Synoptic Scale Wind Field Properties From The SEASAT SASS

Pierson, Willard J.; Sylvester, Winfield B.; Salfi, R. E.

doi:10.1109/oceans.1983.1152134

Cited by 8 publications

(3 citation statements)

References 35 publications

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“…For the case of laboratory wave tank, the friction velocity u. used for calculation is from the original references. For the ocean, u. is obtained from U ~ = ~ddUlo, (A 8) where the drag coefficient (Pierson et al, 1984) is According to Longuet-Higgins (1963) and Phillips (1977), the parasitic capillary waves may be generated by the high curvature of short-gravity waves of 5 30 cm. From the observation of Klinke and J/ihne (1992) at a 5.5 m fetch under Ul0 = 2 6 -1 ms , it is found that the parasitic capillary waves are also generated by the underlying waves of 2 -5 cm, not limited in the above gravity waves.…”

Section: Discussionmentioning

confidence: 99%

Directional spectrum of wind waves: Part II—comparison and confirmation

Liu

Yan

2003

J Ocean Univ. China

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A model on the directional frequency spectrum of wind waves for deep water is introduced. The comparisons of the proposed model with other existing models show that the proposed model is very close to the JONSWAP model and DHH model for describing the developing waves under the normal spectral bandwidth, and has a better description for the transition of the unidirectional spectrum from co -4 to co -s at a position around 3cop, i.e., three time the peak frequency. Comparisons also show that the proposed model describes closely both field data measured by a four-frequency radar and a laser-optical sensor, and laboratory data measured by a laser slope gauge and an imaging optical method. The comparisons further demonstrate that the inverse spectral bandwidth as a new wave parameter is robust for describing the spectral steepness. Finally, the formula on the local spectral-peak angular frequency is confirmed using the observed two-dimensional spectra.based on the laboratory observations of Jfihne and Riemer (1990) and Klinke and Jfihne (1992). The directional spreading function, D (r k ), is given by D(r = sechZ(p~)/S sech2(t3r162 (4) with 10 [ 04408393(~p)-0567]

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Section: Discussionmentioning

confidence: 99%

Directional spectrum of wind waves: Part II—comparison and confirmation

Liu

Yan

2003

J Ocean Univ. China

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“…Further details, including data on the various fields that can be obtained, on the error structure of SASS winds can be found in Pierson et al [1984]. Further details, including data on the various fields that can be obtained, on the error structure of SASS winds can be found in Pierson et al [1984].…”

Section: Most Of the Data Consisting Of The Sass Dealiased Winds In Omentioning

confidence: 99%

Aspects of the determination of winds by means of scatterometry and of the utilization of vector wind data for meteorological forecasts

Pierson¹,

Sylvester²,

Donelan³

1986

J. Geophys. Res.

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Research applicable to measuring winds with a scatterometer and the subsequent use of the data is briefly summarized. Data that demonstrate that (Ū(λ/2)/C(λ)) − 1, which is a quantity closely related to the normal stress, is more closely correlated to the nondimensionalized wave spectrum at L band, (ϕ(ω)ω5/g2), than either Ū(19.5) or u*, which is related to the shear stress, are given. The SOS wind recovery algorithm is shown to fail for light winds (given the power law assumption) and to bias climatological wind data. The data from a scatterometer are far too dense to be used in a synoptic scale analysis. Properties of superobservations to be used for synoptic scale analyses at a 1° resolution are derived and shown to produce very accurate wind fields, given that the scatterometer winds are correct. Superobservations are shown to yield reliable estimates of the horizontal component of the divergence and the curl of the wind stress. Disadvantages of a plus or minus 3‐hour data window for scatterometer data assimilation are described.

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“…Again, Robertson and Thomas (1983) take these theoretical concepts further and Pierson et al (1984) provide a theoretical introduction to scatterometer measurements. They also present some case studies from the Gulf of Alaska experiment.…”

Section: Pta Lgo(g/g O) L4>amentioning

confidence: 99%

An introductory review of the measurement of ocean surface wind vectors with a satellite radar scatterometer

Thomas¹,

Minnett

1986

International Journal of Remote Sensing

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A brief introduction is given to the field of remote measurement of the surface wind vector field over the ocean usingradar scatterometry from satellites.A summary of the physical processes involved in the measurement is given, together with a reviewof recent studiesto employ thesedata in numericalweather prediction modelling, and suggestions are advanced for some future simulation studies.The emphasis here is on the data obtained by SEASAT. The intent is that such data may be used to develop and refine integrated analysis programmes that can take increased advantage of the scatterometer data streams that are planned to be available from ERS-I and N-ROSS commencing in 1989.

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Synoptic Scale Wind Field Properties From The SEASAT SASS

Cited by 8 publications

References 35 publications

Directional spectrum of wind waves: Part II—comparison and confirmation

Directional spectrum of wind waves: Part II—comparison and confirmation

Aspects of the determination of winds by means of scatterometry and of the utilization of vector wind data for meteorological forecasts

An introductory review of the measurement of ocean surface wind vectors with a satellite radar scatterometer

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