Evaluation of hurricane ocean vector winds from WindSat

The ability to accurately measure ocean surface wind vectors from space in all weather conditions is important in many scientific and operational usages. One highly desirable application of satellite-based wind vector retrievals is to provide realistic estimates of tropical cyclone intensity for hurricane monitoring. Historically, the extreme environmental conditions in tropical cyclones (TCs) have been a challenge to traditional space-based wind vector sensing provided by microwave scatterometers. With the advent of passive microwave polarimetry, an alternate tool for estimating surface wind conditions in the TC has become available. This paper evaluates the WindSat polarimetric radiometer's ability to accurately sense winds within TCs. Three anecdotal cases studies are presented from the 2003 Atlantic Hurricane season. Independent surface wind estimates from aircraft flights and other platforms are used to provide surface wind fields for comparison to WindSat retrievals. Results of a subjective comparison of wind flow patterns are presented as well as quantitative statistics for point location comparisons of wind speed and direction.     

A Comparison of the Impact of QuikScat and WindSat Wind Vector Products on Met Office Analyses and Forecasts

Several studies have demonstrated that retrievals of wind vectors from the WindSat polarimetric radiometer are of sufficient quality to be considered for assimilation in operational numerical weather prediction models. In this paper, WindSat data are used in a state-of-the-art global meteorological analysis and forecasting system. Each wind vector contains a directional ambiguity and so is assimilated in a similar way to that of scatterometer data. The forecast impact of using analyses containing information from WindSat data was investigated for a period during August and September of 2005, when a large number of tropical cyclones were present. Forecast errors were reduced in the surface pressure fields, and the average improvement across the forecast range was found to be 1.0%. This is comparable to the improvement of 1.1% found in the same fields when winds were assimilated from the QuikScat scatterometer. The impact on tropical cyclone tracks in the forecasts was also studied. The scatterometer improved (reduced) the track errors markedly by 25% in the analyses. When impacts across the forecast range out to five days were also included, the improvement was found to be 8%. In contrast, the assimilation of WindSat data improved the analysis track errors by 7%, although this figure was found to be 10% across the complete forecast range.      

The accuracy of preliminary WindSat vector wind measurements: comparisons with NDBC buoys and QuikSCAT

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/spl deg/ for the "NESDIS0" product and 1.3 m/s and 23/spl deg/ for the more recently produced "B1" 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.     

An emissivity-based wind vector retrieval algorithm for the WindSat polarimetric radiometer

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/spl deg/ for wind speeds greater than 6 m/s and less than 15/spl deg/ 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.     

Evaluation of WindSat wind vector performance with respect to QuikSCAT estimates

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.     

Polarimetric microwave wind radiometer model function and retrieval testing for WindSat

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 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/spl deg/ for above 7-m/s wind speed. The retrieval analysis supports the consistency of the Windrad05 GMF with the WindSat data.     

Impact of rain on spaceborne Ku-band wind scatterometer data

The accuracy of Ku-band ocean wind scatterometers (i.e., NSCAT and SeaWinds) is impacted to varying degrees by rain. In order to determine how to best flag rain-contaminated wind vector cells and ultimately to calibrate out the effects of rain as much as possible, we must understand the impact of rain on the backscatter measurements that are used to retrieve wind vectors. This study uses collocated SSM/I rain rate measurements, NCEP wind fields, and SeaWinds on QuikSCAT backscatter measurements to empirically fit a simple theoretical model of the effect of rain on /spl sigma//sub 0/, and to check the validity of that model. The chief findings of the study are (1) horizontal polarization measurements are more sensitive to rain than vertical polarization, (2) sensitivity to rain varies dramatically with wind speed, and (3) the additional backscatter due to rain overshadows the rain-related attenuation.     

