Description: Reliable age models are fundamental for any palaeoclimate reconstruction. Available interpolation procedures between age control points are often inadequately reported, and very few translate age uncertainties to proxy uncertainties. Most available modeling algorithms do not allow incorporation of layer counted intervals to improve the confidence limits of the age model in question. We present a framework that allows detection and interactive handling of age reversals and hiatuses, depth-age modeling, and proxy-record reconstruction. Monte Carlo simulation and a translation procedure are used to assign a precise time scale to climate proxies and to translate dating uncertainties to uncertainties in the proxy values. The presented framework allows integration of incremental relative dating information to improve the final age model. The free software package COPRA1.0 facilitates easy interactive usage.

Description: The analysis of palaeoclimate time series is usually affected by severe methodological problems, resulting primarily from non-equidistant sampling and uncertain age models. As an alternative to existing methods of time series analysis, in this paper we argue that the statistical properties of recurrence networks – a recently developed approach – are promising candidates for characterising the system's nonlinear dynamics and quantifying structural changes in its reconstructed phase space as time evolves. In a first order approximation, the results of recurrence network analysis are invariant to changes in the age model and are not directly affected by non-equidistant sampling of the data. Specifically, we investigate the behaviour of recurrence network measures for both paradigmatic model systems with non-stationary parameters and four marine records of long-term palaeoclimate variations. We show that the obtained results are qualitatively robust under changes of the relevant parameters of our method, including detrending, size of the running window used for analysis, and embedding delay. We demonstrate that recurrence network analysis is able to detect relevant regime shifts in synthetic data as well as in problematic geoscientific time series. This suggests its application as a general exploratory tool of time series analysis complementing existing methods.

Description: Sedimentary proxy records constitute a significant portion of the recorded evidence that allows us to investigate paleoclimatic conditions and variability. However, uncertainties in the dating of proxy archives limit our ability to fix the timing of past events and interpret proxy record intercomparisons. While there are various age-modeling approaches to improve the estimation of the age–depth relations of archives, relatively little focus has been placed on the propagation of the age (and radiocarbon calibration) uncertainties into the final proxy record. We present a generic Bayesian framework to estimate proxy records along with their associated uncertainty, starting with the radiometric age–depth and proxy–depth measurements, and a radiometric calibration curve if required. We provide analytical expressions for the posterior proxy probability distributions at any given calendar age, from which the expected proxy values and their uncertainty can be estimated. We illustrate our method using two synthetic data sets and then use it to construct the proxy records for groundwater inflow and surface erosion from Lonar lake in central India. Our analysis reveals interrelations between the uncertainty of the proxy record over time and the variance of proxies along the depth of the archive. For the Lonar lake proxies, we show that, rather than the age uncertainties, it is the proxy variance combined with calibration uncertainty that accounts for most of the final uncertainty. We represent the proxy records as probability distributions on a precise, error-free timescale that makes further time series analyses and intercomparisons of proxies relatively simple and clear. Our approach provides a coherent understanding of age uncertainties within sedimentary proxy records that involve radiometric dating. It can be potentially used within existing age modeling structures to bring forth a reliable and consistent framework for proxy record estimation.

Description: Fire is a natural component of global biogeochemical cycles and closely related to changes in human land use. Whereas climate-fuel relationships seem to drive both global and subcontinental fire regimes, human-induced fires are prominent mainly on a local scale. Furthermore, the basic assumption that relates humans and fire regimes in terms of population densities, suggesting that few human-induced fires should occur in periods and areas of low population density, is currently debated. Here, we analyze human-fire relationships throughout the Holocene and discuss how and to what extent human-driven fires affected the landscape transformation in the Central European Lowlands (CEL). We present sedimentary charcoal composites on three spatial scales and compare them with climate model output and land cover reconstructions from pollen records. Our findings indicate that widespread natural fires only occurred during the early Holocene. Natural conditions (climate and vegetation) limited the extent of wildfires beginning 8500 cal. BP, and diverging subregional charcoal composites suggest that Mesolithic hunter-gatherers maintained a culturally diverse use of fire. Divergence in regional charcoal composites marks the spread of sedentary cultures in the western and eastern CEL. The intensification of human land use during the last millennium drove an increase in fire activity to early-Holocene levels across the CEL. Hence, humans have significantly affected natural fire regimes beyond the local scale – even in periods of low population densities – depending on diverse cultural land-use strategies. We find that humans have strongly affected land-cover- and biogeochemical cycles since Mesolithic times.

Description: Northeastern (NE) India experiences extraordinarily pronounced seasonal climate, governed by the Indian summer monsoon (ISM). The vulnerability of this region to floods and droughts calls for detailed and highly resolved paleoclimate reconstructions to assess the recurrence rate and driving factors of ISM changes. We use stable oxygen and carbon isotope ratios (δ18O and δ13C) from stalagmite MAW-6 from Mawmluh Cave to infer climate and environmental conditions in NE India over the last deglaciation (16–6ka). We interpret stalagmite δ18O as reflecting ISM strength, whereas δ13C appears to be driven by local hydroclimate conditions. Pronounced shifts in ISM strength over the deglaciation are apparent from the δ18O record, similarly to other records from monsoonal Asia. The ISM is weaker during the late glacial (LG) period and the Younger Dryas, and stronger during the Bølling-Allerød and Holocene. Local conditions inferred from the δ13C record appear to have changed less substantially over time, possibly related to the masking effect of changing precipitation seasonality. Time series analysis of the δ18O record reveals more chaotic conditions during the late glacial and higher predictability during the Holocene, likely related to the strengthening of the seasonal recurrence of the ISM with the onset of the Holocene.

