Pollen based annual precipitation for Lake Bayan Nuur ...

• Main Authors: Rudaya, Natalia, Nazarova, Larisa B, Frolova, Larisa A, Palagushkina, Olga V, Soenov, Vasiliy, Cao, Xianyong, Syrykh, Luidmila S, Grekov, Ivan, Otgonbayar, Demberel, Bayarkhuu, Batbayar
• Format: Dataset
• Language: English
• Published: PANGAEA 2023
• Subjects: DEPTH, sediment/rock; AGE; Temperature, air, July; Sediment corer; see description in data abstract; Arctic; Nazarova; Siberia
• Online Access: https://dx.doi.org/10.1594/pangaea.953305; https://doi.pangaea.de/10.1594/PANGAEA.953305

Method for quantitative reconstruction of mean July air temperatures (Tjuly). The quantitative reconstruction of mean July air temperatures (TJuly) is based on calibration chironomid data sets for lakes from northern Russia (Nazarova et al., 2015, doi:10.1016/j.gloplacha.2014.11.015). Mean July air temperatures were inferred using a North Russian (NR) chironomid-based temperature inference model (WA-PLS, 2 component; r 2 boot = 0.81; RMSEP boot =1.43 °C) based on a modern calibration data set of 193 lakes and 162 taxa from East and West Siberia (61-75°N, 50-140 °E, T July range 1.8 - 18.8 °C). The mean July air temperature of the lakes for the calibration data set was derived from New et al. (2002, doi:10.3354/cr021001). The TJuly NR model was previously applied to palaeoclimatic inferences in Europe, arctic Russia, East and West Siberia, and demonstrated a high reliability of the reconstructed parameters. The chironomid-inferred TJuly were corrected to 0 m a.s.l. using a modern July air temperature lapse ...