AI 中文总结
针对北美地区复杂构造活动，引入高度可扩展框架，利用标准计算资源对北美GNSS网络地壳形变进行推断，在保持性能同时实现计算增益，支持大规模监测，助力开放科学。
AI 中文摘要
地球行为的研究因全球导航卫星系统（GNSS）的广泛部署而受益匪浅，能够对地壳形变和长期地球物理趋势进行大规模监测。在这项工作中，我们聚焦于北美地区，其复杂的构造活动，特别是沿西边缘地区，需要能处理和分析分布在广阔空间域的大量GNSS时间序列的方法。分析完整的GNSS网络可提供多尺度形变的连贯视图，能检测长波长信号、细微板内应变和区域一致的速度场。尽管有此类数据，但现有方法对该地区（或其他地区）的大规模分析在计算上仍难以实现。为解决此限制，我们引入了一个高度可扩展的框架（以开源软件实现），可利用标准计算资源对整个北美GNSS网络的地壳形变进行推断。该方法在保持与现有方法相当的推断性能的同时实现了显著的计算增益，证实了现有的构造趋势，从而支持高效的大规模监测并为“开放科学”的持续努力做出贡献。
英文摘要
The study of the Earth's behavior has greatly benefited from the widespread deployment of Global Navigation Satellite Systems (GNSS), enabling large-scale monitoring of crustal deformation and long-term geophysical trends. In this work, we focus on the North American region, where complex tectonic activity, particularly along the western margin, requires methods capable of processing and analyzing large collections of GNSS time series distributed across extensive spatial domains. Analyzing the full GNSS network provides a coherent view of deformation across multiple scales, allowing detection of long-wavelength signals, subtle intraplate strain and regionally consistent velocity fields that are difficult to capture through local or subsampled analyses. Despite the availability of such data, existing methodologies remain computationally prohibitive for large-scale analyses across this region (or others). To address this limitation, we introduce a highly scalable framework (implemented in open-source software) that enables inference on crustal deformation across the full North American GNSS network using standard computational resources. The proposed method achieves substantial computational gains while maintaining inferential performance comparable to existing approaches and confirms existing tectonic trends, thereby supporting efficient large-scale monitoring and contributing to ongoing efforts toward "Open Science".
Comments100 pages, 16 Figures
