Engineering topics
Publications and source records attributed to Freilich, Michael H..
Satellite scatterometer wind velocity measurements are a new source of data for studies of seasonal-to-interannual ocean-atmospere interactions in the Arabian Sea, where the largest and steadiest wind speeds occur in northrern summer.
One year of global surface wind products from multiple operational numerical weather prediction (NWP) forecast/analysis systems are used as comparison data to derive an empirical wind speed model function for the Geosat altimeter. The resulting model function is nearly identical to the modified Chelton-Wentz model for wind speeds from 4.5 to 15 m/s. Highly skewed distributions at low wind speeds are consistent with specular reflections and antenna mispointing errors hypothesized by others on the basis of extremely limited data. Mesoscale variability in the wind field and synoptic scale errors in the NWP products are shown to account for about 30 percent of the observed scatter of sigma(0) at each wind speed. The remaining scatter is largest at low winds, and decreases to a nearly constant value of about 12 percent at speeds greater than 7 m/s. Model function uncertainty expressed more traditionally in units of wind speed is examined for historical model functions as well as the present NWP-based model. The historical models have significant biases at high wind speeds owing to the lack of comparison in situ data used in their construction. The present study demonstrates that modern operational NWP surface wind products are sufficiently accurate to allow development of fully empirical model functions and associated error analyses.
Calculation of accurate vector winds from scatterometers requires knowledge of the relationship between backscatter cross-section and the geophysical variable of interest. As the detailed dynamics of wind generation of centimetric waves and radar-sea surface scattering at moderate incidence angles are not well known, empirical scatterometer model functions relating backscatter to winds must be developed. Less well appreciated is the fact that, given an accurate model function and some knowledge of the dominant scattering mechanisms, significant information on the amplitudes and directional distributions of centimetric roughness elements on the sea surface can be inferred. accurate scatterometer model functions can thus be used to investigate wind generation of short waves under realistic conditions. The present investigation involves developing an empirical model function for the C-band (5.3 GHz) ERS-1 scatterometer and comparing Ku-band model functions with the C-band model to infer information on the two-dimensional spectrum of centimetric roughness elements in the ocean. The C-band model function development is based on collocations of global backscatter measurements with operational surface analyses produced by meteorological agencies. Strengths and limitations of the method are discussed, and the resulting model function is validated in part through comparison with the actual distributions of backscatter cross-section triplets. Details of the directional modulation as well as the wind speed sensitivity at C-band are investigated. Analysis of persistent outliers in the data is used to infer the magnitudes of non-wind effects (such as atmospheric stratification, swell, etc.). The ERS-1 C-band instrument and the Seasat Ku-band (14.6 GHz) scatterometer both imaged waves of approximately 3.4 cm wavelength assuming that Bragg scattering is the dominant mechanism. Comparisons of the C-band and Ku-band model functions are used both to test the validity of the postulated Bragg mechanism and to investigate the directional distribution of the imaged waves under a variety of conditions where Bragg scatter is dominant.
SCANSCAT conceptual scanning radar scatterometer placed in nearly polar orbit around Earth at altitude of 705 km aboard Spacecraft B of NASA's Earth Observing System. Measures radar backscattering from surface of ocean. Data processed on ground into normalized radar-backscattering cross sections, then processed into velocities of winds near surface of ocean by use of empirical mathematical model of relationship between normalized backscattering cross section, wind vector at scanned spot, and angle of incidence and azimuth angle of radar beam. Accuracy and coverage exceeds those of fan-beam scatterometer. Modified versions of scanning plan useful in laser inspection of surface finishes on machined parts.
In this paper, the vector winds produced by the JPL and the Goddard Space Flight Center (GSFC) ambiguity removal methods are compared for 14 days of overlap, and the data are checked for any systematic differences. This comparison draws attention to some possible sources of error in each data set and provides a first-order evaluation of the quality of the two ambiguity removal techniques. It was found that the directional differences are generally small and random, so that no significant differences occurred between spatially and temporally averaged wind fields constructed from the two data sets.
The NASA scatterometer (NSCAT) is an instrument designed to measure the radar backscatter of the ocean's surface for estimating the near-surface wind velocity. A given resolution element is observed from several different azimuth angles. From these measurements the near-surface vector wind over the ocean may be inferred using a geophysical model function relating the normalized radar backscatter coefficient (sigma0) to the near-surface wind. The results of a study to select a polarization mix for NSCAT using an end-to-end simulation of the NSCAT scatterometer and ground processing of the sigma0 measurements into unambiguous wind fields using a median-filter-based ambiguity-removal algorithm are presented. The system simulation was used to compare the wind measurement accuracy and ambiguity removal skill over a set of realistic mesoscale wind fields for various polarization mixes. Considerations in the analysis and simulation are discussed, and a recommended polarization mix is given.
A method by which satellite and surface measurements can be compared in order to validate satellite wind observations is presented. The regression method requires knowledge of the expected differences (due to atmospheric variability and differing averaging) between perfect satellite and perfect buoy measurements. A model for estimating these differences is described. The regression method is applied to comparisons between Seasat Scatterometer (SASS) and U.S. National Data Buoy Office buoy data. Comparisons indicating a dependence of SASS accuracy on sea-surface temperature are summarized.
The NASA Scatterometer (NSCAT) to fly on the U.S. Navy Remote Ocean Sensing System (N-ROSS) mission is presented. The overall N-ROSS mission, the NSCAT flight instrument and groundbased data processing/distribution system, and NASA-supported science and verification activities are described. The N-ROSS system is designed to provide measurements of near-surface wind, ocean topography, wave height, sea-surface temperature, and atmospheric water content over the global oceans. The NSCAT is an improved version of the Seasat scatterometer. It will measure near surface vector winds.