Abstract
SARAL/AltiKA (SRL) is the first altimetry satellite with a Ka-band altimeter. To validate the advantages of the Ka-band altimeter over traditional Ku-band altimeters in marine geodetic applications, a comprehensive analysis is carried out over the South China Sea (SCS) (0–30° N, 105–125° E) from three aspects, namely the influence of load on waveforms, the precision of sea surface heights (SSHs), and the precision of altimeter-derived marine gravity field. Coastal waveforms of SRL, Jason-2, and CryoSat-2 are separately compared with corresponding ocean-type waveforms. The radius of coastal influence on SSHs of SRL/exact repeat mission (SRL/ERM) is the smallest, being about 3 km. Crossover discrepancies, global mean sea surface models, and tide gauge data are used to assess the precision of altimetric SSHs. Compared with the SSH precision of Ku-band Jason-2/ERM, the SSH precision of Ka-band SRL/ERM is 4.6% higher over the SCS and 10% higher in offshore areas. Gridded gravity anomalies are derived from measurements of SRL/drifting phase (SRL/DP) and CryoSat-2 through the inverse Vening-Meinesz formula, respectively. According to the assessment by shipborne gravity data and global marine gravity models, the precision of SRL/DP-derived gravity is higher than that of CryoSat-2-derived gravity over the SCS, especially in offshore areas. In some cycles, ground tracks of SRL/ERM have large drifting of more than 10 km from nominal tracks. The results show that the Ka-band altimeter of SRL has better precision in SSHs and marine gravity recovery than the Ku-band altimeter over the SCS, particularly in offshore areas.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Code availability
The code used during the current study is available from the corresponding author on reasonable request.
References
Andersen, O. B., Jain, M., & Knudsen, P. (2015). The impact of using Jason-1 and Cryosat-2 geodetic mission altimetry for gravity field modeling. In C. Rizos & P. Willis (Eds.), IAG 150 Years. (pp. 205–210). Springer. https://doi.org/10.1007/1345_2015_95.
Andersen, O. B., Knudsen, P., & Stenseng, L. (2015). The DTU13 MSS (mean sea surface) and MDT (mean dynamic topography) from 20 years of satellite altimetry. In S. Jin & R. Barzaghi (Eds.), IGFS 2014. (pp. 111–121). Springer. https://doi.org/10.1007/1345_2015_182.
Andersen, O. B., Knudsen, P., & Stenseng, L. (2018). A new DTU18 MSS mean sea surface—improvement from SAR altimetry. 25 Years of Progress in Radar Altimetry Symposium. Abstracts, 172.
Babu, K. N. (2014). Absolute calibration of SARAL-AltiKa in Kavaratti during its initial calibration validation phase. SARAL International Science and Applications Meeting. http://www.aviso.altimetry.fr/fileadmin/documents/ScienceTeams/Saral2014/22-04-2014/Session-3/KNBabuAltiKaApril2014.pdf
Brown, G. S. (1977). The average impulse response of a rough surface and its applications. IEEE Journal of Ocean Engineering, 2(1), 67–74.
Caldwell, P. C., Merrifield, M. A., & Thompson, P. R. (2015). Sea level measured by tide gauges from global oceans—the Joint Archive for Sea Level holdings (NCEI Accession 0019568), Version 5.5. NOAA National Centers for Environmental Information, Dataset, 10: V5V40S7W
Cartwright, D. E., & Edden, A. C. (1973). Corrected tables of tidal harmonics. Geophysical Journal Royal Astronomical Society, 33(3), 253–264. https://doi.org/10.1111/j.1365-246x.1973.tb03420.x.
CNES (2016). SARAL/AltiKa products handbook. SALP-MU-M-OP-15984-CN, Issue 2.5.
CNES (2017). Along-track level-2+ (L2P) SLA product handbook. SALP-MU-P-EA-23150-CLS, Issue 1.0. https://www.aviso.altimetry.fr/fileadmin/documents/tools/hdbk_L2P_all_missions_except_S3.pdf
Desai, S., Wahr, J., & Beckley, B. (2015). Revisiting the pole tide for and from satellite altimetry. Journal of Geodesy, 89(12), 1233–1243. https://doi.org/10.1007/s00190-015-0848-7.
