Improving the Specular Point Positioning Accuracy of Ship-Borne GNSS-R Observations in China Seas Based on Comprehensive Geophysical Correction

The accurate modeled GNSS-R reflection delay, which is indispensable for the quantification, modeling, and correction of the GNSS-R altimetry sea-state bias, can be obtained based on the accurate modeled position of the specular point. At present, the reflection surface model of the specular point positioning still has the mean dynamic topography (MDT) error and the deviation of the vertical (DOV) error relative to the instantaneous sea surface. In this study, the following studies have been carried out. Based on the ship-borne GNSS-R observations in China seas, we introduced various elevation parameters including the MDT to correct the elevation error of the reflection surface. We introduced the DOV based on the elevation correction, and the DOV correction positioning method was proposed to correct the slope error of the reflection surface. The specular point was positioned on the instantaneous sea reflection surface. We verified the instantaneous sea reflection surface model and the specular point positioning results, analyzed the relationship between the position correction distance and the reflection incident angle, and discussed the spatial distribution characteristics of the MDT correction distance. The results showed that the reflection surface modeling and the specular point positioning were accurate. The positioning error increased to varying degrees with the increase of the reflection incident angle. The MDT correction improved the positioning by 0.91 m, and the DOV correction further improved the positioning by 0.12 m. Based on the combined application of the two kinds of correction positioning, the positioning was comprehensively improved by 0.99 m. The MDT correction of China seas gradually increased from the north to south. While in the regional sea areas, it gradually decreased from the north to south and showed randomness. The relative position between the antennas and their random changes introduced uncertainty, which can be reduced by integration. The new instantaneous sea reflection surface model and the corresponding specular point positioning method can provide accurate modeled reflection delay for the sea-state bias correction of ship-borne GNSS-R observations, and they can be extended to satellite-borne global observations.

Preliminary Significant Wave Height Retrieval from Interferometric Imaging Radar Altimeter Aboard the Chinese Tiangong-2 Space Laboratory

The interferometric imaging radar altimeter (InIRA) aboard the Chinese Tiangong-2 space laboratory is the first spaceborne imaging radar working at low incidence angles. This study focuses on the retrieval of significant wave heights (SWHs) from InIRA data. The retrieved SWHs can be used for correcting the sea state bias of InIRA-derived sea surface heights and can supplement SWH products from other spaceborne sensors. First, we analyzed tilt, range bunching and velocity bunching wave modulations at low incidence angles, and we found clear dependencies between the SWH and two defined factors, range and azimuth integration, for ocean waves in the range and azimuth directions, respectively. These dependencies were further confirmed using InIRA measurements and collocated WaveWatch III (WW3) data. Then, an empirical orthogonal SWH model using the range and azimuth integration factors as model inputs was proposed. The model was segmented by the incidence angle, and the model coefficients were estimated by fitting the collocation at each incidence angle bin. Finally, the SWHs were retrieved from InIRA data using the proposed model. The retrievals were validated using both WW3 and altimeter (JASON2, JASON3, SARAL, and HY2A) SWHs. The validation with WW3 data shows a root mean square error (RMSE) of 0.43 m, while the average RMSE with all traditional altimeter data is 0.48 m. This indicates that the InIRA can be used to measure SWHs.

Cross-Calibrations of the HY-2B Altimeter Using Jason-3 Satellite During the Period of April 2019–September 2020

In 2018, the Haiyang-2B (HY-2B) satellite altimeter was sent to orbit as a follow-up mission of the HY-2A satellite altimeter. The performance of the HY-2B system over the global oceans is considered to be critical. However, its performance is not fully known at the present time. In the present study, the first global quality assessment of the HY-2B Geophysical Data Record (GDR) was presented using comparison and crossover analysis processes of the main parameters and sea level anomalies (SLAs) with Jason-3 GDR data. This study’s assessment results demonstrated that the editing proportion of unqualified data for the HY-2B was 2.67%, which was at a similar level as the Jason-3 (2.86%). In addition, this study’s assessment results of the HY-2B key parameters (mainly the backscatter coefficients, significant wave heights, sea state bias, wet troposphere delays, and ionosphere delays) showed good agreement with the Jason-3, and there were no abnormal trends observed. The mean and standard deviations (STDs) were determined to be (0.21 ± 6.70) cm and (−3.4 ± 6.25) cm for the SLA differences at the self-crossover points of the HY-2B and dual-crossover points between the HY-2B and Jason-3 satellites, respectively. In addition, the SLA crossover analysis results indicated that the accuracy of the sea surface heights for the HY-2B was close to that of the Jason-3 satellite. The spatial distributions of the SLA differences showed no significant errors in the geographic characteristics. The SLA measurements were assessed using a wavenumber spectra method. The obtained results suggested that the power spectrum of the SLAs of the HY-2B satellite followed the regular patterns of the traditional Jason-3 altimeter. Furthermore, based on the spectrum analysis results, it was revealed that the noise level of the HY-2B was lower than that of the Jason-3, indicating a good overall performance of the HY-2B.

