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The objective of this paper is to examine the link between the attenuation coefficients and the interferometric phase center heights, for several frequencies from P- to L-band, and to study the extent to which it depends on the canopy architecture and description. This paper relies on the use of a coherent and full polarimetric scattering model, which simulates the fields backscattered by a forested area. In the first part, we study the behavior with a frequency of the interferometric phase center heights, and in the second part, we focus on the attenuation coefficients. Then, we compare the behaviors of these two quantities, and we propose to empirically derive a relation between these two quantities and the mean forest height. Finally, we investigate if a change in the initial forest or radar configuration has an impact on the determination of this relation. [ABSTRACT FROM AUTHOR]

This paper addresses the capability of synthetic aperture radar and optical images in combination with theoretical models to detect the vegetation water content (VWC) at field level. In this paper, a retrieval algorithm for the estimation of VWC from AirSAR acquired on vegetated fields during the SMEX'02 experiment is addressed. The aforementioned campaign has been chosen because, along with sensor observations, extensive ground truth measurements were acquired. The retrieval procedure, which is based on a Bayesian approach, has been initially developed for soil moisture extraction, It consists of two modules: one is pertinent to bare soils and the other one has been modified for vegetated fields. The last one uses the synergy with optical images to correct for the contribution of VWC. The VWC, a variable in the inversion procedure, as well as soil moisture can be estimated. The results indicate a good correlation with both ground measurements and VWC calculated from Landsat images through the use of normalized difference water index (NDWI). Furthermore, in the inversion procedure, the introduction of the dependence on roughness improves the estimates. This indicates that, even for dense vegetation, the contribution from bare soil greatly influences the radar signal. Three main levels of VWC are discriminated in the inversion procedure: values below 1 kg/m², values between 1 and 3 kg/m², and values greater than 3 kg/m². [ABSTRACT FROM AUTHOR]

This paper discusses the application and adaptation of two existing operational algorithms for land surface emissivity (ϵ) retrieval from different operational satellite/airborne sensors with bands in the visible and near-infrared (VNIR) and thermal IR (TIR) regions: 1) the temperature and emissivity separation algorithm, which retrieves ϵ only from TIR data and 2) the normalized-difference vegetation index thresholds method, in which ϵ is retrieved from VNIR data. [ABSTRACT FROM AUTHOR]

Sea surface salinity can be remotely measured by means of L-band microwave radiometry. However, the brightness temperature also depends on the sea surface temperature and on the sea state, which is probably today one of the driving factors in the salinity retrieval error budgets of the European Space Agency's Soil Moisture and Ocean Salinity (SMOS) mission and the NASA—Comisión Nacional de Actividades Espaciales Aquarius/SAC-D mission. This paper describes the Passive Advanced Unit (PAU) for ocean monitoring. PAU combines in a single instrument three different sensors: an L-band radiometer with digital beamforming (DBF) (PAU-RAD) to measure the brightness temperature of the sea at different incidence angles simultaneously, a global positioning system (GPS) reflectometer [PAU-reflectometer of Global Navigation Satellite Signals (GNSS-R)] also with DBF to measure the sea state from the delay-Doppler maps, and two infrared radiometers to provide sea surface temperature estimates. The key characteristic of this instrument is that both PAU-RAD and the PAU-GNSSIR share completely the RFIIF front-end, and analog-to-digital converters. Since in order to track the GPS-reflected signal, it is not possible to chop the antenna signal as in a Dicke radiometer, a new radiometer topology has been devised which makes uses of two receiving chains and a correlator, which has the additional advantage that both PAU-RAD and PAU-GNSSIR can be operated continuously and simultaneously to perform the sea-state corrections of the brightness temperature. This paper presents the main characteristics of the different PAU subsystems, and analyzes in detail the PAU-radiometer concept. [ABSTRACT FROM AUTHOR]

