Search

An analysis of the coherency properties of specular scattering from ocean and land surfaces as observed in global navigation satellite system-reflectometry (GNSS-R) and signals of opportunity systems is presented. This analysis applies existing approximate models for the coherent and incoherent contributions. Approximate expressions are developed for when one component of the return is likely to dominate as a function of surface and observing system properties. The model developed is then applied for sea surface returns, and the relative contribution of the coherent term is expressed as a function of the receiver height, frequency, incidence angle, and wind speed. For L-band spaceborne measurements, it is shown that coherence is expected only for wind speeds less than 2–3 m/s, while for P-band spaceborne measurements, coherence can dominate returns for wind speeds up to 5–7 m/s. For land surface measurements from space, it is shown that the surface rms height needs to be sufficiently low for coherent components to dominate returns. Coherence dominates for roughness values not exceeding a range of 5–7 cm for the L-band and 15–30 cm for the P-band. For the L-band, these conditions over land are likely to be created primarily by inland water bodies. A model for the specular scattering from a water body, including earth curvature effects, is then developed to highlight the strong dependence of the resulting coherent field on the shape of the water body and any offset in its location from the specular point. These results further clarify the significant variability that should be expected in coherent scattering from inland water bodies. [ABSTRACT FROM AUTHOR]

The Cyclone Global Navigation Satellite System (CYGNSS) is a new NASA earth science mission scheduled to be launched in 2016 that focuses on tropical cyclones (TCs) and tropical convection. The mission's two primary objectives are the measurement of ocean surface wind speed with sufficient temporal resolution to resolve short-time-scale processes such as the rapid intensification phase of TC development and the ability of the surface measurements to penetrate through the extremely high precipitation rates typically encountered in the TC inner core. The mission's goal is to support significant improvements in our ability to forecast TC track, intensity, and storm surge through better observations and, ultimately, better understanding of inner-core processes. CYGNSS meets its temporal sampling objective by deploying a constellation of eight satellites. Its ability to see through heavy precipitation is enabled by its operation as a bistatic radar using low-frequency GPS signals. The mission will deploy an eight-spacecraft constellation in a low-inclination (35°) circular orbit to maximize coverage and sampling in the tropics. Each CYGNSS spacecraft carries a four-channel radar receiver that measures GPS navigation signals scattered by the ocean surface. The mission will measure inner-core surface winds with high temporal resolution and spatial coverage, under all precipitating conditions, and over the full dynamic range of TC wind speeds. [ABSTRACT FROM AUTHOR]

In studying the mass balance of polar ice sheets, fluctuations in firn density near the surface is a major uncertainty. In this paper, we explore these variations at locations on the Greenland Ice Sheet and at the Dome C location in Antarctica. Borehole in situ measurements, snow radar echoes, microwave brightness temperatures, and modeling results from the Community Firn Model (CFM) are used. It is shown that firn density profiles can be represented using three processes: "long-scale" and "short-scale" density variations and "refrozen layers". Consistency with this description is observed in the dynamic range of airborne 0.5–2 GHz brightness temperatures and snow radar echo peaks in measurements performed in Greenland in 2017. Based on these insights, a new analytical partially coherent model is implemented to explain the microwave brightness temperatures using the three-scale description of the firn. Short- and long-scale firn processes are modeled as a 3D continuous random medium with finite vertical and horizontal correlation lengths as opposed to past 1D randomly layered medium descriptions. Refrozen layers are described as deterministic sheets with planar interfaces, with the number of refrozen-layer interfaces determined by radar observations. Firn density and correlation length parameters used in forward modeling to match measured 0.5–2 GHz brightness temperatures in Greenland show consistency with similar parameters in CFM predictions. Model predictions also are in good agreement with multi-angle 1.4 GHz vertically and horizontally polarized brightness temperature measured by the Soil Moisture and Ocean Salinity (SMOS) satellite at Dome C, Antarctica. This work shows that co-located active and passive microwave measurements can be used to infer polar firn properties that can be compared with predictions of the CFM. In particular, 0.5–2 GHz brightness temperature measurements are shown to be sensitive to long-scale firn density fluctuations with density standard deviations in the range of 0.01–0.06 gcm-3 and vertical correlation lengths of 6–20 cm. [ABSTRACT FROM AUTHOR]

