Recurrent transitions to Little Ice Age-like climatic regimes over the Holocene

Holocene climate variability is punctuated by episodic climatic events such as the Little Ice Age (LIA) predating the industrial-era warming. Their dating and forcing mechanisms have however remained controversial. Even more crucially, it is uncertain whether earlier events represent climatic regimes similar to the LIA. Here we produce and analyse a new 7500-year long palaeoclimate record tailored to detect LIA-like climatic regimes from northern European tree-ring data. In addition to the actual LIA, we identify LIA-like ca. 100-800 year periods with cold temperatures combined with clear sky conditions from 540 CE, 1670 BCE, 3240 BCE and 5450 BCE onwards, these LIA-like regimes covering 20% of the study period. Consistent with climate modelling, the LIA-like regimes originate from a coupled atmosphere-ocean-sea ice North Atlantic-Arctic system and were amplified by volcanic activity (multiple eruptions closely spaced in time), tree-ring evidence pointing to similarly enhanced LIA-like regimes starting after the eruptions recorded in 1627 BCE, 536/540 CE and 1809/1815 CE. Conversely, the ongoing decline in Arctic sea-ice extent is mirrored in our data which shows reversal of the LIA-like conditions since the late nineteenth century, our record also correlating highly with the instrumentally recorded Northern Hemisphere and global temperatures over the same period. Our results bridge the gaps between low- and high-resolution, precisely dated proxies and demonstrate the efficacy of slow and fast components of the climate system to generate LIA-like climate regimes.Peer reviewe

Estimation of Biases in RCS Chronologies of Tree Rings

Проводится сравнение RCS- и signal-free RCS- хронологий на нескольких примерах с реальными и модельными измерениями ширины годичных колец деревьев. Модельные измерения, содержащие известный климатический сигнал, строятся на основе реальных с сохранением структуры набора данных. Во всех экспериментах на модельных данных signal-free RCS превосходит обычный RCS. Но в то же время он менее устойчив к сокращению числа серий измерений. Предлагается метод оценки и корректировки возможных смещений в RCS- хронологиях древесных колец, связанных со структурой набора данных (длина и особенности индивидуальных серий, распределение данных во времени). Такая корректировка может проводиться перед построением реконструкций с применением стандартизации региональной кривой (RCS) и ее «очищенной от сигнала» модификации (signal-free RCS) для повышения точности этих реконструкций.We use several examples of modeled and real tree ring width measurements to compare RCS and signal-free RCS chronologies. Modeled data containing known climatic signal are designed to preserve the structure of dataset. All the experiments with modeled data showed the better ability of signal-free RCS to restore climatic signal. At the same time it is less (as compared to conventional RCS) robust to the reduction of sample depth. A method for evaluation and correction of biases connected with the structure of dataset (length and specifics of individual series, their distribution in time) is proposed. Such correction can be carried out before making climate reconstructions with conventional RCS and signal-free RCS chronologies

Estimation of Biases in RCS Chronologies of Tree Rings

Проводится сравнение RCS- и signal-free RCS- хронологий на нескольких примерах с реальными и модельными измерениями ширины годичных колец деревьев. Модельные измерения, содержащие известный климатический сигнал, строятся на основе реальных с сохранением структуры набора данных. Во всех экспериментах на модельных данных signal-free RCS превосходит обычный RCS. Но в то же время он менее устойчив к сокращению числа серий измерений. Предлагается метод оценки и корректировки возможных смещений в RCS- хронологиях древесных колец, связанных со структурой набора данных (длина и особенности индивидуальных серий, распределение данных во времени). Такая корректировка может проводиться перед построением реконструкций с применением стандартизации региональной кривой (RCS) и ее «очищенной от сигнала» модификации (signal-free RCS) для повышения точности этих реконструкций.We use several examples of modeled and real tree ring width measurements to compare RCS and signal-free RCS chronologies. Modeled data containing known climatic signal are designed to preserve the structure of dataset. All the experiments with modeled data showed the better ability of signal-free RCS to restore climatic signal. At the same time it is less (as compared to conventional RCS) robust to the reduction of sample depth. A method for evaluation and correction of biases connected with the structure of dataset (length and specifics of individual series, their distribution in time) is proposed. Such correction can be carried out before making climate reconstructions with conventional RCS and signal-free RCS chronologies

Dynamics of seasonal patterns in geochemical, isotopic, and meteorological records of the elbrus region derived from functional data clustering

A nonparametric clustering method, the Bagging Voronoi K-Medoid Alignment algorithm, which simultaneously clusters and aligns spatially/temporally dependent  curves,  is applied to study various data series from the Elbrus  region (Central Caucasus). We used the algorithm to cluster annual curves obtained by smoothing of the following synchronous data series: titanium concentrations in varved (annually laminated) bottom sediments of proglacial  Lake Donguz-Orun;  an oxygen-18 isotope record in an ice core from Mt. Elbrus; temperature and precipitation observations with a monthly resolution from Teberda and Terskol meteorological stations. The data of different types were clustered independently. Due to restrictions concerned with the availability of meteorological data, we have fulfilled the clustering procedure separately for two periods: 1926–2010 and 1951–2010. The study is aimed to determine whether the instrumental period could be reasonably divided (clustered)  into several sub-periods using different climate and proxy time series; to examine the interpretability of the resulting borders of the clusters (resulting time periods); to study typical patterns of intra-annual variations of the data series. The results of clustering suggest that the precipitation and to a lesser degree titanium decadal-scale data may be reasonably grouped, while the temperature and oxygen-18 series are too short to form meaningful clusters; the intercluster boundaries show a notable degree of coherence between temperature and oxygen-18 data, and less between titanium and oxygen-18 as well as for precipitation series; the annual curves for titanium and partially precipitation data reveal much more pronounced intercluster  variability than the annual patterns of temperature and oxygen-18 data