Transmissions from ground-based systems in C- and X-bands present a significant challenge to the use of these bands for passive microwave remote sensing from aircraft and satellites. Because future missions plan to continue to use these frequencies, it is important to characterize and understand the nature of interference in as much of the candidate spectrum as possible. This paper presents a statistical analysis of interference observed in the continental U.S. using six months of data collected from the C- and X-band channels of the WindSat microwave radiometer. Our findings are consistent with those of previous studies by Li et a!. and Njoku et aL, which are based on data obtained from the Advanced Microwave Scanning Radiometer-EOS using somewhat similar center frequencies and bandwidths. Results show significant radio-frequency interference (RFI) at C-band, including brightnesses in horizontal and vertical polarizations in excess of 330 K, while X-band RFI is less obvious through direct examination of measured linearly polarized brightnesses. Evidence of lower levels of RFI is provided through use of the spectral and polarization indexes of Li et a!., which reveal likely RFI contributions at X-band as well. Further confirmation of X-band RFI is obtained through analysis of the polarimetric channels, which are shown to provide direct evidence of RFI in contrast to the linearly polarized channels. A temporal analysis of the largest C-band RFI sources is also provided in an attempt to further understand their properties. [ABSTRACT FROM AUTHOR]

Every year, floods cause enormous damage and loss of human life all over the world. Regarding the European Union, extreme floods are the most common types of natural disasters (44% of the total in the last decade), and in the future, the number of flash floods is expected to rise. Recent works of the authors have focused on the development of a straightforward and efficient processing algorithm for analyzing and mapping flood damages using optical remotely sensed satellite data and digital terrain models. In this paper, some improvements of the processing technique, both regarding the flood mapping and the water depth estimation, are presented. With respect to the first issue, a new data transformation is introduced, replacing the spectral-temporal principal component analysis (STPCA) with the spectral-temporal minimum noise fraction (STMNF) transformation, while the peak water depth is obtained through more sophisticated interpolation methods. The STMNF-based technique was applied to the data collected for the worst flood of the 20th Century that struck Piemonte Region, Italy, in 1994. Regarding the flood mapping, the STMNF method allowed an overall accuracy of 97.09% with a kappa coefficient of 0.889 to be established, obtaining a user accuracy of 85.76%, and a producer accuracy of 95.96%, with a lower commission error if compared to the previous STPCA method. Regarding the water depth computation, the best results were obtained using the second-order composed splines interpolator, obtaining an overall agreement with ground reference data of about 83%. [ABSTRACT FROM AUTHOR]

How to process phase singular points (SPs), or residues, is a difficult problem in a 2-D phase unwrapping process to generate digital elevation maps (DEMs). Although the minimum-cost network-flow method is an effective and widely used technique, some problems still remain. That is, the method often generates spikes in high SP density areas and long clifflike artifacts for isolated SPs. It also takes a long time to unwrap phase data that contain many SPs. In this paper, we propose a new unwrapping method, namely, singularity-spreading phase unwrapping (SSPU), which solves these problems. In this method, we spread the singularity at SPs around to make the closely located positive and negative SPs combine gently with each other or make the isolated SPs fade away. Experiments demonstrate that the spreading process compensates the distortion in phase values in the vicinities of SPs appropriately for landscape reconstruction. The SSPU generates high-quality DEMs with smaller calculation costs than the conventional method. Besides the simple SSPU, we also present weighted SSPU where we utilize amplitude information to improve the performance further. In addition, we discuss the relationship between landscape characteristics and SSPU performance. [ABSTRACT FROM AUTHOR]

Yueh proposed a method of using the third Stokes parameter TU to correct brightness temperatures such as Tv and Th for polarization rotation. This paper presents an extended error analysis of the estimation of Tv, Th, and TQ Tv - Th by Yueh's method. In order to carry out the analysis, we first develop a forward model of polarization rotation that accounts for the random nature of thermal radiation, receiver noise, and (to first order) calibration. Analytic formulas are then derived for the bias, standard deviation (STD), and root-mean-square error (RMSE) of estimated TQ, Tv, and Th, as functions of scene and radiometer parameters. These formulas are validated through independent calculation via Monte Carlo simulation. Examination of the formulas reveals that: 1) natural TU from planetary surface radiation, of the magnitude expected on Earth at L-band, has a negligible effect on correction for polarization rotation; 2) RMSE is a function of rotation angle Ω, but the value of Ω that minimizes RMSE is not known prior to instrument fabrication; and 3) if residual calibration errors can be sufficiently reduced via postlaunch calibration, then Yueh's method reduces the error incurred by polarization rotation to negligibility. [ABSTRACT FROM AUTHOR]

