The NOAA-21 ATMS, launched in November 2022, collected two-dimensional lunar scan data on March 10, 2023, during its commissioning phase at a Moon phase angle of 34°. The raw data were calibrated using MiCalPS, a microwave calibration and geolocation tool developed at the University of Maryland. Analysis showed that NOAA-21’s lunar antenna gain is generally lower than NOAA-20’s due to sampling rate differences. After correcting for beam pointing errors, disk-averaged lunar brightness temperatures (TDISKB,Moon) were derived for 23–183 GHz. These were compared to NOAA-20 data at 0° phase angle and predictions from the microwave lunar radiative transfer model (ML-RTM). The observed model differences were: −3.3 K (K band), 0.01 K (V), 2.0 K (W), −2.3 K (low-G), and 1.6 K (high-G), consistent with predicted phase delay trends. Further observations at varying Moon phases are recommended to enhance MLRTM validation.

Space-borne microwave sounding instruments have become vital data sources for weather prediction and climate change studies. Among the various radiometer configurations, the total power microwave radiometer is particularly appealing for current and future operational satellites due to its superior sensitivity and simple design. However, its performance is vulnerable to degradation caused by receiver gain fluctuations, electronic 1/f noise, and other time varying receiver characteristics. For Numerical Weather Prediction (NWP) users, 1/f noise introduces inter-channel correlations, complicating the assimilation of affected observations and reducing their accuracy. Addressing this noise issue in ground data processing system is essential to enhance the utility of microwave sounding data. This paper focuses on the characterization and mitigation of noise in current and future microwave sounding instruments, with particular emphasis on the impact of 1/f noise. Various methods are applied to quantitatively characterize noise features in both frequency and time domains. Additionally, the influence of calibration parameters on 1/f noise are analyzed. Based on these findings, we propose a mitigation algorithm for reducing noise during the on-orbit calibration of microwave sounding instruments, aiming to improve the quality of retrieved data for operational use.

Radio Frequency Interference (RFI) has long been a problem for L-band microwave radiometers, such as SMOS, Aquarius and SMAP. This paper reports on the activities performed by the SMAP RFI team to identify and report persistent sources with the aim of decreasing global RFI occurrences at L-band.

The use of a “time-series ratio” soil moisture retrieval approach is under consideration for the upcoming NISAR mission’s soil moisture product. As such, it is of interest to characterize the algorithm’s anticipated error budget as part of pre-launch activities. This paper develops an error model to estimate retrieval errors for the proposed algorithm. The model accounts for error contributions from speckle and thermal noise as well as uncertainties that arise as part of the retrieval process. Spatial and temporal behaviors of the retrieval errors are determined using a SMAP-based soil moisture climatology. The results show that soil moisture retrieval errors from the time-series ratio method meet the 0.06 m3/m3unbiased root mean square error (URMSE) performance metric established for the NISAR soil moisture product.

Lidar elevation maps are utilized in a bistatic electromagnetic scattering model of the Cyclone Global Navigation Satellite System over San Luis Valley in Colorado, USA. The results are compared with results generated using the Shuttle Radar Topography Mission (SRTM) 1 arcsecond global digital elevation model (DEM). The high resolution lidar maps are also used to generate maps of surface roughness at length scales finer than the horizontal resolution of SRTM. Model results using these maps illustrate the importance of the spatial variation of surface roughness on reflectometry signals. Results also highlight the shortcomings of using SRTM in scattering models and show improvements when a lidar DEM is used.

The Soil Moisture Active/Passive Mission was launched in 2015 to provide estimates of global surface soil moisture from its L-Band radiometer measurements. The digital backend included in SMAP's radiometer enables radio frequency interference (RFI) to be detected and filtered in real time. The six-year record of SMAP's RFI data available now allows global monitoring of the RFI environment and its changes over time. An automatic tool has been developed for this purpose that generates a table listing the most persistent and strongest sources. This paper provides an analysis of these tables to examine the evolution of the RFI environment over time. The use of the tables generated for reporting RFI sources to national authorities is also discussed.