Improved SAR Altimetry Techniques in Coastal Island Areas

<p>Improved SAR Altimetry Techniques in Coastal Island Areas</p><p>Synthetic Aperture Radar (SAR) Altimetry has made a remarkable progress over the past years. Advances in data processing, combined with technological progress such as the advent of new Altimetry satellites (Sentinel 3A,3B,6, SWOT etc.) increased the accuracy of the retrieved geophysical parameters (i.e., Sea Level Anomaly, Significant Wave Height and Wind Speed) in coastal zones within several hundred meters from the coastline.</p><p>The improvement in the estimation of the geophysical parameters using SAR Altimetry has been reported by many researchers. The improved accuracy is obtained through the development of new SAR Altimetry retracking algorithms in several research and development projects (i.e., SAR Altimetry Mode Studies and Applications-SAMOSA).  Similar to Low Resolution Mode (LRM) Altimetry, the requirement of specialized retrackers for SAR waveforms is vital in improving the estimated ocean parameters. The waveform retracking is a postprocessing protocol to convert waveforms into scientific parameters of power amplitude (related to wind speed), range (related to sea level), and slope of leading edge (related to SWH) that characterize the observed scene (Idris et al., 2021).</p><p>However, several issues remain open. Close to the coastline, SAR altimeter simultaneously views scattering surfaces of both water and land producing complicated waveform patterns therefore a huge range of waveform shapes is observed. This complexity poses a real challenge to today’s approach to retrack waveform.</p><p>The combination of different retracking algorithms is essential for dealing with this high diversity of altimetric waveform patterns since there is no single retracker that can retrack all of them. However, this raises two significant issues. The first is regarding to the selection of the optimal retracker under various conditions. The lack of a clear guideline on the selection criteria of the optimal retracker limits the use of this combining method. The second is how to reduce the offset caused by switching retrackers, as it results in relative offsets in altimeter-derived SLAs. This offset is partly caused by the retracking method itself, in which the fitting algorithms are affected by noise in the trailing edge due to the SWHs variability (Idris et al., 2018).</p><p>Due to the issues in coastal Altimetry data the focus of this work is:</p><ul><li>1) To improve the sea measurements from the SAR Altimetry missions by developing a new retracking algorithm taking advantage artificial intelligence and machine learning technologies.</li> </ul><p> </p><ul><li>2) To further investigate the assessment of the offset between various retrackers and the use of a neural network for reducing the offset in the retracked SLAs by including information about SWH.</li> </ul><p> </p><ul><li>3) To validate the altimeter derived SLAs by performing tests and comparisons with data from many island coastal areas worldwide.</li> </ul><p>Also, this work aims to improve the Sea State Bias corrections (SSB), which is currently one of the range corrections with the largest uncertainty in the coastal zone (Vignudelli et al., 2019), by providing more accurate sea measurements near the coast.</p>

Preliminary Evaluation and Correction of Sea Surface Height from Chinese Tiangong-2 Interferometric Imaging Radar Altimeter

In this study, we performed preliminary comparative evaluation and correction of two-dimensional sea surface height (SSH) data from the Chinese Tiangong-2 Interferometric Imaging Radar Altimeter (InIRA) with the goal of advancing its retrieval. Data from the InIRA were compared with one-dimensional SSH data from the traditional altimeters Jason-2, Saral/AltiKa, and Jason-3. Because the sea state bias (SSB) of distributed InIRA data has not yet been considered, consistency was maintained by neglecting the SSB for the traditional altimeters. The results of the comparisons show that the InIRA captures the same SSH trends as those obtained by traditional altimeters. However, there is a significant deviation between InIRA and traditional altimeter SSHs; consequently, systematic and parametric biases were analyzed. The parametric bias was found to be related to the incidence angles and a significant wave height. Upon correcting the two biases, the standard deviation significantly reduced to 8.1 cm. This value is slightly higher than those of traditional altimeters, which typically have a bias of ~7.0 cm. The results indicate that the InIRA is promising in providing a wide swath of SSH measurements. Moreover, we recommend that the InIRA retrieval algorithm should consider the two biases to improve SSH accuracy.

Harmony's ocean elevation measurements: potential and performance

<p>Harmony, an Earth Explorer 10 candidate mission, consists of two receive-only Synthetic Aperture Radar (SAR) satellites using Sentinel-1D as the illuminator. The mission will switch between close formation phases and StereoSAR phases, dedicated to relative surface elevation and relative surface motion respectively. Interferometric observations of the ocean have, in the past, been hindered by the quick temporal decorrelation of the sea surface; a result of the along-track baseline that often comes with the cross-track baseline necessary for interferometry. Specialised SAR systems aiming to observe the oceans need to account for the decorrelation of the surface. SWOT overcomes the issue by fixing the two SAR antennas to physically eliminate their along-track separation. Due to the squinted, bistatic nature of the formation, Harmony can act as an altimeter, observing relative sea-surface heights (SSH) over unprecedented wide swaths. Hence, the mission promises to have highly coherent observations of the sea surface, leading to accurate surface elevation measurements. The wide swath will enable the recovery of mesoscale features of the ocean surface in a single pass. We will present the first results of the performance analysis of the mission's observations of elevation over the oceans. The effect of errors, namely the residual Doppler, baseline errors and sea-state bias, on the observations will also be discussed.</p>

Improving Sea Level Anomaly Precision from Satellite Altimetry Using Parameter Correction in the Red Sea

An improved Fourier series model (FSM01) method is used in geophysical and environmental corrections to enhance the final product of the along-track Jason-2 sea level anomaly (SLA) data and extend it near the Red Sea borders. In this study, the ionospheric correction range, wet tropospheric correction range, sea state bias correction range, and dry tropospheric correction range are enhanced and improved using FSM01, which helped to retrieve three more tracks (106, 170, and 234) earlier neglected by the distribution centers and extend the tracks toward the coast. The FSM01 SLA is compared with Jason-2 SLA and Archiving Validation and Interpretation of Satellite Oceanographic (AVISO) SLA for the available five tracks, in which the FSM01 SLA shows a good agreement and higher correlation with the Jason-2 SLA compared with that of AVISO, in addition to filling the gaps in the times series of all tracks. The newly retrieved tracks are also compared with those retrieved by AVISO, and both data points show similar variability, with FSM01 SLA showing no gaps in the time series. The FSM01 SLA was also extended toward the coast and showed high correlation with the coastal tide measurements.