The EZIE mission is a first of its kind to measure the temporal and spatial characteristics of Earth’s ionospheric auroral electrojet currents remotely using a mm-wave radiometer called the Microwave Electrojet Magnetogram (MEM). EZIE measures the 118 GHz oxygen emission line that splits in frequency in the presence of a magnetic field. This effect is known as the Zeeman effect. From these measurements of the 50 km spatial resolution magnetic fields at 80 km altitude the ionospheric currents that caused them can be calculated. The EZIE mission consists of three MEM payloads on three spacecrafts, each MEM contains four polarimetric radiometer receivers with a polyphase filter bank spectrometer. MEM can indirectly measure magnetic field strength and direction. In this paper we present the unique calibration design of the MEM payload that does not include any internal or external calibration sources. We discuss the MEM payload and present results from pre-launch testing and calibration of the MEM system.

The Global Environment Monitoring system is a planned constellation of passive microwave instruments on a CubeSat platform, with the goal of providing high resolution and low-latency global weather observations. GEMS1 was a pathfinder 3U CubeSat mission with a single-band, cross-track scanning passive microwave radiometer, operating around the 118.75 GHz O2 resonance band. During the mission, a number of issues arose in the attitude determination system, resulting in occasional losses of attitude control during acquisitions and significant error in the estimated satellite orientation. Here we present a series of processing steps to determine satellite orientation from data acquired by the radiometer, by analysis of observed limb positions and comparison with radiative transfer modelling. The results of the corrections show significant improvements in geolocation, as evidenced by good co-registration with coastlines and land surface features, enabling further analysis of the GEMS1 archive.

The Lobe Differencing Correlation Radiometer (LDCR) on a small uncrewed aerial system (sUAS) is developed to map high spatial resolution soil moisture, and its performance had been validated during tens of successful fight sorties. A new calibration method is developed that gain and phase imbalances between the two receiver paths are determined and compensated, and a new calibration source is being built to provide a stable reference temperature for in-flight calibration. The LDCR was integrated into two sUAS platforms, one is fixed wing and the other one is multirotor. Flight altitude from a few meters to hundreds of meters can be achieved using these two sUAS platforms to fulfill various spatial resolution requirements. The soil moisture mapping algorithm had been further developed and the soil salinity and slope angle will be included and compensated in the retrieval algorithm.

Information on snow depth on sea ice and bulk sea ice density is required to convert CryoSat-2 radar freeboard (hf) into sea ice thickness (SIT). It is difficult to obtain their information on an Arctic basin scale; therefore, most CryoSat-2 SIT products largely rely on the distributions of snow depth and bulk sea ice density derived from parameterizations, which are based on sea ice type and climatological values. Several observational studies have found that the distributions of parameterized variables are inaccurate compared to the actual distributions. This study aims to develop a new type of retrieval algorithm for snow depth, SIT and bulk density, and ice freeboard in the Arctic winter by synergizing active CryoSat-2 with passive microwave and infrared measurements. Two parameterizations for the snow-ice thickness ratio and bulk sea ice density were combined with the hydrostatic balance and radar wave speed correction equations. Consequently, solutions for the four target variables were obtained and applied to different CryoSat-2hf, derived from empirical and waveform-fitting retracker algorithms. The retrieved thickness-related parameters based onhffrom the lognormal waveform-fitting retracker algorithm showed good agreement with the airborne snow depth, total freeboard, and mooring ice draft measurements. The retrieved multiyear sea ice bulk density was significantly higher than the value of 882 kg m-3, which was used in the previous density parameterization, showing a higher agreement with values from in-situ measurements. The spatial and interannual variabilities of SIT increased when the results from this study were compared with those based on previous parameterizations.

The inversion of satellite-based passive and active atmospheric measurements from radiometer and radiometers requires accommodation of highly nonlinear, non-deterministic, and even uncertain and evolving relationships between the satellite data and parameters of interest. In addition, the limitations in vertical, horizontal, and temporal resolution further confound our use of satellite data. Focusing on the estimation of cloud and precipitation parameters such as surface rain rate, integrated liquid and ice water content, phase distribution, we can trace a number of current developments back to the initial research of Dr. Gail Skofronick-Jackson in the early 1990s. As a NASA Gradute Student Fellow, Dr. Skofronick-Jackson recognized the key problems of nonlinearity, statistical non-determinism, and wavelength-dependent spatial resolution limitations in her development of performance simulations of the NASA proposed NASA Mutiband Imaging Microwave Radiometer (MIMR) instrument [Skofronick-Jackson, 1995]. This proposed six-band passive instrument using a 2-meter antenna provide a range of precipitation sensitive spatial resolutions over the bands of 6, 10, 18 23, 37, and 89 GHz along with mixed channel sensitivities to liquid water path and integrated ice content. In order to accommodate these effects she a nonlinear, multispectral, statistical extension of the CLEAN algorithm used in radio astronomy was developed and tested [Skofronick-Jackson and Gasiewski, 2000]. This iterative algorithm, termed NMS-CLEAN, showed improvements over simple linear methods and became the basis for further simulations exploring for the first time the application of simple two-layer single-perceptron artificial neural networks (ANNs) both in radiometric and radar applications [Xiao and Chandrasekar, 1997]. Perhaps unsurprising by our current understanding of them these ANNs improved upon the retrieval accuracy attainable using even the NMS-CLEAN algorithm within the range of training data available. These developments using MIMR instrument specifications supported the precipitation science essential to the eventual development and launch of AMSR-E, which operated from 2002 to 2017 [e.g., Surussavadee and Staelin, 2008].

A two-scale ocean surface emissivity model tuned to WindSat and Special Sensor Microwave/Imager (SSM/I) polarimetric brightness temperatures for general passive microwave applications is detailed. The model provides a full Stokes vector emissivity calculation at arbitrary microwave frequencies and observation angles for wind speeds of up to 15 m/s. During model development, it was found that the untuned two-scale model generally produced plausible azimuthal behavior in the ocean surface emissivity vector; however, large discrepancies between the untuned model and WindSat and SSM/I observations were observed, in particular for the zeroth-azimuthal-harmonic coefficients. These discrepancies can be ascribed to inaccuracies in contemporary ocean foam coverage and emissivity models. Accordingly, foam influences were treated using machine-tunable correction parameters incorporated as a means of improving and extending the physically based two-scale model. In addition, a hydrodynamic modulation function and the lower cutoff wavenumber for small-scale perturbation integration were treated as empirically tunable. Model tuning was performed by minimizing the$\chi ^{2}$metric over all available wind bins, channel frequencies, polarizations, and azimuthal harmonics. The result is an approximately eightfold reduction in$\chi ^{2}$from its initial untuned model value, indicating that machine tuning can considerably reduce model errors inherent in the two-scale model to levels acceptable for oceanic passive microwave remote sensing applications. The tuned model is independently validated against NASA Global Precipitation Measurement Microwave Instrument (GMI) measurements. The tuned model and GMI observed emissivities, when scaled to the surface temperature, are in agreement to within ±0.3 K root-mean-square (rms) error, thus suggesting good applicability of the model over a wide range of microwave frequencies and wind speeds.

In this study, a method for estimating two-scale roughness influences on the ocean surface emissivity is developed by solving a simplified two-scale ocean emissivity model equation. In this model, scatterings by small-scale roughness are described by the Kirchhoff approximation. For large-scale roughness, the mean local incidence angle (LIA) is introduced to describe slanted surface slope deviation from flat surface. This study focuses on the ocean state under low/moderate wind conditions in order to preclude foam and anisotropic influences within the model. Consequently, a unique pair of two-scale roughness parameters are estimated from the equation using observed ocean emissivities from AMSR2-measured radiances. The results show that the estimated small-scale roughness at 6.925 and 10.65 GHz is linearly correlated with the 10-m height wind speed$U_{10}$. As the frequency reaches 36.5 GHz, however, the scatters between small-scale roughness and$U_{10}$are increased, which suggests that the Kirchhoff bistatic scattering function is not fully suitable to describe the small-scale roughness at this frequency. The linear relationships between mean LIA and$U_{10}$are found with high correlation coefficients. In addition, the estimated mean LIA corresponds well with associated roughness calculated from both observed and modeled ocean wave height spectra. This evidence demonstrates that the proposed large-scale roughness parameterization is physically meaningful and, therefore, the mean LIA has a physical basis in large-scale roughness. In addition, the strong correlations between the roughness parameters and$U_{10}$demonstrate the possibility to estimate$U_{10}$from the AMSR2 data using intermediate parameters that are physically based on ocean surface characteristics.

An endfire synthetic aperture radar (SAR) for use on a cylindrical ice-penetrating cryobot is presented. The SAR facilitates obstacle detection and mapping inside ice for subsurface exploration using such a cryobot vehicle. The SAR is comprised of four azimuthally arranged directional log periodic antenna elements flush-mounted onto the cryobot’s surface. Aperture synthesis is facilitated by the downward trajectory of the cryobot as it slowly melts through ice. The radar front end and back end are designed using commercial-off-the-shelf (COTS) components and a customized field-programmable gate array (FPGA)-based digital design for signal generation, reception, and processing. Theoretical analysis of the SAR geometry is presented for the case of a point target in which the maximum likelihood estimation (MLE) approach is used for position estimator development. The novelty of this system lies in the use of pairs of antennas, with fixed baselines between them, to implement multiple coherent monostatic SARs to estimate target position in three dimensions. Specifically, range estimation is implemented by conventional chirp processing, polar (or elevation) angle estimation is achieved by SAR processing, and azimuth angle estimation is facilitated using pairs of four azimuthally arranged antennas that can be analyzed as multiple fixed baseline interferometric radars. Radar signal coherency tests and experimental validation of point target estimation and spatial resolution performed in a laboratory environment using the endfire SAR are presented in this study.

A persistent challenge in the measurement of soil moisture from satellites stems from the inherently low spatial resolution using active or passive system. The lobe differencing correlation radiometer (LDCR) on a small unmanned aerial system (sUAS) is shown to provide a capability to measure soil moisture at high spatial resolution for a range of scientific and operational purposes. Flight tests of LDCR on a fixed wing sUAS were performed at the Canton, Oklahoma Soilscape site in September 2015, and Irrigation Research Foundation (IRF) in Yuma, Colorado, in June 2016. The LDCR design and performance are discussed, and the calibration using both preflight lab test data and in-flight data over a calm pond was performed to calibrate the radiometer. Radio frequency interference (RFI) from the sUAS platform was observed and mitigated. The LDCR sampling processes are detailed and an implementation of the τ-ω vegetation correction model along with a semiempirical surface roughness correction model incorporating a full-domain soil moisture mapping algorithm is presented. The algorithm uses a weakly nonlinear observation operator suitable for irregular sUAS flight trajectories that maps volumetric soil moisture (VSM) on a user-defined product grid from the sUAS sampling grid. Using LDCR radiometric and thermal measurements, along with Landsat-based vegetation water content (VWC) and soil texture information, soil moisture was mapped at decameter spatial resolution. The retrieved VSM data are favorably compared with in situ VSM measurements and irrigation records. A method for determining LDCR VSM estimation errors is developed to quantify the mapping algorithm accuracy and assess the impact of error sources.

