Reconstruction of the March–August PDSI since 1703 AD based on tree rings of Chinese pine (Pinus tabulaeformis Carr.) in the Lingkong Mountain, southeast Chinese loess Plateau
Abstract. We utilised tree-ring cores, collected from three sites at Lingkong Mountain located in the southeast part of the Chinese Loess Plateau (CLP), to develope a regional ring-width chronology. Significant positive correlations between the tree-ring index and the monthly Palmer drought severity index (PDSI) were identified, indicating that the radial growth of trees in this region was moisture-limited. The March–August mean PDSI was quantitatively reconstructed from 1703 to 2008 with an explained variance of 46.4%. Seven dry periods during 1719–1726, 1742–1748, 1771–1778, 1807–1818, 1832–1848, 1867–1932 and 1993–2008 and six wet periods during 1727–1741, 1751–1757, 1779–1787, 1797–1805, 1853–1864 and 1934–1957 were revealed in our reconstruction. Among them, 1867–1932 and 1934–1957 were identified as the longest dry and wet periods, respectively. On the centennial scale, the 19th century was recognised as the driest century. The drying tendency since 1960s was evident. However, recent drought in 1993–2008 was still within the frame of natural climate variability based on the 306 yr PDSI reconstruction. The dry and wet phases of Lingkong Mountain were in accordance with changes in the summer Asian-Pacific oscillation (IAPO) and sunspot numbers, they also showed strong similarity to other tree-ring based moisture indexes in large areas in and around the CLP, indicating the moisture variability in the CLP was almost synchronous and closely related with large-scale land–ocean–atmospheric circulation and solar activity. Spatial correlation analysis suggested that this PDSI reconstruction could represent the moisture variations for most parts of the CLP, and even larger area of northern China and east Mongolia. Multi-taper spectral analysis revealed significant cycles at the inter-annual (2–7 yr), inter-decadal (37.9 yr) and centennial (102 yr) scales. Results of this study are very helpful for us to improve the knowledge of past climate change in the CLP and enable us to prevent and manage future natural disasters.