PaleoSTeHM v1.0: a modern, scalable spatiotemporal hierarchical modeling framework for paleo-environmental data
<p>Geological records of past environmental change provide crucial insights into long-term climate variability, trends, non-stationarity, and nonlinear feedback mechanisms. However, reconstructing spatiotemporal fields from these records is statistically challenging due to their sparse, indire...
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| Format: | Article |
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Copernicus Publications
2025-05-01
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| Series: | Geoscientific Model Development |
| Online Access: | https://gmd.copernicus.org/articles/18/2609/2025/gmd-18-2609-2025.pdf |
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| author | Y. Lin R. E. Kopp R. E. Kopp A. Reedy A. Reedy M. Turilli M. Turilli S. Jha S. Jha S. Jha E. L. Ashe |
| author_facet | Y. Lin R. E. Kopp R. E. Kopp A. Reedy A. Reedy M. Turilli M. Turilli S. Jha S. Jha S. Jha E. L. Ashe |
| author_sort | Y. Lin |
| collection | DOAJ |
| description | <p>Geological records of past environmental change provide crucial insights into long-term climate variability, trends, non-stationarity, and nonlinear feedback mechanisms. However, reconstructing spatiotemporal fields from these records is statistically challenging due to their sparse, indirect, and noisy nature. Here, we present PaleoSTeHM, a scalable and modern framework for spatiotemporal hierarchical modeling of paleo-environmental data. This framework enables the implementation of flexible statistical models that rigorously quantify spatial and temporal variability from geological data while clearly distinguishing measurement and inferential uncertainty from process variability. We illustrate its application by reconstructing temporal and spatiotemporal paleo-sea-level changes across multiple locations. Using various modeling and analysis choices, PaleoSTeHM demonstrates the impact of different methods on inference results and computational efficiency. Our results highlight the critical role of model selection in addressing specific paleo-environmental questions, showcasing the PaleoSTeHM framework's potential to enhance the robustness and transparency of paleo-environmental reconstructions.</p> |
| format | Article |
| id | doaj-art-437e1a9ff0884670b94256b09ebb88eb |
| institution | Kabale University |
| issn | 1991-959X 1991-9603 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Geoscientific Model Development |
| spelling | doaj-art-437e1a9ff0884670b94256b09ebb88eb2025-08-20T03:49:26ZengCopernicus PublicationsGeoscientific Model Development1991-959X1991-96032025-05-01182609263710.5194/gmd-18-2609-2025PaleoSTeHM v1.0: a modern, scalable spatiotemporal hierarchical modeling framework for paleo-environmental dataY. Lin0R. E. Kopp1R. E. Kopp2A. Reedy3A. Reedy4M. Turilli5M. Turilli6S. Jha7S. Jha8S. Jha9E. L. Ashe10Department of Earth & Planetary Sciences, Rutgers University, Piscataway, NJ, USADepartment of Earth & Planetary Sciences, Rutgers University, Piscataway, NJ, USARutgers Climate and Energy Institute, Rutgers University, New Brunswick, NJ, USADepartment of Earth & Planetary Sciences, Rutgers University, Piscataway, NJ, USARutgers Climate and Energy Institute, Rutgers University, New Brunswick, NJ, USADepartment of Electrical and Computer Engineering, Rutgers University, Piscataway, NJ, USAComputational Science Initiative, Brookhaven National Laboratory, Upton, NY, USARutgers Climate and Energy Institute, Rutgers University, New Brunswick, NJ, USADepartment of Electrical and Computer Engineering, Rutgers University, Piscataway, NJ, USAComputational Science Department, Princeton Plasma Physics Laboratory, Princeton, NJ, USADepartment of Earth & Planetary Sciences, Rutgers University, Piscataway, NJ, USA<p>Geological records of past environmental change provide crucial insights into long-term climate variability, trends, non-stationarity, and nonlinear feedback mechanisms. However, reconstructing spatiotemporal fields from these records is statistically challenging due to their sparse, indirect, and noisy nature. Here, we present PaleoSTeHM, a scalable and modern framework for spatiotemporal hierarchical modeling of paleo-environmental data. This framework enables the implementation of flexible statistical models that rigorously quantify spatial and temporal variability from geological data while clearly distinguishing measurement and inferential uncertainty from process variability. We illustrate its application by reconstructing temporal and spatiotemporal paleo-sea-level changes across multiple locations. Using various modeling and analysis choices, PaleoSTeHM demonstrates the impact of different methods on inference results and computational efficiency. Our results highlight the critical role of model selection in addressing specific paleo-environmental questions, showcasing the PaleoSTeHM framework's potential to enhance the robustness and transparency of paleo-environmental reconstructions.</p>https://gmd.copernicus.org/articles/18/2609/2025/gmd-18-2609-2025.pdf |
| spellingShingle | Y. Lin R. E. Kopp R. E. Kopp A. Reedy A. Reedy M. Turilli M. Turilli S. Jha S. Jha S. Jha E. L. Ashe PaleoSTeHM v1.0: a modern, scalable spatiotemporal hierarchical modeling framework for paleo-environmental data Geoscientific Model Development |
| title | PaleoSTeHM v1.0: a modern, scalable spatiotemporal hierarchical modeling framework for paleo-environmental data |
| title_full | PaleoSTeHM v1.0: a modern, scalable spatiotemporal hierarchical modeling framework for paleo-environmental data |
| title_fullStr | PaleoSTeHM v1.0: a modern, scalable spatiotemporal hierarchical modeling framework for paleo-environmental data |
| title_full_unstemmed | PaleoSTeHM v1.0: a modern, scalable spatiotemporal hierarchical modeling framework for paleo-environmental data |
| title_short | PaleoSTeHM v1.0: a modern, scalable spatiotemporal hierarchical modeling framework for paleo-environmental data |
| title_sort | paleostehm v1 0 a modern scalable spatiotemporal hierarchical modeling framework for paleo environmental data |
| url | https://gmd.copernicus.org/articles/18/2609/2025/gmd-18-2609-2025.pdf |
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