Retrievals of sea ice thickness from passive microwave measurements have been limited to thin ice because microwaves penetrate at most the upper 50 cm of sea ice. To overcome such a limitation, a method of retrieving Arctic basin-scale ice thickness is developed. The physical background of this method is that the scattering optical thickness at microwave frequencies within the freeboard layer is linearly proportional to the physical thickness of the ice freeboard. In this study, we relate the optical thickness estimated from the Advanced Microwave Scanning Radiometer 2 (AMSR2) with ice freeboard estimated from the CryoSat-2 (CS2) by employing a piecewise linear fit. The results show a strong linear relationship between the AMSR2-estimated and CS2-measured ice freeboards with a correlation coefficient of 0.85 and bias and RMSE of 0.0001 and 0.04 m, respectively; this evidence suggests that the method can provide Arctic basin-scale ice freeboard with a comparable accuracy level of CS2. The method is also applied to estimate ice freeboard for the periods of the Scanning Multichannel Microwave Radiometer (SMMR) (1978-1987) and AMSR-E (2002-2011). It is shown that the area-averaged ice freeboard has decreased significantly with the linear trends of 1.5 cm/decade. In addition, there seems to be a change of ice freeboard distributions over the Arctic. Furthermore, the algorithm is extended to the ice thickness retrieval by using the hydrostatic balance equation, showing that operational basin-scale ice thickness retrieval will be possible from satellite passive microwave measurements if a realistic snow depth on sea ice is employed.

A full-Stokes vector model for microwave ocean surface emissivity based on two-scale theory and incorporating a wide range of published results is being developed for broadband microwave satellite data assimilation. The model is based on the six different modules such as ocean surface permittivity, Fresnel emission, omnidirectional wave height spectrum, small-scale perturbation, large-scale correction, and foam effect modules. The results showed that the calculated Full-stokes emissivities range in theoretically expected values and logically understandable variation with respect to incidence and azimuth angle. This model will be used for understanding of the emissivity uncertainties due to inputs of permittivity, ocean height distribution, and foam influences and for assimilation of fully-polarimetric satellite microwave radiances.

Long term direct thermal measurement of the earth's middle and lower tropospheric temperature on a global basis along with the determination of a diurnal temperature climatology is needed to 1) correct historic satellite mid-tropospheric temperature data, 2) estimate the impact of atmospheric greenhouse warming in response to anthropogenic CO2 emissions, 3) inter-calibrate the international fleet of weather satellites, and 4) monitor naturally occurring atmospheric temperature trends. Quantifying anticipated temperature trends on a timely basis requires the globally averaged mid-tropospheric temperature to be observed with a satellite temperature sounding instrument of very high stability and traceability. Stable on-orbit reference instruments are needed to also prevent instrumental drift or deterioration from obscuring trends occurring over several decades. With increased anticipated anthropogenic emission resulting from the imminent deployment of 5G communications electronics and related consumer and defense applications at V-band, radio frequency interference (RFI) detection and mitigation also becomes indispensable for accurate temperature retrievals. A high spectral resolution digital correlating spectrometer at V-band with extremely stable down conversion to precisely characterize spectral variations within a sounding channel and perform real-time RFI detection and mitigation is thus critically needed for climate monitoring. The design, build, and simulation of such an instrument, the V-Band Ultrastable Climate Monitoring Radiometer (VU-CliMMR), being developed at the University of Colorado (CU) Center for Environmental Technology (CET), is discussed.

A horizontally inhomogeneous unified microwave radiative transfer (HI-UMRT) model is presented to study the 3-D effects of the horizontal inhomogeneous clouds on the computed microwave radiances and facilitate satellite radiance assimilation over the horizontally inhomogeneous all-weather conditions. HI-UMRT provides a coupled two-Stokes parameter numerical radiance solution of the 3-D radiative transfer (RT) equation by embedding the existing 1-D UMRT algorithm into an iterative perturbation scheme. The horizontal derivatives in the radiances of the lower perturbation order are treated as the source functions of the azimuthal harmonic perturbation RT equations that are readily solved using the planar-stratified 1-D UMRT algorithm. The horizontal radiance derivative is estimated by central differencing. A perturbation source-function analysis shows that the increase in computing time for the 3-D HI-UMRT model relative to the 1-D UMRT model is moderate, since: 1) the computationally efficient UMRT engine is applied only to the perturbation equations with nontrivial solutions and 2) the layer parameters for the 1-D solution are reused for all higher perturbation orders. Numerical simulations using HI-UMRT based on 3-D cloud profiles simulated by the Weather Research and Forecasting numerical weather model illustrate the convergence of the iterative perturbation series. An intercomparison of the top-of-atmosphere brightness temperature images for HI-UMRT versus the change planar-stratifiedslant path UMRT model illustrates the considerable impact of cloud horizontal inhomogeneities on the computed upwelling microwave radiances.

In January 2019 a Project Authorization Request was submitted to the IEEE standards association with the title "Standard for Calibration of Microwave Radiometers in the 300 MHz to 1 THz Frequency Range for Geoscience Applications". An open committee is being assembled to draft this standard with the purpose of unifying and documenting calibration procedures for a wide range of microwave radiometers. The committee includes members, collaborators, and contributors from academia, international government and private industry. We include ground-based, air-borne, and space-borne systems. The standard will also define standardized terminology, and address procedures required to obtain traceability to fundamental units or constants. The scope of the standard encompasses various radiometer geometries, Dicke switching, total power, and differential, as well as different polarization configurations including fully polarized (full Stoke's) radiometers. The standard will also separately address free-space and single-mode (e.g. transmission-line) radiometer calibration techniques.

This paper presents submillimeter wave (SMMW) propagation and meteorological measurements obtained using the TAIPAS system operated continuously over a period from August 15 to August 30, 2018. The TAIPAS system is a 320-340 GHz, coherent, line-of-sight transmissometer which can be used to measure propagated power and spectral properties of directional electromagnetic (EM) waves at SMMW frequencies at and around the 325.153 GHz water vapor absorption line.The overall goal of the TAIPAS project is to develop a comprehensive predictive model relevant for atmospheric propagation in the range of ~1 MHz - 3000 GHz.

The Lobe Differencing Correlating Radiometer (LDCR) developed at Center for Environmental Technology (CET) at CU, Boulder is a lightweight payload for small unmanned aerial systems (sUAS) enabling remote soil moisture measurement for precision agriculture applications. The second revision of the payload (LDCR Rev B) includes a digital correlation detector for which the data processing flow, instrument calibration, and test data analysis is presented. Cross frequency peak detection, time and frequency domain kurtosis, and complex coherence phase were used to characterize radio frequency interference (RFI) in the high spectral resolution radiometric data. A quiescent state performance analysis using matched loads and antennas revealing RFI generated from the radiometer high speed data acquisition system, and the sUAS communication system is discussed.

A numerical simulator for analysis of the geostationary orbit multispectral passive microwave (Geo-MW) mapping and sounding is described, which mainly includes upwelling brightness temperatures forward, microwave radiometer payload simulation and atmospheric profile retrieval. This simulator allows evaluation and optimization of the ability of microwave sensors to retrieve atmospheric temperature and humidity profile. In this paper, end to end simulation study of a Geo-MW radiometer observation at selected frequencies from 50 to 425 GHz with a real-aperture antenna is performed and the accuracy of the brightness temperature measurement and the atmospheric temperature and humidity profile sounding are quantitatively analyzed and evaluated.

Soil moisture is of fundamental importance to many hydrological, biological and biogeochemical processes, plays an important role in the development and evolution of convective weather and precipitation, and impacts precision agriculture, water resource management, and flood runoff prediction. The launch of NASA's Soil Moisture Active/Passive (SMAP) mission in 2015 provide new passive global measurements of soil moisture and surface freeze/thaw state at fixed crossing times and spatial resolutions of 36 km. There exists a need for measurements of soil moisture on much smaller spatial scales and arbitrary diurnal times for SMAP validation, precision agriculture, flood runoff prediction, evaporation and transpiration studies of boundary layer heat transport, and tundra thaw studies. The Lobe Differencing Correlation Radiometer (LDCR) provides a means of mapping soil moisture on spatial scales as small as several meters (i.e., the height of the platform). Compared with various other proposed methods of validation based on either in situ measurements or existing airborne sensors suitable for manned aircraft deployment, the integrated design of the LDCR on a lightweight small unmanned aerial system (sUAS) can provide sub-watershed (~km scale) coverage at very high spatial resolution (~15 m) suitable for scaling scale studies. The Tempest sUAS, flies at very low operator cost compared to manned aircraft. To demonstrate the LDCR Rev A and Rev B, several flights had been performed during field experiments at the Canton Oklahoma Soilscape site on September 8th and 9th, 2015 and Yuma Colorado Irrigation Research Foundation (IRF) site from June to August 2016, and October 2017. The LDCR antenna temperature and soil moisture maps will be presented, and scientific intercomparisons between LDCR soil moisture data and in-situ measurements will be presented.

The low cost PolarCube 3U CubeSat supports a 118.75 GHz imaging spectrometer for temperature profiling of the troposphere and surface temperature. It is a demonstrator for a constellation of LEO passive microwave imaging and sounding satellites at V and G bands using 3U/6U CubeSats. Such a constellation of ~40 satellites for weather forecasting will provide data at high spatial and temporal resolution to observe rapidly evolving mesoscale weather. The satellite payload is an eight channel, double sideband passive microwave temperature sounder with cross-track scanning and will provide 17.3 km surface resolution from a 450 km orbit. It's antenna system consists of a gold-plated offset paraboloidal reflector scanning at 1 Hz and a 3D printed corrugated feed with a 17.28° waveguide transition. This paper provides an overview of the radiometer including procedures used to determine optimum feed horn/reflector dimensions, phase center and antenna efficiencies. A brief description of the design and functionality of the eight channel intermediate frequency module is also provided. Initial performance results obtained from airborne measurements over Antarctica on the NASA DC-8 in November 2016 indicate a well-functioning radiometer and scanning antenna subsystem. The measured radiometer sensitivity varies from 1.3 to 2.6 K across the eight channels for an integration time of 4.096 ms. Gain stability of the various channels with ambient temperature variations were also measured.

A horizontally inhomogeneous unified microwave radiative transfer (HI-UMRT) model is being developed at the University of Colorado at Boulder to provide 3-dimensional (3-D) analytic forward radiative transfer solutions for 3-D inhomogeneous clouds in severe weather. The HI-UMRT model decomposes the 3-D differential RT equation into a series of azimuthal harmonics and iterative perturbation equations which are readily solved by the existing planar-stratified 1-D UMRT engine. The HI-UMRT solution inherits the properties of unconditional numerical stability, efficiency, and accuracy from the UMRT algorithm not only for spherical hydrometeors but for aspherical cloud ice particles based on the NASA/GSFC DDSCAT database. The HI-UMRT numerical results were produced and compared with 1-D UMRT simulations to evaluate the effects of cloud horizontal inhomogeneities on brightness temperature measurements.

The passive microwave observations from geostationary earth orbit (GEO) are able to enhance the short-time forecasting of tropical cyclones (TCs) due to its ability to track and detect the internal structure of TCs. To assess the operational capabilities of the candidate GEO microwave instruments, the numerical simulations of GEO microwave observation for the three TC cases were carried out. This paper compares the abilities of 3 candidate passive microwave sensors, based on GEM/GOMAS, GeoSTAR and GIMS-II respectively, to observe the upwelling brightness temperatures of TCs at 50-57GHz band. The analysis is based on WRF model variables and radiative transfer mode DOTLRT.

