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Gauged river flow records from China generally span only a few decades, which hampers the detection of long-term, decadal- to centennial-scale cycles and trends in streamflow variability. New and updated tree-ring chronologies help reconstructed the water-year (October–September) streamflow for the Aksu River, which is an important river at the edge of the Taklimakan Desert that drains into the Tarim Basin. The reconstruction dates back to 1692 and has an adjusted r 2 of 0.61 (1957–2006). Based on frequency, intensity and duration of droughts and pluvial events, the lowest streamflows occurred in the 1920s. Since then streamflow has continuously increased, and was exceptionally rapidly after the 1960s, until today. The start and end of the 20th century to the present were the highest streamflow periods. The mid-20th century was the longest and driest period over the past 300 yr. The reconstructed streamflow series has a strong positive correlation with the North Atlantic Oscillation Index. Changes in mid-latitude circulation patterns influencing precipitation may have indirectly resulted in streamflow variations along the Aksu River over the past 300 yr. The rapid increase and the exceptional streamflows of the 1960s are likely linked with global warming and mid-latitude atmospheric circulation changes. [ABSTRACT FROM AUTHOR]

Abstract: Three robust tree-ring density chronologies were developed for the western Tianshan Mountains of northwestern China. The chronologies were significantly correlated and form a regional chronology (GLD). The GLD had significant and positive correlations with temperature of warm seasons. Based on this relationship, the mean minimum temperatures of May to August were reconstructed using the GLD chronology for the period AD 1657 to 2008. The temperature reconstruction exhibited temperature patterns on interannual to centennial timescales, and showed that the end of the 20th century is the warmest period in the past 352years. The reconstructed temperature variation has a teleconnection with large-scale atmospheric–oceanic variability and captures long- and broad-scale regional climatic variations. [Copyright &y& Elsevier]