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Abstract In a COPSS-NISS webinar focused on leadership at the intersection of statistics and genomics, esteemed panelists Drs. Rafael Irizarry and Mingyao Li shared their leadership journeys and provided insights into this interdisciplinary field to inspire future leaders. They discussed the value of statistics in distinguishing signal from noise in the artificial intelligence (AI) era, the strengths of statisticians in ensuring rigor and robustness in genomics research, and the trade-offs between model expressiveness and interpretability. Additionally, they offered advice on how junior faculty can seek collaborations and increase their visibility, balance staying current with technological advancements, while developing methods carefully and thoroughly, and best practices for collaborating with domain experts. The recording of the webinar is available athttps://www.youtube.com/watch?v=t6SsAoh95ig.
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Integrated Sentinel‐1 InSAR and GNSS Time‐Series Along the San Andreas Fault System
Abstract Measuring crustal strain and seismic moment accumulation, is crucial for understanding the growth and distribution of seismic hazards along major fault systems. Here, we develop a methodology to integrate 4.5 years (2015–2019.5) of Sentinel‐1 Interferometric Synthetic Aperture Radar (InSAR) and continuous Global Navigation Satellite System (GNSS) time series to achieve 6 to 12‐day sampling of surface displacements at ∼500 m spatial resolution over the entire San Andreas fault system. Numerous interesting deformation signals are identified with this product (video link:https://www.youtube.com/watch?v=SxNLQKmHWpY). We decompose the line‐of‐sight InSAR displacements into three dimensions by combining the deformation azimuth from a GNSS‐derived interseismic fault model. We then construct strain rate maps using a smoothing interpolator with constraints from elasticity. The resulting deformation field reveals a wide array of crustal deformation processes including, on‐ and off‐fault secular and transient tectonic deformation, creep rates on all the major faults, and vertical signals associated with hydrological processes. The strain rate maps show significant off‐fault components that were not captured by GNSS‐only models. These results are important in assessing the seismic hazard in the region.
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- Award ID(s):
- 1834807
- PAR ID:
- 10372595
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Journal of Geophysical Research: Solid Earth
- Volume:
- 126
- Issue:
- 11
- ISSN:
- 2169-9313
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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