An updated analysis of the ocean surface wind direction signal in passive microwave brightness temperatures

We analyze the wind direction signal for vertically (v) and horizontally (h) polarized microwave radiation at 37 GHz, 19 GHz, and 11 GHz; and an Earth incidence angle of 53/spl deg/. We use brightness temperatures from SSM/I and TMI and wind vectors from buoys and the QUIKSCAT scatterometer. The wind vectors are space and time collocated with the radiometer measurements. Water vapor, cloud water and sea surface temperature are obtained from independent measurements and are uncorrelated with the wind direction. We find a wind direction signal that is noticeably smaller at low and moderate wind speeds than a previous analysis had indicated. We attribute the discrepancy to errors in the atmospheric parameters that were present in the data set of the earlier study. We show that the polarization combination 2v-h is almost insensitive to atmospheric changes and agrees with the earlier results. The strength of our new signals agrees well with JPL aircraft radiometer measurements. It is significantly smaller than the prediction of the two-scale sea surface emission model for low and intermediate wind speeds.     

Ocean surface wind speed and direction retrievals from the SSM/I

A semiempirical model is developed that retrieves ocean surface wind direction information in addition to improved wind speeds from Special Sensor Microwave/Imager (SSM/I) measurements. Radiative transfer and neural network techniques were combined in the authors' approach. The model was trained and tested using clear sky cases, but atmospheric transmittance is retrieved so that retrieval in other than clear sky conditions is possible. With two SSM/I instruments currently providing operational ocean surface wind speed retrievals, the addition of wind direction information and improved wind speed retrievals will enhance the impact of this data in weather prediction models and marine weather forecasting     

Wind speed effect on L-band brightness temperature inferred from EuroSTARRS and WISE 2001 field experiments

The results from two field experiments in the Mediterranean Sea are used to study the wind speed dependence of brightness temperature at L-band. During the EuroSTARRS airborne experiment, an L-band radiometer made measurements across a large wind speed gradient, enabling us to study this dependence at high wind speed. We compare our results with a two-scale emissivity model using several representations of the sea state spectrum. While the results are encouraging, unfortunately the accuracy of the measurements does not permit us to distinguish between the so-called twice Durden and Vesecky spectrum and the Elfouhaily spectrum above 7 m/spl middot/s/sup -1/. The effect of foam is certainly small. During the WISE 2001 field experiment carried on an oil rig, we studied this dependence at low wind speed, finding an abrupt decrease of the wind speed effect on the brightness temperature below 3 m/spl middot/s/sup -1/.     

A systematic comparison of QuikSCAT and SAR ocean surface wind speeds

We performed a systematic comparison of wind speed measurements from the SeaWinds QuikSCAT scatterometer and wind speeds computed from RADARSAT-1 synthetic aperture radar (SAR) normalized radar cross section measurements. These comparisons were made over in the Gulf of Alaska and extended over a two-year period, 2000 and 2001. The SAR wind speed estimates require a wind direction to initialize the retrieval. Here, we first used wind directions from the Navy Operational Global Atmospheric Prediction System (NOGAPS) model. For these retrievals, the standard deviation between the resulting SAR and QuikSCAT wind speed measurements was 1.78 m/s. When we used the QuikSCAT-measured wind directions to initialize the inversion, comparisons improve to a standard deviation of 1.36 m/s. We used these SAR-scatterometer comparisons to generate a new C-band horizontal polarization model function. With this new model function, the wind speed inversion improves to a standard deviation of 1.24 m/s with no mean bias. These results strongly suggest that SAR and QuikSCAT measurements can be combined to make better high-resolution wind measurements than either instrument could alone in coastal areas.     

