SEARCH · Search NASA
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Satellite wind scatterometers are microwave radar instruments designed specifically to measure near-surface wind speed and direction over the global ocean.
Winds over the ocean modulate the air-sea fluxes of heat, moisture, gases and particulates, regulating the crucial coupling between atmosphere and ocean that establishes and maintains global and regional climate. Global mapping (using spaceborne scatterometers) of ocean wind is crucial for many oceanographic and atmospheric studies. An overview of polarimetric wind radiometer (new) technology is given.
This paper investigates the theory of polarimetric passive remote sensing of wind-generated sea surfaces. A two-scale polarimetric scattering and emission model of sea surfaces is developed to interpret existing active and passive remote sensing microwave signatures of sea surfaces, and to investigate the potential application of polarimetic radiometry to ocean surface winds.
Global mapping of near surface ocean winds is crucial for many meteorological, oceanographic and atmospheric studies. The microwave emission from the ocean surface is elliptically polarized and the degree of polarizationand angle is a function of the surface wind speed and direction...A summary of all the ocean polarimetric data vs. wind speed and incidence angle from three flights in 1994 and eight flights in 1995 is presented.
Explore the source record for details and available documents.
The synergism of active and passive microwave techniques for hurricane ocean wind remote sensing is explored. We performed the analysis of Windsat data for Atlantic hurricanes in 2003-2005. The polarimetric third Stokes parameter observations from the Windsat 10, 18 and 37 GHz channels were collocated with the ocean surface winds from the Holland wind model, the QuikSCAT wind vectors and the Global Data Assimilation System (GDAS) operated by the National Center for Environmental Prediction (NCEP). The collocated data were binned as a function of wind speed and wind direction, and were expanded by sinusoidal series of the relative azimuth angles between wind and observation directions. The coefficients of the sinusoidal series, corrected for atmospheric attenuation, have been used to develop an empirical geophysical model function (GMF). The Windsat GMF for extreme high wind compares very well with the aircraft radiometer and radar measurements.
The Ku-band dual-polarized backscatter signatures of ocean surfaces are described in this article with the airborne scatterometer measurements collected in the Hurricane Ocean Wind Experiment in September 1997.
We utilize ocean 10-m wind speed (U 10m ) from the microwave Multi-sensor Advanced Climatology data set to examine the coupling between convective cloud and precipitation processes, synoptic state, and U 10m and to evaluate the representation of U 10m in global climate models (GCMs). We find that midlatitude U 10m is underestimated by GCMs relative to observations. We examine two potential mechanisms to explain this model behavior: cold pool formation in cold air outbreaks (CAOs) associated with downdrafts that enhance U 10m and sea surface temperature (SST) gradients affecting U 10m through thermally forced surface winds at regional scales. When the effects of the CAO index (M) and SST gradients on U 10m are accounted for, a relationship between GCM horizontal resolution and U 10m appears. The strongest correlation between resolution and U 10m is over the western boundary currents characterized by frequent CAOs atop strong SST gradients which drives the strongest surface fluxes on Earth.
Results from Seasat-A scatterometer (SASS) remote sensing of oceanic wind vectors are reviewed, together with the theory of radar backscattering. The SASS was designed to measure the surface wind stress and neutral stability wind vector at 19.5 m altitude. Requirements included windspeeds from 4-24 m/sec to within 2 m/sec or 10%, a 1000 km swath, directions from 0-360 deg to within 20 deg, a 50 km resolution cell, and cross-track and along-track spacing between resolution cells of 100 km. The method was based on Bragg scattering of microwaves from cm-length capillary ocean waves. The strength of the backscatter is proportional to the capillary wave amplitude, which is in equilibrium with the ocean surface wind speed. The measurement grouping, least-squares estimator, and dB deviation model function table for the SASS geophysical algorithm are discussed. Comparisons of SASS, GOASEX, and ground truth wind data are made, and a 0.92 correlation between SASS and ground truth data is determined from regression analysis.
Information about ocean weather is extracted from radar returns with aid of special algorithm. Algorithm determines wind-speeds and wind directions at ocean surface, and from this information can locate low- and high-pressure centers, convergence regions, and zones of strong winds and wind shear associated with ocean weather system fronts.
The retrieval of ocean-surface wind speed from different channel combinations of Seasat SMMR measurements is demonstrated. Wind speeds derived using the best two channel subsets (10.6 H and 18.0 V) were compared with in situ data collected during the Joint Air-Sea Interaction (JASIN) experiment and an rms difference of 1.5 m/s was found. Global maps of wind speed generated with the present algorithm show that the averaged winds are arranged in well-ordered belts.
Explore the source record for details and available documents.
Simulation results show that a scatterometer design using two pencil beams scanning at different incidence angles measures the near-surface oceanic winds from a satellite better under most conditions than previous designs. The return signals from the ocean surface are much stronger than those from the fan beams used previously. Performance on a polar-orbiting satellite is compared with that of a fan beam spaceborne scatterometer. A wider and continuous swath is covered. The improvement in performance is higher at low wind speeds, so it is particularly suitable for measuring the low-mean-speed tropical wind fields. Performance on a low altitude tropic-orbiting platform such as the Space Station is also shown.
Initial estimates of ocean surface wind speed and direction based on observations of reflected Global Positioning System (GPS) signals are presented and compared to QuikSCAT wind fields. The two wind speed estimates are generally in agreement to within 2-3 m/s, and under favorable conditions of well developed seas and stable winds, direction estimates agree to within 10 deg. An overview of the GPS technique is presented as well as a presentation and discussion of these first results.
Satellite scatterometers are active microwave radars designed to yield measurements of near surface horizontal wind velocity over the ocean. Scatterometers are unique in that they are the only existing microwave remote sensing instruments that allow measurements of both wind speed and wind direction. NASA will fly a scatterometer, NSCAT, aboard the Navy Ocean Remote Sensing System (N-ROSS) mission starting in late 1990. N-ROSS is a spaceborne ocean remote sensing system with a planned mission life of three years. In addition to the NSCAT, N-ROSS will have three other microwave instruments mounted on a single satellite flying in a near polar orbit: an altimeter; a special sensor microwave/imager (SSM/I); and a low frequency microwave radiometer. The NSCAT to be flown on N-ROSS is described.
This paper investigates the theory of polarimetric passive remote sensing of wind-generated sea surfaces and the potential application of polarimetric radiometry to ocean surface winds.
The scatterometer on the National Oceanic Satellite System (NOSS) is studied by means of Monte Carlo techniques so as to determine the effect of two additional antennas for alias (or ambiguity) removal by means of an objective criteria technique and a normalized maximum likelihood estimator. Cells nominally 10 km by 10 km, 10 km by 50 km, and 50 km by 50 km are simulated for winds of 4, 8, 12 and 24 m/s and incidence angles of 29, 39, 47, and 53.5 deg for 15 deg changes in direction. The normalized maximum likelihood estimate (MLE) is correct a large part of the time, but the objective criterion technique is recommended as a reserve, and more quickly computed, procedure. Both methods for alias removal depend on the differences in the present model function at upwind and downwind. For 10 km by 10 km cells, it is found that the MLE method introduces a correlation between wind speed errors and aspect angle (wind direction) errors that can be as high as 0.8 or 0.9 and that the wind direction errors are unacceptably large, compared to those obtained for the SASS for similar assumptions.