An airborne microwave wide-band radiometer (500–2000 MHz) was operated for the first time in Antarctica to better understand the emission properties of sea ice, outlet glaciers and the interior ice sheet from Terra Nova Bay to Dome C. The different glaciological regimes were revealed to exhibit unique spectral signatures in this portion of the microwave spectrum. Generally, the brightness temperatures over a vertically homogeneous ice sheet are warmest at the lowest frequencies, consistent with models that predict that those channels sensed the deeper, warmer parts of the ice sheet. Vertical heterogeneities in the ice property profiles can alter this basic interpretation of the signal. Spectra along the lengths of outlet glaciers were modulated by the deposition and erosion of snow, driven by strong katabatic winds. Similar to previous experiments in Greenland, the brightness temperatures across the frequency band were low in crevasse areas. Variations in brightness temperature were consistent with spatial changes in sea ice type identified in satellite imagery and in situ ground-penetrating radar data. The results contribute to a better understanding of the utility of microwave wide-band radiometry for cryospheric studies and also advance knowledge of the important physics underlying existing L-band radiometers operating in space. [ABSTRACT FROM AUTHOR]

This study investigates the use of adaptive radar waveforms in performing a multi‐task operation involving the tracking and classification of a single target. The work applies a previously reported hierarchical fully adaptive radar framework and considers a situation in which the target tracking function is performed using a transmit waveform having adaptive pulse repetition frequency, pulse width, bandwidth, and coherent processing interval parameters, while the classification function can be performed using only a fixed radar waveform. Two alternate strategies for selecting the next waveform are then described. The first strategy is focussed on maintaining fixed measurement performance goals in terms of target range and velocity and classification entropy, while the second approach varies these performance goals depending on the target state. Both approaches are examined for simulated datasets at W‐band representing a moving human target, as well as for laboratory measurements of this scenario. The results for both simulation and experiment show the benefits of including adaptive waveforms in performing multiple radar tasks. [ABSTRACT FROM AUTHOR]

An analysis of the performance of a cross-frequency detection algorithm for pulsed sinusoidal radio frequency interference (RFI) is performed. The performance obtained is compared with that of pulse and kurtosis detection methods that have been previously reported. The results of the study show that the cross-frequency algorithm provides good performance in detecting pulsed sinusoidal RFI at high duty cycles, including the case of continuous sinusoidal interference. The use of the cross-frequency algorithm requires choice of a detection threshold that in practice can be estimated using measured data. The effect of this threshold estimation on the detector performance is also examined. [ABSTRACT FROM AUTHOR]

The performance of the Shapiro-Wilk (S-W) test of normality for the detection of pulsed sinusoidal radio frequency interference (RFI) in microwave radiometry is analyzed. The study is motivated by the fact that the S-W test has been shown in the statistical literature to be effective in detecting a wide variety of non-Gaussian signal types. The basic properties of the S-W test statistic are reviewed, and the implementation of the test in digital hardware is discussed. Because the properties of the test statistic are difficult to obtain analytically, Monte Carlo simulations are utilized to compute performance. Results show that the test can provide reasonable performance in detecting pulsed sinusoidal RFI and that quantization of data has only a minimal impact on the sensitivity achieved. Detection performance is also compared with that of the kurtosis test for normality. It is shown that the S-W test produces comparable but degraded sensitivity compared to that of the kurtosis test in most cases while avoiding the "blind spot" associated with the kurtosis test for pulsed interferers having 50% duty cycle. Test performance is also shown to be improved if a priori knowledge of expected RFI pulse lengths is incorporated. [ABSTRACT FROM AUTHOR]

The Ultra-Wideband Software Defined Microwave Radiometer (UWBRAD) is a wideband radiometer operating from 0.5 to 2 GHz for remote sensing of polar ice sheet temperature profiles. Small-scale (cm to m) fluctuations in firn density in the upper portion of the ice sheet significantly impact observed brightness temperatures. Previously, a fully coherent model based on solving Maxwell’s equations for thousands of layers throughout the entire ice sheet was developed. Density profiles in the model are described as the sum of a smooth average density profile with a spatially correlated random process that represents density fluctuations. In this article, we develop a “partially coherent” implementation of the coherent model that captures the impact of variations in ice density on predicted brightness temperatures while improving computational efficiency. The partially coherent model divides the ice sheet into blocks. Within each block, the coherent model is applied to take into account coherence among the contributions of closely spaced layers. A Monte Carlo procedure is used to calculate the average block reflection and transmission parameters. Between adjacent blocks, interactions are assumed to be incoherent, and the radiative transfer theory is used to incoherently cascade block parameters. Results of the partially coherent model are in good agreement with the fully coherent model and also with Soil Moisture Ocean Salinity (SMOS) and UWBRAD brightness temperature observations. [ABSTRACT FROM AUTHOR]

