# asia_kore001 - Whachae Peak-Sorak Mountain - Breitenmoser Tree Ring Chronology Data #----------------------------------------------------------------------- # 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: # # Online_Resource: https://www.ncdc.noaa.gov/paleo/study/24611 # # Original_Source_URL:https://www.ncdc.noaa.gov/paleo/study/4094 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_kore001 - Whachae Peak-Sorak Mountain - Breitenmoser Tree Ring Chronology Data #-------------------- # Investigators # Investigators: Breitenmoser, P.; Bronnimann, S.; Frank, D. #-------------------- # Description_and_Notes # Description: Data from Breitenmoser 2014 Journal of past Climate supplementary, see publication for ARSTAN standardization details #-------------------- # Publication # Authors: Breitenmoser, P.; Bronnimann, S.; Frank, D. # Published_Date_or_Year: 2014-03-11 # Published_Title: Forward modelling of tree-ring width and comparison with a global network of tree-ring chronologies # Journal_Name: Climate of the Past # Volume: 10 # Edition: # Issue: # Pages: 437-449 # DOI: 10.5194/cp-10-437-2014 # Online_Resource: www.clim-past.net/10/437/2014/ # Full_Citation: # Abstract: We investigate relationships between climate and tree-ring data on a global scale using the process-based Vaganov–Shashkin Lite (VSL) forward model of tree-ring width formation. The VSL model requires as inputs only latitude, monthly mean temperature, and monthly accumulated precipitation. Hence, this simple, process-based model enables ring-width simulation at any location where monthly climate records exist. In this study, we analyse the growth response of simulated tree rings to monthly climate conditions obtained from the CRU TS3.1 data set back to 1901. Our key aims are (a) to assess the VSL model performance by examining the relations between simulated and observed growth at 2287 globally distributed sites, (b) indentify optimal growth parameters found during the model calibration, and (c) to evaluate the potential of the VSL model as an observation operator for data-assimilation-based reconstructions of climate from tree-ring width. The assessment of the growth-onset threshold temperature of approximately 4–6 C for most sites and species using a Bayesian estimation approach complements other studies on the lower temperature limits where plant growth may be sustained. Our results suggest that the VSL model skilfully simulates site level treering series in response to climate forcing for a wide range of environmental conditions and species. Spatial aggregation of the tree-ring chronologies to reduce non-climatic noise at the site level yielded notable improvements in the coherence between modelled and actual growth. The resulting distinct and coherent patterns of significant relationships between the aggregated and simulated series further demonstrate the VSL model’s ability to skilfully capture the climatic signal contained in tree-ring series. Finally, we propose that the VSL model can be used as an observation operator in data assimilation approaches to reconstruct past climate. #-------------------- # Authors: Anderson, D.M., Tardif, R., Horlick, K., Erb, M.P., Hakim, G.J., Noone, D., Perkins, W.A., and E. Steig # Published_Date_or_Year: 2018 # Published_Title: Additions to the last millennium reanalysis multi-proxy database # Journal_Name: Data Science Journal # Volume: # Edition: # Issue: # Pages: # Report_Number: # DOI: # Online_Resource: # Full_Citation: Anderson, D.M., Tardif, R., Horlick, K., Erb, M.P., Hakim, G., J., Noone, D., Perkins, W.A., and E. Steig, submitted. Additions to the last millennium reanalysis multi-proxy database. Data Science Journal. # Abstract: Progress in paleoclimatology increasingly occurs via data syntheses. We describe additions to a collection prepared for use in paleoclimate state estimation, specifically the Last Millennium Reanalysis (LMR). The 2290 additional series include 2152 tree ring chronologies and 138 other series. They supplement the collection used previously and together form a database titled LMRdb 1.0.0. The additional data draws from lake core, ice core, coral, speleothem, and tree ring archives, using published data primarily from the NOAA Paleoclimatology archive and a set of tree ring width chronologies standardized from raw International Tree Ring Data Bank ring width series. In contrast to many previous paleo compilations, the data were not selected (screened) on the basis of their environmental correlation, multi-century length, or other attributes. The inclusion of proxies sensitive to moisture and other environmental variables expands their use in data assimilation. A preliminary calibration using linear regression with mean annual temperature reveals characteristics of the proxy series and their relationship to temperature, as well as the noise and error characteristics of the records. The additional records are structured as individual files in the NOAA Paleoclimatology format and archived at NOAA Paleoclimatology (Anderson et al. 2018) and will continue