从雷达和激光高度计数据中恢复的 SDUST2022GRA 全球海洋重力异常:ICESat-2 激光测高仪的贡献

IF 11.2 1区 地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY
Zhen Li, Jinyun Guo, Chengcheng Zhu, Xin Liu, Cheinway Hwang, Sergey Lebedev, Xiaotao Chang, Anatoly Soloviev, Heping Sun
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引用次数: 0

摘要

摘要。全球海洋重力异常模型主要是从沿轨雷达高度计数据中恢复的。虽然重力异常建模取得了重大进展,但重力异常模型的质量仍然受到缺乏跨轨道大地水准面梯度和雷达高度计数据减少的制约,特别是在沿海和高纬度地区。ICESat-2 激光测高仪使用三对激光束,足迹小,近极轨道,能够确定跨轨道大地水准面梯度,并在某些区域提供更有效的观测。介绍了 ICESat-2 高度计数据处理方法,包括跨轨道大地水准面梯度的确定和沿/跨轨道大地水准面梯度的组合。使用不同的方法确定每个高度计数据误差,从雷达和激光高度计数据中恢复了一个新的全球海洋重力模型SDUST2022GRA。通过已发布的全球重力异常模型(DTU17,V32.1,NSOAS22)和现有的船载重力测量数据,对 SDUST2022GRA 的精度和空间分辨率进行了评估。在全球范围内,SDUST2022GRA 的精度为 4.43 mGal,比其他模式至少高出 0.22 mGal。此外,在局部沿海和高纬度地区,SDUST2022GRA 的精度比其他模式提高了 0.16-0.24 mGal。SDUST2022GRA 的空间分辨率在一定区域内约为 20 千米,略优于其他模式。这些结果表明,SDUST2022GRA 是一个可靠的全球海洋重力异常模式。通过比较加入 ICESat-2 的 SDUST2022GRA 和不加入 ICESat-2 的 SDUST2021GRA,ICESat-2 对提高全球海洋重力异常模式精度的贡献率为 13%,并且随着 ICESat-2 高度计数据在高纬度和沿岸地区所占比例的增加而增加。SDUST2022GRA 可在 https://doi.org/10.5281/zenodo.8337387 网站上免费获取(Li 等人,2023 年)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The SDUST2022GRA global marine gravity anomalies recovered from radar and laser altimeter data: Contribution of ICESat-2 laser altimetry
Abstract. Global marine gravity anomaly models are predominantly recovered from along-track radar altimeter data. While remarkable advancements has been achieved in gravity anomaly modelling, the quality of gravity anomaly model remains constrained by the absence of across-track geoid gradients and the reduction of radar altimeter data, particularly in coastal and high-latitudes regions. ICESat-2 laser altimetry operates three-pair laser beams with a small footprint and near-polar orbit, enabling the determination of across-track geoid gradients and providing more valid observations in certain regions. The ICESat-2 altimeter data processing method is presented including the determination of across-track geoid gradients and the combination of along/across-track geoid gradients. A new global marine gravity model, SDUST2022GRA, is recovered from radar and laser altimeter data using different method for determining each altimeter data error. The accuracy and spatial resolution of SDUST2022GRA is assessed by published global gravity anomaly models (DTU17, V32.1, NSOAS22) and available shipborne gravity measurements. The accuracy of SDUST2022GRA is 4.43 mGal on a global scale, which is at least 0.22 mGal better than that of others models. Moreover, in local coastal and high-latitude regions, SDUST2022GRA achieves an accuracy improvement of 0.16–0.24 mGal compared to others models. The spatial resolution of SDUST2022GRA is approximately 20 km in a certain region, slightly better superior others models. These assessments suggests that SDUST2022GRA is a reliable global marine gravity anomaly model. By comparing SDUST2022GRA with incorporating ICESat-2 and SDUST2021GRA without ICESat-2, the percentage contribution of ICESat-2 to the improvement of gravity anomaly model accuracy is 13 % in the global ocean region, and it is increasing with an proportion of ICESat-2 altimeter data in high-latitude and coastal regions. The SDUST2022GRA are freely available at the site of https://doi.org/10.5281/zenodo.8337387 (Li et al., 2023).
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来源期刊
Earth System Science Data
Earth System Science Data GEOSCIENCES, MULTIDISCIPLINARYMETEOROLOGY-METEOROLOGY & ATMOSPHERIC SCIENCES
CiteScore
18.00
自引率
5.30%
发文量
231
审稿时长
35 weeks
期刊介绍: Earth System Science Data (ESSD) is an international, interdisciplinary journal that publishes articles on original research data in order to promote the reuse of high-quality data in the field of Earth system sciences. The journal welcomes submissions of original data or data collections that meet the required quality standards and have the potential to contribute to the goals of the journal. It includes sections dedicated to regular-length articles, brief communications (such as updates to existing data sets), commentaries, review articles, and special issues. ESSD is abstracted and indexed in several databases, including Science Citation Index Expanded, Current Contents/PCE, Scopus, ADS, CLOCKSS, CNKI, DOAJ, EBSCO, Gale/Cengage, GoOA (CAS), and Google Scholar, among others.
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