The National Aeronautics and Space Administration (NASA) - Indian Space Research Organization (ISRO) Synthetic Aperture Radar (NISAR) mission plan to launch a SAR operating at L- and S-band with a 12-day repeat frequency. A global soil moisture product at 200 m spatial resolution derived from 200 m NISAR radar measurements is currently under development. Although several retrieval algorithms are being investigated, this paper focuses on a “time series ratio” retrieval approach. In order to understand and assess the performance of this algorithm, an error model has been developed and is reported in this paper. The model is applied to examine errors as a function of the instrument characteristics and for a given location. Initial progress in including vegetation effects and in predicting errors as a function of spatial location is also described.

Analyses of GNSS-Reflectometry data sets have demonstrated that coherent signals can be observed over land areas. To fully interpret those measurements, forward modeling of the scattering of the GPS signal over land can be performed. Scattering theories rely on several parameters, but the surface roughness is one of the main unknowns that is usually derived from Digital Elevation Models (DEM). However, standard DEMs are too coarse to provide information on the finest scales of surface roughness. Airborne lidar measurements can provide DEMs at higher spatial resolution and better vertical accuracy than those available from standard DEMs. This paper presents two airborne lidar campaigns that were conducted to support CYGNSS land cal/val activities in the San Luis Valley, CO (where mostly incoherent returns are observed) and near White Sands, NM (where mostly coherent returns are observed). An initial comparison of surface statistics at the two locations is also provided so that insight can be obtained into the surface characteristics necessary to generate either coherent or incoherent scattering for GPS signals reflected from land surfaces.

L- and S-band observations from NASA's Passive/Active L/S band (PALS) sensor from the SMEX02 campaign were used to estimate soil moisture. The retrieval process is based on the “alpha approximation” method. This method utilizes a time-series of normalized radar backscatter measurements as well as ancillary information to estimate soil moisture over the Walnut Creek watershed. The resulting retrieved soil moistures are compared to in-situ soil moisture measurements at multiple test sites within the watershed. The calculations show reasonable results for both L- and S-band and provide further insight into the use of L- and S-bands for the upcoming NASA/ISRO mission.

The NASA ISRO Synthetic Aperture Radar (NISAR) mission is currently under development and will provide global L-band radar observations that will be helpful for various soil moisture applications. The final NISAR soil moisture product will have 200m spatial resolution with 12-day exact revisit time. A time-series ratio algorithm was implemented using NISAR simulated UAVSAR data collected during the SMAPVEX12 field experiment. In this paper, the performance of the time series ratio algorithm was assessed using in situ observations. Performance of the soil moisture retrieval algorithm was also assessed for dual polarization and quad-polarization observations modes.

Wideband microwave radiometry holds promise for new in-sights for passive remote sensing of snow packs. We report on a plot-scale, season-long field experiment using two wide-band microwave radiometers operating with about 1 GHz of bandwidth at L-band frequencies. Despite considerable ra-dio frequency interference (RFI), there remains many 100's of MHz of usable bandwdith for measurement. We report on the wideband signatures of a snowpack that varies in depth from no snow to more than 57 cm deep.

The physical process of GPS signal reflection from Earth's land surface is of interest in order to support the development of land applications using GNSS-Reflectometry (GNSS-R) data. A key question is understanding when GNSS-R land returns should be examined in terms of their reflectivity or normalized radar cross section (NRCS). An airborne lidar DEM obtained near White Sands, NM is used to compute surface roughness properties. The roughness map is then correlated with the recurrence of coherency derived from three years of CYGNSS observations. The results show that “medium scale” rms heights within the first Fresnel zone of less than < ~ 10 cm are associated with coherent reflections. Initial analysis of a raw IF data track further demonstrates the decrease of coherence with increased surface roughness.

In this paper, an Analytical Kirchhoff Solution (AKS) and Numerical Kirchhoff approach (NKA) are used to study coherent and incoherent land surface near specular scattering at L and P bands. The AKS model includes both coherent and incoherent waves, and includes the effects of topographic slopes and elevations. The land profile is modelled as a summation of three scales of surface roughness corresponding to “microwave”, “fine topography”, and “coarse topography”, where the microwave roughness and fine topography are treated as random processes while the coarse topography is deterministic. An airborne lidar survey performed over the San Luis Valley, CO is used to obtain surface roughness information for the simulation results of$\mathrm{P}$and L-band scattering. Results using the lidar surface data show that coherent reflection can dominate returns from a 5 km by 5 km area at P band, while incoherent scattering dominates L band returns in the same scenario.

