Polar Science Center, Applied Physics Laboratory
University of Washingon, Seattle, Washington
Seasonal Ice Prediction
Predictions of September ice extent
Predictions of Alaskan summer ice conditions
The 2010 Polar Science Weekend at the Seattle Pacific Science Center
Seasonal Sea Ice Prediction
I have been interested in the seasonal prediction of sea ice conditions for some years and recently wrote a paper about using model estimates of the state of the ice and ocean conditions to estimate the ice extent up to a year in advance. The idea is that there might be a memory in the system that would allow such predictions. It uses past statistical correlations between the model fields of ice thickness, ice concentration, or ocean temperatures in an earlier month and the ice extent in September.
The method is based on a retrospective analysis of the state of the ice and ocean system created by a high resolution coupled ice/ocean model developed by my colleague Dr Jinlun Zhang. The model uses the observed air temperature, wind, clouds, and precipitation to estimate maps of the ice motion, ice thickness distribution, and ocean temperatures and currents for past years, up to and including the most recent month. Statistical relationships between the model parameters in March (or any other month) and the ice extent in September are found from past years using a method developed by Dr. Drobot. This relationship is then used with the current March model output to predict the September ice extent. The method may be used to predict either the pan-Arctic ice extent or the extent in particular regions. It depends fundamentally on a stable relationship between the various components of the system, such as ice thickness in March compared to the ice extent in September.
It seemed to work fairly well using historical data. However the summer of 2007 showed a tremendous loss of sea ice and the predictions from this method were way too conservative. This has led me to think that the statistical relationships between the ice extent and the state of the ice and ocean are changing rapidly and the past relationships cannot be a reliable guide to the future. However the most recent years are used to improve the model fits, so that extreme years such as 2007 are now included in the prediction.
Predicting ice conditions months in advance is a challenging problem for Arctic scientists. The current condition of the ice pack can help some because we know old thick ice can often survive the summer melt season but new thin ice can't. The exact thickness of the ice in spring that might survive depends on the location and on the air temperatures and cloud cover during the summer, both of which are not possible to predict more than a week or so into the future. Also, the ice extent is strongly dependent on the winds, as we saw in the summer of 2007. It is not possible to accurately predict the strength and direction of the winds months in advance. Depending on the air pressure patterns, the winds may or may not herd the remaining ice to one side of the basin, thus reducing the extent. What we do know is that the reduced ice thickness of recent years will lead to much more variability in the fall ice area and extent because the open water created during the summer is more sensitive to the initial ice conditions and the amount of melt. We still have a lot to learn about seasonal ice prediction.
Lindsay, R. W., J. Zhang, A. J. Schweiger, and M. A. Steele, 2008: Seasonal predictions of ice extent in the Arctic Ocean, J. Geophys. Res., 113, C02023, doi:10.1029/2007JC004259. pdf file
Useful links:
National Snow and Ice Data Center Sea Ice Index. The total ice extent from this site is the parameter we try to predict.
NOAA Sea Ice Outlooks. This site has predictions from a number of different investigators.
My colleague Jinlun Zhang's Ensemble Predicition page which uses quite a different method. I use the output from his model up though the end of the most recent month. These simulations use recent atmospheric data (NCEP Reanalysis) to make a best estimate of the recent ice and ocean conditions. The statistical model outlined above is then used to project the future ice extent. His method runs the model forward in time using the summer months from the past seven years for the atmospheric forcing in seven different projections of the possible future state of the ice.