# Lower Yangtze River 158 Year February-April Precipitation Reconstruction #----------------------------------------------------------------------- # World Data Center for Paleoclimatology, Boulder # and # NOAA Paleoclimatology Program #----------------------------------------------------------------------- # NOTE: Please cite Publication, and Online_Resource and date accessed when using these data. # If there is no publication information, please cite Investigators, Title, and Online_Resource and date accessed. # # # Online_Resource: http://ncdc.noaa.gov/paleo/study/18335 # # Original_Source_URL: ftp://ftp.ncdc.noaa.gov/pub/data/paleo/treering/reconstructions/asia/china/shi2015precip.txt # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Climate Reconstructions #-------------------- # Contribution_Date # Date: 2015-05-19 #-------------------- # Title # Study_Name: Lower Yangtze River 158 Year February-April Precipitation Reconstruction #-------------------- # Investigators # Investigators: Shi, J; Lu, H.; Li, J.; Shi, S.; Wu, S.; Hou, X.; Li, L. #-------------------- # Description_and_Notes # Description: Tree-ring based reconstruction of spring (February-April) precipitation for the lower reaches # of the Yangtze River, southeastern China. #-------------------- # Publication # Authors: Jiangfeng Shi, Huayu Lu, Jinbao Li, Shiyuan Shi, Shuangye Wu, Xinyuan Hou, Lingling Li # Published_Date_or_Year: 2015-05-19 # Published_Title: Tree-ring based February-April precipitation reconstruction for the lower reaches of the Yangtze River, southeastern China # Journal_Name: Global and Planetary Change # Volume: 131 # Edition: # Issue: # Pages: 82-88 # DOI: 10.1016/j.gloplacha.2015.05.006 # Online_Resource: http://www.sciencedirect.com/science/article/pii/S0921818115000910 # Full_Citation: # Abstract: February-April drought strongly affects agriculture and socio-economics in southeastern China, yet its long-term variability has not been assessed due to the shortness of instrumental records. In this study, we reported a 168-year tree-ring width chronology from a steep, low-elevation site with thin soil layers in the Xianxia Mountains, southeastern China. Contrary to the existing chronologies that are mostly temperature sensitive, this chronology contained a strong February-April precipitation signal, indicating great potential for tree-ring based precipitation reconstructions in southeastern China. The reconstruction explained 47.8% of the instrumental variance during 1951-2012. The full reconstruction indicated that there were 3 dry periods (1873-1896, 1924-1971, 1995-2012) and 2 wet periods (1856-1872, 1972-1994) during 1856-2013. The extreme drought in 2011 was not unprecedented for the past 168 years, and the recent severe droughts may be part of interdecadal variations in regional February-April precipitation. Our results also suggested that February-April precipitation in southeastern China was highly influenced by the tropical Pacific climate system, in particular El Nino-Southern Oscillation (ENSO). #------------------ # Funding_Agency # Funding_Agency_Name: Natural Science Foundation of China # Grant: NSFC Project (No. 41271210) #------------------ # Funding_Agency # Funding_Agency_Name: Ministry of Science and Technology of the People's Republic of China # Grant: the National Basic Research Program of China (973 Program) (No. 2010CB950101) #------------------ # Funding_Agency # Funding_Agency_Name: Ministry of Education of the People's Republic of China # Grant: the Fundamental Research Funds for the Central Universities (No. 20620140083) #------------------ # Funding_Agency # Funding_Agency_Name: Jiangsu province # Grant: the Priority Academic Program Development of Jiangsu Higher Education Institutions. #------------------ # Site_Information # Site_Name: Lower Yangtze River # Location: Asia>Eastern Asia>China # Country: China # Northernmost_Latitude: 34.0 # Southernmost_Latitude: 28.0 # Easternmost_Longitude: 122.0 # Westernmost_Longitude: 116.0 # Elevation: m #------------------ # Data_Collection # Collection_Name: Shi2015precip # Earliest_Year: 1856 # Most_Recent_Year: 2013 # Time_Unit: AD # Core_Length: m # Notes: #------------------ # Species # Species_Name: Pinus massoniana # Common_Name: Horse Tail Pine #------------------ # Chronology: # # # # # #---------------- # Variables # # Data variables follow that are preceded by "##" in columns one and two. # Data line variables format: Variables list, one per line, shortname-tab-longname-tab-longname components (9 components: what, material, error, units, seasonality, archive, detail, method, C or N for Character or Numeric data) # ##age_AD age, , , AD, , , , ,N ##precip-FMA precipitation, , , mm, February-April, , , tree-ring reconstruction,N # #---------------- # Data: # Data lines follow (have no #) # Data line format - tab-delimited text, variable short name as header # Missing Values: # age_AD precip-FMA 1856 376.01 1857 344.87 1858 396.88 1859 388.72 1860 426.21 1861 367.85 1862 410.79 1863 410.79 1864 337.31 1865 226.93 1866 406.86 1867 409.58 1868 430.45 1869 462.20 1870 372.99 1871 439.22 1872 365.13 1873 245.68 1874 374.50 1875 359.69 1876 341.24 1877 317.95 1878 337.61 1879 275.62 1880 385.39 1881 400.51 1882 422.89 1883 328.54 1884 370.87 1885 398.69 1886 320.98 1887 304.95 1888 315.54 1889 282.88 1890 366.94 1891 337.61 1892 334.28 1893 313.72 1894 318.56 1895 322.49 1896 330.96 1897 375.41 1898 434.98 1899 418.05 1900 340.63 1901 365.43 1902 327.93 1903 346.38 1904 375.11 1905 337.31 1906 443.45 1907 354.24 1908 299.81 1909 326.72 1910 387.51 1911 432.26 1912 395.37 1913 380.85 1914 322.49 1915 372.69 1916 365.43 1917 305.25 1918 271.69 1919 357.27 1920 394.76 1921 393.25 1922 447.98 1923 457.06 1924 350.92 1925 291.34 1926 359.69 1927 366.94 1928 335.49 1929 338.52 1930 279.85 1931 312.21 1932 366.94 1933 363.31 1934 300.72 1935 418.05 1936 366.94 1937 385.39 1938 294.37 1939 342.15 1940 320.98 1941 422.89 1942 412.00 1943 337.61 1944 259.59 1945 286.81 1946 353.03 1947 355.15 1948 373.90 1949 308.28 1950 455.54 1951 354.24 1952 435.59 1953 292.25 1954 358.78 1955 336.10 1956 294.67 1957 339.73 1958 356.96 1959 491.53 1960 345.47 1961 251.73 1962 298.30 1963 339.12 1964 353.64 1965 370.57 1966 344.57 1967 332.47 1968 320.07 1969 333.07 1970 348.50 1971 303.44 1972 464.01 1973 469.45 1974 374.81 1975 458.87 1976 483.97 1977 458.27 1978 313.12 1979 348.19 1980 357.27 1981 379.04 1982 395.37 1983 447.38 1984 310.09 1985 319.16 1986 341.54 1987 406.25 1988 306.77 1989 326.42 1990 400.51 1991 508.77 1992 468.85 1993 396.88 1994 396.88 1995 287.72 1996 299.51 1997 323.10 1998 352.73 1999 347.59 2000 300.42 2001 355.45 2002 333.68 2003 445.87 2004 328.84 2005 310.09 2006 356.06 2007 350.01 2008 306.16 2009 385.69 2010 448.89 2011 268.66 2012 282.57 2013 391.74