A comparison of three different electromagnetic scattering models for land surface delay-Doppler maps (DDMs) obtained from global navigation satellite system reflectometry (GNSS-R) along a Cyclone Global Navigation Satellite System (CYGNSS) track in the San Luis Valley, Colorado, USA, is presented. The three models are the analytical Kirchhoff solutions (AKS), the Soil And VEgetation Reflection Simulator (SAVERS), and the improved geometrical optics with topography (IGOT). Common inputs to the three models were defined by using field samples of soil moisture and texture, soil surface roughness measurements, and a digital elevation model (DEM). The resulting peak reflectivity profiles of the models and the CYGNSS data all had a range of 10 dB along the selected track, mainly due to the influence of topography. The reflectivities obtained from all three models agreed with one another to within 2.4 dB along the full length of the track. The models also showed general agreement with the corresponding CYGNSS data, although the modeled profiles were higher than CYGNSS Science Data Record Version 3.1 by an average of 5 dB and also smoother. Additional characterization of fine-scale surface roughness is identified as an area for future work to improve model fidelity. An intercomparison of DDM structure for three selected acquisitions is also provided.

Although ice sheet internal temperature is a first-order control on glacier dynamics, relatively few in situ borehole temperature profiles exist. The ultra-wideband software-defined microwave radiometer (UWBRAD) was designed to estimate internal ice sheet temperature (Ti) by measuring microwave brightness temperatures (Tb) from 0.5 GHz to 2 GHz. The retrieval ofTifromTbis not straightforward, however, due in part to the complicating effects of ice density fluctuations onTb. In this paper, we report a simulation study to assess the feasibility of realizing three science goals: the retrieval of a)Tiat 10 m depth to within 1 K; b) vertically-averagedTito within 1 K; and c) the verticalTiprofile to within 1 K RMSE. Two analyses along the Greenland ice divide are presented. First, we assess the ideal UWBRADTiretrieval precision via the Cramér-Rao Lower Bound (CRLB). Second, we perform a “Virtual Experiment” (VE) using synthetic UWBRAD observations. Both the CRLB and VE analyses indicate that the science goals are achievable with the caveats that ice thickness and UWBRADTbprecision impact performance. Assuming a UWBRADTbprecision of 0.5 K, and for places where ice sheet thickness is less than 3 km, all science goals can be achieved. The results of the study provide a strong indication of the potential of UWBRAD to provide valuable Greenland ice temperature profile information to the scientific community.

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 Soil Moisture Active/Passive satellite was launched in 2015 to provide global and continuous maps of land surface soil moisture and freeze-thaw using L-Band microwave radiometry. Even though the 1400-1427 MHz frequency used by SMAP is a protected portion of the spectrum, Radio Frequency Interference (RFI) is still observed that can corrupt the radiometer's measurements. Nine distinct algorithms are implemented as part of SMAP's level 1 processing to detect and filter out RFI contributions. However, any remaining undetected RFI are major concern especially at the locations of cal/val sites used for evaluating soil moisture retrieval performance. This paper presents an analysis of the RFI environment at SMAP cal/val site locations and assesses the impact of RFI on soil moisture retrievals at those locations.

Analyses of GNSS-R data sets have revealed the occasional presence of coherent signals over land areas. Studies have been conducted of modeling such returns using classical scattering theories that consider the geometry, the frequency band, and surface parameters as inputs. The surface roughness is a crucial parameter that is not widely available from ancillary sources. This paper presents a comparison of roughness statistics derived from Digital Elevation Maps (DEMs) having different spatial resolutions, and shows the importance of having a high-resolution DEM in order to resolve small scale roughness. This is particularly important when modeling reflected signals over very flat surfaces where coherency can be significant.

