Archival processes and ice core records in Central Antarctica.
Archival processes leading to the isotopic signal in ice core records may limit the achievable resolution to centennial, or even millennial time scales in Central Antarctica. By studying the impact of precipitation intermittency and isotopic diffusion in a forward model for water isotopes in ice cores, we can predict the theoretical limits for the resolution at which an ice core can be interpreted. Indeed, precipitation intermittency reshuffles the large amount of variability associated with the seasonal cycle, creating a significant amount of white noise across all frequencies, while diffusion acts as a low pass filter, erasing high frequency variability. In this manuscript, we make use of the spectral signature created by both these processes on synthetic ice cores created using ERA-interim temperature and precipitation time series to evaluate how much temperature reconstructions from ice core records are hampered. With a very simple approach, we manage to reproduce the spectra of the isotopic variability in near-surface ice cores, and predict that the limits of the resolution achievable can be multidecadal at best for some of the deep ice core sites from the East Antarctic Plateau. Our results are providing lower bounds for the time scales at which ice core should be interpreted, and suggest that caution should be applied when interpreting high resolution of isotopic composition fluctuations from an individual ice core. This manuscript is under discussion in Climate Of the Past: www.clim-past-discuss.net/cp-2019-134/
The Power Spectrum of Climate Proxy Error
We can use temperature proxies, such as the Mg/Ca ratio in the shells of organisms buried in sediments, to estimate the past temperature of the ocean. As well as getting an estimate for the temperature in the past, it is important to know how certain we are about that temperature estimate. However, our uncertainty about temperatures reconstructed from proxies varies depending on the physical properties of the sediment, the number of measurements taken, and the time-period over which we average the measurements. In a pair of discussion papers, we describe how we can represent these uncertainties as power-spectra of the errors. These error-spectra then allow us to calculate how the uncertainty changes when we average multiple estimates or smoothed (e.g. running mean) versions of the estimated temperature time-series. Part I introduces the theory behind the method and derives analytical expression for the error-spectra based on our understanding of the physical process of proxy creation and interpretation. www.clim-past-discuss.net/cp-2019-150/ Part II describes how the error-spectra method can be used by paleo-climate researchers and how appropriate values for the required parameters can be estimated from data. It gives examples of using the error-spectra approach, via the R package ‘psem’. www.clim-past-discuss.net/cp-2019-153/github.com/earthsystemdiagnostics/psem The image shows a conceptual representation of the Proxy Spectral Error Model (PSEM) for errors due to smoothing of the climate signal by bioturbation. The true climate signal is filtered (smoothed) by processes such as bioturbation. This modifies the power spectrum of the climate (red) in a frequency dependent way, producing the power spectrum of the climate signal after bioturbation (blue). Proxy records are assumed to represent the climate at a particular timescale, (e.g. centennial, millennial), the reference climate spectrum (purple) is the power spectrum of the true climate smoothed to this timescale. The error that bioturbation and other smoothing produces (dashed brown) is a function of the reference and bioturbated climate spectra. Andrew Dolman/Torben Kunz
What climate signal is contained in decadal- to centennial-scale isotope variations from Antarctic ice cores?
Proxy data on climate variations contain noise from many sources. For reliable climate variability estimates, we hence need to determine those temporal scales at which the climate signal in the proxy record dominates the noise. In this contribution, we develop a method to derive timescale-dependent estimates of temperature proxy signal-to-noise ratios, which is applicable to a large set of palaeoclimate records. Specifically, we apply and discuss the method in the context of Antarctic ice-core records. https://doi.org/10.5194/cp-14-2053-2018