Inferring past climate variations from proxies: Separating climate and non-climate variability

The statistical properties of climate variability are often reconstructed and interpreted from single proxy records. However, variation in the proxy record is influenced by both climate and non-climate factors, and these must be understood for climate inferences to be reliable

Stratigraphic noise and its potential drivers across the plateau of Dronning Maud Land, East Antarctica

Stable water isotopologues of snow, firn and ice cores provide valuable information on past climate variations. Yet single profiles are generally not suitable for robust climate reconstructions. Stratigraphic noise, introduced by the irregular deposition, wind-driven erosion and redistribution of snow, impacts the utility of high-resolution isotope records, especially in low-accumulation areas. However, it is currently unknown how stratigraphic noise differs across the East Antarctic Plateau and how it is affected by local environmental conditions. Here, we assess the amount and structure of stratigraphic noise at seven sites along a 120 km transect on the plateau of Dronning Maud Land, East Antarctica. Replicated oxygen isotope records of 1 m length were used to estimate signal-to-noise ratios as a measure of stratigraphic noise at sites characterised by different accumulation rates (43–64 mm w.e. a−1), snow surface roughnesses and slope inclinations. While we found a high level of stratigraphic noise at all sites, there was also considerable variation between sites. At sastrugi-dominated sites, greater stratigraphic noise coincided with stronger surface roughnesses, steeper slopes and lower accumulation rates, probably related to increased wind speeds. These results provide a first step to modelling stratigraphic noise and might guide site selection and sampling strategies for future expeditions to improve high-resolution climate reconstructions from low-accumulation regions.</p

Concerns of assuming linearity in the reconstruction of thermal maxima

Seasonal biases in proxy records are an outstanding issue in deciphering past climate evolution, and may contribute to the current discrepancy between models and proxy reconstructions during the Holocene, which is most pronounced in the northern extratropics. Bova et al. reported a method of transforming seasonal into mean annual temperatures (the SAT method) at low and mid-latitudes, and concluded that the thermal maxima during the Holocene and last interglacial (LIG) were mainly an artefact of a seasonal proxy response. We provide evidence that, in addition to this geographic mismatch, key assumptions of the SAT method are violated, and more importantly, that the method by construction removes thermal maxima. Thus, the main findings of Bova et al.4 probably reflect peculiarities of the SAT method instead of shedding light on the so-called Holocene conundrum

Longpath DOAS tomography on a motorway exhaust gas plume: numerical studies and application to data from the BAB II campaign

International audienceThis paper presents a procedure for performing and optimizing inversions for DOAS tomography and its application to measurement data. DOAS tomography is a new technique to determine 2- and 3-dimensional concentration fields of air pollutants or other trace gases by combining differential optical absorption spectroscopy (DOAS) with tomographic inversion techniques. Due to the limited amount of measured data, the resulting concentration fields are sensitive to the inversion process. Therefore detailed error estimations are needed to determine the quality of the reconstruction. In this paper we compare different row acting methods for the inversion, present a procedure for optimizing the parameters of the reconstruction process and propose a way to estimate the error-fields by numerical studies. The procedure was applied to data from the motorway emission campaign BAB II. Two dimensional NO2 cross sections at right angles to the motorway could be reconstructed qualitatively well at different meteorological situations. Additionally we present error fields for the reconstructions which show the problems and skills of the used measurement setup. Numerical studies on an improved setup for future motorway campaigns show, that DOAS tomography is able to produce high quality concentration maps

Constraints on post-depositional isotope modifications in East Antarctic firn from analysing temporal changes of isotope profiles