to be improved and expanded as part of the LMR Project. The additions represent a four-fold increase in the number of records available for assimilation, provide expanded geographic coverage, and add additional proxy variables. Applications include data assimilation, proxy system model development, and paleoclimate reconstruction using climate field reconstruction and other methods. #------------------ # Funding_Agency # Funding_Agency_Name: Swiss National Science Foundation # Grant: #-------------------- # Funding_Agency_Name: National Science Foundation # Grant:AGS-1304263 # Funding_Agency_Name: National Oceanic and Atmospheric Administration # Grant:NA14OAR4310176 #------------------ # Site_Information # Site_Name: Whachae Peak-Sorak Mountain # Location: # Country: Korea, Republic of # Northernmost_Latitude: 38.13 # Southernmost_Latitude: 38.13 # Easternmost_Longitude: 128.47 # Westernmost_Longitude: 128.47 # Elevation: 1500 m #-------------------- # Data_Collection # Collection_Name: asia_kore001B # Earliest_Year: 1703 # Most_Recent_Year: 1998 # Time_Unit: y_ad # Core_Length: # Notes: {"database":{"database1":"LMR","database2":"Breits"}} {"climateInterpretation":{"basis":"", "climateVariable":"T", "climateVariableDetail":"air", "interpDirection":"positive", "seasonality":"[6, 7, 8]"}}{"VSLite_parameters":{"T1":"4.69605778792","T2":"18.3666393371","M1":"0.0223979292156","M2":"0.315253658905"}} #-------------------- # Species # Species_Name: Korean pine # Species_Code: PIKO #-------------------- # 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 age, , ,years AD, , , , ,N ##trsgi tree ring standardized growth index, tree ring, ,percent relative to mean growth, , Tree Rings, , ,N # #-------------------- # Data: # Data lines follow (have no #) # Data line format - tab-delimited text, variable short name as header # Missing Values: nan # age trsgi 1703 0.745 1704 0.832 1705 0.76 1706 0.837 1707 0.809 1708 1.079 1709 0.799 1710 0.946 1711 0.93 1712 0.891 1713 0.634 1714 0.407 1715 0.662 1716 0.686 1717 0.764 1718 0.832 1719 0.777 1720 0.707 1721 0.97 1722 0.752 1723 1.087 1724 0.666 1725 0.847 1726 1.097 1727 0.879 1728 0.944 1729 0.984 1730 0.836 1731 0.985 1732 1.118 1733 1.018 1734 1.225 1735 1.346 1736 1.582 1737 1.141 1738 1.2 1739 1.224 1740 1.194 1741 0.983 1742 1.078 1743 1.1 1744 1.332 1745 1.44 1746 1.244 1747 0.833 1748 1.022 1749 0.906 1750 1.072 1751 1.054 1752 1.047 1753 1.32 1754 0.922 1755 0.948 1756 0.697 1757 1.016 1758 0.692 1759 0.765 1760 0.99 1761 1.105 1762 1.177 1763 0.745 1764 0.849 1765 0.963 1766 1.317 1767 1.332 1768 1.096 1769 1.247 1770 1.236 1771 0.943 1772 1.016 1773 1.067 1774 0.962 1775 1.03 1776 1.257 1777 1.062 1778 0.927 1779 1.112 1780 1.024 1781 1.131 1782 0.95 1783 0.87 1784 0.894 1785 0.702 1786 0.887 1787 0.975 1788 0.68 1789 0.63 1790 0.74 1791 0.993 1792 1.053 1793 1.369 1794 1.32 1795 0.907 1796 0.905 1797 0.965 1798 0.878 1799 0.879 1800 0.959 1801 0.791 1802 1.062 1803 1.154 1804 1.029 1805 1.091 1806 1.235 1807 0.926 1808 0.823 1809 0.796 1810 0.833 1811 1.006 1812 1.201 1813 0.959 1814 0.911 1815 1.08 1816 1.16 1817 0.92 1818 1.22 1819 1.218 1820 1.344 1821 1.179 1822 1.261 1823 0.949 1824 0.921 1825 0.985 1826 0.791 1827 1.067 1828 1.308 1829 1.247 1830 1.127 1831 0.983 1832 1.15 1833 1.074 1834 0.837 1835 0.8 1836 0.798 1837 0.844 1838 0.783 1839 0.58 1840 0.623 1841 0.275 1842 0.229 1843 0.199 1844 0.186 1845 0.323 1846 0.387 1847 0.521 1848 0.586 1849 0.817 1850 0.68 1851 0.759 1852 0.688 1853 0.945 1854 0.883 1855 1.006 1856 1.12 1857 1.076 1858 1.098 1859 0.917 1860 0.859 1861 0.853 1862 1.07 1863 1.067 1864 1.368 1865 1.192 1866 1.237 1867 1.005 1868 1.489 1869 1.028 1870 1.257 1871 1.52 1872 1.627 1873 1.303 1874 1.302 1875 1.251 1876 1.614 1877 1.326 1878 1.422 1879 0.973 1880 0.947 1881 0.944 1882 1.17 1883 1.178 1884 1.341 1885 0.982 1886 0.911 1887 0.91 1888 0.973 1889 1.14 1890 1.075 1891 1.131 1892 1.021 1893 0.954 1894 1.06 1895 1.373 1896 0.685 1897 0.608 1898 0.675 1899 0.878 1900 1.058 1901 1.26 1902 1.069 1903 0.998 1904 0.655 1905 0.779 1906 0.63 1907 0.85 1908 1.002 1909 0.79 1910 0.828 1911 0.797 1912 0.752 1913 0.696 1914 0.981 1915 1.083 1916 1.037 1917 0.829 1918 0.844 1919 0.889 1920 1.088 1921 1.043 1922 1.058 1923 1.093 1924 1.042 1925 0.917 1926 0.814 1927 0.99 1928 0.822 1929 0.829 1930 1.212 1931 1.162 1932 0.81 1933 0.657 1934 0.58 1935 0.705 1936 0.731 1937 0.851 1938 0.989 1939 1.297 1940 1.075 1941 1.215 1942 1.085 1943 1.443 1944 1.563 1945 1.083 1946 0.65 1947 0.655 1948 0.622 1949 0.788 1950 1.027 1951 1.067 1952 1.094 1953 1.292 1954 1.17 1955 1.052 1956 1.256 1957 1.078 1958 1.088 1959 0.768 1960 0.943 1961 1.191 1962 1.109 1963 1.037 1964 1.163 1965 0.884 1966 0.926 1967 0.799 1968 0.834 1969 0.67 1970 0.591 1971 0.504 1972 0.821 1973 0.966 1974 0.978 1975 0.843 1976 0.756 1977 0.836 1978 0.885 1979 0.976 1980 1.029 1981 0.776 1982 0.895 1983 0.914 1984 0.891 1985 1.141 1986 0.971 1987 0.874 1988 0.916 1989 1.188 1990 1.108 1991 1.166 1992 1.204 1993 0.828 1994 1.098 1995 1.22 1996 0.822 1997 1.148 1998 1.402