWE) and other physical properties of snow and ice. A major task for mission preparation is the development and testing of algorithms for SWE retrieval. The baseline algorithm applies a constrained minimization approach, matching forward computed and measured backscatter by iterating for SWE and effective grain size of the snow volume. Experimental campaigns on Kuand X-band backscatter of snow deliver important information for retrieval development and validation.

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.

GPS reflected signals have become a source of opportunity for remote sensing of the Earth's suface. In this work, we present several capabilities of this technique in two different polar environments: Greenland and Antarctica. The first part is dedicated to the retrieval of sea-ice properties, giving emphasis to the study of the coherent phase for altimetric and roughness estimations, and polarimetric measurements for the determination of the ice salinity variation. The results show good agreement with a tide model and daily ice charts. On the second part, some preliminary results and analysis strategies to retrieve dry snow signatures are presented.

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).

Snow is a critical component of the global water cycle and climate system, and a major source of water supply in many parts of the world. There is a lack of spatially distributed information on the accumulation of snow on land surfaces, glaciers, lake ice, and sea ice. Satellite missions for systematic and global snow observations will be essential to improve the representation of the cryosphere in climate models and to advance the knowledge and prediction of the water cycle variability and changes that depend on snow and ice resources. This paper describes the scientific drivers and technical approach of the proposed Cold Regions Hydrology High-Resolution Observatory (CoReH2O) satellite mission for snow and cold land processes. The sensor is a synthetic aperture radar operating at 17.2 and 9.6 GHz, VV and VH polarizations. The dual-frequency and dual-polarization design enables the decomposition of the scattering signal for retrieving snow mass and other physical properties of snow and ice.

WindSat fully polarimetric passive microwave observations, expressed in the form of the Stokes vector, were analyzed over the Antarctic ice sheet. The vertically and horizontally polarized brightness temperatures (first two Stokes components) from WindSat are shown to be consistent with previous studies. Azimuthal modulations in the third and fourth Stokes components were analyzed and related to surface topography, roughness, and snow morphology. A second harmonic sine function of the azimuth angle was used to estimate the orientation angle of snow features, such as topographic slope and sastrugi. The results show good agreement with the orientations derived in a previous study using scatterometer data at similar frequencies. Seasonal variability in the third and fourth Stokes components is discussed. A consistent pattern of response emerged for 10.7 GHz. Under winter conditions, the large contribution of multiple volume scattering causes a high and regionally varying 10.7-GHz fourth Stokes signal. Under summer conditions, surface scattering dominates and results in a high 10.7-GHz third Stokes signal. The third and fourth Stokes observations at 37 GHz were found to correspond to the smaller penetration depth at this higher frequency, resulting in a low difference between the amplitudes of summer and winter. The study demonstrates the potential of the spaceborne fully polarimetric passive microwave radiometers in monitoring the thermal and morphological properties of large ice sheets.

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.

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.

The 14 papers in this special issue are organized into topical areas and applications, which are in the general order of the MicroRad technical sessions: Radiometer Techniques (4), Vegetation (2), Ocean (2), Atmosphere and Precipitation (4), and Snow and Sea Ice (2).

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 preparation of the satellite mission CoReH2O, one of the six missions which has been 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 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 at the X- and Ku-bands. First the key vegetation types found in snow covered regions where identified on the basis of available global scale data base. A model able to simulating scattering from a vegetated snow-covered terrain was then developed and implemented. Lastly, a sensitivity analysis to vegetation parameters was conducted on sparse vegetation and coniferous forest.

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 COld REgions Hydrology High-resolution Observatory (CoRe-H2O) satellite mission has been selected for scientific and technical studies within the ESA Earth Explorer Programme. The mission addresses the need for spatially detailed snow and ice observations in order to improve the representation of the cryosphere in climate models and to improve the knowledge and prediction of water cycle variability and changes. CoRe-H2O will observe the extent, water equivalent and melting state of the snow cover, accumulation and diagenetic facies of glaciers, and properties of sea ice and lake ice. The sensor is a dual frequency SAR, operating at 17 GHz and 9.6 GHz, VV and VH polarizations. This configuration enables the decomposition of the scattering signal for retrieving physical properties of snow and ice. Scientific preparation activities include experimental field campaigns, improvement of radar backscatter models, and the development of inversion algorithms.