This paper addresses the estimation of adjacency effect in ground spectrum and Landsat-5 pixels. The adjacency effect influences the digital number value of a pixel by adding surface surrounding scatter signals and path scatter signals at the sensor. Along with the increasing use of satellite high-resolution imagery and quantitative remote sensing, much attention has been paid to the experimental measurement and estimation of the natural phenomena of adjacency effects. Based on the theory of radiation transfer, a procedure was designed to measure the reflectance from the surface target materials and the materials in a box which is 1.5 m above the surface to avoid upwelling reflectance. At every 3 × 3 sites, the measurement was carried out during 10:30 to 13:30 of local time at the Guanting Remote Sensing Test Site in north Beijing. The results show that the adjacency effect becomes stronger from visible, near infrared to shortwave infrared wavelength; the adjacency effect weakens with the increase of distance between testing site. At last, the adjacency effect of Landsat-5 image was corrected, and the quality of the resulting image was improved. [ABSTRACT FROM AUTHOR]

It has been proposed that wind vector information derived from passive microwave radiometry may provide an impact on numerical weather forecasts of similar magnitude to that achieved by scatterometers. Polarimetric radiometers have a lower sensitivity to wind direction than scatterometers at low wind speed but comparable sensitivity at high windspeed. In this paper, we describe an experiment which aimed to determine if an observing system only capable of providing wind direction information at wind speeds over 8 ms-1 can provide comparable impact to one providing wind vectors at wind speeds over 2 ms-1. The QuikSCAT dataset used in the experiments has a wide swath and is used operationally by several forecast centers. The results confirm that assimilation of wind vectors from QuikSCAT only for wind speeds above 8 ms-1 gives similar analysis increments and forecast impacts to assimilating wind vectors at all wind speeds above 2 ms-1. Measurements from the WindSat five frequency polarimetric radiometer are compared with calculations from Met Office global forecast fields, and this also confirms that WindSat measurement and radiative transfer model accuracy appears to be sufficiently good to provide useful information for numerical weather prediction. [ABSTRACT FROM AUTHOR]

Passive microwave radiometric (PMW) observations of clouds from multichannel imaging sensors onboard low Earth-orbiting environmental satellites are now a vital operational dataset. The first operational passive microwave sensor was the Special Sensor Microwave/lmager onboard the Defense Meteorological Satellite Program satellites, which has been gathering hydrological data records since 1987, and continued with the Tropical Rainfall Measuring Mission (TRMM) and the Advanced Microwave Scanning Radiometer onboard Aqua. These sensors view the underlying scene with an Earth incidence angle near 53° and with a variable azimuthal angle, depending upon the orbit direction and scan position. The WindSat sensor onboard the Coriolis satellite, launched in January 2003, is a five-channel polarimetric PMW radiometer designed to optimize ocean surface wind vector retrievals. While it does not have 85-GHz channels, an added feature is its unique fore-aft viewing capability across a portion of its fore scan swath. This provides a view of the underlying scene from two separate azimuthal directions, which provides added information on the three-dimensional (3-D) structure of clouds and their evolution. In this paper, we compare WindSat and TRMM Precipitation Radar observations of tropical cyclones (TCs) with Monte Carlo radiative transfer simulations performed on idealized 3-D convective cloud structures. The TC 3-D structure and possible tilt in the convective cloud structure are inferred from the difference between the 37-GHz equivalent blackbody brightness temperatures (TB) from the corresponding fore and aft view observations. The information gained from this analysis is important since asymmetries in the cloud vertical and horizontal structure may be an indication of upper level wind shear, which plays a major role in influencing changes of the TC intensity. [ABSTRACT FROM AUTHOR]

The WindSat instrument was launched on January 6, 2003 as part of a risk reduction effort to assess the potential of using spaceborne fully polarimetric radiometry to measure the marine wind vector. Microwave radiometry on the Special Sensor Microwave/Imager onboard the Defense Meteorological Satellite Program satellites has long provided wind speed measurements. Fully polarimetric radiometry offers the additional possibility of obtaining wind direction as well. By contrast, the QuikSCAT satellite uses active microwave measurements to estimate the wind vector from space. It represents the most comprehensive satellite dataset against which to compare WindSat measurements. In this paper, we systematically compare temporally and spatially coincident WindSat and QuikSCAT wind vector measurements against the design goals of the WindSat instrument, taking into consideration expected differences related to instrument precision and the spatial and temporal variability of the wind field. [ABSTRACT FROM AUTHOR]

