C51A-0662
Revisiting the potential of melt pond fraction as a predictor for the seasonal Arctic sea ice extent minimum

Friday, 18 December 2015
Poster Hall (Moscone South)
Jiping LIU, SUNY at Albany, Albany, NY, United States
Abstract:
Seasonal sea ice prediction is challenging because of high variability in diverse atmospheric and oceanic influences, and because the Arctic climate is changing in ways without precedent for at least the past millennium. A recent modeling study that employed a prognostic melt pond model in a stand-alone sea ice model found that September Arctic sea ice extent can be accurately predicted from the melt pond fraction in May. Here we show that satellite observations do not support the model-based finding that the melt pond fraction in May has the strongest impact on September sea ice extent. Instead, we see no evidence of predictive skill in May. We find that a significantly strong relationship first emerges as the melt pond fraction is integrated from early May to late June, with a persistent strong relationship only occurring after late July. Our results highlight that late spring to mid summer melt pond information is required to improve the prediction skill of the seasonal sea ice minimum. Furthermore, satellite observations indicate a much higher percentage of melt pond formation in May than does the aforementioned model simulation, which points to the need to reconcile model simulations and observations, in order to better understand key mechanisms of melt pond formation and evolution and their influence on sea ice state.