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.

In this paper, the brightness temperatures, and other microwave parameters, measured by using AMSR-E data over two yearly cycles on some test sites selected in different climatic regions of the world, have been related to surface features obtained from ground information and cartography. The areas are characterized by various meteorological conditions and vegetation covers and spread from deserts to dense forests. The analysis was carried out on the data collected with AMSR-E in 2002, 2003 and 2004. The capabilities of the satellite multi- frequency microwave radiometers in the retrieval of land surface parameters were evaluated, focusing the attention to the parameters related to the hydrological cycle, and forest areas. In general, the analysis carried out by using AMSR-E data confirmed the capability of the multi-temporal and multi- frequency analysis in a global scale monitoring of soil moisture as well as snow and vegetation covers, in the limits of the spatial resolution offered by this sensor. An algorithm based on a neural network has been implemented, tested with experimental data collected during SMEX02, and used to generate global maps of soil moisture.

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

This paper investigates the possibility of estimating the soil moisture content (SMC) on a global scale from dual-frequency (C- and X-bands) microwave data of the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E). Because some anomalous behavior was occasionally found in AMSR-E C- and X-band data, a calibration check compared the AMSR-E data with measurements from the SSM/I sensor over two reference targets, namely a Russian evergreen forest and the sea surface, both of which have already been studied in the past. The algorithm for retrieving soil moisture uses both the brightness temperature at C-band in horizontal polarization and the polarization index at X-band for correcting the effects of vegetation. This algorithm is based on a simplified radiative transfer (tau-omega) model, which has been inverted by using the Nelder-Mead iterative minimization method. The algorithm was validated with microwave data collected on two sites during the Microwave Alpine Soil Moisture Experiment 2002 (MASMEx02) and the Soil Moisture Experiment 2002 (SMEX02), respectively. The first site, in Italy, was characterized by natural vegetation covers, whereas the second site, in Iowa (U.S.), was covered primarily in agricultural crops. In general, the soil moisture estimated by the algorithm from AMSR-E data and the SMC measured on the ground were in good agreement with each other in both sites, and five classes of soil moisture were easily identified

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.

An experimental campaign will be carried out in Antarctica at Dome-C in 2005 to investigate low frequency microwave emission of snow pack and to evaluate the potential of Antarctic plateau to act as a calibrator for L-band satellite sensors such as SMOS and HYDROS. Simulations carried out by using a multi-layer electromagnetic model coupled with a glaciological model have shown very small variations (< 0.1K) of L-band emission during the yearly cycle, and confirmed that the low frequency microwave emission mostly comes from the deeper layers of ice.

The ability to estimate the soil moisture content on a global scale from dual-frequency (C- and X-bands) microwave AMSR-E data is investigated in this paper. The C-band AMSR-E data were calibrated by comparing AMSR-E data with past measurements of SSM/I and SMMR sensors over some reference targets as the Amazon forest and the Ocean. An algorithm for the retrieval of soil moisture, based on a simplified form of the radiative transfer theory, was tested and subsequently inverted by using the Nelder-Mead method. The algorithm, which used both the brightness temperature at C-band and the polarization index at X-band, was successfully validated on data collected on two areas in Italy and US, during the MASMEx02 and the SMEX02 experiments, respectively

A study of the melting cycle of snow was carried out by combining microwave active and passive measurements with meteorological data and snow modelling. The experiment took place in the eastern Italian Alps from mid February to late May 2003. Brightness temperature at C-, Ku- and Ka- bands (vertical and horizontal polarizations) and backscattering coefficient at Ku-band (VV), were continuously measured (24 h/day) with ground-based sensors. Remote sensing observations were supported by meteorological data, and snow measurements. A continuous simulation of the snow temperature, depth, and liquid water content was performed for the entire monitoring period by means of a physically based distributed snowmelt model. Both hydrological and remote sensing approaches gave useful and coherent results in describing the snow melting and refreezing cycles. Microwave active and passive data were consistent each other. During the melting cycle, the presence of liquid water caused an increase of absorption with a consequent increase of the brightness temperature and a decrease of the backscattering coefficient