Airborne scatterometers: investigating ocean backscatter under low and high-wind conditions

Attempting to understand and predict weather on a local and global basis has challenged both the scientific and engineering communities. One key parameter in understanding the weather is the ocean surface wind vector because of its role in the energy exchange at the air-sea surface. scatterometers, radars that measure the reflectivity of a target offer a tool with which to remotely monitor these winds from tower-, aircraft-, and satellite-based platforms. This paper introduces three current airborne scatterometer systems, and presents data collected by these instruments under low-, moderate-, and high-wind conditions. The paper focuses on airborne scatterometers because of their ability to resolve submesoscale variations in wind fields. Discrepancies between existing theory and the observations are noted and the concerns in measuring low-wind speeds discussed. Finally, the application of using this technology for estimating the surface-wind vector during a hurricane is demonstrated     

Arc root mobility on piezoelectrically actuated contacts in miniature circuit breakers

A novel contact opening mechanism has been developed using a piezoelectric actuator to open the contacts in a low contact opening velocity circuit breaker. The arc control on the contacts is critical for successful current interruption (10/sup 3/-10/sup 4/ A) in low voltage (<250V) devices. Previous work has shown how arc root commutation from the contact region into the arc chamber is affected by arc chamber materials, contact materials and the gap behind the moving contact for contact velocities between 1ms/sup -1/ and 10ms/sup -1/. This work is extended using a commercially available piezoelectric actuator to open the contacts. Contact opening speeds are assessed and the arc root mobility is characterized under this operating regime. A flexible test apparatus and solid-state high-speed arc imaging system are used to gather data on the arc root during the opening of the contacts. New experimental results are presented on the anode and cathode root velocity and arc root motion in an arc chamber with piezoelectrically actuated contact opening. These results can be used to improve the design of high current low voltage circuit breakers suitable for piezoelectric actuation.     

Simultaneous wind and rain retrieval using SeaWinds data

The SeaWinds scatterometers onboard the QuikSCAT and the Advanced Earth Observing Satellite 2 measure ocean winds on a global scale via the relationship between the normalized radar backscattering cross section of the ocean and the vector wind. The current wind retrieval method ignores scattering and attenuation of ocean rain, which alter backscatter measurements and corrupt retrieved winds. Using a simple rain backscatter and attenuation model, two methods of improving wind estimation in the presence of rain are evaluated. First, if no suitable prior knowledge of the rain rate is available, a maximum-likelihood estimation technique is used to simultaneously retrieve the wind velocity and rain rate. Second, when a suitable outside estimate of the rain rate is available, wind retrieval is performed by correcting the wind geophysical model function for the known rain via the rain backscatter model. The new retrieval techniques are evaluated via simulation and validation with data from the National Centers for Environmental Prediction and the Tropical Rainfall Measuring Mission Precipitation Radar. The simultaneous wind/rain estimation method yields most accurate winds in the "sweet spot" of SeaWinds' swath. On the outer-beam edges of the swath, simultaneous wind/rain estimation is not usable. Wind speeds from simultaneous wind/rain retrieval are nearly unbiased for all rain rates and wind speeds, while conventionally retrieved wind speeds become increasingly biased with rain rate. A synoptic example demonstrates that the new method is capable of reducing the rain-induced wind vector error while producing a consistent (yet noisy) estimate of the rain rate.     

A Wind and Rain Backscatter Model Derived From AMSR and SeaWinds Data

The SeaWinds scatterometer was originally designed to measure wind vectors over the ocean by exploiting the relationship between wind-induced surface roughening and the normalized radar backscatter cross section. Rain can degrade scatterometer wind estimation; however, the simultaneous wind/rain (SWR) algorithm was developed to enable SeaWinds to simultaneously retrieve wind and rain rate data. This algorithm is based on colocating data from the Precipitation Radar on the Tropical Rainfall Measuring Mission and SeaWinds on QuikSCAT. This paper develops a new wind and rain radar backscatter model for SWR using colocated data from the Advanced Microwave Scanning Radiometer (AMSR) and SeaWinds aboard the Advanced Earth Observing Satellite II. This paper accounts for rain height in the model in order to calculate surface rain rate from the integrated rain rate. The performance of SWR using the new wind/rain model is measured by comparison of wind vectors and rain rates to the previous SWR algorithm, AMSR rain rates, and National Center for Environmental Prediction numerical weather prediction winds. The new SWR algorithm produces more accurate rain estimates and improved winds, and detects rain with a low false alarm rate.      

