The Dependence of Sea Brightness Temperature on Surface Wind Direction and Speed. Theory and Experiment

Irisov, V.; Kuźmin, Alexey V.; Pospelov, M.N.; Trokhimovsky, J.G.; Étkin, V. S.

doi:10.1109/igarss.1991.579317

Cited by 34 publications

(7 citation statements)

References 2 publications

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“…This transition was particularly championed by Naval Research Laboratory (NRL) because of the importance of ocean winds to naval operations. At almost the same time as the first SSM/I launch, it was recognized that the polarization of the microwave emission from the ocean's surface varies with wind direction (Irisov et al, 1992; but also reported earlier by V.S. SSM/I is a conically scanning imager that sweeps out a wide swath at a constant incidence angle so that environmental products can be cast in terms of images of the earth over a 1400 km wide swath.…”

Section: Microwate Radiometry and Ocean Surface Windsmentioning

confidence: 76%

Future Directions in Ocean Remote Sensing

Schwartz¹

2004

mar technol soc j

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A B S T R A C TEnormous advances in ocean science and applications have already occurred in part because of the emergence of remote sensing. This paper is an informal set of general predictions about the future of ocean remote sensing. Future directions will include changes in emphasis between equities and the evolution of sensor technologies, and in platforms. There will be more emphasis and capability in coastal remote sensing and in applications oriented toward commerce, natural resources exploitation and environmental stewardship. There will be the operationalization and continued evolution of special purpose ocean remote sensing satellites and of the sensor systems on weather satellite systems. This evolution will be toward both more capability and toward enabling these assets to increase the number and type of measurements from core sensors. New ocean remote sensing platforms will emerge that are either more appropriate to emerging sensor systems or to coastal applications. These will include aircraft and geosynchronous satellite systems for LIDAR, passive microwave, and hyperspectral sensors but will also include commercial imaging satellites.

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Section: Microwate Radiometry and Ocean Surface Windsmentioning

confidence: 76%

Future Directions in Ocean Remote Sensing

Schwartz¹

2004

mar technol soc j

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“…2003.810203 et al [2] and Yueh et al [3]. The inversion of polarimetric ocean microwave emission anisotropies for one-and two-dimensional ocean wind vector imaging was first demonstrated by Piepmeier and Gasiewski [4] via using tripolarimetric measurements at 10.7 and 37 GHz.…”

Section: A Calibration Methods For Fully Polarimetricmentioning

confidence: 99%

“…Based on the formulation for a tripolarimetric radiometer [11] the complete output response of a fully polarimetric radiometer can be written as (2) where is video output response vector; and consist of radiometer gain and offset parameters; and is the instrument noise referred to the video outputs. The off-diagonal elements of represent interchannel crosstalk, which can be the result of one or more hardware limitations, including a) limited polarization isolation in the antenna, b) cross-talk in the video or microwave circuitry, c) unbalance or cross-talk in the correlator, depending on the correlator type and configuration, and d) phase imbalances in the predetected signals used to measure or .…”

Section: A General Requirements For Fully Polarimetric Calibrationmentioning

confidence: 99%

A calibration method for fully polarimetric microwave radiometers

Lahtinen

Gasiewski

Klein

et al. 2003

IEEE Trans. Geosci. Remote Sensing

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Abstract-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.

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“…With the potential of being an alternate technique to active microwave radar, the passive microwave polarimetry for surface wind vector measurements has been investigated in the range of wind speed from 3 to 15 m/s by many aircraft field campaigns [1][2][3][4][5][6][7]. Based on these experimental observations, the US Navy together with the National Polar Orbiting Environmental Satellite System (NPOESS) launched the WindSat with multi-frequency polarimetric radiometers in January 2003 to demonstrate the passive polarimetry for large spatial coverage of ocean surface wind vector measurements from space.…”

Section: Introductionmentioning

confidence: 99%

Polarimetric Microwave Remote Sensing of Hurricane Ocean Winds

Yueh

2006

2006 IEEE International Symposium on Geoscience and Remote Sensing

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We presente the analysis of Windsat data for hurricanes Isabel and Fabian in 2003. The polarimetric third and fourth 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.

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The Dependence of Sea Brightness Temperature on Surface Wind Direction and Speed. Theory and Experiment

Cited by 34 publications

References 2 publications

Future Directions in Ocean Remote Sensing

Future Directions in Ocean Remote Sensing

A calibration method for fully polarimetric microwave radiometers

Polarimetric Microwave Remote Sensing of Hurricane Ocean Winds

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