Seasonal climate signals preserved in biochemical varves: insights from novel high-resolution sediment scanning techniques

Varved lake sediments are exceptional archives of paleoclimatic information due to their precise chronological control and annual resolution. However, quantitative paleoclimate reconstructions based on the biogeochemical composition of biochemical varves are extremely rare, mainly because the climate–proxy relationships are complex and obtaining biogeochemical proxy data at very high (annual) resolution is difficult. Recent developments in high-resolution hyperspectral imaging (HSI) of sedimentary pigment biomarkers combined with micro X-ray fluorescence (µXRF) elemental mapping make it possible to measure the structure and composition of varves at unprecedented resolution. This provides opportunities to explore seasonal climate signals preserved in biochemical varves and, thus, assess the potential for annual-resolution climate reconstruction from biochemical varves. Here, we present a geochemical dataset including HSI-inferred sedimentary pigments and µXRF-inferred elements at very high spatial resolution (60 µm, i.e. > 100 data points per varve year) in varved sediments of Lake Żabińskie, Poland, over the period 1966–2019 CE. We compare these data with local meteorological observations to explore and quantify how changing seasonal meteorological conditions influenced sediment composition and varve formation processes. Based on the dissimilarity of within-varve multivariate geochemical time series, we classified varves into four types. Multivariate analysis of variance shows that these four varve types were formed in years with significantly different seasonal meteorological conditions. Generalized additive models (GAMs) were used to infer seasonal climate conditions based on sedimentary variables. Spring and summer (MAMJJA) temperatures were predicted using Ti and total C (Radj2=0.55; cross-validated root mean square error (CV-RMSE) = 0.7 ∘C, 14.4 %). Windy days from March to December (mean daily wind speed > 7 m s−1) were predicted using mass accumulation rate (MAR) and Si (Radj2=0.48; CV-RMSE = 19.0 %). This study demonstrates that high-resolution scanning techniques are promising tools to improve our understanding of varve formation processes and climate–proxy relationships in biochemical varves. This knowledge is the basis for quantitative high-resolution paleoclimate reconstructions, and here we provide examples of calibration and validation of annual-resolution seasonal weather inference from varve biogeochemical data.

pyam: Analysis and visualisation of integrated assessment and macro-energy scenarios

The open-source Python package pyam provides a suite of features and methods for the analysis, validation and visualization of reference data and scenario results generated by integrated assessment models, macro-energy tools and other frameworks in the domain of energy transition, climate change mitigation and sustainable development. It bridges the gap between scenario processing and visualisation solutions that are "hard-wired" to specific modelling frameworks and generic data analysis or plotting packages. The package aims to facilitate reproducibility and reliability of scenario processing, validation and analysis by providing well-tested and documented methods for working with timeseries data in the context of climate policy and energy systems. It supports various data formats, including sub-annual resolution using continuous time representation and "representative timeslices". The pyam package can be useful for modelers generating scenario results using their own tools as well as researchers and analysts working with existing scenario ensembles such as those supporting the IPCC reports or produced in research projects. It is structured in a way that it can be applied irrespective of a user's domain expertise or level of Python knowledge, supporting experts as well as novice users. The code base is implemented following best practices of collaborative scientific-software development. This manuscript describes the design principles of the package and the types of data which can be handled. The usefulness of pyam is illustrated by highlighting several recent applications.

pyam: Analysis and visualisation of integrated assessment and macro-energy scenarios

The open-source Python package pyam provides a suite of features and methods for the analysis, validation and visualization of reference data and scenario results generated by integrated assessment models, macro-energy tools and other frameworks in the domain of energy transition, climate change mitigation and sustainable development. It bridges the gap between scenario processing and visualisation solutions that are "hard-wired" to specific modelling frameworks and generic data analysis or plotting packages. The package aims to facilitate reproducibility and reliability of scenario processing, validation and analysis by providing well-tested and documented methods for timeseries aggregation, downscaling and unit conversion. It supports various data formats, including sub-annual resolution using continuous time representation and "representative timeslices". The code base is implemented following best practices of collaborative scientific-software development. This manuscript describes the design principles of the package and the types of data which can be handled. The usefulness of pyam is illustrated by highlighting several recent applications.

