The Mediterranean region is expected to be highly impacted by global warming. To better understand and predict shifts in its current climate system, climate time series covering seasonal-to-century scale climate variability are needed.Here we provide a dataset containing a high-resolution reconstruction of autumn precipitation variability for the Central Pyrenees that spans the 1500-2002 CE period. This dataset is based on calcite sublayer width of varved sediments of lake Montcortès. Sediment cores MON12-3A-1G and MON12-2A-1G were retrieved from the deepest basin of the lake. Large-scale thin sections of sediment (120 mm X 35 mm) were extracted and calcite varve sublaminae counted and characterised. The age-depth model was built by combining varve counting and radiometric dating (210Pb, 137Cs and 14C).Long-term trend of the raw calcite width series was removed with a low pass filter by fitting a cubic smoothing spline of 67% of the series length. To find out how well the smoothed calcite series and instrumental regional precipitation match up with each other, correlation and cross correlation methods were applied. Highest correlation values were obtained with autumn precipitation anomalies for the entire calibration period (1900-2002) and for the two halve subperiods (1910–1956 and 1957–2002). The applied statistical tests yield highly significant results. The obtained regression model explained 15.5% (R2-value for the full calibration period) of the September to November precipitation variability. The obtained transfer function allowed inferring past autumn precipitation from calcium carbonate sublayer thickness at annual resolution. The reconstructed series (PPT-SON) provides the first estimations of regional autumn precipitation shifts in the Central Pyrenees since 1500 CE.
Funding was granted by the Spanish Ministry of Economy and Competitivity (MINECO/FEDER) projects MONT-500, ref. CGL2012-33665, MEROMONT, CGL2017-85682-R, G LOBALKARST, ref. CGL2009-08145 and the Catalan University and Research Management Agency (AGAUR) project 2017, ref. SGR 1116.