A. J. Yeo, E. J. Anderson, C. Jablonowski, D. M. Wright, G. E. Mann, A. Fujisaki-Manome, B. Mroczka, D. Titze
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Assessing the Potential for Medium-Range Ice Forecasts in the Laurentian Great Lakes
Real-time forecasted ice information for large lakes, such as the Great Lakes, is critical for essential operations, such as ice breaking, commercial navigation, search and rescue, and oil spill response. Existing forecast products for large lake ice conditions are not available for medium-range time horizons (5–16 days out), yet they could provide important information for decision making, particularly for ice breaking and spill responses. In addition, ice forecasts for Earth's largest lakes at these timescales could be important for Medium-Range Weather (MRW) forecasting. However, the skill of existing operational products in predicting ice conditions at MRW timescales has not been studied. This work aims to determine how well ice forecasts from a coupled large lake hydrodynamic-ice model perform for MRW forecast horizons. Simulations were carried out for the 2022 Great Lakes ice season, using 8 different 16-day forecast periods. Forecast results were compared to observations of meteorology and ice conditions from the U.S. National Ice Center. Results show the MRW ice forecasts in the Great Lakes outperform persistence-based forecasts. These findings could inform the development or extension of lake operational ice forecasting and the potential of coupling between atmospheric and large lake models at medium-range forecast time scales.
期刊介绍:
Water Resources Research (WRR) is an interdisciplinary journal that focuses on hydrology and water resources. It publishes original research in the natural and social sciences of water. It emphasizes the role of water in the Earth system, including physical, chemical, biological, and ecological processes in water resources research and management, including social, policy, and public health implications. It encompasses observational, experimental, theoretical, analytical, numerical, and data-driven approaches that advance the science of water and its management. Submissions are evaluated for their novelty, accuracy, significance, and broader implications of the findings.