Soil moisture is of fundamental importance to many hydrological, biological and biogeochemical processes, plays an important role in the development and evolution of convective weather and precipitation, and impacts precision agriculture, water resource management, and flood runoff prediction. The launch of NASA's Soil Moisture Active/Passive (SMAP) mission in 2015 provide new passive global measurements of soil moisture and surface freeze/thaw state at fixed crossing times and spatial resolutions of 36 km. There exists a need for measurements of soil moisture on much smaller spatial scales and arbitrary diurnal times for SMAP validation, precision agriculture, flood runoff prediction, evaporation and transpiration studies of boundary layer heat transport, and tundra thaw studies. The Lobe Differencing Correlation Radiometer (LDCR) provides a means of mapping soil moisture on spatial scales as small as several meters (i.e., the height of the platform). Compared with various other proposed methods of validation based on either in situ measurements or existing airborne sensors suitable for manned aircraft deployment, the integrated design of the LDCR on a lightweight small unmanned aerial system (sUAS) is capable of providing sub-watershed (~km scale) coverage at very high spatial resolution (~15 m) suitable for scaling scale studies. The Tempest sUAS, flies at very low operator cost compared to manned aircraft. To demonstrate the LDCR several flights had been performed during field experiments at the Canton Oklahoma Soilscape site on September 8th and 9th, 2015 and Yuma Colorado Irrigation Research Foundation (IRF) site from June to August, 2016. The LDCR antenna temperature and soil moisture maps will be presented, and scientific intercomparisons between LDCR soil moisture data and in-situ measurements will be presented.

In this paper, we present a broker based scheme for spectrum sharing to address the ever increasing need for efficient spectrum utilization. We discuss a descriptor language by which to represent requests for spectrum usage. And, we outline a proof-of-concept demonstration of the broker operation on real hardware.

Design, analysis and pre-launch performance of the PolarCube 3U CubeSat 118.75 GHz radiometer payload is presented. Procedures used to determine optimum feed horn/reflector dimensions, phase center and antenna efficiencies based on a full wave Fourier analysis are outlined. A brief description of the design and functionality of the eight channel intermediate frequency board is also provided. Images obtained by the instrument during recent airborne tests over the Antarctic using an aluminium 3D printed corrugated feed indicate a well focused scanning reflector antenna system with high main beam efficiency and good separation between the radiometer channels.

In this paper a forward looking (end fire) synthetic aperture radar (SAR) system is described for the Very deep Autonomous Laser-powered Kilowatt-class Yo-yoing Robotic Ice explorer (VALKYRIE) project. Design and analysis of novel conformal log periodic antennas for the radar and the forward looking SAR ambuguity function is presented. Fabrication and laboratory characterization of the antennas system design and in situ testing of the SAR system are discussed in detail.

A horizontally inhomogeneous unified microwave radiative transfer (HI-UMRT) model based on nonspherical hydrometeor scattering is being developed at University of Colorado at Boulder to facilitate the forward radiative simulations of transmittivity and reflectivity over 3-dimensional inhomogeneous clouds in severe weather. The HI-UMRT model provides a 3-D radiative intensity solution by incorporating the planar-stratified UMRT algorithm with a horizontally inhomogeneous iterative perturbation method. The HI-UMRT solution could inherit the properties of computational stability, efficiency and accuracy from the UMRT algorithm as long as the symmetry of discretized phase matrix computed by discrete dipole approximation (DDA) could be identified for large nonspherical hydrometeors. In this study, the required symmetry of discretized phase matrix in the HI-UMRT model was explicitly defined and a new method of calculating the single-scattering full Stokes matrix based upon the DDSCAT software package was developed. A total of 60 snow/ice aggregates of 16 particle types and of particle sizes from 150 to 1,100 μm covering the full spectrum of DDSCAT database were selected for the study. The result showed that the required symmetry conditions are satisfied for all selected particles. It leads to a conclusion with strong confidence that coupled analytical RT solutions for the first two Stokes parameters with inherent matrix stability and high computational efficiency can be achieved in the HI-UMRT model.

Soil moisture is of fundamental importance to many hydrological, biological and biogeochemical processes, plays an important role in the development and evolution of convective weather and precipitation, and impacts water resource management, agriculture, and flood runoff prediction. The launch of NASA's Soil Moisture Active/Passive (SMAP) mission in 2015 promises to provide new passive global measurements of soil moisture and surface freeze/thaw state at fixed crossing times and spatial resolutions of ~30 km. With the failure of the SMAP radar there exists a need for measurements of soil moisture on much smaller spatial scales and arbitrary diurnal times for SMAP validation, precision agriculture, evaporation and transpiration studies of boundary layer heat transport, and tundra thaw studies. The Lobe Differencing Correlation Radiometer (LDCR) provides a means of mapping soil moisture on spatial scales as small as several meters (i.e., the height of the platform). Compared with various other proposed methods of validation based on either in situ measurements or existing airborne sensors suitable for manned aircraft deployment, the integrated design of the LDCR on a lightweight small unmanned aerial system (sUAS) is capable of providing sub-watershed (~km scale) coverage at very high spatial resolution (~15 m) suitable for scaling scale studies. This sUAS, the Tempest, flies at very low operator cost compared to manned aircraft. To demonstrate the LDCR several flights had been performed during a field experiment at the Canton Oklahoma Soilscape site on September 8th and 9th, 2015. These tests were flown at 25-35 m altitude to obtain differing spatial resolutions. The LDCR brightness temperature and soil moisture mapping algorithm will be analyzed, and scientific intercomparisons of LDCR, SMAP and SMOS data along with situ measurements will be presented.

To assimilate satellite-based passive microwave observation over heavy clouds and precipitation into numerical weather prediction (NWP) systems and thus to improve the performance of it has become an intensely studied topic. These attempts rely on the development of a radiative transfer (RT) model that accounts for particle scattering and accurately simulates the observation process at an acceptable computational speed. In this paper, two existing RT models (the RTTOV and the DOTLRT) are tested and the accuracies are evaluated by comparing the simulated brightness temperature with real observational data of a satellite-based sounder ATMS. RTTOV is much more well-known and widely applied, however, since these two models use different solvers to deal with the scattering effect, whether it is possible to improve the performance of RT model is still open to discussion.

Radiometric sounding measurements used to provide data for weather prediction are strongly affected by the main-beam, ohmic, and spillover efficiencies of the optics, as well as inhomogeneities in the scene and background radiation fields. The interpretation of radiometric data is also affected by the accuracy with which these efficiencies can be determined. This necessitates design of highly precise antenna systems whose patterns are exactly known. Subtle changes in feedhorn design parameters, including changes that induce feedhorn mode phasing such as corrugation depth or step diameters, produce pattern changes at the reflector that are not captured by the widely used Gaussian approximation. To provide a more precise determination of the requisite efficiencies for radiometry, this study focuses on the rigorous and precise numerical analysis of the complex diffracted field produced by a feed at the focal point of a lens/reflector focussing element. The analysis leads to the determination of an optimal feed horn and lens/reflector geometry such that the main beam and spillover efficiencies of the system are maximized, and these and the ohmic efficiency are precisely known. The above analyses is applied to the antenna subsystem of the PolarCube 3U CubeSat payload which comprises a spinning offset paraboloidal main reflector and a stationary corrugated feed.

In this paper a forward-looking synthetic aperture radar (IceSAR) system is described for the `Very deep Autonomous Laser-powered Kilowatt-class Yo-yoing Robotic Ice explorer' (VALKYRIE) project. Fabrication and laboratory characterization of novel log periodic antennas for IceSAR and system design and in situ testing of the synthetic aperture radar system are presented.

Extreme weather observations with temporal resolution of ~15-30 minutes and spatial resolution of ~15-30 km are required to improve forecasting of mesoscale severe weather events. Due to recent advances in microwave receiver and filter technology, the fleet concept of ~30-40 CubeSat nanosatellites has been identified as an alternative but cost effective means to meet the requirements. OSSEs of CubeSat fleet microwave observations are currently required to demonstrate the basic features of the constellation and provide simulated data for the engineering development of the constellation concept in many aspects. To this end, a NWP-based multi-module simulator of the CubeSat fleet concept was developed at University of Colorado at Boulder. In this paper, microwave imaging CubeSat fleet observations at 30 minute temporal resolution were demonstrated. The observed meteorological features of Hurricane Sandy in the selected CubeSat channels were compared. At the end, using simulated CubeSat fleet observations in the development of hydrometric tracking concept, which has potential of efficiently assimilating high temporal resolution observations into NWP model for improved weather forecasting, was discussed.

The numerical simulations of imaging technology for analysis of geostationary multispectral passive microwave observation is described. This paper compares the abilities of three candidate passive microwave sensors to image the upwelling atmospheric brightness temperature. Presented are scattering-based simulations of a land falling hurricane that illustrate the imaging capabilities of a filled-aperture antenna instrument refer to GEM, a Y-shaped aperture synthesis array instrument refer to GeoSTAR and a Ring-shaped aperture synthesis array instrument refer to GIMS.

We present a lobe-differencing antenna designed as a 2×2 rectangular L-band microstrip antenna array that is used for the CU/BlackSwift Technology's Lobe Differencing Correlation Radiometer (LDCR). The antenna array will be integrated into the fuselage of the BST Tempest unmanned aerial system (UAS). A prototype 2×1 microstrip colinear (“MiCo”) antenna array operating at 1.4135GHz, which is the desired system working frequency, was measured to validate the accuracy of HFSS simulation results of input impedance and radiation pattern. Further, a 2×2 MiCo antenna array was investigated by studying how separation of the upper and lower array pairs and orientation impact mutual coupling, resonant frequency, and radiometer sensitivity. Effective use of styrofoam blocks for improving the antenna's mechanical stability and tuning its resonant frequency was studied. An optimal vertical separation distance was identified that minimizes mutual coupling and provides maximum main to back lobe ratio. A method for tuning the antenna resonant frequency was also developed.

The reflectivity spectrum of radiometer calibration targets with alternate geometries is studied in this letter. We have presented normal incidence plane-wave reflectivity of conical array and truncated square pyramid array in the frequency range [6,200] GHz. Irrespective of whether the pyramid cross-section is circular or square, a base-to-height ratio of 1:4 or better is required to achieve reflectivity of -50 dB or lower for frequencies higher than the first Floquet harmonic cutoff frequency. It was found that the variations in the reflectivity at high frequencies are less pronounced for conical arrays compared to square pyramids. This could make conical structures more useful for broadband calibration purposes. In the case of truncated square pyramids, a reduction in tip sharpness affects the reflectivity at high frequencies substantially. It was found that the use of MF117 or MF124 as coating material instead of MF112 can reduce the reflectivity by ~ 15 dB. The study concludes with the use of the unscented transformation to overcome time consuming Monte Carlo simulations in order to quantify the effect of material property uncertainties in computational electromagnetic simulations.

