Great Lakes Observing & Forecasting Systems
Modeling sea ice-ocean-ecosystem changes, and Great Lakes ice modeling, measurements, and climate changes
Overview and Objectives
The objective of this study is to improve our understanding of ocean and sea ice circulation in the Bering-Chukchi-Beaufort seas and the Laurentian Great Lakes, using the combination of a high-resolution Coupled Ice-Ocean Model (CIOM) and Princeton Regional Ocean Forecast (and Hindcast) System’s data-assimilation methodologies. A 3-D, 9-compartment, Physical-Ecosystem Model, coupled to CIOM, is used to study the ice-ocean-ecosystem dynamics in the same region. This study will have a broad impact on 1) understanding the ice-ocean-ecosystem dynamics that explain the high primary productivity region in the Arctic Ocean, seasonal phytoplankton blooms, and interannual variability, and 2) ice edge variability due to climate changes and the subsequent impacts on primary and secondary productivity. The models developed through this project can be applied to the Great Lakes Earth System Model (GLESM). Using the experience via the development of the Bering Sea ice-ocean-ecosystem models, we are developing our GLESM. In particular, the ice-ocean models and ecosystem models bear the similar features of subpolar ice-covered waters.
Publications
Clites, A.H., J. Wang, and Z. Yang. Great Lakes Ice Cover Database Update: 1973 – 2015, Proceedings of the 23rd IAHR International Symposium on Ice, Ann Arbor, MI, May 31-June3, 2016.
Hawley, N., D. Beletsky, and J. Wang, Time Series Measurements of Ice Thickness in Lake Erie, Proceedings of the 23rd IAHR International Symposium on Ice, Ann Arbor, MI, May 31-June 3, 2016, 8 pages.
Hu, H., J. Wang, H. Liu, and J. Goes (2016), Simulation of phytoplankton distribution and variation in the Bering-Chukchi Sea using a 3-D physical-biological model, J. Geophys. Res. Oceans, 121, doi:10.1002/ 2016JC011692.
Hu, H., J. Wang, H. Liu, and J. Goes, Simulations of Seasonal Variations of Sea Ice and Plankton in the Bering and Chukchi Seas, Proceedings of the 23rd IAHR International Symposium on Ice, Ann Arbor, MI, May 31-June 3, 2016, 9 pages.
Lei, R., P. Heil, J. Wang, Z. Zhang, Q. Li, and N. Li (2016), Characterization of sea-ice kinematic in the Arctic outflow region using buoy data. Polar Research 35(22658):1-15, DOI:10.3402/polar.v35.22658.
Manome, A., and J. Wang 2016. Simulating sea ice in the Arctic Ocean and Eastern Siberian Sea, Proceedings of the 23rd IAHR International Symposium on Ice, Ann Arbor, MI, May 31-June 3, 2016, 8 pages.
Wang, J., X. Bai, Z. Yang, A. Clites, H. Hu, and P. Chu, Projection of Great Lakes Seasonal Ice Cover using Multi-Variable Regression Models, The 23rd IAHR International Symposium on Ice, Ann Arbor, MI, May 31-June 3, 2016, 8 pages.
Presentations
Manome, A., and J. Wang 2016. Simulating sea ice in the Arctic Ocean and Eastern Siberian Sea, The 23rd IAHR International Symposium on Ice, Ann Arbor, MI, May 31-June 3, 2016.
Hu, H., J. Wang, H. Liu, and J. Goes, Simulations of Seasonal Variations of Sea Ice and Plankton in the Bering and Chukchi Seas, The 23rd IAHR International Symposium on Ice, Ann Arbor, MI, May 31-June 3, 2016.
Wang, J., X. Bai, Z. Yang, A. Clites, H. Hu, and P. Chu, Projection of Great Lakes Seasonal Ice Cover using Multi-Variable Regression Models, The 23rd IAHR International Symposium on Ice, Ann Arbor, MI, May 31-June 3, 2016.
Resources
PrincipaI Investigator(s):
Hongyan Zhang (CILER)
NOAA Technical Lead(s):
Jia Wang (NOAA-GLERL)