Electromagnetic scattering and emission from 1-D rough surfaces with multiple elevations are studied using full-wave simulations. Both the root-mean-square (rms) heights and the surface length are large compared to the wavelength. A novel multilevel steepest decent-sparse matrix canonical grid (MLSD-SMCG) method is proposed to address limitations in the original SMCG. The uniform Nystrom method and neighborhood impedance boundary condition (NIBC) are also incorporated in solving the dual surface integral equations (SIEs) of the method of moments (MoM). Simulation results are illustrated at L-band for soil and ocean surfaces. The surface rms heights and lengths are up to 1.43 and 243.8 m corresponding to 6 and 1024 wavelengths at 1.26 GHz, respectively. For ocean surfaces, the wind speeds up to 20 m/s are considered, and the entire spectrum is included to capture all relevant surface length scales. Numerical results indicate the proposed approach is computationally efficient and accurate. Energy conservation checks in simulations are at 10−4 for ocean scattering and emission. Also, the effects of wind-driven roughness on ocean emissivity are further investigated using the proposed approach in terms of wind speed and observation angle for both polarizations. [ABSTRACT FROM AUTHOR]

Enhanced-resolution L-band brightness temperature (TB) image time series generated from observations collected over the Greenland Ice Sheet by NASA's Soil Moisture Active Passive (SMAP) satellite are used to map Greenland's perennial firn aquifers from space. Exponentially decreasing L-band TB signatures are correlated with perennial firn aquifer areas identified via the Center for Remote Sensing of Ice Sheets (CReSIS) Multi-Channel Coherent Radar Depth Sounder (MCoRDS) that was flown by NASA's Operation IceBridge (OIB) campaign. An empirical algorithm to map extent is developed by fitting these signatures to a set of sigmoidal curves. During the spring of 2016, perennial firn aquifer areas are found to extend over ∼66 000 km 2. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

This paper investigates the performance of multiple approaches, including maximum likelihood estimation (MLE), for determining the Doppler frequency of radar returns from clutter scatterers. Fields backscattered from clutter are modeled as a complex stationary random process with a specified temporal correlation function received in the presence of additive thermal noise at a specified clutter-to-noise ratio. The MLE implementation is formulated, and its results are then compared through a simulation study to those obtained from traditional pulse-pair processing and other fast Fourier transform based methods in terms of error statistics and computational complexity. The methods are also compared for measurements of sea clutter from an X-band radar system. The results of the study show that the MLE approach has modest advantages over other methods in certain conditions, but that the performance gains obtained may often be insufficient to justify the extra computational cost or a-priori knowledge requirements of the method. [ABSTRACT FROM AUTHOR]

The demand for microwave spectrum for commercial and industrial use has been increasing rapidly over the last decade, putting stress on the limited spectral resources for passive microwave remote sensing. Radio frequency interference from man-made sources is expected to become worse over the coming years. At 1.4 GHz, the SMAP mission has implemented and demonstrated advanced interference detection algorithms for its microwave radiometer. This scheme will not be feasible at higher microwave frequencies (above 6 GHz) due to much larger radiometer bandwidths used and the limited downlink data volume available to implement RFI filtering algorithms in the ground processing. In this paper, we present the design, development, and test of an advanced on-board interference detection and RFI filtering digital back-end that is capable of operation for a 1 GHz-radiometer bandwidth. We describe the combined RFI detection algorithms implemented in the digital backend’s firmware and the on-board RFI filtering of interference-corrupted data that will be necessary to limit downlink rate requirements for future high-frequency microwave missions. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

