# asia_russ123w - Kozhim - 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/4479 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_russ123w - Kozhim - 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: Kozhim # Location: # Country: Russia # Northernmost_Latitude: 65.45 # Southernmost_Latitude: 65.45 # Easternmost_Longitude: 60.58 # Westernmost_Longitude: 60.58 # Elevation: 400 m #-------------------- # Data_Collection # Collection_Name: asia_russ123wB # Earliest_Year: 1611 # 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":"4.71006289256","T2":"16.8152962095","M1":"0.0221734640947","M2":"0.420714380837"}} #-------------------- # Species # Species_Name: Siberian larch # Species_Code: LASI #-------------------- # 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 1611 1.378 1612 1.516 1613 0.489 1614 1.105 1615 1.22 1616 1.427 1617 0.854 1618 1.408 1619 1.534 1620 0.963 1621 0.969 1622 1.195 1623 0.858 1624 0.941 1625 0.648 1626 0.446 1627 1.217 1628 1.206 1629 1.033 1630 0.655 1631 0.917 1632 1.011 1633 0.791 1634 0.356 1635 0.655 1636 1.396 1637 1.693 1638 0.907 1639 1.002 1640 0.37 1641 0.403 1642 0.766 1643 0.937 1644 0.703 1645 0.513 1646 0.61 1647 0.853 1648 1.223 1649 0.846 1650 1.087 1651 1.18 1652 0.787 1653 1.312 1654 1.401 1655 0.955 1656 1.531 1657 1.002 1658 1.437 1659 1.252 1660 1.043 1661 0.941 1662 1.078 1663 0.941 1664 0.746 1665 0.911 1666 0.609 1667 0.597 1668 0.778 1669 1.296 1670 1.064 1671 1.508 1672 1.624 1673 1.336 1674 1.423 1675 1.311 1676 0.9 1677 0.445 1678 1.0 1679 0.534 1680 0.958 1681 1.171 1682 1.074 1683 0.891 1684 0.731 1685 0.869 1686 0.663 1687 0.818 1688 1.108 1689 1.154 1690 1.249 1691 1.374 1692 1.484 1693 0.995 1694 0.214 1695 1.167 1696 1.379 1697 0.797 1698 0.905 1699 1.092 1700 0.929 1701 0.99 1702 1.008 1703 1.286 1704 1.561 1705 1.53 1706 1.126 1707 1.458 1708 1.506 1709 0.931 1710 1.321 1711 0.792 1712 0.752 1713 0.609 1714 0.795 1715 1.21 1716 1.25 1717 0.877 1718 0.745 1719 1.131 1720 0.905 1721 1.051 1722 0.568 1723 0.812 1724 1.247 1725 1.242 1726 1.238 1727 1.256 1728 1.338 1729 1.128 1730 0.307 1731 1.024 1732 0.562 1733 0.934 1734 0.681 1735 0.725 1736 0.71 1737 1.13 1738 1.047 1739 1.215 1740 1.024 1741 0.959 1742 0.847 1743 0.396 1744 1.098 1745 0.801 1746 0.964 1747 1.044 1748 0.565 1749 0.954 1750 0.538 1751 1.051 1752 0.41 1753 0.641 1754 1.208 1755 0.74 1756 0.413 1757 0.811 1758 1.335 1759 0.928 1760 1.135 1761 1.055 1762 1.305 1763 0.628 1764 1.132 1765 0.949 1766 0.501 1767 1.11 1768 0.895 1769 1.176 1770 0.711 1771 0.96 1772 0.216 1773 0.32 1774 1.05 1775 0.763 1776 0.718 1777 0.843 1778 1.148 1779 1.099 1780 0.602 1781 0.988 1782 1.148 1783 0.622 1784 0.467 1785 1.261 1786 0.642 1787 1.131 1788 1.205 1789 1.219 1790 1.256 1791 1.489 1792 1.38 1793 1.317 1794 1.01 1795 1.235 1796 1.647 1797 0.984 1798 0.885 1799 0.762 1800 0.881 1801 0.773 1802 0.652 1803 0.713 1804 0.834 1805 1.189 1806 0.82 1807 1.261 1808 1.393 1809 1.027 1810 0.555 1811 0.769 1812 0.951 1813 0.933 1814 0.663 1815 0.461 1816 0.271 1817 0.648 1818 0.276 1819 0.877 1820 0.804 1821 0.635 1822 0.839 1823 1.008 1824 0.884 1825 0.385 1826 0.79 1827 1.364 1828 1.337 1829 2.046 1830 1.742 1831 0.925 1832 1.295 1833 1.099 1834 0.456 1835 1.057 1836 0.523 1837 1.233 1838 0.43 1839 1.158 1840 1.113 1841 1.15 1842 1.49 1843 1.118 1844 2.0 1845 1.88 1846 1.814 1847 1.876 1848 1.894 1849 1.756 1850 2.057 1851 2.047 1852 1.469 1853 1.231 1854 1.148 1855 0.789 1856 1.549 1857 0.465 1858 0.701 1859 0.901 1860 0.946 1861 0.717 1862 0.748 1863 0.185 1864 0.972 1865 0.633 1866 0.815 1867 0.823 1868 0.816 1869 1.239 1870 1.182 1871 0.398 1872 0.754 1873 0.751 1874 0.444 1875 0.392 1876 0.416 1877 0.926 1878 0.893 1879 0.685 1880 0.739 1881 0.604 1882 0.371 1883 0.465 1884 0.937 1885 0.604 1886 0.707 1887 1.188 1888 1.052 1889 0.555 1890 1.776 1891 0.572 1892 1.104 1893 0.875 1894 0.866 1895 1.143 1896 0.612 1897 1.395 1898 1.202 1899 0.706 1900 0.88 1901 0.852 1902 0.971 1903 0.538 1904 1.01 1905 0.678 1906 0.878 1907 0.737 1908 0.475 1909 0.726 1910 0.294 1911 1.039 1912 0.516 1913 1.076 1914 0.653 1915 1.158 1916 1.041 1917 0.771 1918 1.303 1919 0.961 1920 1.073 1921 1.335 1922 1.896 1923 1.713 1924 0.366 1925 1.391 1926 1.277 1927 1.191 1928 1.195 1929 0.956 1930 0.232 1931 0.559 1932 0.215 1933 0.646 1934 0.62 1935 0.711 1936 1.015 1937 1.034 1938 1.079 1939 1.41 1940 0.837 1941 1.102 1942 1.605 1943 0.765 1944 1.015 1945 1.074 1946 0.89 1947 0.638 1948 1.091 1949 0.908 1950 0.844 1951 0.537 1952 1.748 1953 1.557 1954 1.673 1955 1.535 1956 1.806 1957 1.304 1958 1.429 1959 1.302 1960 1.136 1961 1.233 1962 0.826 1963 1.827 1964 1.617 1965 1.312 1966 1.1 1967 0.525 1968 1.352 1969 1.13 1970 0.543 1971 0.85 1972 0.477 1973 1.06 1974 1.162 1975 0.665 1976 0.91 1977 1.129 1978 1.069 1979 0.873 1980 1.147 1981 1.337 1982 1.026 1983 1.538 1984 1.435 1985 1.371 1986 0.791 1987 0.636 1988 0.94 1989 1.506 1990 1.341