A unified microwave radiative transfer (UMRT) model is presented for computing the thermal radiation emitted from any geophysical medium composed of planar layers of either densely or tenuously distributed moderately sized spherical scatterers. UMRT employs the discrete-ordinate eigenanalysis (DOE) method with layer adding to solve the differential radiative transfer equation for such multilayer structures. UMRT inherits the symmetrization and analytical diagonalization and factorization techniques of symmetric and positive definite matrices from the discrete-ordinate tangent linear radiative transfer (DOTLRT) model presented by Voronovich These techniques ensure accuracy, numerical stability, and rapid computation for all matrix operations required for DOE along with a fast Jacobian calculation for radiance assimilation purposes. UMRT extends the applicability of DOTLRT by including both the Mie theory and the dense media radiative transfer (DMRT) theory. Other nontrivial extensions within UMRT are the following: 1) The vertical and horizontal radiation intensities are coupled within each layer by applying the reduced Mie or DMRT phase matrices, and 2) the physical temperature profile of a layer is allowed to be linear in height. The symmetry properties of both the reduced Mie and DMRT phase matrices are proved, and the associated scattering and absorption coefficients are compared and discussed. The UMRT slab formulation is validated by imposing energy conservation, and the numerical results for some nominal cases are produced and discussed.

A technique for the detection of the presence of a broad but limited class of interfering signals resulting from common modulation methods in radiometer data is presented. The technique exploits the asymmetry of the signals' modulation constellation in I-Q space and the resulting effect on the statistical 2D probability distribution of a low SNR signal when demodulated and distributed in I-Q space. The statistical limitations of this technique and its application to radiometry are discussed.

A unified microwave radiative transfer (UMRT) model is developed for rapid, stable, and accurate level-centric calculation of the thermal radiation emitted from any geophysical media comprised of planar multilayer of either densely or loosely distributed, moderately sized spherical scatterers, and also rapid calculation of the Jacobian between the observed brightness temperatures with respect to any relevant radiative parameter, such as scattering and absorption coefficients, medium temperature and temperature lapse rate, and others. UMRT includes both the surface Fresnel reflection and transmission and the internal volumetric reflection and transmission accounting for a planar multilayer strcuture with refracting layers. This paper focuses on developping the general radiative transfer solution under the UMRT multilayer framework and the formulation of associated Jacobian procedure. Details of formulation and validation of the UMRT-Jacobian and comparison between the upwelling radiations obtained from the UMRT model with field measurements are presented here.

A comparison of snow depths on sea ice was made using airborne altimeters and an Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) simulator. The data were collected during the March 2006 National Aeronautics and Space Administration (NASA) Arctic field campaign utilizing the NASA P-3B aircraft. The campaign consisted of an initial series of coordinated surface and aircraft measurements over Elson Lagoon, Alaska and adjacent seas followed by a series of large-scale (100 km × 50 km) coordinated aircraft and AMSR-E snow depth measurements over portions of the Chukchi and Beaufort seas. This paper focuses on the latter part of the campaign. The P-3B aircraft carried the University of Colorado Polarimetric Scanning Radiometer (PSR-A), the NASA Wallops Airborne Topographic Mapper (ATM) lidar altimeter, and the University of Kansas Delay-Doppler (D2P) radar altimeter. The PSR-A was used as an AMSR-E simulator, whereas the ATM and D2P altimeters were used in combination to provide an independent estimate of snow depth. Results of a comparison between the altimeter-derived snow depths and the equivalent AMSR-E snow depths using PSR-A brightness temperatures calibrated relative to AMSR-E are presented. Data collected over a frozen coastal polynya were used to intercalibrate the ATM and D2P altimeters before estimating an altimeter snow depth. Results show that the mean difference between the PSR and altimeter snow depths is -2.4 cm (PSR minus altimeter) with a standard deviation of 7.7 cm. The RMS difference is 8.0 cm. The overall correlation between the two snow depth data sets is 0.59.

This paper presents an approach for the fast accurate computation of several useful Mie-based parameters for homogeneous, spherical, liquid water, and ice hydrometeor distributions over a wide range of frequencies, mean hydrometeor diameters, and physical temperatures as occur in the terrestrial atmosphere. The absorption coefficient, scattering coefficient, backscattering coefficient, and phase asymmetry parameters are cast into functions of three independent variables: frequency, temperature, and mean diameter. An exponential drop size distribution with a constant fractional volume of is used to model polydispersed hydrometeors. The ranges used for frequency, temperature, and mean diameter are [1, 1000] GHz, , and [0.002, 20] mm, respectively. The functions are then sampled on a logarithmic grid. Trivariate cubic spline interpolation using nonuniform basis splines (B-splines) is then used to efficiently represent these 3-D functions in a compact library. By using this method, four important criteria are achieved: 1) fast random computability of any of these parameters given the values of frequency, temperature, and mean diameter; 2) minimal memory usage by storage of only B-spline coefficients; 3) representation of parameters using well-behaved functional forms amenable to analytical differentiation for the evaluation of Jacobians, or alternatively, for higher accuracy, B-spline coefficients calculated using true Jacobian values can be used; and 4) negligibly small and bounded error over the entire domain of the library. These procedures result in considerable acceleration of microwave radiative transfer simulations across a broad frequency spectrum, as demonstrated in calculations for both scattering and nonscattering atmospheres. The methods discussed can also be applied to other geophysical problems requiring rapid calculation of series-based functions of several independent variables, where the function evaluation is a time-consuming process, and maximum error bounds are critical.

A 1-D variational (1DVAR) retrieval technique has been developed for obtaining temperature and humidity profiles from observations of the Ground-Based Scanning Radiometer (GSR) operating at millimeter-wavelengths. The GSR was deployed in two Arctic experiments held at the Atmospheric Radiation Measurement Program in Barrow, Alaska. Temperature and humidity profiles retrieved with the 1DVAR technique are compared with simultaneous radiosonde observations (RAOBs) during the Radiative Heating in Underexplored Bands Campaign (February–March 2007). Examples and statistical results are presented and discussed to demonstrate the achieved retrieval accuracy and vertical resolution. The 1DVAR retrievals based on GSR observations improve the NWP background up to 5 km, particularly in the lower 3 km. The present implementation achieved an root-mean-square (rms) error with respect to RAOB within 1.5 K for temperature and 0.10 g/kg for humidity profiles of up to 5 km in height, with 2.9 and 2.0 degrees of freedom for signal, respectively. Using the interlevel covariance definition of the vertical resolution, the 1DVAR retrievals showed a$ < 1$-km vertical resolution of up to 5 km for both temperature and humidity profiles. The integrated water vapor obtained from the retrieved humidity profiles showed an rms accuracy within 0.10$\hbox{kg/m}^{2}$, with small bias$( < 0.01\ \hbox{kg/m}^{2})$and excellent correlation (0.96).

The seven papers in this special issue are grouped into five categories: UAV platforms and platform systems; UAV sensors and sensor systems; UAV data processing; UAV telemetry; and UAV applications.

We present a detailed analysis of the airborne passive microwave remote-sensing data that were collected at a broad range of microwave bands and at a high spatial resolution during the 2002 and 2003 National Aeronautics and Space Administration Cold Land Processes Experiment (CLPX). An accurate measurement of snowpack properties using passive microwave observations requires the detailed knowledge of the relationship between snowpack geophysical parameters and the upwelling polarimetric brightness signature. The principle microwave instrument used for the CLPX was the polarimetric scanning radiometer (PSR), which provided ~100-m resolution maps of the snow emissivity at all Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) bands during several intensive observation periods over the Colorado Rocky Mountains. The observed conditions included drought, normal snowpack, and spring snowmelt. The PSR and related ground-based observations of snowpack properties made during the 2002 and 2003 CLPX campaigns provide a comprehensive high-resolution passive microwave data set. Results show that the high-resolution PSR data exhibit emissivity modes that are similar to those observed in the historical data sets, and that the empirical relationships between the emissivity and the snow water equivalent (SWE), after the effects of macrovegetation are removed, closely match those found in the past theoretical studies. The use of the 89-GHz channel in the empirical relationships provides improved accuracy under dry snow conditions and a small SWE; however, the variability of the SWE-emissivity relationships increases with an increasing SWE. A summary of the observed relationships between the emissivity spectra of snow and snowpack properties is presented. Comparison of the total water content from the AMSR-E and PSR observations shows that the satellite measurements underestimated the total volume of water storage from airborne observations on the average by a factor of five.

One of the most critical of environmental parameters yet to be adequately measured is sea surface salinity, which impacts major ocean circulation and a number of biological oceanic processes. We discuss here the design of a new digital radiometer system to address the issues surrounding the accurate mapping of sea surface brightness temperatures at L-band with high spatial and temporal resolution, and suitable for deployment on small long endurance UAVs. The lobe-differencing correlation radiometer employs a highly stable design and digital processing using demonstrated techniques for anthropogenic radio frequency interference mitigation.

A full-Stokes vector model for the microwave emissivity of an anisotropic wind driven ocean surface based on measured satellite data and using a two-scale model for surface emission is being developed for the purpose of assimilation of satellite microwave radiances. The model is based on the Ohio State University two-scale code and tuned to WindSat full-Stokes emissivity data as analyzed by Meissner and Wentz. Several physical inconsistencies were corrected in the model. The tuned model results over a range of wind speeds from 0-20 m/sec show good agreement in the 0th, 1st, and 2ndazimuthal brightness temperature harmonics. A bias model for the tuned code was developed to account for residual discrepancies.

The University of Colorado (CU) Center for Environmental Technology (CET) has developed a Ground- Based Scanning Radiometer (GSR) and deployed it during two important Arctic Experiments relevant to climate research. The first was the Arctic Winter Radiometric Experiment during March-April 2004 and the second was the Radiative Heating in Underexplored Bands Campaign (RHUBC) in February-March 2007. This paper summarizes some of the design details of the instrument and gives new results from both campaigns

Measurements of water vapor and clouds in the polar regions are difficult, because conventional instruments show little sensitivity (~1.3 K/mm) to low amounts. On the other hand, millimeter- and submillimeter-wavelength radiometry offers greatly enhanced sensitivity (up to 51.4 K/mm, depending upon frequency). For this reason, the National Oceanic and Atmospheric Administration's Physical Science Division designed a new instrument, the Ground-Based Scanning Radiometer (GSR), for continuous and unattended observations at millimeter and submillimeter wavelengths (50-380 GHz). The GSR was deployed for the first time during the Arctic winter radiometric experiment in March-April 2004. In this paper, we discuss the GSR calibration procedure, which allows for accurate measurements during clear and cloudy skies. Error-budget analysis and comparison with independent measurements show an absolute accuracy on the order of 1-2 K. Examples of multifrequency and multiangle GSR observations are illustrated, representing a valuable new data set for the study of water vapor, clouds, and atmospheric absorption models in the Arctic.