Description: High-resolution palynological analysis on annually laminated sediments of Sihailongwan Maar Lake (SHL) provides new insights into the Holocene vegetation and climate dynamics of NE China. The robust chronology of the presented record is based on varve counting and AMS radiocarbon dates from terrestrial plant macro-remains. In addition to the qualitative interpretation of the pollen data, we provide quantitative reconstructions of vegetation and climate based on the method of biomization and weighted averaging partial least squares regression (WA-PLS) technique, respectively. Power spectra were computed to investigate the frequency domain distribution of proxy signals and potential natural periodicities. Pollen assemblages, pollen-derived biome scores and climate variables as well as the cyclicity pattern indicate that NE China experienced significant changes in temperature and moisture conditions during the Holocene. Within the earliest phase of the Holocene, a large-scale reorganization of vegetation occurred, reflecting the reconstructed shift towards higher temperatures and precipitation values and the initial Holocene strengthening and northward expansion of the East Asian summer monsoon (EASM). Afterwards, summer temperatures remain at a high level, whereas the reconstructed precipitation shows an increasing trend until approximately 4000 cal. yr BP. Since 3500 cal. yr BP, temperature and precipitation values decline, indicating moderate cooling and weakening of the EASM. A distinct periodicity of 550–600 years and evidence of a Mid–Holocene transition from a temperature-triggered to a predominantly moisture-triggered climate regime are derived from the power spectra analysis. The results obtained from SHL are largely consistent with other palaeoenvironmental records from NE China, substantiating the regional nature of the reconstructed vegetation and climate patterns. However, the reconstructed climate changes contrast with the moisture evolution recorded in S China and the mid-latitude (semi-)arid regions of N China. Whereas a clear insolation-related trend of monsoon intensity over the Holocene is lacking from the SHL record, variations in the coupled atmosphere-Pacific Ocean system can largely explain the reconstructed changes in NE China.

Description: The incorporation of water isotopologues into the hydrology of general circulation models (GCMs) facilitates the comparison between modeled and measured proxy data in paleoclimate archives. However, the variability and drivers of measured and modeled water isotopologues, as well as the diversity of their representation in different models, are not well constrained. Improving our understanding of this variability in past and present climates will help to better constrain future climate change projections and decrease their range of uncertainty. Speleothems are a precisely datable terrestrial paleoclimate archives and provide well-preserved (semi-)continuous multivariate isotope time series in the lower latitudes and mid-latitudes and are therefore well suited to assess climate and isotope variability on decadal and longer timescales. However, the relationships of speleothem oxygen and carbon isotopes to climate variables are influenced by site-specific parameters, and their comparison to GCMs is not always straightforward. Here we compare speleothem oxygen and carbon isotopic signatures from the Speleothem Isotopes Synthesis and Analysis database version 2 (SISALv2) to the output of five different water-isotope-enabled GCMs (ECHAM5-wiso, GISS-E2-R, iCESM, iHadCM3, and isoGSM) over the last millennium (850–1850 CE). We systematically evaluate differences and commonalities between the standardized model simulation outputs. The goal is to distinguish climatic drivers of variability for modeled isotopes and compare them to those of measured isotopes. We find strong regional differences in the oxygen isotope signatures between models that can partly be attributed to differences in modeled surface temperature. At low latitudes, precipitation amount is the dominant driver for stable water isotope variability; however, at cave locations the agreement between modeled temperature variability is higher than for precipitation variability. While modeled isotopic signatures at cave locations exhibited extreme events coinciding with changes in volcanic and solar forcing, such fingerprints are not apparent in the speleothem isotopes. This may be attributed to the lower temporal resolution of speleothem records compared to the events that are to be detected. Using spectral analysis, we can show that all models underestimate decadal and longer variability compared to speleothems (albeit to varying extents). We found that no model excels in all analyzed comparisons, although some perform better than the others in either mean or variability. Therefore, we advise a multi-model approach whenever comparing proxy data to modeled data. Considering karst and cave internal processes, e.g., through isotope-enabled karst models, may alter the variability in speleothem isotopes and play an important role in determining the most appropriate model. By exploring new ways of analyzing the relationship between the oxygen and carbon isotopes, their variability, and co-variability across timescales, we provide methods that may serve as a baseline for future studies with different models using, e.g., different isotopes, different climate archives, or different time periods.

Description: The projected increases in Earth’s mean temperature entail substantial changes in the climate’s variability. Appropriate mitigation and adaptation measures require understanding of these changes since they impact for example the occurrence of extreme events. While projections of the global mean temperature are relatively well constrained based on the employed forcing scenario, they are highly uncertain with respect to the hydrological cycle and local temperature variability. Thus, examining how periods of past warming can help constrain these changes is of vital importance.To this end, we examine how the variability of surface temperature and precipitation changes in simulations of past and future warming from climate models of varying complexity and compare these with changes in proxy-based reconstructions. Based on the simulations, we analyze the moments of the distributions of temperature and precipitation (variance, skewness and kurtosis), as well as the power spectra with a focus on societally-relevant annual to centennial timescales. The analysis contrasts the projected changes under future warming scenarios with those found in transient simulations of the Last Deglaciation from models ranging from an energy balance model to Earth System Models. Changes observed in the simulations of the Last Deglaciation often highly depend on timescale and forcings, in particular changing volcanic activity, meltwater release and ice distributions alter patterns of variability. Based on this, we examine how the faster rate of future change impacts, and potentially limits, the conclusions to be drawn about future climatic changes based on past periods of warming.