Publications

Dong, X., Massonnet, F., Nie, Y., Richaud, B., Gau, Y., Hoffman, L., Wang, Y., Yang, Q. (2026). Incorporating Subsurface Oceanic Variables Improves Seasonal Antarctic Sea Ice Prediction With Neural Networks.

Giglio, D., Sala, J., Gilson, J., Hoffman, L., Kawzenuk, B., Mills, B. K-A., Purkey, S. G., Scanderbeg, M., Subramanian, A. C., Wilson, A. M., Ralph, F. M (2025). Adaptive Sampling of the Upper Ocean by Autonomous Floats During Atmospheric River Precipitation.

Hoffman, L., Massonnet, F., Sticker, A. (2025). Probabilistic forecasts of September Arctic sea ice extent at the interannual timescale with data-driven statistical models.

Hoffman, L., Mazloff, M. R., Gille, S. T., Giglio, D., Heimbach, P. (2025). Evaluating the trustworthiness of explainable artificial intelligence (XAI) methods applied to regression predictions of Arctic sea-ice motion.

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.

Hoffman, L., Mazloff, M. R., Gille, S. T., Giglio, D., Varadarajan, A. (2022). Ocean Surface Salinity Response to Atmospheric River Precipitation in the California Current System.