Ground-based observations at millimeter (mm) and submillimeter (submm) wavelengths were collected at the atmospheric radiation measurement program site at Barrow, AK, during the Arctic winter by a new 25-channel radiometer. A weighting function analysis is presented to demonstrate the enhanced sensitivity of mm- and submm-wave (50-400 GHz) radiometers to low vapor and liquid water contents with respect to conventional instruments such as the ones operating at centimeter (cm) wavelengths (20-30 GHz). In addition, based on measurements, we carried out a quantitative analysis of mm- and submm-wavelength sensitivity, yielding improvement factors from 1.5 to 69 for precipitable water vapor (PWV) and 3 to 4 for liquid water path (LWP) when compared to 20-30 GHz radiometers. Furthermore, using a simulated data set, we evaluate the effect of hydrometeor scattering: given the conditions occurring during the experiment, the scattering contribution is within the instrumental noise for most, but not all, of the considered channels. With the same data set, we demonstrate that in the dry conditions of the Arctic, a simple linear regression yields satisfactory results when applied on selected mm- and submm-wave channels. For a dual-channel combination, the expected accuracy is ~0.23 (0.007) mm for PWV (LWP), when using mm- and submm-wavelengths, whereas it is 0.37 (0.012) mm using cm-wave channels. When the retrieval is applied to real observations, the accuracy is found in agreement with theoretical expectations.

This paper describes C-band Radio Frequency In- terference (RFI) measurements made from NASA's WB-57 high- altitude aircraft using the PSR/CXI system of NOAA/ETL and the C-band Interference Suppressing Radiometer (CISR) digital backend of the Ohio State University (OSU) ElectroScience Laboratory. The observations discussed were performed during a test flight on Aug. 25th, 2005 over Texas cities as well as the Gulf of Mexico at a typical altitude of 62,000 feet.

The results of seasonal L-band (1.4 GHz) soil moisture (SM) measurements and their analysis are described. The measurements were performed using a radiometer mounted at the top of the 300-m tall ETL Boulder Atmospheric Observatory (BAO) tower during period of 2004-2005.Insitusoil moisture measurements were made in the center of the radiometer antenna footprint using time-domain reflectometer (TDR) probes installed at 5, 10 and 15 cm depth. Radiative transfer theory predicts that L-band radiation from soil originates from deeper within the soil compared with commonly used remote sensing microwave bands at higher frequencies. Results from this experiment indicate such generally higher sensitivity to subsurface SM content. On the other hand, a significant amount of scattering variability is also observed for the same level of in situ SM measured at 5 cm depth. Our radiometric experiments support the hypothesis that different vertical gradients of SM can lead to different reflectivity values for the same SM level at a fixed depth. Further investigation is needed to quantify the role of grassy vegetation for L-band soil reflectivity during spring and summer seasons.

An assessment of Advanced Microwave Scanning Radiometer Earth Observing System (AMSR-E) sea ice concentrations under winter conditions using ice concentrations derived from Landsat-7 Enhanced Thematic Mapper Plus (ETM+) imagery obtained during the March 2003 Arctic sea ice validation field campaign is presented. The National Oceanic and Atmospheric Administration Environmental Technology Laboratory's Airborne Polarimetric Scanning Radiometer Measurements, which were made from the National Aeronautics and Space Administration P 3B aircraft during the campaign, were used primarily as a diagnostic tool to understand the comparative results and to suggest improvements to the AMSR-E ice concentration algorithm. Based on the AMSR-E/ETM+ comparisons, a good overall agreement with little bias (~1%) for areas of first year and young sea ice was found. Areas of new ice production result in a negative bias of about 5% in the AMSR-E ice concentration retrievals, with a root mean square error of 8%. Some areas of deep snow also resulted in an underestimate of the ice concentration (~10%). For all ice types combined and for the full range of ice concentrations, the bias ranged from 0% to 3%, and the rms errors ranged from 1% to 7%, depending on the region. The new-ice and deep-snow biases are expected to be reduced through an adjustment of the new-ice and ice-type C algorithm tie points

Corruption of C-band microwave brightness observations by radio-frequency interference (RFI) has been reported in recent data from orbiting radiometers; methods for mitigating these effects are of great importance for the design of future spaceborne microwave radiometers. One approach that has been suggested involves the use of multiple subchannels at C-band as opposed to a single channel; the use of multiple subchannels allows RFI to be detected and mitigated by analyzing relationships among subchannel brightnesses. While this approach has been utilized in previous airborne measurements, demonstrations of the RFI mitigation performance achieved have been difficult to obtain. To address this issue, an enhanced airborne system for observing radio-frequency interference effects on C-band microwave radiometers was developed, and is described in this paper. The system includes a traditional microwave radiometer with four C-band subchannels, so that RFI removal is possible using a subchannel mitigation algorithm. In addition, the system includes a digital receiver with the capability of providing high temporal and spectral resolution observations of interference. This high-resolution data allows improved understanding of RFI sources to be obtained, and also allows analysis of subchannel mitigation algorithm performance. Observations using the system in a test flight near Wallops Island, VA are described. Results show the four subchannel approach generally to be effective in mitigating the observed RFI sources, although examples are also illustrated using the digital receiver data to demonstrate failure of this approach. While studies of the digital receiver data alone could be performed to demonstrate further improvements in RFI mitigation, issues with this initial dataset limit the extent of such studies. Nevertheless, the results obtained still demonstrate qualitatively the improved RFI mitigation that can be achieved in brightness observations through the use of digital receivers

Part of the Earth Observing System Aqua Advanced Microwave Scanning Radiometer (AMSR-E) Arctic sea ice validation campaign in March 2003 was dedicated to the validation of snow depth on sea ice and ice temperature products. The difficulty with validating these two variables is that neither can currently be measured other than in situ. For this reason, two aircraft flights on March 13 and 19, 2003, were dedicated to these products, and flight lines were coordinated with in situ measurements of snow and sea ice physical properties. One flight was in the vicinity of Barrow, AK, covering Elson Lagoon and the adjacent Chukchi and Beaufort Seas. The other flight was farther north in the Beaufort Sea (about 73degN, 147.5degW) and was coordinated with a Navy ice camp. The results confirm the AMSR-E snow depth algorithm and its coefficients for first-year ice when it is relatively smooth. For rough first-year ice and for multiyear ice, there is still a relationship between the spectral gradient ratio of 19 and 37 GHz, but a different set of algorithm coefficients is necessary. Comparisons using other AMSR-E channels did not provide a clear signature of sea ice characteristics and, hence, could not provide guidance for the choice of algorithm coefficients. The limited comparison of in situ snow-ice interface and surface temperatures with 6-GHz brightness temperatures, which are used for the retrieval of ice temperature, shows that the 6-GHz temperature is correlated with the snow-ice interface temperature to only a limited extent. For strong temperature gradients within the snow layer, it is clear that the 6-GHz temperature is a weighted average of the entire snow layer

Aircraft-acquired passive microwave data, laser radar height observations, RADARSAT synthetic aperture radar imagery, and in situ measurements obtained during the AMSR-Ice03 experiment are used to investigate relationships between microwave emission and ice characteristics over several space scales. The data fusion allows delineation of the shore-fast ice and pack ice in the Barrow area, AK, into several ice classes. Results show good agreement between observed and Polarimetric Scanning Radiometer (PSR)-derived snow depths over relatively smooth ice, with larger differences over ridged and rubbled ice. The PSR results are consistent with the effects on snow depth of the spatial distribution and nature of ice roughness, ridging, and other factors such as ice age. Apparent relationships exist between ice roughness and the degree of depolarization of emission at 10, 19, and 37 GHz. This depolarization would yield overestimates of total ice concentration using polarization-based algorithms, with indications of this seen when the NT-2 algorithm is applied to the PSR data. Other characteristics of the microwave data, such as effects of grounding of sea ice and large contrast between sea ice and adjacent land, are also apparent in the PSR data. Overall, the results further demonstrate the importance of macroscale ice roughness conditions such as ridging and rubbling on snow depth and microwave emissivity

Accurate knowledge of snow-depth distribution over sea ice is critical for polar climate studies. Current snow-depth-over-sea-ice retrieval algorithms do not sufficiently account for variations in snow and ice physical properties that can affect the accuracy of retrievals. For this reason, airborne microwave observations were coordinated with ground-based measurements of snow depth and snow properties in the vicinity of Barrow, AK, in March 2003. In this paper, the effects of snowpack properties and ice conditions on microwave signatures are examined using detailed surface-based measurements and airborne observations in conjunction with a thermal microwave-emission model. A comparison of the Microwave Emission Model of Layered Snowpacks (MEMLS) simulations with detailed snowpack and ice data from stakes along the Elson Lagoon and the Beaufort Sea and radiometer data taken from low-level flights using a Polarimetric Scanning Radiometer (PSR-A) shows that MEMLS can be used to simulate snow on sea ice and is a useful tool for understanding the limitations of the snow-depth algorithm. Analysis of radiance data taken over the Elson Lagoon and the Beaufort Sea using MEMLS suggests that the radiometric differences between the two locations are due to the differences in sea-ice emissivity. Furthermore, measured brightness temperatures suggest that the current snow-depth retrieval algorithm is sufficient for areas of smooth first-year sea ice, whereas new algorithm coefficients are needed for rough first-year sea ice. Snowpack grain size and density remain an unresolved issue for snow-depth retrievals using passive-microwave radiances

This paper examines the sensitivity of Advanced Microwave Scanning Radiometer (AMSR-E) brightness temperatures (Tbs) to surface roughness by a using radiative transfer model to simulate AMSR-E Tbs as a function of incidence angle at which the surface is viewed. The simulated Tbs are then used to examine the influence that surface roughness has on two operational sea ice algorithms, namely: (1) the National Aeronautics and Space Administration Team (NT) algorithm and (2) the enhanced NT algorithm, as well as the impact of roughness on the AMSR-E snow depth algorithm. Surface snow and ice data collected during the AMSR-Ice03 field campaign held in March 2003 near Barrow, AK, were used to force the radiative transfer model, and resultant modeled Tbs are compared with airborne passive microwave observations from the Polarimetric Scanning Radiometer. Results indicate that passive microwave Tbs are very sensitive even to small variations in incidence angle, which can cause either an over- or underestimation of the true amount of sea ice in the pixel area viewed. For example, this paper showed that if the sea ice areas modeled in this paper were assumed to be completely smooth, sea ice concentrations were underestimated by nearly 14% using the NT sea ice algorithm and by 7% using the enhanced NT algorithm. A comparison of polarization ratios (PRs) at 10.7, 18.7, and 37 GHz indicates that each channel responds to different degrees of surface roughness and suggests that the PR at 10.7 GHz can be useful for identifying locations of heavily ridged or rubbled ice. Using the PR at 10.7 GHz to derive an "effective" viewing angle, which is used as a proxy for surface roughness, resulted in more accurate retrievals of sea ice concentration for both algorithms. The AMSR-E snow depth algorithm was found to be extremely sensitive to instrument calibration and sensor viewing angle, and it is concluded that more work is needed to investigate the sensitivity of the gradient ratio at 37 and 18.7 GHz to these factors to improve snow depth retrievals from spaceborne passive microwave sensors

The first estimates of the average bulk heat transfer coefficient for Arctic sea ice are presented as a function of mean ice thickness. Turbulent heat flux measurements made by the NASA P-3 over the St. Lawrence Island polynya (SLIP) and Kuskokwim Bay in the Bering Sea during AMSR-Ice03 were used to estimate the values of the heat transfer coefficient$C_ H$. Estimates of ice thickness were made from the algorithm of Perovich using broadband albedos obtained from Moderate Resolution Imaging Spectroradiometer data. Plots of$C_ H$as a function of ice thickness showed a nearly linear relationship for ice thicknesses in the range of 0–14 cm in the polynyas. Previous estimates of$C_ H$for different cases over the SLIP were$1.2 times 10^-3$, but no estimates of ice thickness were available. These results will allow more accurate estimates of heat fluxes from the thin-ice areas of polynyas using satellite retrievals.