This paper evaluates the retrieval of soil moisture in the top 5-cm layer at 3-km spatial resolution using L-band dual-copolarized Soil Moisture Active-Passive (SMAP) synthetic aperture radar (SAR) data that mapped the globe every three days from mid-April to early July, 2015. Surface soil moisture retrievals using radar observations have been challenging in the past due to complicating factors of surface roughness and vegetation scattering. Here, physically based forward models of radar scattering for individual vegetation types are inverted using a time-series approach to retrieve soil moisture while correcting for the effects of static roughness and dynamic vegetation. Compared with the past studies in homogeneous field scales, this paper performs a stringent test with the satellite data in the presence of terrain slope, subpixel heterogeneity, and vegetation growth. The retrieval process also addresses any deficiencies in the forward model by removing any time-averaged bias between model and observations and by adjusting the strength of vegetation contributions. The retrievals are assessed at 14 core validation sites representing a wide range of global soil and vegetation conditions over grass, pasture, shrub, woody savanna, corn, wheat, and soybean fields. The predictions of the forward models used agree with SMAP measurements to within 0.5 dB unbiased-root-mean-square error (ubRMSE) and −0.05 dB (bias) for both copolarizations. Soil moisture retrievals have an accuracy of 0.052 m3/m3 ubRMSE, −0.015 m3/m3 bias, and a correlation of 0.50, compared to in situ measurements, thus meeting the accuracy target of 0.06 m3/m3 ubRMSE. The successful retrieval demonstrates the feasibility of a physically based time series retrieval with L-band SAR data for characterizing soil moisture over diverse conditions of soil moisture, surface roughness, and vegetation. [ABSTRACT FROM PUBLISHER]

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. [ABSTRACT FROM AUTHOR]

A dual-copolarization algorithm to classify inland open water bodies free of flooded vegetation using an L-band radar is presented and evaluated, with a view to applying the method to the Soil Moisture Active Passive (SMAP) mission for hydrological science and soil moisture retrieval applications. Past radar-based water body detection algorithms have applied a threshold to a single-polarization measurement, with water body detection declared if the observed cross section is less than the specified threshold. However, such methods are subject to ambiguities associated with scene variability and terrain slopes, making a universal threshold value difficult to derive and complicating the global application of such methods. Because SMAP will provide measurements in both HH and VV polarizations, the copolarization ratio is also available for water body detection. A threshold of −3 dB applied to the HH/VV polarization ratio is found effective in detecting water bodies at 40° incidence angle based on analysis of theoretical model predictions and measurements from airborne synthetic aperture radar and the spaceborne Aquarius scatterometer. When the water surface is calm and its radar response is very small (i.e., at the radar thermal noise level), the HH/VV ratio method fails. However, a combination of an HH/VV threshold (at −3 dB) and an HH threshold (at −25 dB) is shown to allow water body classification even in this situation. This proposed “combined” algorithm is assessed in four different geophysical scenarios. The resulting water body detection error is shown to be less than 10% for these cases, which satisfies SMAP requirements to allow accurate soil moisture retrieval, and the corresponding false alarm rate is smaller than 2%. The robustness of the proposed approach to subpixel heterogeneity has been also investigated. The performance of the algorithm remains sensitive to the noise level of the radar observations: for SMAP, a radar noise-equivalent sigma0 of −28.5 dB or less is required in order to facilitate acceptable performance. [ABSTRACT FROM AUTHOR]

Spatially diverse multiple-input multiple-output (MIMO) radar systems combine multistatic measurements of the target under view into a single detection algorithm and are thereby expected to alleviate the effects of fading on target radar cross sections (RCS) as the angle of observation is varied. Previous analytical studies of target detection for this case have shown that MIMO radar detection performance can exceed that of the corresponding phased array radar if both sufficient spatial diversity and signal-to-noise ratio (SNR) are achieved. These results have been based on a statistical model for the multistatic RCS of the target that is similar to the traditional Swerling models of the monostatic RCS. The degree to which these results are applicable to specific target geometries therefore remains uncertain. To address this issue, two studies of MIMO radar target detection incorporating realistic RCS properties for specific target geometries were performed. The first study utilized a numerical method to compute the multistatic RCS of a helicopter-like target observed at center frequency 200 MHz, while the second involved radar measurements of an unmanned aerial vehicle (UAV) target at 2.75 and 4.5 GHz. MIMO radar configurations having two transmitters and either three (for the radar measurements) or four (numerical simulations) receivers were used. In both cases, multistatic received fields were combined with regulated thermal noise levels in postprocessing to study target detection performance. Because in general the azimuthal orientation of a specific target with respect to the radar is uncertain, the detection performance results shown are averaged over the azimuthal orientation angle of the target. The average over target orientation can also be interpreted as similar to an average over ?trials? of a statistical target description, enabling comparisons of field properties averaged over target orientation with similar ensemble averages from the statistical models of the literature. Although detection performance curves for the specific targets considered are not identical to those predicted analytically by the statistical target model, results for these targets confirm that the MIMO radar system can achieve enhanced detection performance as compared with the corresponding phased array radar system. [ABSTRACT FROM AUTHOR]