Radio-frequency interference (RFI) in the spaceborne multichannel radiometer data of WindSat and the Advanced Microwave Scanning Radiometer-EOS is currently being detected using a spectral difference technique. Such a technique does not explicitly utilize multichannel correlations of radiometer data, which are key information in separating RFI from natural radiations. Furthermore, it is not optimal for radiometer data observed over ocean regions due to the inherent large natural variability of spectral difference over ocean. In this paper, we first analyzed multivariate WindSat and Scanning Multichannel Microwave Radiometer (SMMR) data in terms of channel correlation, information content, and principal components of WindSat and SMMR data. Then two methods based on channel correlation were developed for RFI detection over land and ocean. Over land, we extended the spectral difference technique using principal component analysis (PCA) of RFI indices, which integrates statistics of target emission/scattering characteristics (through RFI indices) and multivariate correlation of radiometer data into a single statistical framework of PCA. Over ocean, channel regression of X-band can account for nearly all of the natural variations in the WindSat data. Therefore, we use a channel regression-based model difference technique to directly predict RFI-free brightness temperature, and therefore RFI intensity. Although model difference technique is most desirable, it is more difficult to apply over land due to heterogeneity of land surfaces. Both methods improve our knowledge of RFI signatures in terms of channel correlations and explore potential RFI mitigation, and thus provide risk reductions for future satellite passive microwave missions such as the NPOESS Conical Scanning Microwave Imager/Sounder. The new RFI algorithms are effective in detecting RFI in the C. and X.band Windsat radiometer channels over land and ocean. [ABSTRACT FROM AUTHOR]

Postlaunch calibration of the WindSat polarimetric microwave radiometer indicates the presence of thermal gradients across the calibration warm load during some portions of the year. These gradients are caused by reflected solar illumination or eclipse and increase total calibration errors. This paper describes the WindSat warm load and presents the measured on-orbit data which clearly illustrate the anomalous responses seen in the warm load calibration data. Detailed thermal modeling predictions of the WindSat on-orbit performance are presented along with the satellite orbital geometry model with solar inputs in order to explain the physical causes of the thermal gradients. To reduce the resultant calibration errors during periods of anomalous warm load behavior, a correction algorithm was developed which uses the physical temperatures of the gain stages in the receiver electronics to calculate an effective gain. This calibration algorithm is described, and its performance and expected accuracy are examined. [ABSTRACT FROM AUTHOR]

The WindSat microwave polarimetric radiometer consists of 22 channels of polarized brightness temperatures operating at five frequencies: 6.8, 10.7, 18.7, 23.8, and 37.0 GHz. The 10.7-, 18.7-, and 37.0-GHz channels are fully polarimetric (vertical/horizontal, ±45° and left-hand and right-hand circularly polarized) to measure the four Stokes radiometric parameters. The principal objective of this Naval Research Laboratory experiment, which flies on the USAF Coriolis satellite, is to provide the proof of concept of the first passive measurement of ocean surface wind vector from space. This paper presents details of the on-orbit absolute radiometric calibration procedure, which was performed during of a series of satellite pitch maneuvers. During these special tests, the satellite pitch was slowly ramped to +45° (and -45°), which caused the WindSat conical spinning antenna to view deep space during the forward (or aft portion) of the azimuth scan. When viewing the homogeneous and isotropic brightness of space (2.73 K) through both the main reflector and the cold-load calibration reflector, it is possible to determine the absolute calibration of the individual channels and the relative calibration bias between polarimetric channels. Results demonstrate consistent and stable channel calibrations (with very small brightness biases) that exceed the mission radiometric calibration requirements. [ABSTRACT FROM AUTHOR]

An improved Backus—Gilbert resampling scheme is developed and applied on Advanced Microwave Scanning Radiorneter-EOS (AMSR-E) brightness temperature swath data. The new resampling scheme has two improvements over the Special Sensor Microwave Imager and AMSR-E resampling schemes currently used to produce standard brightness products. First, the use of a circular Gaussian footprint as the reference footprint achieves near-circular synthesized footprints for all channels. The near-circular synthesized footprints diminish the effect of different orientations of the synthesized elliptical footprints produced by the standard algorithm. Second, a better synthesized footprint spatial resolution for the 6.925- and 10.65-GHz channels in the across scan direction is achieved with a significant reduction in noise level. Oversampling by AMSR-E at these frequencies enables this improvement. [ABSTRACT FROM AUTHOR]

