The backscatter coefficient measured by satellite radar altimeters is crucial for retrieving sea surface wind speed and correcting sea state biases in sea surface height products, with its calibration directly determining altimetry accuracy. While tropical rainforests are preferred calibration sites for large-incidence-angle radars (e.g., microwave scatterometer), desert environments demonstrate superior performance in altimeter calibration. The backscattering characteristics of China’s HY-2 satellite altimeters over desert regions remain underexplored. This study focuses on HY-2C altimeter by conducting waveform retracking and statistical analysis over typical Chinese desert areas, addressing missing official data products over land surfaces. (e.g., surface elevation and backscatter coefficient). Results reveal that typical desert waveforms exhibit remarkable similarity to ocean counterparts, enabling successful backscatter coefficient retrieval through waveform retracking, with the Fast Adaptive algorithm achieving optimal performance. HY-2C’s Track 62 demonstrates excellent backscatter coefficient stability (Ku/C-band standard deviations: 0.320 dB/0.367 dB). Collinear comparisons with Jason-3 Track 166 (spatial proximityR=0.83, RMSE=0.20dB). This work enhances HY-2C’s backscatter coefficients measurement capability over desert/land surfaces, providing critical insights for future altimeter calibration site selection.

The radar altimeter onboard China's HY-2B satellite was launched in October 2018. In this paper, we processed the HY-2B L1 altimetry data from October 2020 to April 2021. The radar freeboard was preliminarily estimated from the HY-2B altimetry data over the Arctic sea ice. We validated the HY-2B radar freeboard estimates using the radar freeboard products from the Alfred Wegener Institute (AWI). The overall difference between the HY-2B radar freeboard estimates and the AWI data is$0.088\pm 0.057\ \mathrm{m}$.

The radar altimeter onboard China's HY-2B satellite was launched in October 2018. In this paper, the precision of the HY-2B elevation measurements over the Antarctica ice sheet (AIS) and the Greenland ice sheet (GrIS) is assessed through crossover analysis. The TFMRA (threshold first maximum re-tracker) algorithms is applied to retrack the waveforms of HY-2B altimeter. The precision of the HY-2B altimeter elevations is found to vary as a function of the threshold of the surface slope from$\sim 48 \text{ cm}$to$\sim 51\text{ cm}$over the AIS, and from$\sim 23\text{ cm}$to$\sim 34 \text{ cm}$over the GrIS. When compared with results obtained from time-coincident SARAL altimeter, the standard deviation of the crossover differences between the SARAL and HY-2B altimeters varies from$\sim 68 \text{ cm}$to$\sim 101 \text{ cm}$over the AIS, and from$\sim 56\text{ cm}$to$\sim 102\text{ cm}$over the GrIS.

In the grid processing of the deflection of the vertical (DOV) for marine gravity recovery, the traditional least squares collocation (LSC) gridding method only considers the accuracy difference between different satellite radar altimeters, but ignores the accuracy difference between different observation points of the same radar altimeter. In order to solve this problem, a new LSC gridding method weighted by the accuracy of observation points is proposed in this paper. The new method sets the quality parameters of each observed value according to the dispersion of the data and gives corresponding weights to each residual along-track DOV for LSC gridding based on the error propagation law. Then, based on the 1’ × 1’ gridded DOV obtained by the traditional method and the new method, the inverse Vening Meinesz formula with one-dimensional FFT and the remove and restore method were used to recover the 1’ × 1’ gridded gravity field in the South China Sea. The validation of ship-measured gravity data shows that the new DOV gridding method can effectively improve the accuracy of the marine gravity field derived from HY-2A and CryoSat-2 data. The new method is also applicable to other similar satellite altimeter data, and will bring significant improvements to the recovery of higher-precision ocean gravity fields.

This paper assesses the sea surface height (SSH), significant wave height (SWH) and wind speed (U) measurements derived from Haiyang-2B (HY-2B) altimeter products from April 2019 to September 2019. Crossover analysis is used to assess to SSH measurements. The mean standard deviations of the SSH crossover differences for HY-2B is 5.09 cm, which is lower than Jason-2 (5.31 cm) and Jason-3 (5.27 cm). Compared with the National Data Buoy Center (NDBC) observations, the HY-2B SWH measurements show a root-mean-square error (RMSE) of 0.205 m with a positive bias of 0.150 m. The HY-2B wind speed measurements show a RMSE of 1.139 m/s with a negative bias of 0.563 m/s. The SSH, SWH and wind speed measurements from HY-2B products show high accuracy, but should be further calibrated.

