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Xinhong Xiao, Postgraduate of School of Geospatial Engineering and Science, Sun Yat-sen University, China. His main research direction is gravity field modeling and its applications.
Outline
As the largest ice sheet storage area in the world, Antarctica's gravity field characteristics are key data for studying ice sheet mass balance, sea level changes, and polar resource exploration. However, current gravity field modeling in polar regions faces two major challenges: First, the satellite orbital inclination limit (e.g., the GOCE mission has observation gaps within the latitude circle of 83.3°), which causes ill-posed problems in satellite gravity inversion. Although some studies have improved this using methods like Tikhonov regularization and spherical cap regularization, the applicability of different regularization methods in polar regions lacks systematic evaluation. Second, multi-source gravity data have frequency band limitations, and the study of frequency band characteristics in combined gravity models is relatively scarce. To address these issues, this paper utilizes international Antarctic airborne gravity datasets, including AntGG and PolarGap. It systematically evaluates the accuracy of six satellite gravity field models (such as DIR_R6 and GOCO06s) and five combined gravity models (such as EGM2008 and XGM2019e) in Antarctica, from both spatial and spectral perspectives. The study reveals the error distribution characteristics of different models in Antarctica and further quantifies the contribution characteristics of each model in different frequency bands. The results show that global gravity field models exhibit lower quality within the polar gap at the 83.3°S latitude circle, and introducing additional measurement data combined with regularization methods can significantly improve their accuracy. Additionally, among the combined gravity field models, the XGM2019e_2159 model performs best in Antarctica, and the inclusion of satellite altimetry data significantly improves its quality in oceanic regions. The findings of this study will provide experimental references for data selection and gravity field model optimization in Antarctic gravity field research.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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