Analysis of surface roughness and morphology of first-year sea ice melt ponds: implications for microwave scattering

Variations in wind forcing over summer first-year sea ice (FYI) melt ponds occur at hourly to weekly scales and are a significant contributor to microwave backscatter (/spl sigma//spl deg/) variability observed from spaceborne synthetic aperture radar (SAR) platforms (e.g., ENVISAT-ASAR and RADARSAT-1). This variability impairs our ability to use SAR to derive information on summer sea ice thermodynamic state and energy balance parameters such as albedo and melt pond fraction. The surface roughness contribution of FYI melt ponds in the Canadian Arctic Archipelago to like-polarized, C-band /spl sigma//spl deg/ estimates is analyzed through a spectral and statistical analysis of surface wave height profiles for varying wind speeds, upwind fetch lengths, and melt pond depths. A unique derivation of melt pond surface wave height spectra is presented based on digital video of melt pond surface wave trains. Significant scale surface roughness was observed even at wind speeds of 3 m/spl middot/s/sup -1/, resulting in small perturbation model estimates of /spl sigma//spl deg/ (HH) ranging from -5 dB at 20/spl deg/ incidence to -22 dB at 50/spl deg/ incidence. Results from a multivariate linear regression analysis show that 53.5% of observed variance in /spl sigma//spl deg/ (HH or VV) can be explained by wind speed, upwind fetch from melt pond edges, and melt pond depth, with no appreciable difference in the relative contribution of explanatory variables. Modeled omnidirectional /spl sigma//spl deg/ as a function of wind speed and incidence angle for 100-m transects collected throughout the melt pond season act to elaborate the role of fetch and depth, as well as the modulating effect of hummocks, on /spl sigma//spl deg/.     

Comparison of WindSat brightness temperatures with two-scale model predictions

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 0-20 m/s and for vertically integrated atmospheric water vapor concentrations from 0-70 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.     

Polarization rotation and the third Stokes parameter: the effects of spacecraft attitude and Faraday rotation

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 points to a misspecification of the reported spacecraft attitude. A single attitude correction of -0.16/spl deg/ roll and 0.18/spl deg/ 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.     

Directional analysis of SAR images aiming at wind direction

Currently, the retrieval of wind fields from synthetic aperture radar (SAR) images suffers from inadequate knowledge of the wind direction. State-of-the-art spectral analysis works fine on open seas, but is limited in spatial resolution. The method described here is based on the local gradients computed with standard image processing algorithms. It handles image features not caused by wind and can be applied to irregularly shaped regions. The new method has already been applied to many images from the European Remote sensing Satellite SARs and RADARSAT-1 ScanSAR, usually supplying reasonable wind fields. The spatial sampling most frequently used was 20 /spl times/ 20 and 10/spl times/10 km/sup 2/. In some cases, samplings down to 1/spl times/1 km/sup 2/ were tested. This paper describes the local gradients method including the filtering of nonwind generated image features and gives some application examples.     

Aircraft measurements of the microwave scattering signature of the ocean

Microwave scattering signatures of the ocean have been measured over a range of surface wind speeds from 3 m/s to 23.6 m/s using the AAFE RADSCAT scatterometer in an aircraft. Normalized scattering coefficients are presented for vertical and horizontal polarizations as a function of incidence angle (nadir to55deg) and radar azimuth angle (0degto360deg) relative to surface wind direction. For a given radar polarization, incidence angle, and azimuth angle relative to the wind direction, these scattering data exhibit a power law dependence on surface wind speed. The relation of the scattering coefficient to azimuth angle obtained during aircraft circles (antenna conical scans) is anisotropic and suggests that microwave scatterometers can be used to infer both wind speed and direction. These results have been used for the design of the Seasat-A Satellite Scatterometer (SASS) to be flown in 1978 on this first NASA oceanographic satellite.