Tomorrow, April 1st, I'll be doing a short presentation on the Sea Ice Prediction Workshop that will be webcast by UCAR. I'll be talking 10-15 minutes about the ASIB, ASIG and ASIF, and about increasing public interest in Arctic sea ice. You can view the webcast here.
It was always clear how difficult it is to forecast the Arctic sea ice melting season, but this realization reached an even deeper level in the last two years (more about that a couple of paragraphs below). A lot of scientists are working hard to improve the science of predicting the yearly sea ice minimum, and some of them have now evaluated these forecasting efforts, using data from the interagency "system-scale, cross-disciplinary, long-term arctic research program" SEARCH (Study of Environmental Arctic Change) Sea Ice Outlook, which was set up after the drastic sea ice decline of 2007. These monthly SIO predictions have been extensively covered on the ASIB the past 4 melting seasons.
The study by Stroeve et al. (including ASIB guest blogger Larry Hamilton) is called Predicting September Sea Ice Ensemble Skill of the Search Sea Ice Outlook 2008–2013, has just been published in Geophysical Research Letters, and its abstract reads as follows:
Since 2008, the SEARCH Sea Ice Outlook has solicited predictions of September sea ice extent from the Arctic research community. Individuals and teams employ a variety of modeling, statistical and heuristic approaches to make these predictions. Viewed as monthly ensembles each with one or two dozen individual predictions, they display a bimodal pattern of success. In years when observed ice extent is near its trend, the median predictions tend to be accurate. In years when the observed extent is anomalous, the median and most individual predictions are less accurate. Statistical analysis suggests that year-to-year variability, rather than methods, dominate the variation in ensemble prediction success. Furthermore, ensemble predictions do not improve as the season evolves. We consider the role of initial ice, atmosphere and ocean conditions, and summer storms and weather in contributing to the challenge of sea ice prediction.