An unresolved issue in global soil moisture retrieval using passive microwave sensors is the spatial integration of heterogeneous landscape features to the nominal 50 km footprint observed by most satellite systems. One of the objectives of the Soil Moisture Experiments 2004 (SMEX04) was to address some aspects of this problem, specifically variability introduced by topography and convective precipitation. Other goals included understanding the role of the land surface in the North American Monsoon System. Data were collected during the month of August 2004 at three scales; ground based point measurements, aircraft passive microwave mapping, and satellite observations using AMSR-E and other sensors. SMEX04 was conducted over two regions: Arizona - semi-arid climate with sparse vegetation and moderate topography, and Sonora (Mexico) - moderate vegetation with strong topographic gradients. The Polarimetric Scanning Radiometer (PSR/CX) was flown on a Naval Research Lab P-3B aircraft as part of SMEX04 (11 dates of coverage over Arizona and 10 over Sonora). General meteorological conditions, the PSR/CX data sets and selected comparisons of this data to AMSR-E are presented.

We appreciate that authors Kerr et al. concur that our paper [ibid., vol.42, no.7, p.1387-98 (2004)] provides the right approach to the analysis of potential interference from anthropogenic sources to remote sensing satellites. The potential for such interference is likely to grow as new active systems are developed, necessitating acceptable procedures for interference analysis based on accepted scientific knowledge and engineering principles. While some simple clarifications are in order to improve the acceptability of our procedure, we suggest, however, that Kerr et al. have not studied our paper in detail and misinterpret several points.

Soil Moisture Experiment 2003 (SMEX03) was the second in a series of field campaigns using the National Oceanic and Atmospheric Administration Polarimetric Scanning Radiometer (PSR/CX) designed to validate brightness temperature (T/sub B/) data and soil moisture retrieval algorithms for the Advanced Microwave Scanning Radiometer (AMSR-E) for the Earth Observing System on the Aqua satellite. Objectives related to the PSR/CX during SMEX03 included: calibration and validation of AMSR-E T/sub B/ observations over different climate/vegetation regions of the U.S. [Alabama (AL), Georgia (GA), Oklahoma (OK)], identification of possible areas of radio-frequency interference (RFI), comparison of X-band observations from Tropical Rainfall Measurement Mission Microwave Imager (TMI), AMSR-E, and PSR/CX, and exploring the potential of soil moisture retrieval algorithms using C- and X-band imagery in diverse landscapes. In the current investigation, more than 100 flightlines of PSR/CX data were extensively processed to produce gridded T/sub B/ products for the four study regions. Due to the lack of significant rainfall in OK, generally dry soil moisture conditions were observed. Observations obtained over AL include a wide range of soil moisture and vegetation conditions. Results from the AL site clearly showed a lack of sensitivity to rainfall/soil moisture under forest canopy cover. Quantitative comparisons made with the TMI validated that both the PSR/CX and AMSR-E X-band channels were well calibrated. Spectral analyses indicated that the PSR/CX observations at C-band also are reasonable. As expected, there were varying degrees of RFI in the AMSR-E C-band data for the study sites that will prevent further soil moisture analysis using these data. X-band comparisons of the PSR/CX high-resolution and AMSR-E and TMI low-resolution data indicated a linear scaling for the range of conditions studied in SMEX03. These results will form the basis for further soil moisture investigations.

The local spatial scales of tropical precipitating systems were studied using Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) rain rate imagery from the TRMM satellite. Rain rates were determined from TMI data using the Goddard Profiling (GPROF) Version 5 algorithm. Following the analysis of Ricciardulli and Sardeshmukh (RS), who studied local spatial scales of tropical deep convection using global cloud imagery (GCI) data, active precipitating months were defined alternatively as those having greater than either 0.1 mm/h or 1 mm/h of rain for more than 5% of the time. Spatial autocorrelation values of rain rate were subsequently computed on a 55/spl times/55 km grid for convectively active months from 1998 to 2002. The results were fitted to an exponential correlation model using a nonlinear least squares routine to estimate a spatial correlation length at each grid cell. The mean spatial scale over land was 90.5 km and over oceans was 122.3 km for a threshold of 0.1 mm/h of rain with slightly higher values for a threshold of 1 mm/h of rain. An error analysis was performed which showed that the error in these determinations was of order 2% to 10%. The results of this study should be useful in the design of convective schemes for general circulation models and for precipitation error covariance models for use in numerical weather prediction and associated data assimilation schemes. The results of the TMI study also largely concur with those of RS, although the more direct relationship between the TMI data and rain rate relative to the GCI imagery provide more accurate correlation length estimates. The results also confirm the strong impact of land in producing short spatial scale convective rain.

Soil Moisture Experiments 2003 (SMEX03) was the second in a series of field campaigns using the NOAA Polarimetric Scanning Radiometer (PSR/CX) designed to validate brightness temperature data and soil moisture retrieval algorithms for the Advanced Microwave Scanning Radiometer on the Aqua satellite. Data from the TRMM Microwave Imager were also used for X-band comparisons. The study was conducted in different climate/vegetation regions of the US (Alabama, Georgia, Oklahoma). In the current investigation, more than one hundred flightlines of PSR/CX data were extensively processed to produce gridded brightness temperature products for the four study regions. Variations associated with soil moisture were not as large as hoped for due to the lack of significant rainfall in Oklahoma. Observations obtained over Alabama include a wide range of soil moisture and vegetation conditions. Comparisons were made between the PSR and AMSR for all sites

An airborne system for observing radio frequency interference at C-band is described. The digital receiver included has the capability of providing high temporal and spectral resolution of interference, as well as implementing simple mitigation strategies. Plans for observations with the system are discussed.

The data from aircraft and ship campaigns in February 2003 in conjunction with high resolution satellite images aid in validating sea ice concentrations derived from AMSR-E brightness temperatures. Patrol Vessel SOYA conducted time series observations of geophysical parameters such as ice type, floe size, snow cover vertical profiles of snow and ice surface temperature, density, grain size, and salinity. Surface data were used to interpret aircraft microwave and visible channel data used to interpret high resolution Landsat-7 and MODIS images. The latter were then utilized to interpret the ice concentration data derived from AMSR-E. The co-registered images of aircraft PSR: Landsat-7 and MODIS data exhibit good coherence in signatures. In highly consolidated ice cover, the ice concentrations were in agreement to within 5 to 10% in ice concentration. However, in highly divergent areas, the derived ice concentration has a negative bias due to the dominant presence of new ice. The new ice has relatively lower emissivity than first year ice which is snow cover and is affected by waves and wetness. The relationship between the thickness and brightness temperature of sea ice was studied in detail.

The NASA Cold-land Processes Field Experiment-1 (CLPX-1) involved several instruments in order to acquire data at different spatial resolutions. Indeed, one of the main tasks of CLPX-1 was to explore scaling issues associated with microwave remote sensing of snowpacks. To achieve this task, microwave brightness temperatures collected at 18.7, 36.5, and 89 GHz at LSOS test site by means of the University of Tokyo's Ground Based Microwave Radiometer-7 (GBMR-7) were compared with brightness temperatures recorded by the NOAA Polarimetric Scanning Radiometer (PSR/A) and by SSM/I and AMSR-E radiometers. Differences between different scales observations were observed and they may be due to the topography of the terrain and to observed footprints. In the case of satellite and airborne data, indeed, it is necessary to consider the heterogeneity of the terrain and the presence of trees inside the observed scene becomes a very important factor. Also when comparing data acquired only by the two satellites, differences were found. Different acquisition times and footprint positions, together with different calibration and validation procedures, can be responsible for the observed differences.

A multiinstrument radiometric experiment was conducted on the North Slope of Alaska near Barrow, Alaska, during March 9 to April 9 2004. Initial radiometric and radiosonde data from this experiment are presented.

The full utilization of satellite-based passive microwave imagery for weather forecasting rests on the ability to assimilate radiances into numerical weather prediction (NWP) models for highly scattering and absorbing hydrometeor states. State vector updates need to be performed rapidly enough to maintain pace with the sensor data stream and require, in particular, rapid calculation of the tangent linear relationship (Jacobian) between the observed antenna temperatures and the NWP prognostic hydrometeor parameters. To facilitate the use of both spaceborne and airborne passive microwave data in numerical forecasting, we present a new rapid multiple-stream discrete-ordinate algorithm for calculating the Jacobian under arbitrary scattering and absorbing conditions. The algorithm is based on the layer-adding method for a plane-parallel atmosphere for which the number of operations required to compute the solution is proportional to the number of layers. A nontrivial aspect of the problem is the stable calculation of the reflectance and transmittance operators in highly scattering layers for which a diagonalization technique and analytical factorization of specific matrices are used to ensure stability. Scaling calculations suggest that the new algorithm will be suitable for use in real-time all-weather microwave radiance assimilation.

The automotive industry is currently considering the introduction of short-range radars (SRR) operating near 24 GHz for improving road traffic safety. SSRs are intended to observe the full azimuthal space cover around a vehicle using up to eight sensors. The sensors would operate in an ultrawideband (UWB) mode, occupying 3-5 GHz of bandwidth. Interference from SRR transmitters with passive microwave remote sensing satellites used for weather and climate monitoring could occur as the result of several coupling mechanisms, including direct coupling via the transmit antenna beam and scattering and diffraction of the transmitted signals from leading vehicles, buildings, and other nearby objects. In this study, we estimate the amount of coupling anticipated to occur from SRRs, including the direct and scattered contributions. The calculations are based on bistatic scattering measurements of a typical automobile and ray optical simulations of reflection and propagation in an urban environment. Using these calculations, the maximum allowable SRR transmitted power for interference levels acceptable for meteorological and climatological remote sensing applications are quantified. The study provides criteria for SRR operation with the Earth Exploration Satellite Service on a noninterference basis.

Precipitation sensitivity calculations suggest that a geosynchronous microwave (GEM) sounder/imager using millimeter- and submillimeter-wave channels at 50-57, 118, 183, 340, 380, and 424 GHz with a 2-3 meter diameter real aperture antenna will provide time-resolved radiance data valuable for tracking convective precipitation events using a numerical weather prediction (NWP) model. Presented are scattering-based Jacobian simulations of a landfalling hurricane that illustrate the capabilities of GEM for precipitation measurement and NWP-based radiance assimilation.

Coupling of emissions from wideband vehicular collision avoidance radars into passive microwave satellites can impart significant interference to earth remote sensing applications. One of the most physically obvious coupling mechanisms is reflection of the main lobe of the radar by another vehicle toward the main lobe of the radiometer. Since vehicular radars will commonly illuminate another close-in leading vehicle it is suspected that such scattering scenarios will be commonplace. In order to estimate the interference from a collection of such vehicular radars to a passive microwave satellite we performed numerical simulations to determine the system coupling coefficient C sm ,. The only reflection taken into account is that from the rear window of the leading vehicle. We considered three typical styles of automobiles having rear window angles of 25(, 35( (( (, and 45( (( (. It is shown that reflection of radiation from vehicular radars from the rear windows of automobiles can alone easily cause a significant amount of coupling (-10 to -20 dB) with space-borne radiometers. Additional scattering can be expected from other metallic parts of the leading automobile and by other nearby objects such as trees, railings, barriers, and the tilted roofs of buildings.

