Dharamjali speleothem trace elements and stable isotopes

A 25-cm long predominantly aragonite stalagmite was collected November 2, 2005 from Dharamjali Cave (29.5°N, 80.2°E) in the central Himalayas. This dataset contains stable isotope, trace element, XRF, U/Th dating, and dripwater data. The age model spans 4.2 to 2.3 ka BP, and the dataset records seasonal shifts in hydroclimate from 4.2 to 3.1 ka BP. Using the DHAR-1A half of the speleothem, 750 samples were milled at 100–300 µm resolution for stable isotope analysis (δ18O and δ13C) and analyzed at GFZ Potsdam. Further high-resolution stable isotope analysis at the University of Cambridge included 876 samples from the bottom 4 cm of the mirroring slab DHAR-1B, covering c. 4.2–3.6 ka BP. The δ44/40Ca measurements were made on 60 aragonite samples of aragonite and 1 calcite sample milled between 4.2 and 2.8 ka BP. The elemental composition of DHAR-1B was determined first with an Avaatech XRF scanner at the University of Cambridge, and later using laser ablation inductively-coupled plasma mass spectrometry (LA-ICP-MS) at the University of Waikato. U-series dating was performed at Caltech on 22 samples. Twelve U-series ages (between 2.55 and 4.14 ka BP) were used to construct the age models, using ensembles of 2000 Monte Carlo simulations for each proxy using the MATLAB-based COPRA script (Breitenbach et al., 2012, https://doi.org/10.5194/cp-8-1765-2012).

2005年11月2日，科研人员于喜马拉雅中部的达拉姆贾利洞穴（Dharamjali Cave，地理坐标29.5°N，80.2°E）采集了一根长25厘米、以文石（aragonite）为主要成分的石笋。本数据集涵盖稳定同位素、微量元素、X射线荧光光谱（XRF）、铀钍（U/Th）测年以及滴水观测数据。该年代标尺的时间跨度为4.2至2.3 ka BP，数据集记录了4.2至3.1 ka BP时段内水文气候的季节尺度变化。研究选取该洞穴碳酸盐沉积（speleothem）的DHAR-1A组分，以100–300微米（µm）的采样分辨率研磨制备750件样品，用于稳定同位素（δ¹⁸O与δ¹³C）分析，并于波茨坦德国地质研究中心（GFZ Potsdam）完成测试分析。剑桥大学后续开展了高分辨率稳定同位素分析，对镜像薄片DHAR-1B底部4厘米层位的876件样品进行测试，覆盖约4.2–3.6 ka BP的时段。钙同位素δ⁴⁴/⁴⁰Ca的测试针对60件文石样品与1件方解石样品完成，上述样品均研磨自4.2至2.8 ka BP的石笋段。DHAR-1B的元素组成首先通过剑桥大学的Avaatech XRF扫描仪完成测定，后续则依托怀卡托大学的激光剥蚀电感耦合等离子体质谱仪（LA-ICP-MS）开展分析。铀系测年工作于加州理工学院（Caltech）对22件样品完成。研究采用12个有效铀系测年结果（时间跨度为2.55至4.14 ka BP）构建年代标尺，针对每一项代用指标，通过基于MATLAB的COPRA脚本运行2000次蒙特卡洛（Monte Carlo）模拟集合完成建模（Breitenbach等，2012，https://doi.org/10.5194/cp-8-1765-2012）。