The isotopic composition of water in ice sheets is extensively used to infer past climate changes. In low-accumulation regions their interpretation is, however, challenged by poorly constrained effects that may influence the initial isotope signal during and after deposition of the snow. This is reflected in snow-pit isotope data from Kohnen Station, Antarctica, which exhibit a seasonal cycle but also strong interannual variations that contradict local temperature observations. These inconsistencies persist even after averaging many profiles and are thus not explained by local stratigraphic noise. Previous studies have suggested that post-depositional processes may significantly influence the isotopic composition of East Antarctic firn. Here, we investigate the importance of post-depositional processes within the open-porous firn (≳ 10 cm depth) at Kohnen Station by separating spatial from temporal variability. To this end, we analyse 22 isotope profiles obtained from two snow trenches and examine the temporal isotope modifications by comparing the new data with published trench data extracted 2 years earlier. The initial isotope profiles undergo changes over time due to downward advection, firn diffusion and densification in magnitudes consistent with independent estimates. Beyond that, we find further modifications of the original isotope record to be unlikely or small in magnitude (≪ 1 ‰ RMSD). These results show that the discrepancy between local temperatures and isotopes most likely originates from spatially coherent processes prior to or during deposition, such as precipitation intermittency or systematic isotope modifications acting on drifting or loose surface snow

What climate signal is contained in decadal- to centennial-scale isotope variations from Antarctic ice cores?

Ice-core-based records of isotopic composition are a proxy for past temperatures and can thus provide information on polar climate variability over a large range of timescales. However, individual isotope records are affected by a multitude of processes that may mask the true temperature variability. The relative magnitude of climate and non-climate contributions is expected to vary as a function of timescale, and thus it is crucial to determine those temporal scales on which the actual signal dominates the noise. At present, there are no reliable estimates of this timescale dependence of the signal-to-noise ratio (SNR). Here, we present a simple method that applies spectral analyses to stable-isotope data from multiple cores to estimate the SNR, and the signal and noise variability, as a function of timescale. The method builds on separating the contributions from a common signal and from local variations and includes a correction for the effects of diffusion and time uncertainty. We apply our approach to firn-core arrays from Dronning Maud Land (DML) in East Antarctica and from the West Antarctic Ice Sheet (WAIS). For DML and decadal to multi-centennial timescales, we find an increase in the SNR by nearly 1 order of magnitude ( ∼ 0.2 at decadal and  ∼ 1.0 at multi-centennial scales). The estimated spectrum of climate variability also shows increasing variability towards longer timescales, contrary to what is traditionally inferred from single records in this region. In contrast, the inferred variability spectrum for WAIS stays close to constant over decadal to centennial timescales, and the results even suggest a decrease in SNR over this range of timescales. We speculate that these differences between DML and WAIS are related to differences in the spatial and temporal scales of the isotope signal, highlighting the potentially more homogeneous atmospheric conditions on the Antarctic Plateau in contrast to the marine-influenced conditions on WAIS. In general, our approach provides a methodological basis for separating local proxy variability from coherent climate variations, which is applicable to a large set of palaeoclimate records.</p

Sedproxy: a forward model for sediment-archived climate proxies

Climate reconstructions based on proxy records recovered from marine sediments, such as alkenone records or geochemical parameters measured on foraminifera, play an important role in our understanding of the climate system. They provide information about the state of the ocean ranging back hundreds to millions of years and form the backbone of paleo-oceanography.However, there are many sources of uncertainty associated with the signal recovered from sediment-archived proxies. These include seasonal or depth-habitat biases in the recorded signal; a frequency-dependent reduction in the amplitude of the recorded signal due to bioturbation of the sediment; aliasing of high-frequency climate variation onto a nominally annual, decadal, or centennial resolution signal; and additional sample processing and measurement error introduced when the proxy signal is recovered.Here we present a forward model for sediment-archived proxies that jointly models the above processes so that the magnitude of their separate and combined effects can be investigated. Applications include the interpretation and analysis of uncertainty in existing proxy records, parameter sensitivity analysis to optimize future studies, and the generation of pseudo-proxy records that can be used to test reconstruction methods. We provide examples, such as the simulation of individual foraminifera records, that demonstrate the usefulness of the forward model for paleoclimate studies. The model is implemented as an open-source R package, sedproxy, to which we welcome collaborative contributions. We hope that use of sedproxy will contribute to a better understanding of both the limitations and potential of marine sediment proxies to inform researchers about earth's past climate.</p

Glacial legacies on interglacial vegetation at the Pliocene-Pleistocene transition in NE Asia

