| 摘要: |
| 为突破单一数据的局限, 需充分利用已有数据源开展海平面变化研究。本文基于我国首套自主研发的海洋气候数据集(Climate Data Records, CDRs), 联合长期验潮站和GNSS(Global Navigation Satellite System)观测数据, 对南海海域1993—2019年的海平面时空变化进行分析。结果表明1993—2019年南海海域海平面变化总体呈显著上升趋势: 基于CDRs数据的海平面上升速率约为3.73±0.75 mm/a; 基于验潮站数据的相对海平面平均上升速率为3.03±0.82 mm/a; 经GNSS校正后的绝对海平面上升速率在(2.68±0.48)~(4.60±0.81) mm/a, 与CDRs数据通过反距离插值计算出的海平面变化速率一致。多源观测数据的研究结果相互印证, 验证了分析的可靠性。最后对南海海域海平面变化的影响因素进行了探讨, 发现地面垂直运动和ENSO(El Niño-Southern Oscillation)对海平面变化的影响不可忽视。 |
| 关键词: 海洋气候数据集 验潮站 GNSS 时空分析 南海 |
| DOI：10.11759/hykx20231020001 |
| 分类号:P229 |
| 基金项目:国家重点研发计划项目(2016YFA0600102) |
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| Spatiotemporal variation of sea level in the South China Sea based on a combination of tide measurement stations, GNSS, and climate datasets |
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Zhang Han1, Zhao Jian1, Xu Gang1, Sun Weifu2
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1.College of Oceanography and Space Informatics, China University of Petroleum, Qingdao 266580, China;2.First Institute of Oceanography, Ministry of Natural Resources, Qingdao 266061, China
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| Abstract: |
| Based on China’s first self-developed dataset of marine climate data records (CDRs) and combined with long-term data obtained from tide measurement stations, along with Global Navigation Satellite System (GNSS) observation data, the paper analyzes the spatiotemporal characteristics of sea level variations in the South China Sea from 1993 to 2019. Based on CDR data, the sea level change in the South China Sea during 1993-2019 showed a remarkable upward trend, with a rising rate of about 3.73 ± 0.75 mm/a. The analysis of the data obtained from the tide measurement stations showed a variation in the rise rate of the sea level between −5.53 ± 1.62 mm/a and 8.52 ± 0.81 mm/a; the average rise rate was ~3.03 ± 0.82 mm/a. The absolute sea level rise rate corrected by GNSS data was between 2.68 ± 0.48 and 4.60 ± 0.81 mm/a, which was consistent with the absolute rate of the sea level variation calculated using CDRs by performing inverse distance interpolation. Finally, the influence factors of the sea level variation in the South China Sea are discussed, and it is found that the influence of vertical ground movement and El Niño-Southern Oscillation on the sea level variation cannot be ignored. |
| Key words: climate data records tide measurement station GNSS spatiotemporal analysis South China Sea |