Synthetic aperture radar interferometry is limited by temporal and geometrical decorrelation. Permanent scatterers (PSs) are helpful to overcome these problems, but their density in agricultural and out-of-town areas is not always sufficient. The forthcoming availability of satellite platforms with thinner orbital tubes and shorter revisit times will enhance the use of interferogram stacks, which are usable for distributed and progressively decorrelating targets, like those found in agricultural areas. To estimate the possibilities of the interferogram stack technique, a Markovian model for the temporal decorrelation is considered. ERS-l data measured in C-band over Rome with a three-day repeat cycle are used to identify the parameters for this model, namely, the decorrelation time (estimated as 40 days) and the short-term coherence (estimated as 0.6). In the hypothesis of small deviations from a model of the motion, the optimal weights to be used to combine a sequence of interferograms taken at intervals that are shorter than the decorrelation time are calculated in the cases of progressive and sinusoidal ground motion. The dispersion of the optimal estimate of the motion is then determined. This model is extended to frequencies other than C-band. These evaluations are compared with the known results obtained for PSs. As an example, the case of a time interval between the takes of T = 12 days is considered. With N consecutive images, interferogram stack results are equivalent to PSs if the pixel count in the window used to smooth the interferograms grows with N². [ABSTRACT FROM AUTHOR]

The University of Michigan Microwave Geophysics Group participated in the Cold Lands Processes Experiment from February to April 2003 by deploying its Truck Mounted Radiometer System-3 (TMRS-3) to perform temporal monitoring of the snow pack at the local scale observation site (LSOS). The LSOS was located at the Fraser Experimental Forest headquarters in the mountains near Fraser, CO. The small clearing in which the TMRS-3 was deployed was adjacent to tall evergreen trees. To quantify the amount of the downwelling brightness from these trees onto the snow pack, the TMRS-3 periodically observed these trees. Microwave brightness data were collected from the trees every 15° from horizontal incidence to 45° from zenith. Both polarizations were observed for 6.7, 19, and 37 GHz. A rapid decrease in brightness is evident as the radiometers were pointed progressively upward. The next May, an upward-looking hemispherical (‘fish-eye’) photograph was taken from the center of the clearing, and it reveals a significant sky background through the incomplete canopy. By superimposing Gaussian approximations to the microwave antenna gain pattern of the individual TMRS-3 radiometers onto the photograph, we estimated the amount that the main beams were filled with canopy and with sky. Comparison of the measured data to that expected for a partially filled main beam indicates that the needle-leaf canopy is roughly an isotropic emitter having emissivities at frequencies between 6.7 and 37 GHz of between 0.93 and 0.97 with air temperature as a proxy for tree temperature. [ABSTRACT FROM AUTHOR]

Superresolution mapping is a set of techniques to increase the spatial resolution of a land cover map obtained by soft-classification methods. In addition to the information from the land cover proportion images, supplementary information at the sub-pixel level can be used to produce more detailed and accurate land cover maps. The proposed method in this research aims to use fused imagery as an additional source of information for superresolution mapping using the Hopfield neural network (HNN). Forward and inverse models were incorporated in the HNN to support a new reflectance constraint added to the energy function. The value of the function was calculated based on a linear mixture model. In addition, a new model was used to calculate the local end-member spectra for the reflectance constraint. A set of simulated images was used to test the new technique. The results suggest that fine spatial resolution fused imagery can be used as supplementary data for superresolution mapping from a coarser spatial resolution land cover proportion imagery. [ABSTRACT FROM AUTHOR]

A new type of microwave radiometer detector has been developed that is capable of identifying high and low levels of radio-frequency interference (RFI) and of reducing or eliminating its effect on the measured brightness temperatures. High-level, localized RFI can be easily identified by its unnatural appearance in brightness temperature imagery. Low-level or persistent RFI can be much more difficult to identify and filter out. The agile digital detector (ADD) can discriminate between RFI and natural thermal emission signals by directly measuring higher order moments of the signal than the variance that is traditionally measured. After detection, the ADD then uses spectral filtering methods to selectively remove the RFI. ADD performance is experimentally verified in controlled laboratory tests and in the field near a commercial air traffic control radar. High-level RFI is easily identified and removed. Very low level RFI contamination, with power levels as low as the radiometric measurement uncertainty of the radiometer, is also shown to be reliably detected and removed. [ABSTRACT FROM AUTHOR]

