The Arctic Sea Ice Volume Anomaly time series is calculated using the Pan-Arctic Ice Ocean Modeling and Assimilation System (PIOMAS) developed at APL/PSC. Updates will be generated at approximately monthly intervals.
Posts Tagged «modelingshow»
Lindsay, R. W. and J. Zhang, “Assimilation of ice concentration in an ice-ocean model”, J. Atmos. Ocean. Tech., 23, 742-749, 2006.
Lindsay, R.W., J. Zhang, A. Schweiger, and M.A. Steele, Seasonal predictions of ice extent in the Arctic Ocean, J. Geophys. Res., 113, C02023, doi:10.1029/2007JC004259, 2008.
The overarching goal of the MIZMAS project is to enhance our understanding of MIZ processes and interactions, and to strengthen our prediction capability of future climate change, particularly the changes in both the ITD and the FSD, in the CBS. We propose numerical investigations of the historical and contemporary changes in the sea ice and upper ocean of the CBSMIZ. We also plan to investigate future changes of the CBSMIZ under global warming scenarios. These investigations involve new and potentially transformative theoretical and numerical work to develop, implement, and validate a new coupled ice–ocean Marginal Ice Zone Modeling and Assimilation System (MIZMAS) that will enhance the representation of the unique MIZ processes by incorporating a FSD and corresponding model improvements.
Significant changes in arctic climate have been detected in recent years. One of the most striking changes is the decline of sea ice concurrent with changes in atmospheric circulation and increased surface air temperature.
Proshutinsky, A., I. Ashik, S. Hakkinen, E. Hunke, R. Krishfield, M. Maltrud, W. Maslowski, and J. Zhang,’ Sea level variability in the Arctic Ocean from AOMIP models’, J. Geophys Res., 112, C04S08, doi:10.1029/2006JC003916, 2007.
Schmidt, G.A. and others including J. Zhang, Configuration and assessment of the GISS ModelE2 contributions to the CMIP5 archive, J. Adv. Model. Earth Syst., 6, no. 2, 141-184, doi:10.1002/2013MS000265, 2014.
Schweiger, A., R. Lindsay, J. Zhang, M. Steele, H. Stern, R. Kwok, Uncertainty in modeled arctic sea ice volume, J. Geophys. Res., 116, C00D06, doi:10.1029/2011JC007084, 2011.
Project investigators aim to improve upon the existing seasonal ensemble forecasting system and use the system to predict sea ice conditions in the arctic and subarctic seas with lead times ranging from two weeks to three seasons.
The AOMIP science goals are to validate and improve Arctic Ocean models in a coordinated fashion and investigate variability of the Arctic Ocean and sea ice at seasonal to decadal time scales, and identify mechanisms responsible for the observed changes.
Zhang, J., R. Lindsay, A. Schweiger, and M. Steele, The impact of an intense summer cyclone on 2012 Arctic sea ice retreat, Geophys. Res. Lett, 40, doi:10.1002/grl.50190, 2013.