Open Access. Powered by Scholars. Published by Universities.®
- Keyword
-
- College of Forest Resources and Environmental Science (1)
- Copper fluxes (1)
- Copper “Halo” (1)
- Deep learning (1)
- Department of Biological Sciences (1)
-
- Department of Computer Science (1)
- Department of Mechanical Engineering-Engineering Mechanics (1)
- Department of Social Sciences (1)
- Earth system (1)
- Great Lakes (1)
- Keweenaw Bay (1)
- LSTM (1)
- Lake Superior (1)
- Lake surface temperature (1)
- Land clearance (1)
- Mercury ratios (1)
- Mining (1)
- Model integration (1)
- Tailings movement (1)
- Tribal boundaries (1)
- XAI (1)
Articles 1 - 3 of 3
Full-Text Articles in Life Sciences
Climate Projections Over The Great Lakes Region: Using Two-Way Coupling Of A Regional Climate Model With A 3-D Lake Model, Pengfei Xue, Xinyu Ye, Jeremy S. Pal, Philip Y. Chu, Miraj Kayastha, Chenfu Huang
Climate Projections Over The Great Lakes Region: Using Two-Way Coupling Of A Regional Climate Model With A 3-D Lake Model, Pengfei Xue, Xinyu Ye, Jeremy S. Pal, Philip Y. Chu, Miraj Kayastha, Chenfu Huang
Michigan Tech Publications
Warming trends in the Laurentian Great Lakes and surrounding areas have been observed in recent decades, and concerns continue to rise about the pace and pattern of future climate change over the world's largest freshwater system. To date, most regional climate models used for Great Lakes projections either neglected the lake-atmosphere interactions or are only coupled with a 1-D column lake model to represent the lake hydrodynamics. This study presents a Great Lakes climate change projection that has employed the two-way coupling of a regional climate model with a 3-D lake model (GLARM) to resolve 3-D hydrodynamics essential for large …
Integrating Deep Learning And Hydrodynamic Modeling To Improve The Great Lakes Forecast, Pengfei Xue, Aditya Wagh, Gangfeng Ma, Yilin Wang, Yongchao Yang, Tao Liu, Chenfu Huang
Integrating Deep Learning And Hydrodynamic Modeling To Improve The Great Lakes Forecast, Pengfei Xue, Aditya Wagh, Gangfeng Ma, Yilin Wang, Yongchao Yang, Tao Liu, Chenfu Huang
Michigan Tech Publications
The Laurentian Great Lakes, one of the world’s largest surface freshwater systems, pose a modeling challenge in seasonal forecast and climate projection. While physics-based hydrodynamic modeling is a fundamental approach, improving the forecast accuracy remains critical. In recent years, machine learning (ML) has quickly emerged in geoscience applications, but its application to the Great Lakes hydrodynamic prediction is still in its early stages. This work is the first one to explore a deep learning approach to predicting spatiotemporal distributions of the lake surface temperature (LST) in the Great Lakes. Our study shows that the Long Short-Term Memory (LSTM) neural network, …
Copper-Rich “Halo” Off Lake Superior's Keweenaw Peninsula And How Mass Mill Tailings Dispersed Onto Tribal Lands, W. Charles Kerfoot, Noel Urban, Jaebong Jeong, Carol Maclennan, Sophia Ford
Copper-Rich “Halo” Off Lake Superior's Keweenaw Peninsula And How Mass Mill Tailings Dispersed Onto Tribal Lands, W. Charles Kerfoot, Noel Urban, Jaebong Jeong, Carol Maclennan, Sophia Ford
Michigan Tech Publications
Over a century ago, shoreline copper mills sluiced more than 64 million metric tonnes of tailings into Lake Superior, creating a “halo” around the Keweenaw Peninsula with a buried copper peak. Here we examine how tailings from one of the smaller mills (Mass Mill, 1902–1919) spread as a dual pulse across southern Keweenaw Bay and onto tribal L'Anse Indian Reservation lands. The fine (“slime clay”) fraction dispersed early and widely, whereas the coarse fraction (stamp sands) moved more slowly southward as a black sand beach deposit, leaving scattered residual patches. Beach stamp sands followed the path of sand eroding from …