# asia_russ066w - Khandiga River - 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/4463 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_russ066w - Khandiga River - 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: Khandiga River # Location: # Country: Russia # Northernmost_Latitude: 62.47 # Southernmost_Latitude: 62.47 # Easternmost_Longitude: 137.75 # Westernmost_Longitude: 137.75 # Elevation: 400 m #-------------------- # Data_Collection # Collection_Name: asia_russ066wB # Earliest_Year: 1675 # Most_Recent_Year: 1990 # 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":"5.05058237412","T2":"19.1336260222","M1":"0.0217032978303","M2":"0.205814939269"}} #-------------------- # Species # Species_Name: Dahurian larch # Species_Code: LAGM #-------------------- # 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 1675 1.241 1676 1.098 1677 0.815 1678 0.589 1679 0.388 1680 1.05 1681 1.549 1682 1.473 1683 1.4 1684 1.228 1685 1.09 1686 0.968 1687 0.548 1688 0.689 1689 0.955 1690 0.223 1691 1.101 1692 0.427 1693 1.298 1694 1.144 1695 0.443 1696 0.66 1697 0.978 1698 0.75 1699 0.761 1700 0.752 1701 1.168 1702 1.21 1703 0.858 1704 1.164 1705 0.992 1706 1.126 1707 1.004 1708 0.544 1709 0.728 1710 0.796 1711 0.939 1712 0.91 1713 0.93 1714 0.836 1715 1.11 1716 1.17 1717 1.024 1718 0.793 1719 0.989 1720 1.026 1721 1.132 1722 1.02 1723 1.348 1724 1.123 1725 0.839 1726 1.123 1727 1.266 1728 0.404 1729 0.898 1730 0.612 1731 0.467 1732 0.868 1733 0.826 1734 0.82 1735 0.826 1736 1.214 1737 0.991 1738 0.974 1739 1.085 1740 0.768 1741 1.011 1742 1.138 1743 1.009 1744 0.963 1745 1.129 1746 1.13 1747 1.025 1748 0.834 1749 0.933 1750 1.194 1751 1.279 1752 1.149 1753 1.025 1754 0.878 1755 1.108 1756 1.186 1757 1.245 1758 0.813 1759 1.066 1760 0.99 1761 0.799 1762 0.915 1763 0.892 1764 0.418 1765 1.05 1766 1.081 1767 1.419 1768 1.228 1769 1.219 1770 0.687 1771 0.636 1772 0.794 1773 0.981 1774 1.034 1775 1.035 1776 1.223 1777 1.251 1778 0.803 1779 0.817 1780 0.751 1781 1.055 1782 1.158 1783 1.182 1784 0.982 1785 1.075 1786 1.02 1787 1.155 1788 0.799 1789 0.842 1790 0.943 1791 0.769 1792 1.305 1793 1.508 1794 1.252 1795 1.265 1796 0.539 1797 0.14 1798 0.696 1799 0.66 1800 0.617 1801 0.774 1802 1.011 1803 0.977 1804 0.767 1805 1.181 1806 1.077 1807 1.327 1808 1.49 1809 1.657 1810 1.478 1811 1.007 1812 0.801 1813 0.876 1814 1.15 1815 0.712 1816 1.19 1817 0.774 1818 0.242 1819 1.264 1820 0.971 1821 1.096 1822 1.201 1823 0.666 1824 0.912 1825 0.716 1826 1.108 1827 1.041 1828 1.025 1829 1.113 1830 1.078 1831 1.382 1832 0.901 1833 1.238 1834 1.346 1835 1.276 1836 1.221 1837 0.575 1838 0.344 1839 0.627 1840 0.88 1841 0.941 1842 0.706 1843 1.08 1844 1.132 1845 0.883 1846 0.945 1847 0.994 1848 1.234 1849 1.045 1850 0.889 1851 1.12 1852 1.198 1853 0.757 1854 0.542 1855 0.076 1856 0.652 1857 0.736 1858 0.971 1859 0.915 1860 1.118 1861 1.016 1862 0.738 1863 0.536 1864 0.713 1865 0.791 1866 0.972 1867 1.322 1868 1.578 1869 1.749 1870 1.455 1871 1.018 1872 1.182 1873 1.458 1874 1.205 1875 1.049 1876 0.837 1877 0.854 1878 1.343 1879 1.055 1880 1.122 1881 1.336 1882 0.892 1883 1.441 1884 1.085 1885 0.739 1886 0.643 1887 0.874 1888 0.745 1889 1.03 1890 1.151 1891 1.46 1892 1.317 1893 1.795 1894 1.277 1895 1.5 1896 1.609 1897 1.639 1898 1.409 1899 1.283 1900 1.176 1901 1.063 1902 1.206 1903 1.364 1904 1.225 1905 0.883 1906 1.251 1907 1.079 1908 1.194 1909 0.837 1910 1.048 1911 0.712 1912 1.078 1913 0.878 1914 0.627 1915 0.821 1916 1.096 1917 0.902 1918 1.049 1919 1.343 1920 0.897 1921 1.106 1922 0.921 1923 0.983 1924 1.118 1925 0.69 1926 0.659 1927 0.859 1928 1.113 1929 0.877 1930 1.089 1931 1.437 1932 1.263 1933 1.057 1934 1.312 1935 0.963 1936 1.435 1937 1.668 1938 1.519 1939 1.239 1940 0.943 1941 0.752 1942 0.693 1943 0.319 1944 0.845 1945 0.68 1946 0.777 1947 0.768 1948 0.889 1949 1.007 1950 0.737 1951 0.931 1952 0.882 1953 1.065 1954 1.053 1955 0.746 1956 0.376 1957 0.854 1958 0.524 1959 0.892 1960 1.104 1961 1.233 1962 0.98 1963 0.779 1964 0.81 1965 0.752 1966 0.848 1967 0.989 1968 0.713 1969 0.898 1970 0.867 1971 0.726 1972 0.468 1973 1.049 1974 1.035 1975 1.098 1976 0.823 1977 0.928 1978 0.914 1979 0.752 1980 0.582 1981 1.021 1982 0.451 1983 0.67 1984 0.694 1985 0.647 1986 0.787 1987 0.793 1988 0.784 1989 0.845 1990 1.076