Guo, J., Chang, X., Hwang, C., Sun, J., & Han, Y. (2010). Oceanic surface geostrophic velocities determined with satellite altimetric crossover method. Chinese Journal of Geophysics, 53(6), 926–936. https://doi.org/10.3969/j.issn.0001-5733.2010.11.006 in Chinese.
Guo, J., Wang, J., Hu, Z., Hwang, C., Chen, C., & Gao, Y. (2015). Temporal-spatial variations of sea level over Chinese seas derived from altimeter data of TOPEX/Poseidon, Jason-1 and Jason-2 from 1993 to 2012. Chinese Journal of Geophysics, 58(9), 3103–3120. https://doi.org/10.6038/cjg20150908 in Chinese.
Hernandez, F., & Schaeffer, P. (2001). The CLS01 mean sea surface: a validation with the GSFC00.1 Surface. . CLS Ramonville.
Hsiao, Y., Hwang, C., Cheng, Y., Chen, L., Hsu, H., Tsai, J., Liu, C., Wang, C., & Kao, Y. (2016). High-resolution depth and coastline over major atolls of South China Sea from satellite altimetry and imagery. Remote Sensing of Environment, 176, 69–83. https://doi.org/10.1016/j.rse.2016.01.016.
Hwang, C. (1998). Inverse Vening Meinesz formula and deflection-geoid formula: applications to the predictions of gravity and geoid over the South China Sea. Journal of Geodesy, 72(5), 304–312. https://doi.org/10.1007/s001900050169.
Hwang, C., & Chang, E. (2014). Seafloor secrets revealed. Science, 346, 32–33. https://doi.org/10.1126/science.1260459.
Hwang, C., & Parsons, B. (1995). Gravity anomalies derived from Seasat, Geosat, ERS-1 and TOPEX/POSEIDON altimetry and ship gravity: a case study over the Reykjanes Ridge. Geophysical Journal International, 122(2), 551–568. https://doi.org/10.1111/j.1365-246X.1995.tb07013.x.
Hwang, C., Hsu, H., & Jang, R. (2002). Global mean sea surface and marine gravity anomaly from multi-satellite altimetry: applications of deflection-geoid and inverse Vening Meinesz formulae. Journal of Geodesy, 76(8), 407–418. https://doi.org/10.1007/s00190-002-0265-6.
Kosempa, M., & Chambers, D. P. (2014). Southern Ocean velocity and geostrophic transport fields estimated by combining Jason altimetry and Argo data. Journal of Geophysical Research: Oceans, 119(8), 4761–4776. https://doi.org/10.1002/2014jc009853.
Lickley, M. J., Hay, C. C., Tamisiea, M. E., & Mitrovica, J. X. (2018). Bias in estimates of global mean sea level change inferred from satellite altimetry. Journal of Climate, 31(13), 5263–5271. https://doi.org/10.1175/jcli-d-18-0024.1.
Morton, B., & Blackmore, G. (2001). South China Sea. Marine Pollution Bulletin, 42(12), 1236–1263. https://doi.org/10.1016/s0025-326x(01)00240-5.
Pavlis, N. K., Holmes, S. A., Kenyon, S. C., & Factor, J. K. (2012). The development and evaluation of the Earth Gravitational Model 2008 (EGM2008). Journal of Geophysical Research, 117(B4), B04406. https://doi.org/10.1029/2011jb008916.
Prandi, P., Philipps, S., Pignot, V., & Picot, N. (2015). SARAL/AltiKa global statistical assessment and cross-calibration with Jason-2. Marine Geodesy, 38(sp1), 297–312. https://doi.org/10.1080/01490419.2014.995840.
Pujol, M., Schaeffer, P., Faugère, Y., Raynal, M., Dibarboure, G., & Picot, N. (2018). Gauging the improvement of recent mean sea surface models: a new approach for identifying and quantifying their errors. Journal of Geophysical Research: Oceans, 123(8), 5889–5911. https://doi.org/10.1029/2017jc013503.
Rio, M., Mulet, S., & Picot, N. (2014). Beyond GOCE for the ocean circulation estimate: synergetic use of altimetry, gravimetry, and in situ data provides new insight into geostrophic and Ekman currents. Geophysical Research Letters, 41(24), 8918–8925. https://doi.org/10.1002/2014gl061773.
Sandwell, D. T., Garcia, E., Soofi, K., Wessel, P., Chandler, M., & Smith, W. H. F. (2013). Toward 1-mGal accuracy in global marine gravity from CryoSat-2, Envisat, and Jason-1. Leading Edge, 32(8), 892–899.
