Wind direction over the ocean determined by an airborne, imaging, polarimetric radiometer system

Laursen, Brian Søgaard; Skou, N.

doi:10.1109/36.934086

Cited by 20 publications

(13 citation statements)

References 7 publications

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“…4) Viewing geometry: Only incidence angles of 25 and 35 have been used in the derivation of SST because of the smaller errors associated with sea surface emissivity uncertainty, reflected down-welling atmospheric radiance, and pointing errors [8]. Actual SST and its total error have been calculated from the CE312 radiometric measurements and the meteorological parameters collected from November 15 to December 23, 2000, and from January 8 to 13,2001. SST error are generally below 0.2 K. These results have been compared with the sea temperatures registered by the oceanographic buoys and the AVHRR for four different dates (Fig.…”

Section: Analysis Of Ir Radiometric Datamentioning

confidence: 99%

“…This conclusion is not definitive and is being addressed specifically by the LOSAC campaign. 4 In the past years, improved methods have been developed to model the polarimetric emission of the sea surface [11]- [13] and retrieved wind speed vector. However, these models have been developed or tuned at higher frequencies, typically 19 and 37 GHz.…”

Section: A Incidence Angle and Azimuth Signaturesmentioning

confidence: 99%

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Sea surface emissivity observations at L-band: first results of the Wind and Salinity Experiment WISE 2000

Camps

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Etcheto

et al. 2002

IEEE Trans. Geosci. Remote Sensing

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Abstract-Sea surface salinity can be measured by passive microwave remote sensing at L-band. In May 1999, the European Space Agency (ESA) selected the Soil Moisture and Ocean Salinity (SMOS) Earth Explorer Opportunity Mission to provide global coverage of soil moisture and ocean salinity. To determine the effect of wind on the sea surface emissivity, ESA sponsored the Wind and Salinity Experiment (WISE 2000). This paper describes the field campaign, the measurements acquired with emphasis in the radiometric measurements at L-band, their comparison with numerical models, and the implications for the remote sensing of sea salinity.

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Section: Analysis Of Ir Radiometric Datamentioning

confidence: 99%

Section: A Incidence Angle and Azimuth Signaturesmentioning

confidence: 99%

Sea surface emissivity observations at L-band: first results of the Wind and Salinity Experiment WISE 2000

Camps

Font

Etcheto

et al. 2002

IEEE Trans. Geosci. Remote Sensing

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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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“…8, 10.7, 18.7, 23.8, and 37.0 GHz are similar to those of the AMSR-E sensor except that WindSat does not have an 89 GHz channel. The frequencies at 10.7, 18.7, and 23.8 GHz are fully polarized, and these polarization signals contain a small dependence on wind direction that can be used for wind vector retrievals [Yueh et al, 1995;Laursen and Skou, 2001]. WindSat covers a 1025 km active swath and provide both fore and aft views of the swath.…”

Section: Windsatmentioning

confidence: 99%

Insights on the OAFlux ocean surface vector wind analysis merged from scatterometers and passive microwave radiometers (1987 onward)

Jin

2014

JGR Oceans

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A high-resolution global daily analysis of ocean surface vector winds (1987 onward) was developed by the Objectively Analyzed air-sea Fluxes (OAFlux) project. This study addressed the issues related to the development of the time series through objective synthesis of 12 satellite sensors (two scatterometers and 10 passive microwave radiometers) using a least-variance linear statistical estimation. The issues include the rationale that supports the multisensor synthesis, the methodology and strategy that were developed, the challenges that were encountered, and the comparison of the synthesized daily mean fields with reference to scatterometers and atmospheric reanalyses. The synthesis was established on the bases that the low and moderate winds (<15 m s 21 ) constitute 98% of global daily wind fields, and they are the range of winds that are retrieved with best quality and consistency by both scatterometers and radiometers. Yet, challenges are presented in situations of synoptic weather systems due mainly to three factors: (i) the lack of radiometer retrievals in rain conditions, (ii) the inability to fill in the data voids caused by eliminating rainflagged QuikSCAT wind vector cells, and (iii) the persistent differences between QuikSCAT and ASCAT high winds. The study showed that the daily mean surface winds can be confidently constructed from merging scatterometers with radiometers over the global oceans, except for the regions influenced by synoptic weather storms. The uncertainties in present scatterometer and radiometer observations under high winds and rain conditions lead to uncertainties in the synthesized synoptic structures.

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Wind direction over the ocean determined by an airborne, imaging, polarimetric radiometer system

Cited by 20 publications

References 7 publications

Sea surface emissivity observations at L-band: first results of the Wind and Salinity Experiment WISE 2000

Sea surface emissivity observations at L-band: first results of the Wind and Salinity Experiment WISE 2000

Polarimetric Microwave Remote Sensing of Hurricane Ocean Winds

Insights on the OAFlux ocean surface vector wind analysis merged from scatterometers and passive microwave radiometers (1987 onward)

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