A comparison of three different electromagnetic scattering models for delay-Doppler maps (DDMs) of global navigation satellite system reflectometry (GNSS-R) from land is performed along a Cyclone Global Navigation Satellite System (CYGNSS) track over a validation site in the San Luis Valley, Colorado, USA. The peak reflectivity profiles of all three models and of the corresponding CYGNSS data are found to be in general agreement and are strongly influenced by topography. An intercomparison of DDM structure for one acquisition is also included. Efforts to refine the model results using a high resolution lidar survey are ongoing.

S-band observations from NASA's Passive/Active L/S Band (PALS) radar from the SMEX02 campaign were used to estimate soil moisture. The “alpha” method is applied for this process, in which a time series of ratios of normalized radar cross section values at successive measurements is used to infer the corresponding soil moisture time series given ancillary information on the minimum and maximum soil moisture values expected over the time series. Results are examined as a function of the polarization and crop type. The results show reasonable retrieval performance, indicating the potential of using S-band observations from the future NASA/ISRO SAR (NISAR) mission.

The NASA ISRO Synthetic Aperture Radar (NISAR) mission is currently under development and is scheduled for launch in 2022. The NISAR mission will provide global data sets of Earth land surface dynamics that are critical for multiple Earth Science disciplines including observations of ecosystem carbon and water cycles. Global L-band radar observations at high spatial resolution will be helpful for soil moisture applications. One of the goals of the NISAR mission is to provide a global soil moisture product at 200 m resolution with a global revisit frequency of 6 days. A time-series ratio algorithm was implemented using NISAR simulated SMAPVEX12 UAVSAR data, which is an L-band airborne radar backscatter measurement. For a NISAR-like configuration, backscatter at incidence angles from 30 to 50 degrees was considered in this study. The initial retrieval statistics following comparisons with in-situ ground truth show correlation coefficients (R) to be about 0.81, and the unbiased RMSE to be about 0.06 m3/m3. Results from dual co-polarization and/or cross-polarization modes were evaluated and considered for performance improvement.

This paper presents a study of snowpack thermal emissions at long wavelengths and over a wide frequency band. Brightness temperature measurements of a snow layer are reported and used to estimate the travel time through the layer. The Ultra-Wideband Software-Defined Radiometer (UWBRAD) and the Wideband Autocorrelation Radiometer (WiBAR) were deployed at the Keweenaw Research Center (KRC) from February to April 2020 to demonstrate these techniques. Results on snowpack brightness temperature and thickness measurements are presented and discussed.

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.

NASA's CYclone Global Navigation Satellite System (CYGNSS) mission operates a constellation of 8 small satellites that provide ocean wind speed measurements with dense spatial coverage and a median revisit time of about 4 hours. This paper investigates the possibility of using the “rapid revisit” characteristics of CYGNSS measurements to create a detector of convective activity by examining the variability of CYGNSS wind speeds over small intervals in space and time.

The National Aeronautics and Space Administration (NASA) - Indian Space Research Organization (ISRO) Synthetic Aperture Radar (NISAR) is being developed in order to provide highly spatial resolution L- and S-band backscatter observations of the Earth's surface. Remotely sensed soil moisture is one of NISAR applications of interest. This paper reports an initial analysis of the possibility of using NISAR modes to retrieve soil moisture based on two different methods: a snapshot method and the time series technique. Preliminary results of the forward modeling of the backscattered signal over land and the soil moisture retrievals are presented for bare surfaces.

Radio-frequency interference (RFI) has had a detrimental effect on L-band passive observatories such as SMOS, Aquarius and SMAP. A better knowledge of the characteristics of RFI signals might help mitigate this issue by leading to additional and better focused RFI detection algorithms and it might help identify RFI emitters on the ground. In this study we present approaches to retrieve some of the features of the RFI signals using SMAP data and we present some statistical considerations about the temporal and spectral characteristics of RFI sources.