Reduced Temperature Sensitivity of Maximum Latewood Density Formation in High-Elevation Corsican Pines under Recent Warming

Maximum latewood density (MXD) measurements from long-lived Black pines (Pinus nigra spp. laricio) growing at the upper treeline in Corsica are one of the few archives to reconstruct southern European summer temperatures at annual resolution back into medieval times. Here, we present a compilation of five MXD chronologies from Corsican pines that contain high-to-low frequency variability between 1168 and 2016 CE and correlate significantly (p < 0.01) with the instrumental April–July and September–October mean temperatures from 1901 to 1980 CE (r = 0.52−0.64). The growth–climate correlations, however, dropped to −0.13 to 0.02 afterward, and scaling the MXD data resulted in a divergence of >1.5 °C between the colder reconstructed and warmer measured temperatures in the early-21st century. Our findings suggest a warming-induced shift from initially temperature-controlled to drought-prone MXD formation, and therefore question the suitability of using Corsican pine MXD data for climate reconstruction.

Seasonal climate signals preserved in biochemical varves: insights from novel high-resolution sediment scanning techniques

Varved lake sediments are exceptional archives of paleoclimatic information due to their precise chronological control and annual resolution. However, quantitative paleoclimate reconstructions based on the biogeochemical composition of biochemical varves are extremely rare mainly because the climate-proxy relationships are complex, and obtaining biogeochemical proxy data at very high (annual) resolution is difficult. Recent developments in high-resolution hyperspectral imaging (HSI) of sedimentary pigment biomarkers combined with micro X-ray fluorescence (μXRF) elemental mapping make it possible to measure the structure and composition of varves at unprecedented resolution. This provides opportunities to explore (seasonal) climate signals preserved in biochemical varves and, thus, assess the potential for annual resolution climate reconstruction from biochemical varves. Here, we present a geochemical dataset including HSI-inferred sedimentary pigments and uXRF-inferred elements at very high spatial resolution (60 μm, i.e. > 100 data points per varve year) in varved sediments of Lake Żabińskie, Poland over the period 1966–2019 CE. We compare this data with local meteorological observations to explore and quantify how changing seasonal meteorological conditions influenced sediment composition and varve formation processes. Based on the dissimilarity of within-varve multivariate geochemical time series, we classified varves into four types. Multivariate analysis of variance shows that these four varve types were formed in years with significantly different seasonal meteorological conditions. Generalized additive models (GAMs) were used to infer seasonal climate conditions based on sedimentary variables. Spring and summer (MAMJJA) temperature were predicted using Ti and total C (R2adj = 0.55; cross-validated root mean square error (CV-RMSE) = 0.7 °C, 14.4%). Windy days from March to December (mean daily wind speed > 7 m/s) were predicted using mass accumulation rate (MAR) and Si (R2adj = 0.48; CV-RMSE = 19.0%). This study demonstrates that high-resolution scanning techniques are promising tools to improve our understanding of varve formation processes and climate-proxy relationships in biochemical varves. This knowledge is the basis for quantitative high-resolution paleoclimate reconstructions, and here we provide examples of calibration and validation of annual resolution seasonal weather inference from varve biogeochemical data.

Semi-automated counting of complex varves through image autocorrelation

Annual resolution sediment layers, known as varves, can provide continuous and high-resolution chronologies of sedimentary sequences. In addition, varve counting is not burdened with the high laboratory costs of geochronological analyses. Despite a more than 100-year history of use, many existing varve counting techniques are time consuming and difficult to reproduce. We present countMYvarves, a varve counting toolbox which uses sliding-window autocorrelation to count the number of repeated patterns in core scans or outcrop photos. The toolbox is used to build an annually-resolved record of sedimentation rates, which are depth-integrated to provide ages. We validate the model with repeated manual counts of a high sedimentation rate lake with biogenic varves (Herd Lake, USA) and a low sedimentation rate glacial lake (Lago Argentino, Argentina). In both cases, countMYvarves is consistent with manual counts and provides additional sedimentation rate data. The toolbox performs multiple simultaneous varve counts, enabling uncertainty to be quantified and propagated into the resulting age-depth model. The toolbox also includes modules to automatically exclude non-varved portions of sediment and interpolate over missing or disrupted sediment. CountMYvarves is open source, runs through a graphical user interface, and is available online for download for use on Windows, macOS or Linux at https://doi.org/10.5281/zenodo.4031811.