Broad-scale climate control of vegetation is widely assumed. Vegetation-climate lags are generally thought to have lasted no more than a few centuries. Here our palaeoecological study challenges this concept over glacial-interglacial timescales. Through multivariate analyses of pollen assemblages from Lake El'gygytgyn, Russian Far East and other data we show that interglacial vegetation during the Plio-Pleistocene transition mainly reflects conditions of the preceding glacial instead of contemporary interglacial climate. Vegetation-climate disequilibrium may persist for several millennia, related to the combined effects of permafrost persistence, distant glacial refugia and fire. In contrast, no effects from the preceding interglacial on glacial vegetation are detected. We propose that disequilibrium was stronger during the Plio-Pleistocene transition than during the Mid-Pliocene Warm Period when, in addition to climate, herbivory was important. By analogy to the past, we suggest today's widespread larch ecosystem on permafrost is not in climate equilibrium. Vegetation-based reconstructions of interglacial climates used to assess atmospheric CO 2-Temperature relationships may thus yield misleading simulations of past global climate sensitivity

Regional but not global temperature variability underestimated by climate models at supradecadal timescales

Knowledge of the characteristics of natural climate variability is vital when assessing the range of plausible future climate trajectories in the next decades to centuries. The reliable detection of climate fluctuations on multidecadal to centennial timescales depends on proxy reconstructions and model simulations, as the instrumental record extends back only a few decades in most parts of the world. Systematic comparisons between model-simulated and proxy-based inferences of natural variability, however, often seem contradictory. Locally, simulated temperature variability is consistently smaller on multidecadal and longer timescales than is indicated by proxy-based reconstructions, implying that climate models or proxy interpretations might have deficiencies. In contrast, at global scales, studies found agreement between simulated and proxy reconstructed temperature variations. Here we review the evidence regarding the scale of natural temperature variability during recent millennia. We identify systematic reconstruction deficiencies that may contribute to differing local and global model–proxy agreement but conclude that they are probably insufficient to resolve such discrepancies. Instead, we argue that regional climate variations persisted for longer timescales than climate models simulating past climate states are able to reproduce. This would imply an underestimation of the regional variability on multidecadal and longer timescales and would bias climate projections and attribution studies. Thus, efforts are needed to improve the simulation of natural variability in climate models accompanied by further refining proxy-based inferences of variability.This study was undertaken by members of CVAS and 2k Network, working groups of the Past Global Changes (PAGES) Global Research association. This is a contribution to the SPACE ERC, STACY and PALMOD projects. The SPACE ERC project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement no. 716092). STACY has been funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation, project no. 395588486). This work has also been supported by the German Federal Ministry of Education and Research (BMBF), through the PalMod project (subprojects 01LP1926B (O.B.), 01LP1926D (M.C.) and 01LP1926C (B.E., P.S. and N.W.)) from the Research for Sustainability initiative (FONA). B.E. is supported by the Heinrich Böll Foundation. E.M.-C. was supported by the PARAMOUR project, funded by the Fonds de la Recherche Scientifique–FNRS and the FWO under the Excellence of Science (EOS) programme (grant no. O0100718F, EOS ID no. 30454083). A.H. was supported by a Legacy Grant from the Australian Research Council Centre of Excellence for Australian Biodiversity and Heritage. B.M. was supported by LINKA20102 and the Spanish Ministry of Science and Innovation project CEX2018‐000794‐S. The work originated from discussions at the CVAS working group of PAGES at a workshop at the Internationales Wissenschaftsforum Heidelberg, which was funded by a Hengstberger Prize. We thank N. Beech, C. Brierley, F. Gonzalez-Rouco and M. MacPartland for comments on earlier drafts of the manuscript. This manuscript uses data provided by the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP and PMIP. We thank the research groups for producing and kindly making their model outputs, measurements and palaeoclimate reconstructions available to us. Editorial assistance, in the form of language editing and correction, was provided by XpertScientific Editing and Consulting Services. We acknowledge support by the Open Access Publication Funds of Alfred-Wegener-Institut Helmholtz Zentrum für Polar- und Meeresforschung.Peer ReviewedPostprint (author's final draft