South Asian precipitation amount and extreme variability are predicted to increase due to thermodynamic effects of increased 21st-century greenhouse gases, accompanied by an increased supply of moisture from the southern hemisphere Indian Ocean. We reconstructed South Asian summer monsoon precipitation and runoff into the Bay of Bengal to assess the extent to which these factors also operated in the Pleistocene, a time of large-scale natural changes in carbon dioxide and ice volume. South Asian precipitation and runoff are strongly coherent with, and lag, atmospheric carbon dioxide changes at Earth’s orbital eccentricity, obliquity, and precession bands and are closely tied to cross-equatorial wind strength at the precession band. We find that the projected monsoon response to ongoing, rapid high-latitude ice melt and rising carbon dioxide levels is fully consistent with dynamics of the past 0.9 million years.

No abstract

The response of Asian Monsoon subsystems to both hemispheric climate forcing and external orbital forcing are currently issues of vigorous debate. The Indian Summer Monsoon is the dominant monsoon subsystem in terms of energy flux, constituting one of Earth's most dynamic expressions of ocean-atmosphere interactions. Yet the Indian Summer Monsoon is grossly under-represented in Asian Monsoon palaeoclimate records. Here we present high-resolution records of Indian Summer Monsoon induced rainfall and fluvial runoff recovered in a sediment core from the Bay of Bengal across Termination II, 139 to 127 thousand years ago, including coupled measurements of the oxygen isotopic composition and Mg/Ca, Mn/Ca, Nd/Ca and U/Ca ratios in surface-ocean dwelling foraminifera. Our data reveal a millennial-scale transient strengthening of the Asian Monsoon that punctuates Termination II associated with an oscillation of the

X‐ray fluorescence (XRF) core scanning of marine and lake sediments has been extensively used to study changes in past environmental and climatic processes over a range of timescales. The interpretation of XRF‐derived element ratios in paleoclimatic and paleoceanographic studies primarily considers differences in the relative abundances of particular elements. Here we present new XRF core scanning data from two long sediment cores in the Andaman Sea in the northern Indian Ocean and show that sea level related processes influence terrigenous inputs based proxies such as Ti/Ca, Fe/Ca, and elemental concentrations of the transition metals (e.g., Mn). Zr/Rb ratios are mainly a function of changes in median grain size of lithogenic particles and often covary with changes in Ca concentrations that reflect changes in biogenic calcium carbonate production. This suggests that a common process (i.e., sea level) influences both records. The interpretation of lighter element data (e.g., Si and Al) based on low XRF counts is complicated as variations in mean grain size and water content result in systematic artifacts and signal intensities not related to the Al or Si content of the sediments. This highlights the need for calibration of XRF core scanning data based on discrete sample analyses and careful examination of sediment properties such as porosity/water content for reliably disentangling environmental signals from other physical properties. In the case of the Andaman Sea, reliable extraction of a monsoon signal requires accounting for the sea level influence on the XRF data.

Abstract. Planktonic foraminifera are widely used in biostratigraphic, palaeoceanographic and evolutionary studies, but the strength of many study conclusions could be weakened if taxonomic identifications are not reproducible by different workers. In this study, to assess the relative importance of a range of possible reasons for among-worker disagreement in identification, 100 specimens of 26 species of macroperforate planktonic foraminifera were selected from a core-top site in the subtropical Pacific Ocean. Twenty-three scientists at different career stages – including some with only a few days experience of planktonic foraminifera – were asked to identify each specimen to species level, and to indicate their confidence in each identification. The participants were provided with a species list and had access to additional reference materials. We use generalised linear mixed-effects models to test the relevance of three sets of factors in identification accuracy: participant-level characteristics (including experience), species-level characteristics (including a participant's knowledge of the species) and specimen-level characteristics (size, confidence in identification). The 19 less experienced scientists achieve a median accuracy of 57 %, which rises to 75 % for specimens they are confident in. For the 4 most experienced participants, overall accuracy is 79 %, rising to 93 % when they are confident. To obtain maximum comparability and ease of analysis, everyone used a standard microscope with only 35× magnification, and each specimen was studied in isolation. Consequently, these data provide a lower limit for an estimate of consistency. Importantly, participants could largely predict whether their identifications were correct or incorrect: their own assessments of specimen-level confidence and of their previous knowledge of species concepts were the strongest predictors of accuracy.