The sensitivity of radar backscattering to the principal hydrological parameters, such as vegetation biomass, soil moisture, and surface roughness, is discussed. Results obtained by using multifrequency synthetic aperture radar (SAR) data measured by the Jet Propulsion Laboratory Airborne Synthetic Aperture Radar, Spaceborne Imaging Radar-C, and European Remote Sensing 1/2 sensors are summarized. The sensitivity of L- and C-bands to spatial variations of plant and soil parameters is masked by the presence of surface roughness, which in turn affects the radar signal. However, from the observation of data collected at different dates and averaged over a relatively wide area that includes several fields, the correlation to soil moisture and vegetation biomass is found to be significant, since the effects of spatial variations are smoothed. On the other hand, the sensitivity to surface roughness becomes appreciable when multitemporal data are averaged in time, thus reducing the effects of temporal moisture variations.

Airborne microwave radiometric measurements were carried out in June 1999 and January 2002 on three forest stands in Tuscany (Italy), in order to investigate the the potential contribution of microwave radiometry in analysing the differences between summer and winter features of trees. The analysis of the collected data pointed out that the use of microwave emission at the highest frequencies makes it possible to separate between several forest types, whereas L-band emission is more related to tree biomass. At low biomass and low frequency, emission is more affected by the seasonal differences, since contributions from soil and from soil-trunk interaction are important. For higher values of biomass and/or frequency emission is mostly dominated by branches and less sensitive to season.

In this paper, an experiment aimed at investigating the water balance after soil thawing and the radiation budget is described. The experiment was carried out by combining microwave remote sensing measurements with ground and meteorological data. The higher frequencies were found to be very sensitive to the characteristics of snow, whereas the lower ones were much more influenced by the soil conditions. The sensitivity to soil moisture was well demonstrated at L-band, although the soil was covered by a thick layer of grass, and, to a minor extent, also at C-band.

A study of the melting cycle of snow was carried out by combining microwave radiometric measurements with conventional micrometeorological data and snow modelling. The experiment took place in the eastern Italian Alps. The high sensitivity of microwave emission at 19 and 37 GHz to the melting refreezing-cycles of snow was confirmed. Moreover, micro-meteorological data provided additional insight on the processes. Simulations obtained with electromagnetic and hydrological models were consistent with experimental data.

This work describes a nonparametric algorithm suitable for scene classification, either supervised or not, starting from a number of pixel features derived from SAR observations. Pixel vectors composed by simple features derived from the backscatter coefficients of one or more bands and/or polarizations are iteratively clustered into dynamically upgraded classes. Possible "a priori" knowledge coming from ground truth data may be used to initialize the procedure, but is not mandatory. Experiments on MAC-91 NASA/JPL AIRSAR data on the Montespertoli test site show that seven features derived from each of L-HV and P-HV observations are capable to discriminate seven agricultural cover classes with an overall pixel accuracy of 60%, when the algorithm learns from 10% of the truth data and classifies the remaining 90%.

An experiment aiming at studying the scattering properties of a collection of dielectric cylinders placed on a reflecting plane has been performed by using the EMSL of the JRC of Ispra Italy. Experimental data have been compared with simulations performed with a coherent electromagnetic model.

The capability of multi-frequency microwave radiometers in retrieving soil moisture profiles was investigated by using both experimental data collected in a experiment with IROE microwave radiometers and an electromagnetic model (Integral Equation Model, IEM). The experimental data and the IEM results were used to train an artificial neural network in order to invert the soil moisture data and reproduce the soil moisture profiles.

Microwave sensors are of primary importance in mapping surface states and measuring some significant quantities which affect the hydrological cycle. A space mission aiming at monitoring soil moisture and surface salinity at a global scale is suggested. The mission is based on a combination of polarimetric active and passive microwave sensors.

The influence of the shape and dimensions of plant constituents on the backscattering of agricultural vegetation is investigated. Multifrequency multitemporal polarimetric data, collected at C- and L-bands by means of airborne and satellite synthetic aperture radar (SAR), showed that the relations between the backscattering of crops and the vegetation biomass depend on plant type, and that there are different trends for "narrow" and "broad" leaf crops. In the latter crops, backscattering increases with an increase in the biomass, especially at L-band. This behavior is typical of media in which scattering is dominant, whereas on "narrow leaf" plants, the trend is flat or decreasing, denoting a major contribution of absorption. Theoretical simulations obtained with a discrete element radiative transfer model have confirmed that a different backscattering of crops with the same biomass may be due to plant geometry.