The idea of using the Radon transform to measure the alignment of linear features in synthetic aperture radar (SAR) data has breathed new life into the ‘look displacement’ class of Doppler ambiguity resolution algorithms. In these algorithms, the slope of target energy is estimated to obtain the satellite beam pointing angle accurately enough to resolve the Doppler ambiguity. After explaining the method and adding some minor improvements, it is shown how it can work well on satellite SAR data. Then, an alternate method is developed that combines the ideas of the Radon and look displacement algorithms to obtain a computationally simpler and more accurate algorithm. In addition, the quality checks of the ‘spatial diversity’ approach are used to increase the robustness of the algorithm. Even though the algorithm was conceived for high-contrast scenes, it works remarkably well in low to medium contrast scenes as well. [ABSTRACT FROM AUTHOR]

The isotopic ratio of molecules often provides valuable information about past or presently occurring processes in the atmosphere because chemical and physical processes may give rise to isotope fractionation of molecular species. However, there are so far no published satellite measurements on the spatial and temporal variations of ozone isotopes in the stratosphere. Spectroscopic remote sensing methods can theoretically be used to observe ozone isotope fractionation on a global scale, but sufficient accuracy has not yet been achieved. A new generation of submillimeter-wave receivers employing sensitive superconductor-insulator-superconductor (SIS) detector technology will provide new opportunities for precise remote sensing measurements of ozone isotopes on a global scale. We have estimated the observation capabilities of two different SIS instruments, namely the space-station-borne Japanese Experimental Module/Sub-Millimeter-wave Limb Emission Sounder (JEM/SMILES) instrument, currently planned for launch in 2008, as well as the airborne Submillimeter wave Atmospheric Sounder/Airborne Submillimeter SIS Radiometer (SUMAS/ASUR) sensor. Measurements of the airborne sensor, conducted in 1996, are presented in order to demonstrate the detection of normal-O3 and asymmetric-18-O3 in the SMILES frequency bands. In the ideal case, JEM/SMILES has the capability to measure the ozone isotope enrichment (δMO3) in the middle stratosphere with a precision of ∼12‰∼11‰, and ∼9‰, for asymmetric-18-O3, symmetric-17-O3, asymmetric-17-O3, respectively, for a daily zonal mean product with resolution of 10° in latitude. The systematic error, including contributions of all instrumental and spectroscopic uncertainties, is estimated to be of the order of 100‰ to 200‰ and should be reduced by prelaunch laboratory measurements and in-flight calibrations. A remaining bias in the SMILES measurements will have to be quantified by dedicated validation campaigns. JEM/SMILES should then be capable to provide valuable information on the global distribution and seasonal variation of ozone isotope fractionation in the stratosphere. This new technology will allow us to shed new light on this still open issue in atmospheric sciences. [ABSTRACT FROM AUTHOR]

WindSat, the first satellite polarimetric microwave radiometer, and the NPOESS Conical Microwave Imager/Sounder both have as a key objective the retrieval of the ocean surface wind vector from radiometric brightness temperatures. Available observations and models to date show that the wind direction signal is only 1–3 K peak-to-peak at 19 and 37 GHz, much smaller than the wind speed signal. In order to obtain sufficient accuracy for reliable wind direction retrieval, uncertainties in geophysical modeling of the sea surface emission on the order of 0.2 K need to be removed. The surface roughness spectrum has been addressed by many studies, but the azimuthal signature of the microwave emission from breaking waves and foam has not been adequately addressed. Recently, a number of experiments have been conducted to quantify the increase in sea surface microwave emission due to foam. Measurements from the Floating Instrumentation Platform indicated that the increase in ocean surface emission due to breaking waves may depend on the incidence and azimuth angles of observation. The need to quantify this dependence motivated systematic measurement of the microwave emission from reproducible breaking waves as a function of incidence and azimuth angles. A number of empirical parameterizations of whitecap coverage with wind speed were used to estimate the increase in brightness temperatures measured by a satellite microwave radiometer due to wave breaking in the field of view. These results provide the first empirically based parameterization with wind speed of the effect of breaking waves and foam on satellite brightness temperatures at 10.8, 19, and 37 GHz. [ABSTRACT FROM AUTHOR]

