Predicting Antarctic net snow accumulation at the kilometer scale and its impact on observed height changes | CU Experts

Sub-grid-scale processes occurring at or near the surface of an ice; sheet have a potentially large impact on local and integrated net; accumulation of snow via redistribution and sublimation. Given; observational complexity, they are either ignored or parameterized over; large-length scales. Here, we train random forest models to predict 1-km; variability in net accumulation over the Antarctic Ice Sheet using; atmospheric variables and topographic characteristics as predictors.; Observations of net snow accumulation from both in situ and airborne; radar data provide the input observable targets needed to train the; random forest models. We find that kilometer-scale processes modify; local net accumulation by as much as 172% of the atmospheric model; mean. The correlation in space between the predicted net accumulation; variability and satellite-derived surface-height change indicates that; kilometer-scale processes operate differently through time, driven; largely by the seasonal anomalies in snow accumulation.

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