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Predicting Antarctic Net Snow Accumulation at the Kilometer Scale and Its Impact on Observed Height Changes

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 t...

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Detalles Bibliográficos
Autores principales: Medley, B., Lenaerts, J. T. M., Dattler, M., Keenan, E., Wever, N.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9787652/
https://www.ncbi.nlm.nih.gov/pubmed/36589269
http://dx.doi.org/10.1029/2022GL099330
Descripción
Sumario: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 (RF) models to predict variability in net accumulation over the Antarctic Ice Sheet using atmospheric variables and topographic characteristics as predictors at 1 km resolution. Observations of net snow accumulation from both in situ and airborne radar data provide the input observable targets needed to train the RF models. We find that local net accumulation deviates 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 surface processes operate differently through time, driven largely by the seasonal anomalies in snow accumulation.