Sandwell, D. T., Muller, R. D., Smith, W. H. F., Garcia, E., & Francis, R. (2014). New global marine gravity model from CryoSat-2 and Jason-1 reveals buried tectonic structure. Science, 346, 65–67. https://doi.org/10.1126/science.1258213.
Sandwell, D. T., Harper, H., Tozer, B., & Smith, W. H. F. (2019). Gravity field recovery from geodetic altimeter missions. Advances in Space Research. https://doi.org/10.1016/j.asr.2019.09.011.
SARAL. (2015). Saral GDR quality assessment report cycle 024 28–05–2015/02–07–2015. SALP-RP-P2-EA-22250-CLS024, Issue 01.1.
Schaeffer, P., Faugere, Y., Legeais, J. F., Ollivier, A., Guinle, T., & Picot, N. (2012). The CNES CLS11 global mean sea surface computed from 16 years of satellite altimeter data. Marine Geodesy, 35(sp1), 3–19. https://doi.org/10.1080/01490419.2012.718231.
Shih, H., Hwang, C., Barriot, J. P., Mouyen, M., Corréia, P., Lequeux, D., & Sichoix, L. (2015). High-resolution gravity and geoid models in Tahiti obtained from new airborne and land gravity observations: data fusion by spectral combination. Earth, Planets and Space, 67(1), 124. https://doi.org/10.1186/s40623-015-0297-9.
Smith, W. H. F. (2015). Resolution of seamount geoid anomalies achieved by the SARAL/AltiKa and Envisat RA2 satellite radar altimeters. Marine Geodesy, 38(sp1), 644–671. https://doi.org/10.1080/01490419.2015.1014950.
Yuan, J., Guo, J., Liu, X., Zhu, C., Niu, Y., Li, Z., Ji, B., & Ouyang, Y. (2020). Mean sea surface model over China seas and its adjacent ocean established with the 19-year moving average method from multi-satellite altimeter data. Continental Shelf Research, 192(1), 104009. https://doi.org/10.1016/j.csr.2019.104009.
Zhang, S., & Sandwell, D. T. (2016). Retracking of SARAL/AltiKa radar altimetry waveforms for optimal gravity field recovery. Marine Geodesy, 40(1), 40–56.
Zhu, C., Guo, J., Hwang, C., Gao, J., Yuan, J., & Liu, X. (2019). How HY-2A/GM altimeter performs in marine gravity derivation: assessment in the South China Sea. Geophysical Journal International, 219(2), 1056–1064. https://doi.org/10.1093/gji/ggz330.
Zhu, C., Guo, J., Gao, J., Liu, X., Hwang, C., Yu, S., Yuan, J., Ji, B., & Bin, G. (2020). Marine gravity determined from multi-satellite GM/ERM altimeter data over the South China Sea: SCSGA V1.0. Journal of Geodesy, 94, 50. https://doi.org/10.1007/s00190-020-01378-4.
Acknowledgements
We are very grateful to AVISO and ESA for providing altimeter data. We are very grateful to NCEI and Second Institute of Oceanography of MNR, China, for providing shipborne gravimetric data. This study is supported by the National Natural Science Foundation of China (Grant Nos. 41774001, 41374009), the SDUST Research Fund (Grant No. 2014TDJH101), and Fujian Natural Science Foundation (Grant No. 2019J01649).
Funding
This study is supported by the National Natural Science Foundation of China (grant nos. 41774001, 41374009), the SDUST Research Fund (grant no. 2014TDJH101), and Fujian Natural Science Foundation (grant no. 2019J01649).
Author information
Authors and Affiliations
Contributions
X.L. and J.G. designed the research. C.Z., S.Y., and J.Y. developed the algorithm. C.Z., Y.N., Z.L., and Y.G. analyzed data. C.Z. wrote the manuscript with contributions from X.L., J.G., and J.Y. All authors were involved in discussions throughout the development.
Corresponding authors
Ethics declarations
Conflict of interest
No conflicts of interest exist in the submission of this manuscript.
Additional information
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
Zhu, C., Liu, X., Guo, J. et al. Sea Surface Heights and Marine Gravity Determined from SARAL/AltiKa Ka-band Altimeter Over South China Sea. Pure Appl. Geophys. 178, 1513–1527 (2021). https://doi.org/10.1007/s00024-021-02709-y
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00024-021-02709-y