Field experiments were conducted to evaluate the effects of dense agricultural crop conditions on soil moisture retrieval using passive microwave remote sensing. Aircraft observations were collected using a new version of the Polarimetric Scanning Radiometer (PSR) that provided C band and X band channels. Observations were also available from the Aqua satellite Advanced Microwave Scanning Radiometer (AMSR-E) at the same frequencies. Soil Moisture Experiments 2002 (SMEX02) was conducted over a three-week period during the summer near Ames, Iowa, an area which is dominated by corn and soybeans. Aircraft data were processed and channels selected to minimize radiofrequency interference. A preliminary comparison of he aircraft (PSR) and satellite (AMSR-E) 10.7 GHz data showed comparable brightness temperature values. Sensitivity of brightness temperature to soil moisture was observed for nearly all the ground validation sites, even under dense corn canopies. Similar sensitivities were observed for C and X band channels. These results illustrate the potential to develop soil moisture retrieval techniques for wide range of agricultural conditions using AMSR-E frequencies.

Multispectral polarimetric microwave brightness temperature maps of snowpack in the Colorado Rocky Mountains were obtained using the NOAA Polarimetric Scanning Radiometer (PSR) during three Cold Land Processes Experiments (CLPX) in February 2002, February 2003, and March 2003. The PSR CLPX data offers unique high-resolution information about snow extent, polarimetric emissivity, and snow water equivalent at scales commensurate with natural inhomogeneities in terrain and precipitation patterns. The data is being used for several purposes including snowpack and snowmelt hydrology, calibration and validation of the AMSR-E sensor, cryospheric satellite sensor design, wideband snow emissivity modeling, and snowpack change detection. Initial results from CLPX02 using the PSR/A scanhead are presented showing brightness temperature, emissivity, and estimated snow water equivalent (SWE) maps.

The results of GPS L-band (L1, /spl lambda/ = 19 cm) surface reflection measurements observed using multiple polarizations and receiving antenna gains are described. The measurements were performed using the 300 m tall ETL Boulder Atmospheric Observatory (BAO) tower during summer through fall of 2002. In this experiment, the first seasonal measurements of bare soil moisture from a stationary location using bistatic reflection of signal of opportunity were performed. Several receiving antennas offering various gain and polarization sensitivities were used. Theoretical modeling of bistatic surface scattering shows that the magnitude and width of the reflected waveform depend on the dielectric permittivity of the soil, vegetation cover, and soil roughness. By observing from a fixed tower over low grass, the roughness of the reflecting area remains constant, hence variations in the signal are uniquely related to changes in the dielectric permittivity, and therefore, to soil moisture. To investigate polarization sensitivity of the reflected signal to soil moisture, four endfire (/spl sim/ 12 dB) antennas with complete circular and orthogonal polarization sensitivities were used. The high-gain antennas increased the received dynamic range and reduced surface multipath radio wave interference. Seasonal retrievals of soil-moisture content from multi-polarization GPS reflection data is presented and compared with in-situ soil moisture measurements.

A technique for absolute end-to-end calibration of a fully polarimetric microwave radiometer is presented. The technique is based on the tripolarimetric calibration technique of Gasiewski and Kunkee, but is extended to provide a means of calibrating all four Stokes parameters. The extension is facilitated using a biaxial phase-retarding microwave plate to provide a precisely known fourth Stokes signal from the Gasiewski-Kunkee (GK) linearly polarized standard. The relations needed to determine the Stokes vector produced by the augmented standard are presented, and the effects of nonidealities in the various components are discussed. The application of the extended standard to determining the complete set of radiometer constants (the calibration matrix elements) for the National Oceanic and Atmospheric Administration Polarimetric Scanning Radiometer in a laboratory environment is illustrated. A calibration matrix inversion technique and error analysis are described, as well. The uncertainties associated with practical implementation of the fully polarimetric standard for spaceborne wind vector measurements are discussed relative to error thresholds anticipated for wind vector retrieval from the U.S. National Polar-Orbiting Environmental Satellite System.

The concept of microwave sounding from geostationary orbit is over three decades old, but can now be facilitated using submillimetre-wave sounding technology. A "GEM" concept has been pursued in the U.S. in the past few years, and now a "GOMAS" proposal has been submitted to ESA for implementation. The principle is to extend the number of bands usually exploited for sounding (54 GHz for temperature and 183 GHz for humidity) to higher frequencies (118 and 425 GHz for temperature, 380 GHz for humidity), so as to obtain higher geometric resolution for a given antenna size. Measurements in absorption bands at frequencies differently affected by liquid and ice water, enable simultaneous retrieval of temperature and humidity profiles, cloud ice and liquid columnar amounts and gross profile and, most important, precipitation, appropriately sampled at time intervals of some 15 minutes. The paper will highlight the basic concepts and technical features of the GEM/GOMAS project and comment about feasibility and sizing elements.

Relentless development of the microwave spectrum for telecommunications and other active services enhances the risk of anthropogenic interference to the passive Earth Exploration Satellite Service (EESS). While spectral allocation remains the primary basis for avoiding interference between the passive and active services, it is also prudent to consider the use of interference mitigation technology for passive microwave remote sensing, especially for spectral regions wherein primary EESS allocation is non-negotiable. Accordingly, we consider several means of detecting and correcting for anthropogenic interference in passive microwave imagery, including spectral subbanding, polarization detection, polarimetric detection, and azimuthal detection. A spectral subband technique applicable to either narrow-band and/or window channels is demonstrated with C-band data obtained using the NOAA Polarimetric Scanning Radiometer (PSR) airborne imaging system. The technique provides very good rejection of strong interference, and is readily applicable for implementation on future airborne and spaceborne passive microwave sensors.

The IEEE Geoscience and Remote Sensing Society (GRSS) Technical Committee on Frequency Allocation in Remote Sensing (FARS) is charged with providing recommendations and responses to queries on interference and frequency allocation issues in passive and active microwave remote sensing. In response to questions stemming from proposals to develop ultra-wideband (UWB) vehicular radar systems operating in the 22-27 GHz frequency range a technical assessment on the potential for radio frequency interference to passive Earth remote sensing activities was prepared. The study suggests that interference to the passive services at power levels several orders of magnitude above threshold levels is likely from commercial deployment of vehicular UWB radar and telecommunications systems.

The development of the NOAA Polarimetric Scanning Radiometer (PSR) system commenced in the fall of 1995, with the first-generation system operated on the NASA P-3B aircraft to study passive microwave ocean surface wind signatures in March, 1997. The PSR system consist of sets of polarimetric radiometers housed within standardized gimbal-mounted scanhead drums. Each scanhead is rotatable by a gimbaled positioner so that the radiometers can view any angle within 70/spl deg/ elevation of nadir and at any azimuthal angle (1.32/spl pi/ sr solid angle), as well as external hot and ambient calibration targets. The configuration supports conical, cross-track, along-track, fixed-angle stare, and spotlight scan modes. Scanheads are designed for in-flight operation without the need for a radome (i.e. in contact with the aircraft slipstream), thus allowing precise calibration and imaging without superimposed radome signatures. The conical scan mode allows the full Stokes' vector to be imaged without polarization mixing. The PSR has been used in several successful airborne missions, demonstrating the first 2-dimensional ocean surface wind vector mapping, high-resolution hurricane rainband imaging and satellite rainfall rate validation, C-band soil moisture imaging, high-resolution sea-ice mapping, and ocean internal wave imaging. Since its inaugural mission there have been several new hardware developments that have extended the capability of the PSR system in terms of the observable spectrum, polarizations, and compatibility with various aircraft. Currently in progress are developments which will provide the capability to perform wideband airborne hydrological studies with a single suite of synchronized, compatible sensor heads. This suite will include the PSR/CX, PSR/S, and PSR/L scanheads, which collectively extend the capabilities of the original PSR/A scanhead. Four positioners are anticipated to be available for operation in 2003. Each assembly (scanhead and positioner) was designed for integration into several aircraft, including the NASA DC-8, Orion P-3B, and WB-57F, Scaled Composites' Proteus, Airplatforms, Inc. Canberra B-6, U.S. Navy P-3A, and NASA ER-2. Upon completion, the PSR system will provide passive polarimetric microwave imagery at most of the channels in the range of 1.4 to /spl sim/800 GHz that are useful for spaceborne or airborne hydrological remote sensing. Studies planned using the system include vapor-to-runoff phase monitoring of precipitation, estuarian runoff and mixing, targeted forecasting, and cirrus generation by convection.

A multiband Polarimetric Scanning Radiometer (PSR) was integrated onto the NASA DC-8 aircraft (N717NA) and flown from August through September of 1998 during the third Convection and Moisture Experiment (CAMEX3) and Texas-Florida Under-flight (TEFLUN-B) campaign. The PSR is a unique conically-scanned imaging radiometer with channels at 10.7, 18.7, 21.5, 37.0 and 89.0 GHz, measuring both vertical and horizontal polarizations at each of these frequencies. These channels correspond to several key bands of the DMSP (Defense Meteorological Satellite Program) SSM/I (Special Sensor Microwave Imager) and the NASA TRMM (Tropical Rainfall Measuring Mission) TMI (TRMM Microwave Imager). The PSR was developed by Georgia Institute of Technology and the NOAA Environmental Technology Laboratory. It is the first airborne imaging radiometer to provide a research quality set of high spatial resolution multiband polarimetric microwave imagery within and around a hurricane. A nonlinear statistical emission algorithm was developed for rain rate retrieval, similar to that described by Skofronick-Jackson and Gasiewski (1995). We use the PSR/A 10.7 GHz channels of horizontal and vertical polarization because of their predominantly monotonic response to near-surface rain rate from 0 to /spl sim/50 mm/hr. An initial comparison of the PSR retrieved rain rate to coincidently observed rain rate retrieved using NASA JPL's Airborne Rain Mapping Radar (ARMAR) shows favorable agreement over at least an order of magnitude in rain rate intensity. Discrepancies are within the standard deviations of the PSR retrieval algorithm and can be explained by differences in the observation geometries of the sensors and by differences in the physical measurement principals between the two instruments. Further comparison of the PSR rain rate retrieval with the TMI level 2A12 rain rate product is similarly favorable. Some discrepancies can be explained by the differences in spatial resolution of the two passive microwave instruments and the different nature of the two retrieval algorithms. Despite these differences, the correlation coefficient between the TMI and the PSR coincidentally observed rain rates is 0.92 and 0.91 for PSR horizontal and vertical channels (respectively), for rain rates from /spl sim/1 to /spl sim/16 mm/hr.

