Sea State Bias in Radar Altimetry Revisited

Hausman, Jessica; Zlotnicki, Victor

doi:10.1080/01490419.2010.487804

Cited by 13 publications

(6 citation statements)

References 13 publications

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“…We know that SSB corrections predominantly account for two types of error: EM bias and tracker bias. The EM bias is a physical property of the oceans and the radar wavefront, and thus common to altimeters with the same frequency [41,42]. As both JASON1 and JASON2 measure the same sea state with identical frequency, the EM bias is identical for JASON1 and JASON2 for the same period.…”

Section: Discussionmentioning

confidence: 87%

Plasmaspheric Electron Content Inferred from Residuals between GNSS-Derived and TOPEX/JASON Vertical TEC Data

et al. 2018

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Abstract:The plasmasphere, which is located above the ionosphere, is a significant component of Earth's atmosphere, and the plasmasphere electron content (PEC) distribution is determined by different physical mechanisms to those of the ionosphere electron content (IEC). However, the observation for the PEC is very limited. In this study, we introduced a methodology (called zero assumption method, which is based on the assumption that PEC can reach zero) to extract the PEC over TOPEX/JASON (T/J) and global navigation satellite system (GNSS) overlapping areas. Results show that the daily systematic bias (T/J vertical TEC > GNSS-derived vertical TEC) for both low (2009) and high (2011) solar activity condition is consistent, and the systematic bias for JASON2 and JASON1 is different. We suggest that systematic biases predominantly arise from the sea state bias (SSB), especially the tracker bias. After removing the systematic bias, we extracted reliable PEC inferred from differences between GNSS-derived vertical TEC and T/J vertical TEC data. Finally, the characteristics of the plasmaspheric component distribution for different local times, latitudes, and seasons were investigated.

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Section: Discussionmentioning

confidence: 87%

Plasmaspheric Electron Content Inferred from Residuals between GNSS-Derived and TOPEX/JASON Vertical TEC Data

et al. 2018

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“…Hausman and Zlotnicki (2010) recently tested various approaches to estimating SSB on output from an ocean model. Hausman and Zlotnicki (2010) recently tested various approaches to estimating SSB on output from an ocean model.…”

Section: Sea State Biasmentioning

confidence: 99%

Gravimetric Methods – Satellite Altimeter Measurements

Chambers

2015

Treatise on Geophysics

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“…Meanwhile, ocean waves may impact altimeter wind retrieval in many ways. For instance, wave crests are usually rougher than wave troughs, which is a very important effect for retrieving sea surface height termed electromagnetic bias (e.g., [16]). It may also impact U10 retrievals because the RCS is a "linear average" over the ~7km footprint for the 1-Hz data.…”

Section: Introductionmentioning

confidence: 99%

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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Sea State Bias in Radar Altimetry Revisited

Cited by 13 publications

References 13 publications

Plasmaspheric Electron Content Inferred from Residuals between GNSS-Derived and TOPEX/JASON Vertical TEC Data

Plasmaspheric Electron Content Inferred from Residuals between GNSS-Derived and TOPEX/JASON Vertical TEC Data

Gravimetric Methods – Satellite Altimeter Measurements

Improving Altimeter Wind Speed Retrievals Using Ocean Wave Parameters

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