A soil moisture retrieval algorithm is proposed that takes advantage of the simultaneous radar and radiometer measurements by the forthcoming NASA Soil Moisture Active Passive (SMAP) mission. The algorithm is designed to downscale SMAP L-band brightness temperature measurements at low resolution ( ~ 40 km) to 9-km brightness temperature by using SMAP's L-band synthetic aperture radar (SAR) backscatter measurements at high resolution (1-3 km) in order to estimate soil moisture at 9-km resolution. The SMAP L-band SAR and radiometer instruments are designed to provide coincident observations at constant incidence angle, but at different spatial resolutions, across a wide swath. The algorithm described here takes advantage of the correlation between temporal fluctuations of brightness temperature and backscatter observed when viewing targets simultaneously at the same angle. Surface characteristics that affect the brightness temperature and backscatter measurements influence the signals at different time scales. This feature is applied in an approach in which fine-scale spatial heterogeneity detected by SAR observations is applied on coarser-scale radiometer measurements to produce an intermediate-resolution disaggregated brightness temperature field. These brightness temperatures are then used with established radiometer-based algorithms to retrieve soil moisture at the intermediate resolution. The capability of the overall algorithm is demonstrated using data acquired by the airborne passive and active L-band system from field campaigns and also by simulated global dataset. Results indicate that the algorithm has the potential to retrieve soil moisture at 9-km resolution, with the accuracy required for SMAP, over regions having vegetation up to 5- kg/m2 vegetation water content. The results show a reduction in root mean square error of volumetric soil moisture (40% improvement in the statistics) from the minimum performance defined as the soil moisture retrieved using radiometer measurements re-sampled to the intermediate scale. [ABSTRACT FROM PUBLISHER]

Two algorithms used in microwave radiometry radio-frequency interference (RFI) detection and mitigation the pulse detection algorithm and the kurtosis detection algorithm. The relative performance of the algorithms is compared both analytically and empirically. Their probabilities of false alarm under RFI-free conditions and of detection when RFI is present are examined. The downlink data rate required to implement each algorithm in a spaceborne application is also considered. The kurtosis algorithm is compared to a pulse detection algorithm operating under optimal RFI detection conditions. The performance of algorithms is also analyzed as a function of varying characteristics of the RFI. The RFI detection probabilities of both algorithms under varying subsampling conditions are compared and validated using data obtained from a field campaign. Implementation details, resource usage, and postprocessing requirements are also addressed for both algorithms. [ABSTRACT FROM AUTHOR]

This study presents an assessment of a pre-operational soil moisture product at 1 km resolution derived from satellite data acquired by the European Radar Observatory Sentinel-1 (S-1), representing the first space component of the Copernicus program. The product consists of an estimate of surface soil volumetric water content Θ [ m 3/ m 3] and its uncertainty [ m 3/ m 3], both at 1 km. The retrieval algorithm relies on a time series based Short Term Change Detection (STCD) approach, taking advantage of the frequent revisit of the S-1 constellation that performs C-band Synthetic Aperture Radar (SAR) imaging. The performance of the S-1 Θ product is estimated through a direct comparison between 1068 S-1 Θ images against in situ Θ measurements acquired by 167 ground stations located in Europe, America and Australia, over 4 years between January 2015 and December 2020, depending on the site. The paper develops a method to estimate the spatial representativeness error (SRE) that arises from the mismatch between the S-1 Θ retrieved at 1 km resolution and the in situ point-scale Θ observations. The impact of SRE on standard validation metrics, i.e., root mean square error (RMSE), Pearson correlation (R) and linear regression, is quantified and experimentally assessed using S-1 and ground Θ data collected over a dense hydrologic network (4 − 5 stations / km 2) located in the Apulian Tavoliere (Southern Italy). Results show that for the dense hydrological network the RMSE and correlation are ~0.06 m 3/ m 3 and 0.71, respectively, whereas for the sparse hydrological networks, i.e., 1 station / km 2, the SRE increases the RMSE by ~0.02 m 3/ m 3 (70% Confidence Level). Globally, the S-1 Θ product is characterized by an intrinsic (i.e., with SRE removed) RMSE of ~0.07 m 3/ m 3 over the Θ range [0.03, 0.60] m 3/ m 3 and R of 0.54. A breakdown of the RMSE per dry, medium and wet Θ ranges is also derived and its implications for setting realistic requirements for SAR-based Θ retrieval are discussed together with recommendations for the density of in situ Θ observations. • A pre-operational 1 km soil moisture product (Θ) from S-1 is developed. • The co-registered Θ uncertainty layer at 1 km resolution is also provided. • The S-1 Θ product validation according to CEOS WGCV is illustrated. • The impact of the spatial representativeness error on metrics is quantified. • Requirements for validating high-resolution Θ products are identified. [ABSTRACT FROM AUTHOR]

