Volume 42 Issue 12
Dec.  2023
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Xuyang Wei, Xin Liu, Zhen Li, Xiaotao Chang, Hongxin Luo, Chengcheng Zhu, Jinyun Guo. Gravity anomalies determined from mean sea surface model data over the Gulf of Mexico[J]. Acta Oceanologica Sinica, 2023, 42(12): 39-50. doi: 10.1007/s13131-023-2178-6
Citation: Xuyang Wei, Xin Liu, Zhen Li, Xiaotao Chang, Hongxin Luo, Chengcheng Zhu, Jinyun Guo. Gravity anomalies determined from mean sea surface model data over the Gulf of Mexico[J]. Acta Oceanologica Sinica, 2023, 42(12): 39-50. doi: 10.1007/s13131-023-2178-6

Gravity anomalies determined from mean sea surface model data over the Gulf of Mexico

doi: 10.1007/s13131-023-2178-6
Funds:  The National Natural Science Foundation of China under contract Nos 42274006, 42174041 and 41774001; the Research Fund of University of Science and Technology under contract No. 2014TDJH101.
More Information
  • Corresponding author: E-mail: xinliu1969@126.com
  • Received Date: 2022-12-19
  • Accepted Date: 2023-02-28
  • Available Online: 2023-06-01
  • Publish Date: 2023-12-01
  • With the improvements in the density and quality of satellite altimetry data, a high-precision and high-resolution mean sea surface model containing abundant information regarding a marine gravity field can be calculated from long-time series multi-satellite altimeter data. Therefore, in this study, a method was proposed for determining marine gravity anomalies from a mean sea surface model. Taking the Gulf of Mexico (15°–32°N, 80°–100°W) as the study area and using a removal-recovery method, the residual gridded deflections of the vertical (DOVs) are calculated by combining the mean sea surface, mean dynamic topography, and XGM2019e_2159 geoid, and then using the inverse Vening-Meinesz method to determine the residual marine gravity anomalies from the residual gridded DOVs. Finally, residual gravity anomalies are added to the XGM2019e_2159 gravity anomalies to derive marine gravity anomaly models. In this study, the marine gravity anomalies were estimated with mean sea surface models CNES_CLS15MSS, DTU21MSS, and SDUST2020MSS and the mean dynamic topography models CNES_CLS18MDT and DTU22MDT. The accuracy of the marine gravity anomalies derived by the mean sea surface model was assessed based on ship-borne gravity data. The results show that the difference between the gravity anomalies derived by DTU21MSS and CNES_CLS18MDT and those of the ship-borne gravity data is optimal. With an increase in the distance from the coast, the difference between the gravity anomalies derived by mean sea surface models and ship-borne gravity data gradually decreases. The accuracy of the difference between the gravity anomalies derived by mean sea surface models and those from ship-borne gravity data are optimal at a depth of 3–4 km. The accuracy of the gravity anomalies derived by the mean sea surface model is high.
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  • Andersen O B, Abulaitijiang A, Zhang Shengjun, et al. 2021. A new high resolution mean sea surface (DTU21MSS) for improved sea level monitoring. In: Proceedings of EGU General Assembly 2021. Vienna: EGU,
    Andersen O B, Knudsen P, Berry P A M. 2010. The DNSC08GRA global marine gravity field from double retracked satellite altimetry. Journal of Geodesy, 84(3): 191–199. doi: 10.1007/s00190-009-0355-9
    Andersen O B, Vest A L, Knudsen P. 2005. The KMS04 multi-mission mean sea surface. In: Proceedings of Workshop: GOCINA: Improving Modelling of Ocean Transport and Climate Prediction in the North Atlantic Region Using GOCE Gravimetry. Novotel, Luxembourg: Centre European de Geodynamique et de Seimologie
    Chelton D B, Walsh E J, MacArthur J L. 1989. Pulse compression and sea level tracking in satellite altimetry. Journal of Atmospheric and Oceanic Technology, 6(3): 407–438. doi: 10.1175/1520-0426(1989)006<0407:PCASLT>2.0.CO;2
    Fairhead J D, Green C M, Odegard M E. 2001. Satellite-derived gravity having an impact on marine exploration. The Leading Edge, 20(8): 873–876. doi: 10.1190/1.1487298
    Fu L L, Cazenave A. 2001. Satellite Altimetry and Earth Sciences: A Handbook of Techniques and Applications. San Diego: Academic Press
    Gopalapillai S. 1974. Non-global recovery of gravity anomalies from a combination of terrestrial and satellite altimetry data. Columbus: Ohio State University
    Gozzard S, Kusznir N, Franke D, et al. 2019. South China Sea crustal thickness and oceanic lithosphere distribution from satellite gravity inversion. Petroleum Geoscience, 25(1): 112–128. doi: 10.1144/petgeo2016-162
    Guo Jinyun, Chang Xiaotao, Hwang C, et al. 2010. Oceanic surface geostrophic velocities determined with satellite altimetric crossover method. Chinese Journal of Geophysics, 53(6): 926–934. doi: 10.1002/cjg2.1563
    Guo Jinyun, Luo Hongxin, Zhu Chengcheng, et al. 2022. Accuracy comparison of marine gravity derived from HY-2A/GM and CryoSat-2 altimetry data: a case study in the Gulf of Mexico. Geophysical Journal International, 230(2): 1267–1279. doi: 10.1093/gji/ggac114