Two preliminary, six-month long global WindSat vector wind datasets are validated using buoys and QuikSCAT measurements. Buoy comparisons yield speed and direction root mean square accuracies of 1.4 m/s and 25° for the ‘NESDIS0’ product and 13 m/s and 23° for the more recently produced ‘B 1’ product from the Naval Research Laboratory. WindSat along- and across-wind random component errors of 0.7–1.0 and 2.6–2.8 m/s (respectively) are larger than those calculated for QuikSCAT in the same period. Global WindSat-QuikSCAT comparisons generally confirmed the buoy analyses. While simple rain flags based directly on WindSat brightness temperature measurements alone are shown to overflag for rain systematically, the advanced ‘Environmental Data Record’ rain flag in the B1 product matches well with Special Sensor Microwave/Imager rain detection frequency and preserves the accuracy of the unflagged vector wind measurements. [ABSTRACT FROM AUTHOR]

The Naval Research Laboratory WindSat polarimetric radiometer was launched on January 6, 2003 and is the first fully polarimetric radiometer to be flown in space. WindSat has three fully polarimetric channels at 10.7, 18.7, and 37.0 GHz and vertically and horizontally polarized channels at 6.8 and 23.8 GHz. A first-generation wind vector retrieval algorithm for the WindSat polarimetric radiometer is developed in this study. An atmospheric clearing algorithm is used to estimate the surface emissivity from the measured WindSat brightness temperature at each channel. A specular correction factor is introduced in the radiative transfer equation to account for excess reflected atmospheric brightness, compared to the specular assumption, as a function wind speed. An empirical geophysical model function relating the surface emissivity to the wind vector is derived using coincident QuikSCAT scatterometer wind vector measurements. The confidence in the derived harmonics for the polarimetric channels is high and should be considered suitable to validate analytical surface scattering models for polarized ocean surface emission. The performance of the retrieval algorithm is assessed with comparisons to Global Data Assimilation System (GDAS) wind vector outputs. The root mean square (RMS) uncertainty of the closest wind direction ambiguity is less than 20° for wind speeds greater than 6 m/s and less than 15° at 10 m/s and greater. The retrieval skill, the percentage of retrievals in which the first-rank solution is the closest to the GDAS reference, is 75% at 7 m/s and 85% or higher above 10 m/s. The wind speed is retrieved with an RMS uncertainty of 1.5 m/s. [ABSTRACT FROM AUTHOR]

WindSat is a space-based polarimetric microwave radiometer designed to demonstrate the capability to measure the ocean surface wind vector using a radiometer. We describe a nonlinear iterative algorithm for simultaneous retrieval of sea surface temperature, columnar water vapor, columnar cloud liquid water, and the ocean surface wind vector from WindSat measurements. The algorithm uses a physically based forward model function for the WindSat brightness temperatures. Empirical corrections to the physically based model are discussed. We present evaluations of initial retrieval performance using a six-month dataset of WindSat measurements and collocated data from other satellites and a numerical weather model. We focus primarily on the application to wind vector retrievals. [ABSTRACT FROM AUTHOR]

A geophysical model function (GMF), relating the directional response of polarimetric brightness temperatures to ocean surface winds, is developed for the WindSat multifrequency polarimetric microwave radiometer. This GMF is derived from the WindSat data and tuned with the aircraft radiometer measurements for very high winds from the Hurricane Ocean Wind Experiment in 1997. The directional signals in the aircraft polarimetric radiometer data are corroborated by coincident Ku-band scatterometer measurements for wind speeds in the range of 20–35 m/s. We applied an iterative retrieval algorithm a using the polarimetric brightness temperatures from 18-, 23-, and 37-GHz channels. We find that the root-mean-square direction difference between the Global Data Assimilation System winds and the closest WindSat wind ambiguity is less than 20° for above 7-m/s wind speed. The retrieval analysis supports the consistency of the Windrad05 GMF with the WindSat data. [ABSTRACT FROM AUTHOR]