HY-2A (Haiyang-2A) is China's the first ocean dynamic environment satellite and is equipped with a radar altimeter as one of the primary payloads. HY-2A shifted the geodetic mission (GM) in March 2016. In this paper, we present the gravity field inverted by the HY-2A/GM data from March 2016 to December 2017 in the South China Sea (105°-125°E, 5°-25°N) with a resolution of 1'* 1'. The gravity anomaly is computed by inverse Vening-Meinesz formula with a one-dimensional FFT method during remove-restore procedure with the EGM2008 model as the reference model. In addition, the same period data of Cryosat-2 was inverted using the same method, and the NGDC shipboard gravity data was used for verification. The results show that the accuracy of HY-2A altimetry-derived gravity field is comparable to that of Cryosat-2. Meanwhile, the standard deviation between HY-2A and Cryosat-2 marine gravity field is 3.744mGal.

Since March 2016, the HY-2A satellite has swifted to the drift orbit with a repeat cycle of 168 days and has accumulated geodetic data for more than two years. This paper assesses the reprocessed sea surface height (SSH) measurements derived from the HY-2A geodetic mission (GM) data. The standard deviation of the SSH crossover differences for reprocessed HY-2A/GM data is 5.22 cm, which is close to the results from Jason-2 (5.49 cm) and Jason-3 (5.35 cm). The standard deviations of the SSH crossover differences between HY-2A and Jason-2 and Jason-3 are 5.25 cm and 5.31 cm, respectively. Sea level anomaly (SLA) power spectra analysis shows that the reprocessed HY-2A data have low noise level with respect to Jason-2 and Jason-3.

Haiyang-2B (HY-2B) is the second ocean dynamic environment satellite of China and was launched on launched on October 26th, 2018. Radar altimeter is one of HY-2B's main payloads and mainly used to provide sea surface height (SSH), significant wave height (SWH) and sea surface wind speed measurements. In this paper, the range noise level of HY-2B radar altimeter is estimated and compared with Jason-2 and Jason-3 altimeters. The noise level of HY-2B radar altimeter for an SWH of 2 m is estimated to be 1.38 cm, which is lower than those of Jason-2 and Jason-3 (1.60 cm). Sea level anomaly (SLA) power spectra analysis also shows that the HY-2B altimeter has low noise level with respect to Jason-2 and Jason-3. Therefore, the HY-2B radar altimeter has the potential to provide sea surface height measurements of high precision.

HY-2 satellites are the ocean dynamic environmental satellite series in China and the radar altimeters onboard are land-compatible ones particularly suitable for the coastal applications. In this paper, the HY-2A altimetry data are extracted and reprocessed offshore Hong Kong. The results show good agreement with the Jason-2 and tide gauge measurements, indicating the potential of HY-2A satellite altimetry in coastal applications.

This paper assesses the reprocessed sea surface height (SSH) and significant wave height (SWH, or Hs) measurements derived from Haiyang-2A (HY-2A) radar altimeter using Jason-2 and buoy observations. The mean standard deviations of the SSH crossover differences for HY-2A and Jason-2 are 5.123 cm and 5.202 cm, respectively. The mean standard deviation of the SSH crossover differences between HY-2A and Jason-2 is 5.23 cm, Compared with the National Data Buoy Center (NDBC) SWH measurements, the reprocessed HY-2A SWH measurements show a root-mean-square error (RMSE) of 0.221 m with a positive bias of 0.149 m. After calibrated with the two-branched corrections, the RMSE for the reprocessed HY-2A SWH measurements is reduced to 0.160 m, which is even lower than that for Jason-2 (0.228 m). Therefore, the reprocessed HY-2A SSH and SWH measurements are of high accuracy.

The radar altimeter onboard China's HY-2A satellite was launched in August 2011 and it can provide the surface elevation measurements from 80.6 °N to 80.6 °S. In this letter, the precision of the HY-2A elevation measurements over the Antarctica ice sheet (AIS) and the Greenland ice sheet (GrIS) is assessed through crossover analysis. We process the HY-2A sensor geophysical dataset records (SGDR) data from June 1, 2014 to June 14, 2014. The OCOG, Ice-1 and Ice-2 algorithms are applied to retrack the waveforms of HY-2A altimeter over the AIS and GrIS. Crossover analysis shows that the Ice-2 algorithm performs best among the three algorithms. The precision of the HY-2A altimeter elevations are found to vary as a function of the threshold of the surface slope from ~56 cm to ~63 cm over the AIS, and from ~29 cm to ~50 cm over the GrIS.

The sea state bias (SSB) has become the dominant source of error in satellite altimetry. The operational SSB correction models are two-dimensional (2-D) nonparametric models based on the wind speed (U) and the significant wave height (SWH) that can be directly measured by the altimeters. This paper estimates the sea state bias of HY-2A radar altimeter using a three-dimensional (3-D) nonparametric model based on SWH from HY_2A interim geophysical dataset records (IGDR), U and the mean wave period (MWP) from the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis project ERA-Interim. The 3-D SSB estimates can increase the explained variance by 1.72 cm2, or 1.31 cm RMS relative to the traditional 2-D SSB estimates based on U and SWH.