The significance of climate variability on early modern European grain prices

Grain was the most important food source in early modern Europe (c. 1500–1800), and its price influenced the entire economy. The extent to which climate variability determined grain price variations remains contested, and claims of solar cycle influences on prices are disputed. We thoroughly reassess these questions, within a framework of comprehensive statistical analysis, by employing an unprecedentedly large grain price data set together with state-of-the-art palaeoclimate reconstructions and long meteorological series. A highly significant negative grain price–temperature relationship (i.e. colder = high prices and vice versa) is found across Europe. This association increases at larger spatial and temporal scales and reaches a correlation of$$-\,0.41$$-0.41considering the European grain price average and previous year June–August temperatures at annual resolution, and of$$-\,0.63$$-0.63at decadal timescales. This strong relationship is of episodic rather than periodic (cyclic) nature. Only weak and spatially inconsistent signals of hydroclimate (precipitation and drought), and no meaningful association with solar variations, are detected in the grain prices. The significant and persistent temperature effects on grain prices imply that this now rapidly changing climate element has been a more important factor in European economic history, even in southern Europe, than commonly acknowledged.

A novel high-resolution laser-melting sampler for discrete analyses of ion concentrations and stable water isotopic compositions in firn and ice cores

&lt;p&gt;Ice cores preserve past climatic changes and, in some cases, astronomical signals. Here we present a newly developed automated ice-core sampler that employs laser melting. A hole in an ice core approximately 3 mm in diameter is melted and heated well below the boiling point by laser irradiation, and the meltwater is simultaneously siphoned by a 2 mm diameter movable evacuation nozzle that also holds the laser fiber. The advantage of sampling by laser melting is that molecular ion concentrations and stable water isotope compositions in ice cores can be measured at high depth resolution, which is advantageous for ice cores with low accumulation rates. This device takes highly discrete samples from ice cores, attaining depth resolution as small as ~3 mm with negligible cross contamination; the resolution can also be set at longer lengths suitable for validating longer-term profiles of various ionic and water isotopic constituents in ice cores. This technique allows the detailed reconstruction of past climatic changes at annual resolution and the investigation of transient ionic and isotopic signals within single annual layers in low-accumulation cores, potentially by annual layer counting.&lt;/p&gt;

Identification du rythme annuel de précipitation des carbonates pariétaux pour un calage micro-chronologique des occupations archéologiques pyrogéniques : cas de la Grotte Mandrin (Malataverne, Drome, France)

In rock shelters and caves, the geo-archaeological reading of sediments can allow, in favourable cases, a micro-chronological study of traces of anthropogenic activities and in particular in the use of fire. And if the recurrence in the use of fireplaces can sometimes be identified by a micromorphological study of the structures, it is very uncertain that all the different combustion episodes can be identified. It turns out that paleo-fire events can be recorded elsewhere than in the hearths. For instance, they can be recorded as soot marks trapped in speleothems, which are witnesses of fires in cavities. They can be the object of a fuliginochronological study (lat. fuliginosus, fuligo: soot), which consists in studying the succession of soot deposits trapped in a matrix. Some limestone concretions have another advantage, which is to be annually laminated. When this is the case, the joint study of soot films and calcite doublets makes it possible to set paleo-fire chronicles on a micro-chronological scale of measured time. In this study, we demonstrate, through the joint analysis of crystalline fabric alternations and seasonal variations of strontium (Sr) in concretions, that the calcite doublets observed in the fine parietal carbonated crusts of the Grotte Mandrin archaeological site are indeed annual. To do so, we use laser-induced plasma microspectroscopy (LIBS - Laser Induced Breackdown Spectroscopy), which allows to reveal variations of minor and traces elements in speleothems' carbonates on an annual to sub-annual scale through the analysis of transects or maps. Thus, soot film sequences can be indexed to the annual carbonate precipitation calendar and the joint study of soot film and calcite doublets makes it possible to set paleo-fire chronicles on a micro-chronological scale of measured time (annual resolution). The study of the rhythmicities of the occupations on this site then becomes accessible.