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Antarctic Surface Mass Balance: Natural Variability, Noise, and Detecting New Trends
Author(s) -
King Matt A.,
Watson Christopher S.
Publication year - 2020
Publication title -
geophysical research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.007
H-Index - 273
eISSN - 1944-8007
pISSN - 0094-8276
DOI - 10.1029/2020gl087493
Subject(s) - noise (video) , white noise , ice core , environmental science , range (aeronautics) , climatology , geology , statistics , mathematics , computer science , materials science , composite material , artificial intelligence , image (mathematics)
The emergence of new, statistically robust trends in Antarctic surface mass balance (SMB) requires an understanding of the underlying SMB variability (noise). We show that simple white or AR[1] noise models do not adequately represent the variability of SMB in both the RACMO2.3p2 SMB model output (1979–2017) and composite ice core records (1800–2010), underestimating low‐frequency variability. By testing a range of noise models, we find that a Generalized Gauss Markov (GGM) model better approximates the noise around a linear trend. The general preference for GGM noise applies over spatial scales from the total ice sheet down to individual drainage basins. Over the longest timescales considered, trend uncertainties are 1.3–2.3 times larger using a GGM model compared to using an AR1 model at the ice sheet scale. Overall, our results suggest that larger trends or longer periods are required before new SMB trends can be robustly separated from background noise.