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Article

Evaluation of ICESat-2 Significant Wave Height Data with Buoy Observations in the Great Lakes and Application in Examination of Wave Model Predictions

1
Cooperative Institute for Great Lakes Research, School for Environment and Sustainability, University of Michigan, 4840 S State Rd., Ann Arbor, MI 48108, USA
2
Climate & Space Sciences and Engineering, University of Michigan, 2455 Hayward St., Ann Arbor, MI 48109, USA
3
NOAA Great Lakes Environmental Research Laboratory, 4840 S State Rd., Ann Arbor, MI 48108, USA
4
Great Lakes Research Center, Michigan Technological University, 1400 Townsend Drive, Houghton, MI 49931, USA
*
Author to whom correspondence should be addressed.
Remote Sens. 2024, 16(4), 679; https://doi.org/10.3390/rs16040679
Submission received: 4 January 2024 / Revised: 8 February 2024 / Accepted: 9 February 2024 / Published: 14 February 2024

Abstract

High waves and surges associated with storms pose threats to the coastal communities around the Great Lakes. Numerical wave models, such as WAVEWATCHIII, are commonly used to predict the wave height and direction for the Great Lakes. These predictions help determine risks and threats associated with storm events. To verify the reliability and accuracy of the wave model outputs, it is essential to compare them with observed wave conditions (e.g., significant wave height), many of which come from buoys. However, in the Great Lakes, most of the buoys are retrieved before those lakes are frozen; therefore, winter wave measurements remain a gap in the Great Lakes’ data. To fill the data gap, we utilize data from the Inland Water Surface Height product of the Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) as complements. In this study, the data quality of ICESat-2 is evaluated by comparing with wave conditions from buoy observations in the Great Lakes. Then, we evaluate the model quality of NOAA’s Great Lakes Waves-Unstructured Forecast System version 2.0 (GLWUv2) by comparing its retrospective forecast simulations for significant wave height with the significant wave height data from ICESat-2, as well as data from a drifting Spotter buoy that was experimentally deployed in the Great Lakes. The study indicates that the wave measurements obtained from ICESat-2 align closely with the in situ buoy observations, displaying a root-mean-square error (RMSE) of 0.191 m, a scatter index (SI) of 0.46, and a correlation coefficient of 0.890. Further evaluation suggests that the GLWUv2 tends to overestimate the wave conditions in high wave events during winter. The statistics show that the RMSE in 0–0.8 m waves is 0.257 m, while the RMSE in waves higher than 1.5 m is 0.899 m.
Keywords: significant wave height; ICESat-2; buoy observation; WAVEWATCHIII; the Great Lakes; winter observation significant wave height; ICESat-2; buoy observation; WAVEWATCHIII; the Great Lakes; winter observation

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MDPI and ACS Style

Li, L.; Fujisaki-Manome, A.; Miller, R.; Titze, D.; Henderson, H. Evaluation of ICESat-2 Significant Wave Height Data with Buoy Observations in the Great Lakes and Application in Examination of Wave Model Predictions. Remote Sens. 2024, 16, 679. https://doi.org/10.3390/rs16040679

AMA Style

Li L, Fujisaki-Manome A, Miller R, Titze D, Henderson H. Evaluation of ICESat-2 Significant Wave Height Data with Buoy Observations in the Great Lakes and Application in Examination of Wave Model Predictions. Remote Sensing. 2024; 16(4):679. https://doi.org/10.3390/rs16040679

Chicago/Turabian Style

Li, Linfeng, Ayumi Fujisaki-Manome, Russ Miller, Dan Titze, and Hayden Henderson. 2024. "Evaluation of ICESat-2 Significant Wave Height Data with Buoy Observations in the Great Lakes and Application in Examination of Wave Model Predictions" Remote Sensing 16, no. 4: 679. https://doi.org/10.3390/rs16040679

APA Style

Li, L., Fujisaki-Manome, A., Miller, R., Titze, D., & Henderson, H. (2024). Evaluation of ICESat-2 Significant Wave Height Data with Buoy Observations in the Great Lakes and Application in Examination of Wave Model Predictions. Remote Sensing, 16(4), 679. https://doi.org/10.3390/rs16040679

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