An efficient implementation of the two-scale model of sea surface thermal emission and atmospheric reflection is described. The model is applied in a study of the reflection of downwelling atmospheric radiation. Results show that reflected downwelling radiation can increase azimuthal variations of total observed brightnesses. [ABSTRACT FROM AUTHOR]

Predictions of the polarized microwave brightness temperatures over the ocean are made using a two-scale surface bidirectional reflectance model combined with an atmospheric radiative transfer model. The reflected atmospheric radiation is found to contribute significantly to the magnitude and directional dependence of the brightness temperatures. The predicted brightness temperatures are also sensitive to the form of the shortwave spectrum. Calculations are made using a new physically based model for the wave spectrum, and preliminary comparisons are made with WindSat observations at 10.7, 18.7, and 37 GHz, for wind speeds ranging from 0ߝ20 mIs and for vertically integrated atmospheric water vapor concentrations from 0ߝ70 mm. Predictions of the mean (azimuthally averaged) brightness temperatures for vertical and horizontal polarization agree quite well with WindSat observations over this range of wind speeds and water vapor concentrations. The predicted azimuthal variations of the third and fourth Stokes parameters also agree fairly well with the observations, except for the fourth Stokes parameter at 37 GHz. Further adjustments of the wave spectrum are expected to improve the agreement. [ABSTRACT FROM AUTHOR]

The third Stokes parameter of ocean surface brightness temperatures measured by the WindSat instrument is sensitive to the rotation angle between the polarization vectors at the ocean surface and the instrument. This rotation angle depends on the spacecraft attitude (roll, pitch, yaw) as well as the Faraday rotation of the electromagnetic radiation passing through the Earth's ionosphere. Analyzing the WindSat antenna temperatures, we find biases in the third Stokes parameter as function of the along-scan position of up to 1.5 K in all feedhorns. This point to a misspecification of the reported spacecraft attitude. A single attitude correction of -0.16° roll and 0.18° pitch for the whole instrument eliminates all the biases. We also study the effect of Faraday rotation at 10.7 GHz on the accuracy of the third Stokes parameter and the sea surface wind direction retrieval and demonstrate how this error can be corrected using values from the International Reference Ionosphere for the total electron content when computing Faraday rotation. [ABSTRACT FROM AUTHOR]

Geolocation and pointing accuracy analyses of the WindSat flight data are presented. The two topics were intertwined in the flight data analysis and will be addressed together. WindSat has no unusual geolocation requirements relative to other sensors, but its beam pointing knowledge accuracy is especially critical to support accurate polarimetric radiometry. Pointing accuracy was improved and verified using geolocation analysis in conjunction with scan bias analysis. Two methods were needed to properly identify and differentiate between data time tagging and pointing knowledge errors. Matchups comparing coastlines indicated in imagery data with their known geographic locations were used to identify geolocation errors. These coast-line matchups showed possible pointing errors with ambiguities as to the true source of the errors. Scan bias analysis of U, the third Stokes parameter, and of vertical and horizontal polarizations provided measurement of pointing offsets resolving ambiguities in the coastline matchup analysis. Several geolocation and pointing bias sources were incrementally eliminated resulting in pointing knowledge and geolocation accuracy that met all design requirements. [ABSTRACT FROM AUTHOR]

Absolute calibration of WindSat's third and fourth Stokes brightness temperatures (T3 and T4) is needed at the tenth of Kelvin level in order to adequately resolve their dependence on wind direction. Previous aircraft based fully polarimetric microwave radiometers have generally relied on ‘circle flights,’ during which a single area of the ocean is observed at all azimuth angles, to estimate residual biases in the calibration of its polarimetric channels. WindSat, the first spaceborne fully polarimetric microwave radiometer, operates in low earth orbit and thus cannot execute this traditional calibration technique. A new method is presented to estimate the residual biases that are present in WindSat's T3 and T4 estimates. The method uses a vicarious cold reference brightness temperature applied to measurements made by WindSat at ±45° slant linear (TP and TM) and left- and right-hand circular (TL and TR) polarization. WindSat derives the third and fourth Stokes brightness temperatures by the differences TP - TM and TL - TR, respectively. The method is demonstrated by applying it to the 10.7-GHz WindSat observations. Calibration biases of 0.2–0.6 K are determined with a precision of 0.04 K. [ABSTRACT FROM AUTHOR]