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A Generalized Approach to Estimating Diffusion Length of Stable Water Isotopes From Ice‐Core Data
Author(s) -
Kahle Emma C.,
Holme Christian,
Jones Tyler R.,
Gkinis Vasileios,
Steig Eric J.
Publication year - 2018
Publication title -
journal of geophysical research: earth surface
Language(s) - English
Resource type - Journals
eISSN - 2169-9011
pISSN - 2169-9003
DOI - 10.1029/2018jf004764
Subject(s) - firn , ice core , diffusion , smoothing , geology , sampling (signal processing) , ice sheet , environmental science , mineralogy , soil science , mathematics , physics , computer science , statistics , filter (signal processing) , thermodynamics , glacier , climatology , geomorphology , computer vision
Diffusion of water vapor in the porous firn layer of ice sheets damps high‐frequency variations in water‐isotope profiles. Through spectral analysis, the amount of diffusion can be quantified as the“diffusion length,” the mean cumulative diffusive displacement of water molecules relative to their original location at time of deposition. In this study, we use two types of ice‐core data, obtained from either continuous‐flow analysis or discrete sampling, to separate diffusional effects occurring in the ice sheet from those arising through analytical processes in the laboratory. In both Greenlandic and Antarctic ice cores, some characteristics of the power spectral density of a data set depend on the water‐isotope measurement process. Due to these spectral characteristics, currently established approaches for diffusion estimation do not work equally well for newer, continuously measured data sets with lower instrument noise levels. We show how smoothing within the continuous‐flow analysis system can explain these spectral differences. We propose two new diffusion‐estimation techniques, which can be applied to either continuously or discretely measured data sets. We evaluate these techniques and demonstrate their viability for future use. The results of this study have the potential to improve climate interpretation of ice‐core records as well as models of firn densification and diffusion.