Microwave radiometric measurements using airborne instruments in a frequency range from L- to Ka-band were carried out over six broad-leaved and one coniferous forest stands in Tuscany, Italy. Ground measurements of the main tree parameters were performed on the same stands. The analysis of the collected data indicated that the use of microwave emission at the highest frequencies makes it possible to identify some forest types, whereas L-band emission is more closely related to tree biomass. The relationships between emission and some significant tree parameters such as leaf area index, basal area, woody volume, and crown transparency are presented and discussed. The significant relationship between L-band emission and woody volume is further analyzed by means of a first-order radiative transfer model.

Field measurements of microwave emission from snow-covered soil were carried out in 1996, 1997, and 1999 on the Italian Alps using a three-frequency dual polarized microwave system. At the same time, nivological time measurements were carried out using standard methods and an electromagnetic contact probe. Collected data confirmed the possibility of separating wet from dry snow and of estimating the water equivalent of dry snow. Simulations performed by means of a model based on the dense medium radiative theory (DMRT) were able to reproduce experimental data very well.

The sensitivity of microwave emission at different frequencies to soil moisture in bare and vegetated soils has been investigated using experimental data. Since the best frequency for the measurement of soil moisture (L-band) is absent in current satellite sensors, it is necessary to seek alternative solutions. An algorithm is proposed for the retrieval of soil moisture based on the sensitivity to moisture of both the brightness temperature and the polarization index at C-band, one that is able to correct for the effect of vegetation by means of the polarization index at X-band. The algorithm has been tested by using experimental data collected with airborne microwave radiometers on agricultural areas and validated by using the data sets of special sensor microwave/imager (SMM/I) and scanning multichannel microwave radiometer (SMMR). These research activities are planned in view of coming new satellites: AQUA (NASA) and ADEOS-II (NASDA), which will be launched by the end of 2001. These will have new generation microwave radiometers (AMSR-E and AMSR) onboard, which show much better characteristics with respect to the previous sensors, in particular an enhanced spatial resolution.

Multifrequency polarimetric scattering and emissivity measurements have been carried out on three experimental dielectric models, characterized by random surfaces with different statistics. The results of the measurements have been compared with simulations obtained through physical models based on the classical approximations of physical optics (PO), geometrical optics (GO), small perturbation (SP), and integral equation model (IEM). The comparison of experimental data with theory has shown that, even when the parameters of the observed surface are well determined and known, some discrepancy may exist between models and measurements. Except for a few cases, this discrepancy is quite small and may be insignificant for many practical applications. The IEM has been proven to have a wider range of applicability with respect to other tested approximations.

The sensitivity of backscattering coefficient, measured by ERS-1 and JERS-1 radars, to vegetation biomass is discussed and compared with the best results achieved using multifrequency polarimetric JPL-AIRSAR data. Experimental results show that measurements with JERS-1/L-band and ERS-1/C-band SAR provide the means for detecting vegetation growth. In particular, the C-band signal of ERS radar was found to be very well correlated to forest woody volume.

Microwave emission from crops characterized by long vertical structures has been investigated by using experimental data at 10 and 37 GHz and a model based on radiative transfer theory. The effects of single-plant constituents on the total emission from crops are evaluated by means of measurements carried out on plants in natural conditions and after sequential cuts of fruits, leaves, and stems. The experimental results are discussed in terms of emission and scattering properties of the crop. The dependence of optical depth and single-scattering albedo on plant water content has been estimated.

The effects of spatial distribution of the scattering elements on microwave emission from random media have been investigated using an experimental model composed of long, thin vertical dielectric cylinders on a reflecting screen. The measurements have been carried out at 10 and 37 GHz, H, V polarizations and different nadir and azimuth angles. Random "uniform" and "cluster" distributions as well as periodic "row" configurations with different volume fractions have been studied. When the cylinders are distributed in nearly circular clusters or in parallel rows significant emission enhancement with respect to uniform distribution is detected at 10 GHz and incidence angle lower than 50/spl deg/, whereas, at 37 GHz the emission is lower for clusters and strongly dependent on azimuth angle for the "row" configuration.