scholarly journals Review of "Pervasive diffusion of climate signals recorded in ice-vein ionic impurities” by Felix S. L. Ng

2020 ◽  
Author(s):  
Alan Rempel
2020 ◽  
Author(s):  
Felix S. L. Ng

Abstract. A theory of vein impurity transport conceived two decades ago predicts that signals in the bulk concentration of soluble ions in ice migrate under a temperature gradient. If valid, it would mean that some palaeoclimatic signals deep in ice cores (signals from vein impurities as opposed to matrix/grain-boundary impurities) suffer displacements that upset their dating and alignment with other proxies. We revisit the vein physical interactions to show that a strong diffusion prevents such signals from surviving into deep ice. It arises because the Gibbs–Thomson effect, which the original theory had neglected, perturbs the impurity concentration of the vein water wherever the bulk impurity concentration carries a signal. Thus no distinct vein signals will reach a depth where their displacement matters; accordingly, the palaeoclimatic concern posed by the original theory no longer stands. Simulations with signal peaks introduced in shallow ice at the GRIP and EPICA Dome C ice-core sites confirm that rapid damping and broadening eradicates their form by two-thirds way down the ice column; artificially reducing the solute diffusivity in water (to mimic partially-connected veins) by 103 times or more is necessary for signals to penetrate into the lowest several hundred metres with minimal loss of amplitude. The deep solute peaks observed in ice cores can only be explained by widespread vein disconnection or a dominance of matrix/grain-boundary impurities at depth (including their recent transfer to veins); in either case, the deep peaks would not have displaced far. Decomposing the vein and matrix impurity contributions will aid robust reconstruction from ion records.


Nature ◽  
10.1038/35356 ◽  
1998 ◽  
Vol 391 (6667) ◽  
pp. 575-577 ◽  
Author(s):  
Ruth G. Curry ◽  
Michael S. McCartney ◽  
Terrence M. Joyce

2017 ◽  
Vol 24 (4) ◽  
pp. 681-694 ◽  
Author(s):  
Yuxin Zhao ◽  
Xiong Deng ◽  
Shaoqing Zhang ◽  
Zhengyu Liu ◽  
Chang Liu ◽  
...  

Abstract. Climate signals are the results of interactions of multiple timescale media such as the atmosphere and ocean in the coupled earth system. Coupled data assimilation (CDA) pursues balanced and coherent climate analysis and prediction initialization by incorporating observations from multiple media into a coupled model. In practice, an observational time window (OTW) is usually used to collect measured data for an assimilation cycle to increase observational samples that are sequentially assimilated with their original error scales. Given different timescales of characteristic variability in different media, what are the optimal OTWs for the coupled media so that climate signals can be most accurately recovered by CDA? With a simple coupled model that simulates typical scale interactions in the climate system and twin CDA experiments, we address this issue here. Results show that in each coupled medium, an optimal OTW can provide maximal observational information that best fits the characteristic variability of the medium during the data blending process. Maintaining correct scale interactions, the resulting CDA improves the analysis of climate signals greatly. These simple model results provide a guideline for when the real observations are assimilated into a coupled general circulation model for improving climate analysis and prediction initialization by accurately recovering important characteristic variability such as sub-diurnal in the atmosphere and diurnal in the ocean.


2014 ◽  
Vol 22 (1) ◽  
pp. 28-29 ◽  
Author(s):  
Margit Schwikowski ◽  
A Eichler ◽  
TM Jenk ◽  
I Mariani
Keyword(s):  

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