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 Soil Moisture Active/Passive satellite microwave radiometer has been providing measurements of L-band thermal emission from Earth for more than 2 years. SMAP retrieves surface soil moisture from its brightness temperature measurements, and continues to provide science products to the user community. Even though the SMAP radiometer operates in a protected band, its measurements are still corrupted by Radio Frequency Interference (RFI) caused by illegal in-band transmissions or out-of-band emissions. The SMAP radiometer was designed to include special hardware to enable RFI detection and filtering using multiple detection algorithms. Given the good overall performance of SMAP algorithms to detect RFI sources, an automatic tool to report source properties automatically was developed and is now operational. This paper provides a preliminary analysis of the outputs of this reporting tool with a particular focus on the evolution of the RFI environment observed by SMAP during its period of operations.

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

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

The measurements made by the Soil Moisture Active/Passive (SMAP) mission are affected by the presence of Radio Frequency Interference (RFI) in the protected 1400-1427 MHz band. In SMAP data processing, the main protection against RFI is a sophisticated RFI detection algorithm which flags sub-samples in time and frequency that are contaminated by RFI and removes them before estimating the brightness temperature. This contribution presents two additional approaches that have been developed to address the RFI concern in SMAP. The first consists in locating sources of RFI, which can then be reported; once located, it becomes possible to report RFI sources to spectrum management authorities, which can lead to less RFI being experienced by SMAP in the future. The second is an additional RFI detection method that is based on detecting outliers in the spatial distribution of measured antenna temperatures.

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 Soil Moisture Active/Passive (SMAP) satellite mission measures Earth's radiation in the protected portion of the spectrum at 1.413 GHz (L-band) to retrieve geophysical quantities of the surface, such as soil moisture and the frozen/thawed state of the soil. The presence of radio-frequency interference (RFI) in this band is significant and impacts the quality of SMAP measurements. Knowing the location of the sources of RFI is important, because it can help to identify the source itself and also be used to develop strategies to mitigate its impact of the RFI on the data. This paper presents an algorithm that takes advantage of the viewing geometry of SMAP to locate sources of RFI. The results are validated using known locations of RFI sources and by comparison with the measurements of Soil Moisture and Ocean Salinity (SMOS) and Aquarius, two other satellite missions with L-band microwave radiometers operating in the protected band. Comparison with RFI of known location suggests that the algorithm is accurate to 1-2 km. The median distance between the locations reported by SMOS and this algorithm is 2.27 km. A study of the relationship between the localization error and the number of observations of RFI sources shows that the median localization error is about 2 km with 12 observations and about 1 km with 30 observations.

The Ultra-Wideband Microwave Radiometer observes scene brightness temperatures over the frequency range 0.5-2 GHz, which primarily includes frequency bands that are not protected for passive microwave observations. This document presents UWBRAD's RFI mitigation algorithms and examples of the RFI environment encountered during a September 2016 flight campaign that included flights in Canada and Greenland.

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.

NASA's Soil Moisture Active and Passive (SMAP) satellite was launched in January 2015 to provide global measurements of soil moisture and freeze/thaw state. Soil moisture products are derived from SMAP radiometer measurements acquired at L Band (1.4 GHz). Even though this is a protected band, unauthorized transmitters emitting either within the band or in adjacent bands cause radio frequency interference (RFI). Because RFI contributions corrupt the radiometer measurements and therefore can lead to biases in retrieved soil moisture, the SMAP radiometer includes special hardware to enable RFI detection and filtering using multiple detection algorithms. This paper investigates the performance of SMAP's RFI detectors, which include pulse, cross-frequency, kurtosis, and polarimetric methods, as a function of the power of the RFI sources. Methods for examining residual RFI remaining after detection and filtering is applied are also discussed.

The ultra-wideband software-defined microwave radiometer (UWBRAD) is designed to provide ice sheet internal temperature by measuring low frequency microwave emission. A Bayesian framework is designed to retrieve the ice sheet internal temperature from simulated UWBRAD brightness temperature (Tb). Experiment results showed feasibility to estimate ice sheet internal temperature and improvement of priors.

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.