Microwave radiometry has provided valuable spaceborne observations of Earth's geophysical properties for decades. The recent SMOS, Aquarius, and SMAP satellites have demonstrated the value of measurements at 1400 MHz for observing surface soil moisture, sea surface salinity, sea ice thickness, soil freeze/thaw state, and other geophysical variables. However, the information obtained is limited by penetration through the subsurface at 1400 MHz and by a reduced sensitivity to surface salinity in cold or wind-roughened waters. Recent airborne experiments have shown the potential of brightness temperature measurements from 500-1400 MHz to address these limitations by enabling sensing of soil moisture and sea ice thickness to greater depths, sensing of temperature deep within ice sheets, improved sensing of sea salinity in cold waters, and enhanced sensitivity to soil moisture under vegetation canopies. However, the absence of significant spectrum reserved for passive microwave measurements in the 500-1400 MHz band requires both an opportunistic sensing strategy and systems for reducing the impact of radio-frequency interference. Here, we summarize the potential advantages and applications of 500-1400 MHz microwave radiometry for Earth observation and review recent experiments and demonstrations of these concepts. We also describe the remaining questions and challenges to be addressed in advancing to future spaceborne operation of this technology along with recommendations for future research activities.

This article describes progress relating to a previously reported matched filter retrieval approach for the estimation of hurricane maximum winds using delay Doppler map (DDM) measurements of the Cyclone Global Navigation Satellite System (CYGNSS) mission. The retrievals presented are based on comparisons of these measured DDMs, and their simulated counterparts as a set of storm parameters are varied. The analysis presented examines the dependencies of retrieval performance on the synthetic storm model used as part of the forward modeling process using a set of CYGNSS storm-observing full DDM downlinks containing 68 tracks and spanning 18 storms over the period 2017-2020. Based on the combined use of multiple parametric storm models, retrieved hurricane maximum wind speed estimates showed correlations of 92%, root-mean-square error (RMSE) of 6.05 m/s, unbiased RMSE of 6.05 m/s, mean difference of 4.83 m/s, and a bias of 0.09 m/s relative to reference data. Mean retrieval error relative to storm maximum wind is 11.11%. The dependence of retrieval error on measurement maximum delay extent is also analyzed using CYGNSS Raw I/F downlinks, from which a significant near-monotonic decrease in retrieval errors is observed as the delay extent of the measurement is increased. The analysis presented in this work highlights the potential for using matched filter retrieval methodologies for cyclone wind speed estimation in spaceborne Global Navigation Satellite Systems Reflectometry systems.

A theoretical investigation of energy conservation, reflectivity, and emissivity in the scattering of electromagnetic waves from 3D multilayer media with random rough interfaces using the second-order small perturbation method (SPM2) is presented. The approach is based on the extinction theorem and develops integral equations for surface fields in the spectral domain. Using the SPM2, we calculate the scattered and transmitted coherent fields and incoherent fields. Reflected and transmitted powers are then found in the form of 2D integrations over wavenumber in the spectral domain. In the integrand, there is a summation over the spectral densities of each of the rough interfaces with each weighted by a corresponding kernel function. We show in this paper that there exists a "strong" condition of energy conservation in that the kernel functions multiplying the spectral density of each interface obey energy conservation exactly. This means that energy is conserved independent of the roughness spectral densities of the rough surfaces. Results of this strong condition are illustrated numerically for up to 50 rough interfaces without requiring specification of surface roughness properties. Two examples are illustrated. One is a multilayer configuration having weak contrasts between adjacent layers, random layer thicknesses, and randomly generated permittivity profiles. The second example is a photonic crystal of periodically alternating permittivities of larger dielectric contrast. The methodology is applied to study the effect of roughness on the brightness temperatures of the Antarctic ice sheet, which is characterized by layers of ice with permittivity fluctuations in addition to random rough interfaces. The results show that the influence of roughness can significantly increase horizontally polarized thermal emission while leaving vertically polarized emissions relatively unaffected.