    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. doi: 10.1007/s001900050169
    Hwang C, Chang E T Y. 2014. Seafloor secrets revealed. Science, 346: 32–33. doi: 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. doi: 10.1111/j.1365-246X.1995.tb07013.x
    Ismael M. 2014. Tectonostratigraphic stages in the Mesozoic opening and subsidence of the Gulf of Mexico based on deep-penetration seismic reflection data in the salt-free eastern part of the basin [dissertation]. Houston: University of Houston
    Jin Taoyong, Li Jiancheng. 2012. Calibration of the linear drift of mean sea level change from satellite altimetry using tide gauge observations. Geomatics and Information Science of Wuhan University (in Chinese), 37(10): 1194–1197. doi: 10.13203/j.whugis2012.10.020
    Li Zhen, Guo Jinyun, Ji Bing, et al. 2022a. A review of marine gravity field recovery from satellite altimetry. Remote Sensing, 14(19): 4790. doi: 10.3390/rs14194790
    Li Yang, Guo Jinyun, Sun Yu, et al. 2022b. Inversion of global sea level change and its component contributions by combining time-varying gravity data and altimetry data. Acta Geodaetica et Cartographica Sinica, 51(8): 1768–1778. doi: 10.11947/j.AGCS.2022.20210169
    Liu Liang, Jiang Xiaoguang, Liu Shanwei, et al. 2016. Calculating the marine gravity anomaly of the South China Sea based on the inverse stokes formula. IOP Conference Series: Earth and Environmental Science, 46: 012062. doi: 10.1088/1755-1315/46/1/012062
    Mulet S, Rio M H, Etienne H, et al. 2021. The new CNES-CLS18 global mean dynamic topography. Ocean Science, 17(3): 789–808. doi: 10.5194/os-17-789-2021
    Pujol M I, Schaeffer P, Faugère Y, et al. 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. doi: 10.1029/2017JC013503
    Rapp R H. 1979. Geos 3 data processing for the recovery of geoid undulations and gravity anomalies. Journal of Geophysical Research: Solid Earth, 84(B8): 3784–3792. doi: 10.1029/JB084iB08p03784
    Sandwell D, Garcia E, Soofi K, et al. 2013. Toward 1-mGal accuracy in global marine gravity from CryoSat-2, Envisat, and Jason-1. The Leading Edge, 32(8): 892–899. doi: 10.1190/tle32080892.1
    Sandwell D T, Müller R D, Smith W H F, et al. 2014. New global marine gravity model from CryoSat-2 and Jason-1 reveals buried tectonic structure. Science, 346(6205): 65–67. doi: 10.1126/science.1258213
    Sandwell D T, Smith W H F. 1997. Marine gravity anomaly from Geosat and ERS 1 satellite altimetry. Journal of Geophysical Research: Solid Earth, 102(B5): 10039–10054. doi: 10.1029/96jb03223
    Smith G N. 1974. Mean gravity anomaly prediction from terrestrial gravity data and satellite altimetry data [dissertation]. Columbus: The Ohio State University Columbus
    Stanev E V, Peneva E L. 2001. Regional sea level response to global climatic change: Black Sea examples. Global and Planetary Change, 32(1): 33–47. doi: 10.1016/S0921-8181(01)00148-5
    Wan Xiaoyun, Yu Jinhai. 2013. Mean dynamic topography calculated by GOCE gravity field model and CNES-CLS2010 mean sea surface height. Chinese Journal of Geophysics (in Chinese), 56(6): 1850–1856. doi: 10.6038/cjg20130607
    Yang Junjun, Jekeli C, Liu Lintao. 2018. Seafloor topography estimation from gravity gradients using simulated annealing. Journal of Geophysical Research: Solid Earth, 123(8): 6958–6975. doi: 10.1029/2018jb015883
    Yuan Jiajia, Guo Jinyun, Zhu Chengcheng, et al. 2021. High-resolution sea level change around China seas revealed through multi-satellite altimeter data. International Journal of Applied Earth Observation and Geoinformation, 102: 102433. doi: 10.1016/j.jag.2021.102433
    Yuan Jiajia, Guo Jinyun, Zhu Chengcheng, et al. 2023. SDUST2020 MSS: A global 1′ × 1′ mean sea surface model determined from multi-satellite altimetry data. Earth System Science Data, 15(1): 155–169. doi: 10.5194/essd-15-155-2023
    Zaron E D. 2019. Simultaneous estimation of ocean tides and underwater topography in the Weddell Sea. Journal of Geophysical Research: Oceans, 124(5): 3125–3148. doi: 10.1029/2019JC015037
    Zhu Chengcheng, Guo Jinyun, Hwang C, et al. 2019. How HY-2A/GM altimeter performs in marine gravity derivation: assessment in the South China Sea. Geophysical Journal International, 219(2): 1056–1064. doi: 10.1093/gji/ggz330
    Zhu Chengcheng, Guo Jinyun, Yuan Jiajia, et al. 2021. Refining altimeter-derived gravity anomaly model from shipborne gravity by multi-layer perceptron neural network: a case in the South China Sea. Remote Sensing, 13(4): 607. doi: 10.3390/rs13040607
    Zhu Chengcheng, Guo Jinyun, Yuan Jiajia, et al. 2022. SDUST2021GRA: Global marine gravity anomaly model recovered from Ka-band and Ku-band satellite altimeter data. Earth System Science Data, 14(10): 4589–4606. doi: 10.5194/essd-14-4589-2022
    Zingerle P, Pail R, Gruber T, et al. 2020. The combined global gravity field model XGM2019e. Journal of Geodesy, 94(7): 66. doi: 10.1007/s00190-020-01398-0
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