Multi-fractal structure in Arctic sea ice satellite data

Since 21th century, Arctic sea ice has shown significant decrease especially during summer season. These decline has been considered by climate scientists as a critical sign of the effect of global warming. Especially, IPCC global climate models confirmed the recent decline of Arctic sea ice and predict the more decline in the near future. Even with rather significant amount of inter-model variability in climate models, satellite data during around 30 years support the results of climate models. However, the decline of Arctic sea ice is confirmed based on monthly averaged data and linear regression after erasing seasonal cycle. Even with strong conjecture of the real decline of Arctic sea ice, we cannot exclude one part of natural oscillations affecting Arctic sea ice physics due to strong non-stationarity. It is also possible not to make any conclusive statements using the monthly averaged data due to a lack of data or multi-fractal structure of data excluded in the data. Here, we will use MF-DFA (Multi-Fractal Detrended Fluctuation Analysis) to determine the multi-scale structure of Arctic sea ice area and albedo using AVHRR Polar Pathfinder Twice-Daily 5km EASE-grid composites, which is expected to decide whether the decline shown in the linear regression of the monthly averaged data can be considered as the real decline caused by global warming or not. Also, the multi-scale structure information drawn from this analysis is expected to give us the guideline for selecting significant physics for low-order Arctic sea ice