The Advanced Microwave Scanning Radiometer (AMSR) holds promise for retrieving soil moisture in regions with low levels of vegetation. Algorithms for this purpose have been proposed, but none have been rigorously evaluated due to a lack of datasets. Accordingly, the Southern Great Plains 1999 Experiment (SGP99) was designed to provide C-band datasets for AMSR algorithm development and validation. Ground observations of soil moisture and related variables were collected in conjunction with aircraft measurements using a C-band radiometer similar to the AMSR sensor (6.92 GHz), the Polarimetric Scanning Radiometer with its C-band scanhead (PSR/C). The study region has been the focus of several previous remote sensing field experiments and contains vegetation conditions compatible with the expected capabilities of C-band for soil moisture retrieval. Flights were conducted under a wide range of soil moisture conditions, thus providing a robust dataset for validation. A significant issue found in data processing was the removal of anthropogenic radio-frequency interference. Several approaches to estimating the parameters of a single-channel soil moisture retrieval algorithm were used. PSR/C soil moisture images show spatial and temporal patterns consistent with meteorological and soil conditions, and the dynamic range of the PSR/C observations indicates that the AMSR instrument can provide useful soil moisture information.

The microphysical parameterization of clouds and rain cells plays a central role in atmospheric forward radiative transfer models used in calculating microwave brightness temperatures. The absorption and scattering properties of a hydrometeor-laden atmosphere are governed by particle phase, size distribution, aggregate density, shape, and dielectric constant. This study investigates the sensitivity of brightness temperatures with respect to the microphysical cloud parameterization. Calculated wideband (6-410 GHz) brightness temperatures were studied for four evolutionary stages of an oceanic convective storm using a rive-phase hydrometeor model in a planar-stratified scattering-based radiative transfer model. Five other microphysical cloud parameterizations were compared to the baseline calculations to evaluate brightness temperature sensitivity to gross changes in the hydrometeor size distributions and the ice-air-water ratios in the frozen or partly frozen phase. The comparison shows that enlarging the raindrop size or adding water to the partly frozen hydrometeor mix warms brightness temperatures by as much as 55 K at 6 GHz. The cooling signature caused by ice scattering intensifies with increasing ice concentrations and at higher frequencies. An additional comparison to measured Convection and Moisture Experiment (CAMEX-3) brightness temperatures shows that in general all but two parameterizations produce calculated T/sub B/s that fall within the CAMEX-3 observed minima and maxima.

This paper presents a method for compensating the elevation angle fluctuations occurring in airborne radiometry due to aircraft roll and pitch. The correction is based on a radiative transfer model, and is demonstrated by real data from conical scans over the ocean, showing good results.

The retrieval of ocean surface wind fields in both one and two dimensions is demonstrated using passive polarimetric microwave imagery obtained from a conical-scanning airborne polarimeter. The retrieval method is based on an empirical geophysical model function (GMF) for ocean surface thermal emission and an adaptive maximum likelihood (ML) wind vector estimator. Data for the GMF were obtained using the polarimetric scanning radiometer/digital (PSR/D) on the NASA P-3 aircraft during the Labrador Sea Deep Convection Experiment in 1997. To develop the GMF, a number of buoy overflights and GPS dropsondes were used, out of which a GMF of 10.7, 18.7, and 37.0 GHz azimuthal harmonics for the first three Stokes parameters was constructed for the SSM/I incident angle of 53.1/spl deg/. The data show repeatable azimuthal harmonic coefficient amplitudes of /spl sim/2-3 K peak-to-peak, with a 100% increase in harmonic amplitudes as the frequency is increased from 10.7 to 37 GHz. The GMF is consistent with and extends the results of two independent studies of SSM/I data and also provides a model for the third Stokes parameter over wind speeds up to 20 m/s. The aircraft data show that the polarimetric channels are much less susceptible to geophysical noise associated with maritime convection than the first two Stokes parameters. The polarimetric measurement technique used in the PSR/D also demonstrates the viability of digital correlation radiometry for aircraft or satellite measurements of the full Stokes vector. The ML retrieval algorithm incorporates the additional information on wind direction available from multiple looks and polarimetric channels in a straightforward manner and accommodates the reduced SNRs of the first two Stokes parameters in the presence of convection by weighting these channels by their inverse SNR.

The design, analysis, and demonstration of a digital-correlation microwave polarimeter for use in Earth remote sensing is presented. The authors begin with an analysis of a three-level digital correlator and develop the correlator transfer function and radiometric sensitivity. A fifth-order polynomial regression is derived for inverting the digital correlation coefficient into the analog statistic. In addition, the effects of quantizer threshold asymmetry and hysteresis are discussed. A two-look unpolarized calibration scheme is developed for identifying correlation offsets. The developed theory and calibration method are verified using a 10.7 GHz and a 37.0 GHz polarimeter. The polarimeters are based upon 1-GS/s three-level digital correlators and measure the first three Stokes parameters. Through experiment, the radiometric sensitivity is shown to approach the theoretical as derived earlier in the paper and the two-look unpolarized calibration method is successfully compared with results using a polarimetric scheme. Finally, sample data from an aircraft experiment demonstrates that the polarimeter is highly useful for ocean wind-vector measurement.

An iterative algorithm incorporating CLEAN deconvolution concepts for precipitation parameter retrieval using passive microwave imagery is presented. The CLEAN algorithm was originally designed to deconvolve single-channel radio astronomy images. In order to use CLEAN to retrieve precipitation parameters from multispectral passive-microwave imagery, extensions of the algorithm to accommodate nonlinear, multispectral, and statistical data mere designed and implemented. The primary advantage of the nonlinear multispectral statistical (NMS) CLEAN retrieval algorithm relative to existing algorithms is the use of high-resolution (high-frequency) imagery to guide the retrievals of precipitation parameters from lower resolution (Low-frequency) imagery. The NMS-CLEAN retrieval algorithm was used to estimate rain rate (RR) and integrated ice content (IIC) using simulated imagery of oceanic convection as would be observed from six channels of the proposed Advanced Microwave-Scanning Radiometer. Both the accuracy and structural detail of the retrieved rain rate were improved relative to the retrievals from a single-step, nonlinear, statistical algorithm. Reduced error and improved spatial resolution of a more minor magnitude was also seen in the integrated ice-content retrievals. This study also showed that spatially-simple storm structures resulted in better performance of the NMS-CLEAN retrieval algorithm.

The use of passive 118-GHz O/sub 2/ observations of rain cells for precipitation cell-top altitude estimation is demonstrated by using a multilayer feedforward neural network retrieval system. Rain cell observations at 118 GHz were compared with estimates of the cell-top altitude obtained by optical stereoscopy. The observations were made with 2-4-km horizontal spatial resolution by using the millimeter-wave temperature sounder (MTS) scanning spectrometer aboard the NASA ER-2 research aircraft during the Genesis of Atlantic Lows Experiment (GALE) and the Cooperative Huntsville Meteorological Experiment (COHMEX) in 1986. The neural network estimator applied to MTS spectral differences between clouds, and nearby clear air yielded an rms discrepancy of 1.76 km for a combined cumulus, mature, and dissipating cell set and 1.44 km for the cumulus-only set. An improvement in rms discrepancy to 1.36 km was achieved by including additional MTS information on the absolute atmospheric temperature profile. An incremental method for training neural networks was developed that yielded robust results, despite the use of as few as 56 training spectra. Comparison of these results with a nonlinear statistical estimator shows that superior results can be obtained with a neural network retrieval system. Imagery of estimated cell-top altitudes was created from 118-GHz spectral imagery gathered from CAMEX, September through October 1993, and from cyclone Oliver, February 7, 1993.

A comparison of clear-air brightness temperatures is performed between radiometric measurements and atmospheric radiative transfer calculations. The measurements were made using the NASA Goddard Space Flight Center's Millimeter-wave Imaging Radiometer (MIR) in a series of airborne and ground-based atmospheric experiments at six millimeter-wave frequencies: 89; 150; 183.3/spl plusmn/1, /spl plusmn/3, /spl plusmn/7; and 220 GHz. With the inclusion of the 220 GHz channel, these measurements are the first passive observations of the atmosphere made simultaneously at the six frequencies. The MIR was operated concurrently with supporting meteorological instruments (radiosonde and Raman lidar) to construct a paired set of both spatially and temporally coincident calibrated brightness temperatures and atmospheric profile parameters. Calculated brightness temperatures based on the measured atmospheric profile parameters were obtained using a numerical radiative transfer model. Incremental water-vapor weighting functions were used to study the impact of radiosonde hygrometer errors on the radiative transfer calculations. The aircraft-based brightness temperature comparisons are generally within 3 K for the channels sensitive to the lower atmospheric levels (89, 150, 183.3/spl plusmn/7, and 220 GHz), but show discrepancies of up to 11 K for the opaque channels (183.3/spl plusmn/1 and /spl plusmn/3 GHz) caused primarily by radiosonde bias. The ground-based calculations are similarly found to be sensitive to hygrometer errors in the lower atmosphere. Ground-based comparisons between MIR observations and lidar-based calculations are typically within /spl plusmn/6 K.>

A numerical simulator for analysis of multispectral passive microwave mapping and retrieval is described. This simulator allows evaluation and optimization of satellite-based cloud and precipitation parameter retrieval algorithms. It contains three major components: the forward radiative transfer model, the sensor observation model, and the parameter retrieval algorithm. Simulated spaceborne observations of an oceanic tropical squall sampled at five stages in time are demonstrated for a simplified version of the proposed Earth Observation System (EOS) Multifrequency Imaging Microwave Radiometer (MIMR). The simulator uses a nonlinear statistical retrieval algorithm consisting of a Karhunen-Loeve (KL) transform, a projection operator, a nonlinear inverse mapping and a linear minimum mean-square error estimator. Retrievals of rain rate and integrated ice content are performed for each evolutionary frame at both full spatial resolution (1.5 km) and the degraded spatial resolution of a MIMR-class system. Results are presented for both KL-based and brightness temperature-based retrieval algorithms. It is found that the KL-based algorithm has a reduced complexity and performs better than the brightness temperature-based algorithm for degraded resolution imagery, especially for rain rate retrievals. In addition, rain rate retrievals are more affected by low image resolution than are integrated ice content retrievals. Retrieval accuracy of both rain and integrated ice is also found to depend on the evolutionary stage of the storm.>

Linear statistical temperature profile retrievals from nadiral passive 118-GHz O/sub 2/ spectra are demonstrated using time- and space-coincident microwave observations and radiosonde profiles. Separate retrievals are demonstrated for winter and summer midlatitude conditions in clear air over land; observations during both day and night are included. The retrieval operator is a linear-statistical minimum mean-squared-error estimator. A purely statistical retrieval operator circumvents the effects of radiative transfer model uncertainties and biases in either the radiosonde or Millimeter-wave Temperature Sounder data. The retrieved profile rms errors are approximately 0.7-1.2 K for either the winter or summer tropospheres.>

Potential uses of specific extremely high frequency (EHF) and submillimeter-wave (SMMW) channels at 90, 166, 283, 220, 325, 340, and 410 GHz for passive spaceborne remote sensing of the troposphere and lower stratosphere are investigated using an iterative numerical radiative transfer model. Collectively, these channels offer potential for high spatial resolution imaging using diffraction-limited apertures of practical size, along with the ability to profile water vapor, map precipitation beneath optically opaque cloud cover, and to measure nonprecipitating cloud (e.g. cirrus) parameters. A passive airborne imaging instrument for tropospheric meteorological sensing at 90, 150, 183+or-1, 3, 7, 220, and 325+or-1, 3, 9 GHz, called the Millimeter-wave Imaging Radiometer (MIR), is described.>