The Soil Moisture Active Passive (SMAP) mission, launched January 31, 2015, provides global observations of 1.4 GHz Earth thermal emissions from space through its L-band radiometer. Although SMAP's radiometer passband lies within the protected 1.4-1.427 GHz band, both unauthorized in-band transmitters as well as out-of-band emissions from transmitters operating at frequencies adjacent to this allocated spectrum have been documented as sources of radio frequency interference (RFI) to the L-band radiometers on SMOS and Aquarius. Low level RFI (0.1-10 Kelvin) is especially problematic as it can be mistaken for natural variability and if left unmitigated can corrupt radiometer measurements leading to flawed retrievals. SMAP has an aggressive approach to RFI mitigation using an advanced digital microwave radiometer to provide time and frequency measurements as well as a comprehensive ground processing algorithm.

The National Aeronautics and Space Administration's (NASA) Soil Moisture Active and Passive (SMAP) mission, which was launched on January 31, 2015, is providing global measurements of soil moisture and freeze/thaw state. The SMAP radiometer operates within the protected Earth Exploration Satellite Service passive frequency allocation of 1400-1427 MHz. However, unauthorized in-band transmitters and out-of-band emissions from transmitters operating at frequencies adjacent to this allocated spectrum are known to cause interference to microwave radiometry in this band. Because measurement corruption by these terrestrial transmissions, which is referred to as radio-frequency interference (RFI), threatens mission success, the SMAP radiometer includes special flight hardware to enable the detection and filtering of RFI. Results from the first year of SMAP data show the presence of RFI with frequent occurrence over Asia and Europe. During the calibration/validation stage of the mission, the RFI detection and mitigation algorithms were modified to provide enhanced performance. Analysis of the L1B_TB products indicates good algorithmic performance with respect to RFI detection and removal. However, some regions of the globe (e.g., Japan) continue to experience complete data loss. This paper summarizes updates to the SMAP RFI processing algorithms based on prelaunch tests and on-orbit measurements, as well as RFI information obtained in SMAP's first year on orbit.

We propose a planar-layered medium-based radar backscat-ter model to predict coherence trends, in Interferometric Synthetic Aperture Radar (InSAR) images, manifest when interrogating planar-layered dielectric geophysical subsurfaces. This InSAR coherence model improves upon past ones in two ways: Incorporation of “multi-bounce”, arising from the guidance behavior of minimally-attenuating and high-contrast dielectric slabs, as well as azimuthal deviation in antenna pointing. Including the former renders this model especially suitable for analyzing coherence modifications (decorrelation and phase bias) arising from remote sensing of low-attenuating targets (e.g., dry soil), which augments applicability to high-attenuating targets (e.g., wet, salty soils) readily analyzed with many traditional InSAR models. Representing the model's key contributions, we discuss two predicted trends: Namely, in the limit of a perfectly guiding dielectric slab (i.e., zero attenuation and infinite dielectric contrast), the interferometric correlation is inversely proportional to the InSAR perpendicular baseline length and the phase bias linearly diverges.

Existing models for the short-wave spectrum of the sea surface are not consistent with microwave satellite data when multi-bands and multi-incidence data sets are considered. We devise a simple parametric model for the short-wave omnidirectional spectrum of the sea surface on the basis of a three-band (C, Ku, and Ka) and multi-incidence (low, moderate, and large) data set and an improved analytical scattering model, namely the non-Gaussian Weighted Curvature Approximation. This spectrum is also constrained by several optical measurements which provide a priori conditions on the total and filtered mean-square slopes. It is compared with classical models such as Elfouhaily and Kudryavtsev unified curvature spectra. Significant differences are observed at wave numbers corresponding to the range of decimeter scales. The new spectrum is by construction fully consistent with the omnidirectional normalized radar cross section of the multi-band data set.

The simulation and interpretation of microwave sea radar return in the near-nadir region are still issues in view of the limitations of the geometrical optics approximation and the multiscale and non-Gaussian nature of the surface. We show that an unambiguous and fully consistent physical approach can be reached in the framework of the physical optics. The model is developed on the basis of various satellite and airborne C-, Ku-, and Ka-band measurements using different reference surface roughness spectra. As found, the introduction of a peakedness correction based upon the excess kurtosis of slopes is necessary to obtain consistent analysis across the microwave frequency range. The model yields accurate simulations for the omnidirectional near-nadir normalized radar cross section in different frequency bands, provided the spectrum satisfies some a priori constraints on the distribution of the total and filtered slopes.