资源环境科技发展态势分析平台

Wind-swept snow self-organizes into bedforms. These bedforms affect local and global energy fluxes but have not been incorporated into Earth system models because the conditions governing their development are not well understood. To address this difficulty, we created statistical classifiers, drawn from 736 hr of time-lapse footage in the Colorado Front Range, that predict bedform presence as a function of wind speed and time since snowfall. These classifiers provide the first quantitative predictions of bedform and sastrugi presence in varying weather conditions. We find that the likelihood that a snow surface is covered by bedforms increases with time since snowfall and with wind speed and that the likelihood that a surface is covered by sastrugi increases with time and with the highest wind speeds. Our observations will be useful to Earth system modelers and represent a new step toward understanding self-organized processes that ornament 8% of the surface of the planet.

Plain Language Summary Wind-swept snow does not lie flat. It self-organizes and forms dunes, ripples, and anvil-shaped sastrugi. These textures cover about 8% of the surface of the Earth. They absorb more light and heat than flat snow, but they are not yet included in major climate models. We observed many fields of bedforms in the Colorado Front Range. We used these data to create and test rules that predict when snow surfaces are flat, when they form bedforms, and when they form sastrugi. These are intended to allow snow and Earth system modelers to estimate and forecast the extent of snow bedforms. We identify the wind speeds and weather variables which exert the greatest control on the shapes of snow surfaces. Snow scientists will be able to use our results to predict the behavior of wind-blown snow more reliably from less data. Finally, our results point toward the forces that which drive the self-organization of wind-blown snow, which may inspire new process-based studies of snow movement around the Earth.