Abstract. 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 (R²_adj = 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 (R²_adj = 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.

中文翻译：

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生化脉管中保存的季节性气候信号：新型高分辨率沉积物扫描技术的见解

摘要。曲折的湖泊沉积物由于其精确的时间控制和年度分辨率，是古气候信息的特殊档案。然而，基于生化阀门生化地球化学成分的定量古气候重建非常罕见，主要是因为气候代理关系复杂，并且很难以很高的（年）分辨率获得生化地球替代数据。沉积颜料生物标志物的高分辨率高光谱成像（HSI）与微X射线荧光（μXRF）元素映射相结合的最新发展，使得以前所未有的分辨率测量瓣膜的结构和组成成为可能。这提供了探索生物化学阀门中保存的（季节性）气候信号的机会，因此，评估从生物化学途径进行年度分辨率气候重建的潜力。在这里，我们介绍了一个地球化学数据集，包括HSI推断的沉积色素和uXRF推断的元素，其空间分辨率非常高（60μm，即每个脉动年大于100个数据点），位于波兰Żabiskiskie1966-2019年期间CE。我们将该数据与当地气象观测资料进行比较，以探索和量化变化的季节性气象条件如何影响沉积物成分和阀门形成过程。根据脉内多元地球化学时间序列的不相似性，我们将脉分为四类。多变量方差分析表明，这四种类型的阀门是在几年内形成的，其季节气象条件明显不同。基于沉积变量，使用广义加性模型（GAM）推断季节气候条件。使用Ti和总C（R² _ADJ  = 0.55; 交叉验证的均方根误差（CV-RMSE）= 0.7°C，14.4％）。使用质量累积率（MAR）和Si（R ² _adj  = 0.48; CV-RMSE = 19.0％）来预测3月至12月的大风天（平均每日风速> 7 m / s ）。这项研究表明，高分辨率扫描技术是有前途的工具，可以增进我们对生物化学瓣膜中瓣膜形成过程和气候-代理关系的了解。这些知识是定量高分辨率古气候重建的基础，在这里，我们提供了根据瓦尔韦生物地球化学数据对年分辨率季节性天气推断进行校准和验证的示例。