Absolute Calibration of Jason-1 and Envisat Altimeter Ku-Band Radar Cross Sections from Cross Comparison with TRMM Precipitation Radar Measurements

Tran, N.; Zanifé, O. Z.; Chapron, Bertrand; Vandemark, D.; Vincent, Patrick

doi:10.1175/jtech1791.1

Cited by 9 publications

(4 citation statements)

References 44 publications

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“…Caudal et al [38] suggested that, compared with altimeters, in contrast with TOPEX, TRMM PR is biased by +1.2 dB whereas GEOdetic SATellite (GEOSAT) is biased by −0.7 dB. Tran et al [39] demonstrated that PR data (version 5) are lower in magnitude by approximately 1.46 dB than those of JASON-1 and larger by approximately 1.40 dB than ENVISAT measurements.…”

Section: A Satellite Datamentioning

confidence: 99%

Relationships Between Ku-Band Radar Backscatter and Integrated Wind and Wave Parameters at Low Incidence Angles

Chu

Karaev

2012

IEEE Trans. Geosci. Remote Sensing

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By using ten years of collocated Precipitation Radar and buoy data, the relationships between Ku-band normalized radar cross section (σ • ) and integrated wind and wave parameters (e.g., significant wave height, wave period, wave steepness, and wave age) at low incidence angles are analyzed for different sea states using correlation and dependence analysis. The results show that the relationships are significantly different for different sea states. Second, the potential for inverting these parameters directly from a single σ • is investigated. The results reveal that the retrieval of wind speed above 10 m (U 10 ) is most suitable for a nonpure-swell sea and that the performance of significant wave height (H s ) retrieval decreases with the ratio of swell to wind waves. For wave period and wavelength, a feasible inversion can only be performed for a wind-wave-dominated sea. Wave steepness (δ a ) is strongly correlated with σ • in all sea states and can even be higher than that for U 10 in pure-swell seas. It is suggested from the present data set that real wave age (β) may be retrieved from a swell-dominated sea and, therefore, has a low-value cutoff. Furthermore, the extent to which U 10 retrieval depends on sea state is examined by calculating the correlation coefficient between σ • residuals and various standard wave parameters and, then, by determining the partial correlation coefficient between σ • and each wave parameter controlled by U 10 . Both results indicate that wind direction is better taken into account above 13.5 • . Moreover, an auxiliary parameter related to wave slope, such as wave steepness, would help to improve retrieval performance. Significant wave height data are of secondary use, but an implementation with real wave age information might not significantly improve wind speed retrieval. To improve the performance of H s and wave period retrieval, auxiliary information, such as wind speed, wave steepness, or wave age, is needed. Finally, multivariable empirical models are proposed.Index Terms-Integral wave parameter, low-incidence-angle remote sensing, radar cross section, radar signal analysis.

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Section: A Satellite Datamentioning

confidence: 99%

Relationships Between Ku-Band Radar Backscatter and Integrated Wind and Wave Parameters at Low Incidence Angles

Chu

Karaev

2012

IEEE Trans. Geosci. Remote Sensing

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“…To develop a new algorithm we start by observing trends using the combined collocated data from the six altimeters, a total of 30,733 data points. Differences in calibration between altimeters are small, of the order of tenths of meters for H s and tenths of decibels for σ 0 , and the greater number of data points makes trends in the data easier to observe (absolute calibrations of H s against buoy data are given in , and relative calibrations of σ 0 can be found in the work of, e.g., Callahan et al [1994] and Tran et al [2005]). Since different period parameters are useful for different applications ( T z is often used for ocean engineering, while T e is used for wave energy applications), we will consider how altimeter measurements relate to both T z and T e .…”

Section: Development Of the New Period Algorithmmentioning

confidence: 99%

A parametric model for ocean wave period from K_u band altimeter data

Mackay¹,

Retzler²,

Challenor³

et al. 2008

J. Geophys. Res.

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[1] Using a large collocated data set of altimeter and buoy measurements, we examine the relationship between the altimeter Ku-band measurements of significant wave height, H s , backscatter coefficient, s 0 , and the buoy wave period. This is used to derive an empirical altimeter wave period model for TOPEX, Poseidon, Jason-1, ERS-2, Envisat, and GEOSAT follow-on. We show that there is a step change in the response of s 0 at around 13 dB and above this value s 0 is not related to wave period. The results are compared to algorithms proposed by two previous authors (Gommenginger et al., 2003;Quilfen et al., 2004) and examined in terms of absolute accuracy (RMS error), ability to replicate the joint distribution of wave height and period, and residual trends with various parameters. The new algorithm is shown to perform better than the previous algorithms in all metrics considered. Finally, we demonstrate that there is a limiting accuracy achievable for a function of the form f(H s , s 0 ) and that our model comes close to this.Citation: Mackay, E. B. L., C. H. Retzler, P. G. Challenor, and C. P. Gommenginger (2008), A parametric model for ocean wave period from K u band altimeter data,

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“…As already demonstrated in previous analysis (e.g. [ 15 , 11 , 16 ]), our methodology is based on a co-location strategy. Here, we took advantage of the availability of an extensive collocation dataset between radar cross-section measurements and independent wind fields from the European Centre for Medium-Range Weather Forecasts (ECMWF) model surface wind analyses.…”

Section: Introductionmentioning

confidence: 99%

Combined Wind Vector and Sea State Impact on Ocean Nadir-Viewing Ku- and C-Band Radar Cross-Sections

Tran

Chapron

2006

Sensors

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Abstract:The authors report the first results in studying the polarization anisotropy of the microwave backscatter from nadir observations provided by Jason-1 altimeter in both Kuand C-band. A small but clear wind direction signal for wind speeds above 6 m/s is revealed. These azimuthal variations of radar cross-section increase with increasing wind speed up to 14 m/s. The signatures then level off at higher winds. These results extend, for the first time, recent theoretical improved scattering approximation, and point some similarities between scattering and emission mechanisms at nadir. The observed directional effect can thus be interpreted as a signature of the curvature anisotropy of wind-generated short-scale waves. Sensitivities to both wind speed and sea state are also reported in the present analysis.

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Absolute Calibration of Jason-1 and Envisat Altimeter Ku-Band Radar Cross Sections from Cross Comparison with TRMM Precipitation Radar Measurements

Cited by 9 publications

References 44 publications

Relationships Between Ku-Band Radar Backscatter and Integrated Wind and Wave Parameters at Low Incidence Angles

Relationships Between Ku-Band Radar Backscatter and Integrated Wind and Wave Parameters at Low Incidence Angles

A parametric model for ocean wave period from K_u band altimeter data

Combined Wind Vector and Sea State Impact on Ocean Nadir-Viewing Ku- and C-Band Radar Cross-Sections

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Absolute Calibration of Jason-1 and Envisat Altimeter Ku-Band Radar Cross Sections from Cross Comparison with TRMM Precipitation Radar Measurements

Cited by 9 publications

References 44 publications

Relationships Between Ku-Band Radar Backscatter and Integrated Wind and Wave Parameters at Low Incidence Angles

Relationships Between Ku-Band Radar Backscatter and Integrated Wind and Wave Parameters at Low Incidence Angles

A parametric model for ocean wave period from Ku band altimeter data

Combined Wind Vector and Sea State Impact on Ocean Nadir-Viewing Ku- and C-Band Radar Cross-Sections

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Product

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A parametric model for ocean wave period from K_u band altimeter data