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A list of all the posts and pages found on the site. For you robots out there, there is an XML version available for digesting as well.
Pages
Posts
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Blog Post number 4
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Blog Post number 1
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portfolio
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publications
Evaluation of Ocean Currents Observed from Autonomous Surface Vehicles
Published in Journal of Atmospheric and Oceanic Technology, 2023
Wave Gliders are instrument platforms that efficiently collect measurments of the upper ocean and lower atmosphere on the air-sea interface. Various motions at this interface, such as the oscillations of multiple different surface gravity waves, impact the orientation of these autonomous surface vehicles in space. As a result, the measurements of upper ocean currents from the platform-mounted Acoustic Doppler Current Profilers (ADCPs) must account for fluctuations in the platform’s orientation. Correcting for the Wave Glider’s motion on the sea surface with additional GPS/IMU position and attitude records ensured that the spatiotemporal evolution of currents was accurately represented. See more at https://doi.org/10.1175/JTECH-D-23-0066.1.
Recommended citation: Hodges, B. A., Grare, L., Greenwood, B., Matsuyoshi, K., Pizzo, N., Statom, N. M., Farrar, J. T., & Lenain, L. (2023). Evaluation of Ocean Currents Observed from Autonomous Surface Vehicles. Journal of Atmospheric and Oceanic Technology, 40(10), 1121-1136.
Machine Learning for Daily Forecasts of Arctic Sea Ice Motion: An Attribution Assessment of Model Predictive Skill
Published in Artificial Intelligence for the Earth Systems, 2023
The presence of sea ice affects planetary energy budgets and high-latitude ecosystems, playing a significant role in Earth’s system. Ice-Tethered Profilers (ITPs) are instrumented buoys that enable the collection of sea ice trajectories in the Arctic Ocean. Using this data and reanalysis products, three different machine learning and statistical models are employed to forecast velocities of sea ice and their performances are evaluated. See more at https://doi.org/10.1175/AIES-D-23-0004.1.
Recommended citation: Hoffman, L., Mazloff, M. R., Gille, S. T., Giglio, D., Bitz, C. M., Heimbach, P., & Matsuyoshi, K. (2023). Machine Learning for Daily Forecasts of Arctic Sea Ice Motion: An Attribution Assessment of Model Predictive Skill. Artificial Intelligence for the Earth Systems, 2(4), Article 230004, 230004.
talks
Airborne observations of wave-current interactions at submesoscale features
Published:
See you at OSM 2026!
teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.
Teaching experience 2
Workshop, University 1, Department, 2015
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