Atmospheric methane grew very rapidly in 2014 (12.7 ± 0.5 ppb/year), 2015 (10.1 ± 0.7 ppb/year), 2016 (7.0 ± 0.7 ppb/year), and 2017 (7.7 ± 0.7 ppb/year), at rates not observed since the 1980s. The increase in the methane burden began in 2007, with the mean global mole fraction in remote surface background air rising from about 1,775 ppb in 2006 to 1,850 ppb in 2017. Simultaneously the¹³C/¹²C isotopic ratio (expressed as δ¹³C_CH4) has shifted, now trending negative for more than a decade. The causes of methane's recent mole fraction increase are therefore either a change in the relative proportions (and totals) of emissions from biogenic and thermogenic and pyrogenic sources, especially in the tropics and subtropics, or a decline in the atmospheric sink of methane, or both. Unfortunately, with limited measurement data sets, it is not currently possible to be more definitive. The climate warming impact of the observed methane increase over the past decade, if continued at >5 ppb/year in the coming decades, is sufficient to challenge the Paris Agreement, which requires sharp cuts in the atmospheric methane burden. However, anthropogenic methane emissions are relatively very large and thus offer attractive targets for rapid reduction, which are essential if the Paris Agreement aims are to be attained.

Atmospheric measurements show an increase in CH₄ from the 1980s to 1998 followed by a period of near‐zero growth until 2007. However, from 2007, CH₄ has increased again. Understanding the variability in CH₄ is critical for climate prediction and climate change mitigation. We examine the role of CH₄ sources and the dominant CH₄ sink, oxidation by the hydroxyl radical (OH), in atmospheric CH₄ variability over the past three decades using observations of CH₄, C₂H₆, and δ¹³C_CH4 in an inversion. From 2006 to 2014, microbial and fossil fuel emissions increased by 36 ± 12 and 15 ± 8 Tg y⁻¹, respectively. Emission increases were partially offset by a decrease in biomass burning of 3 ± 2 Tg y⁻¹ and increase in soil oxidation of 5 ± 6 Tg y⁻¹. A change in the atmospheric sink did not appear to be a significant factor in the recent growth of CH₄.

We use a high‐resolution water isotope record from the West Antarctic Ice Sheet Divide ice core (WDC) to evaluate the effects of water isotope diffusion for the last 29 ka B.P. Using spectral analysis of the data, we determine diffusion lengths in depth and time domains. The diffusion length quantifies the mean cumulative diffusive displacement of water molecules relative to their original location at time of deposition. We simulate the observed signal with models and find that our understanding of processes and conditions in the ice sheet is incomplete. With the effects of ice‐deformational thinning removed, portions of the Holocene record show total diffusion lengths smaller than predicted for a lower limit case of diffusion through a single ice crystal. Such reduced diffusion is probably due to structural features such as crusts and tortuous porosity that inhibit vapor transport in the firn. In the late glacial portion of the record, diffusion lengths double between ~19.5 and 17 ka B.P. Known dependencies of diffusion on climatic variables do not account for this enhancement in models, and we hypothesize that it could arise from thermal gradients in the firn column, impurity‐driven enhancement of solid ice diffusion, or changes in firn grain properties that alter vapor access to open pores. Despite model uncertainties, the WDC diffusion length chronology will be an essential input to future studies of high‐frequency variability in the water isotope climate record, as it allows for the effects of diffusion to be removed.

North American ecosystems absorb more CO ₂ from the atmosphere during El Niño than during La Niña periods.

Data from the South Pole ice core (SPC14) are used to constrain climate conditions and ice‐flow‐induced layer thinning for the last 54,000 years. Empirical constraints are obtained from the SPC14 ice and gas timescales, used to calculate annual‐layer thickness and the gas‐ice age difference (Δage), and from high‐resolution measurements of water isotopes, used to calculate the water‐isotope diffusion length. Both Δage and diffusion length depend on firn properties and therefore contain information about past temperature and snow‐accumulation rate. A statistical inverse approach is used to obtain an ensemble of reconstructions of temperature, accumulation‐rate, and thinning of annual layers in the ice sheet at the SPC14 site. The traditional water‐isotope/temperature relationship is not used as a constraint; the results therefore provide an independent calibration of that relationship. The temperature reconstruction yields a glacial‐interglacial temperature change of 6.7 ± 1.0°C at the South Pole. The sensitivity of δ¹⁸O to temperature is 0.99 ± 0.03 ‰°C⁻¹, significantly greater than the spatial slope of 0.8‰°C⁻¹ that has been used previously to determine temperature changes from East Antarctic ice core records. The reconstructions of accumulation rate and ice thinning show millennial‐scale variations in the thinning function as well as decreased thinning at depth compared to the results of a 1‐D ice flow model, suggesting influence of bedrock topography on ice flow.

Permutation entropy techniques can be useful for identifying anomalies in paleoclimate data records, including noise, outliers, and post-processing issues. We demonstrate this using weighted and unweighted permutation entropy with water-isotope records containing data from a deep polar ice core. In one region of these isotope records, our previous calculations (See Garland et al. 2018) revealed an abrupt change in the complexity of the traces: specifically, in the amount of new information that appeared at every time step. We conjectured that this effect was due to noise introduced by an older laboratory instrument. In this paper, we validate that conjecture by reanalyzing a section of the ice core using a more advanced version of the laboratory instrument. The anomalous noise levels are absent from the permutation entropy traces of the new data. In other sections of the core, we show that permutation entropy techniques can be used to identify anomalies in the data that are not associated with climatic or glaciological processes, but rather effects occurring during field work, laboratory analysis, or data post-processing. These examples make it clear that permutation entropy is a useful forensic tool for identifying sections of data that require targeted reanalysis—and can even be useful for guiding that analysis.