Estimating the Sea State Bias of Jason-2 Altimeter From Crossover Differences by Using a Three-Dimensional Nonparametric Model

Jiang, Maofei; Xu, Ke; Liu, Yalong; Wang, Lei

doi:10.1109/jstars.2016.2557839

Cited by 19 publications

(6 citation statements)

References 35 publications

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“…Fig. 5(c) shows that the U10 tends to be underestimated for MWP < 6 s and overestimated for MWP > 6 s. It is shown that seastate bias for measuring the sea surface height is closely linked to MWP because the shape of the Stokes wave is dependent on the MWP [22]. This effect seems to also be effective for altimeter U10 retrieving.…”

Section: Correlation Of the U10 Errormentioning

confidence: 93%

“…In the three wave parameters, the SWH is the one that has been widely used for wind speed retrieval in previous studies (e.g., [10], [12], [15]) as it is directly available from the altimeter. In addition, algorithms have been presented to use U10, SWH, and MWP to correct sea-state bias in measuring sea surface height (e.g., [22]). This study shows that MWP is also an effective parameter in improving the accuracy of altimeter U10 retrieval.…”

Section: Retrieval Improvementmentioning

confidence: 99%

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Improving Altimeter Wind Speed Retrievals Using Ocean Wave Parameters

Jiang

Zheng

2020

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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Spaceborne altimeters are an important data source for obtaining global sea surface wind speeds (U10). Although many altimeter U10 algorithms have been proposed and they perform well, there is still room for improvement. In this study, the data from ten altimeters were collocated with buoys to investigate the error of the altimeter U10 retrievals. The U10 residuals were found to be significantly dependent on many oceanic and atmospheric parameters. Because these oceanic and atmospheric parameters are intercorrelated, an asymptotic strategy was used to isolate the impact of different parameters and establish a neural-networkbased correction model of altimeter U10. The results indicated that significant wave heights and mean wave periods are effective in correcting U10 retrievals, probably due to the tilting modulation of long-waves on the sea surface. After the wave correction, the rootmean-square error between the U10 from altimeters and buoys was reduced from 1.45 to 1.24 m/s and the impacts of thermodynamic parameters, such as sea surface (air) temperate, became negligible. The U10 residuals after correction showed that the atmospheric instability can lead to errors on extrapolated buoy U10. The buoy measurements with large air-sea temperature differences need to be excluded in the Cal/Val of remotely sensed U10.

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Section: Correlation Of the U10 Errormentioning

confidence: 93%

Section: Retrieval Improvementmentioning

confidence: 99%

Improving Altimeter Wind Speed Retrievals Using Ocean Wave Parameters

Jiang

Zheng

2020

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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“…However, the MWP is less dependent on U10 than the SWH so that the CC of the MWP is only slightly reduced after re-calibration. Figure 6c shows that the U10 tends to be underestimated for MWP < 6 s and overestimated for MWP > 6 s. It is shown that sea-state bias for measuring the sea surface height is closely linked to MWP because the shape of the Stokes wave is dependent on the MWP [22]. This effect seems to also be effective for altimeter U10 retrieving.…”

Section: Correlation Of the U10 Errormentioning

confidence: 94%

Improving Altimeter Wind Speed Retrievals Using Ocean Wave Parameters

Jiang¹,

Zheng²,

Mu³

2020

Preprint

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Spaceborne altimeters are an important data source for obtaining global sea surface wind speeds (U10). Although many altimeter U10 algorithms have been proposed and they perform well, there is still room for improvement. In this study, the data from ten altimeters were collocated with buoys to investigate the error of the altimeter U10 retrievals. The U10 residuals were found to be significantly dependent on many oceanic and atmospheric parameters. Because these oceanic and atmospheric parameters are inter-correlated, an asymptotic strategy was used to isolate the impact of different parameters and establish a neural-network-based correction model of altimeter U10. The results indicated that significant wave heights and mean wave periods are effective in correcting U10 retrievals, probably due to the tilting modulation of long-waves on the sea surface. After the wave correction, the root-mean-square error of the retrieved U10 was reduced from 1.42 m/s to 1.24 m/s and the impacts of thermodynamic parameters, such as sea surface (air) temperate, became negligible. The U10 residuals after correction showed that the atmospheric instability can lead to errors on extrapolated buoy U10. The buoy measurements with large air-sea temperature differences need to be excluded in the Cal/Val of remotely sensed U10.

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“…As an example, the map of NCEP total heat flux at 18:00 UTC on 5 July 2015 is shown in Figure 4; in this figure, triangles represent the geographic locations of the available Argos stations (>20) used in this study. In addition, SWH measurements were obtained from the altimeter Jason-2, which is a follow-on satellite to that of the Jason-1 oceanography mission of the National Aeronautics and Space Administration (NASA) and is a valuable source of global wave distributions [49]. These SWH data were used to validate the WW3-simulated SWH data.…”

Section: Methodsmentioning

confidence: 99%

A Study of Wave-Induced Effects on Sea Surface Temperature Simulations during Typhoon Events

Sun

Shao

et al. 2021

JMSE

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In this work, we investigate sea surface temperature (SST) cooling under binary typhoon conditions. We particularly focus on parallel- and cross-type typhoon paths during four typhoon events: Tembin and Bolaven in 2012, and Typhoon Chan-hom and Linfa in 2015. Wave-induced effects were simulated using a third-generation numeric model, WAVEWATCH III (WW3), and were subsequently included in SST simulations using the Stony Brook Parallel Ocean Model (sbPOM). Four wave-induced effects were analyzed: breaking waves, nonbreaking waves, radiation stress, and Stokes drift. Comparison of WW3-simulated significant wave height (SWH) data with measurements from the Jason-2 altimeter showed that the root mean square error (RMSE) was less than 0.6 m with a correlation (COR) of 0.9. When the four typhoon-wave-induced effects were included in sbPOM simulations, the simulated SSTs had an RMSE of 1 °C with a COR of 0.99 as compared to the Argos data. This was better than the RMSE and COR recovered between the measured and simulated SSTs, which were 1.4 °C and 0.96, respectively, when the four terms were not included. In particular, our results show that the effects of Stokes drift, as well as of nonbreaking waves, were an important factor in SST reduction during binary typhoons. The horizontal profile of the sbPOM-simulated SST for parallel-type typhoon paths (Typhoons Tembin and Bolaven) suggested that the observed finger pattern of SST cooling (up to 2 °C) was probably caused by drag from typhoon Tembin. SST was reduced by up to 4 °C for cross-type typhoon paths (Typhoons Chan-hom and Linfa). In general, mixing significantly increased when the four wave-induced effects were included. The vertical profile of SST indicated that disturbance depth increased (up to 100 m) for cross-type typhoon paths because the mixing intensity was greater for cross-type typhoons than for parallel-type typhoons.

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Estimating the Sea State Bias of Jason-2 Altimeter From Crossover Differences by Using a Three-Dimensional Nonparametric Model

Cited by 19 publications

References 35 publications

Improving Altimeter Wind Speed Retrievals Using Ocean Wave Parameters

Improving Altimeter Wind Speed Retrievals Using Ocean Wave Parameters

Improving Altimeter Wind Speed Retrievals Using Ocean Wave Parameters

A Study of Wave-Induced Effects on Sea Surface Temperature Simulations during Typhoon Events

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