# asia_russ121w - Kostomuksha - 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/4473 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_russ121w - Kostomuksha - 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: Kostomuksha # Location: # Country: Russia # Northernmost_Latitude: 64.53 # Southernmost_Latitude: 64.53 # Easternmost_Longitude: 31.03 # Westernmost_Longitude: 31.03 # Elevation: 225 m #-------------------- # Data_Collection # Collection_Name: asia_russ121wB # Earliest_Year: 1603 # Most_Recent_Year: 1992 # 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":"4.62044795826","T2":"17.1678259853","M1":"0.0223116490046","M2":"0.358442867745"}} #-------------------- # Species # Species_Name: Scots pine # Species_Code: PISY #-------------------- # 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 1603 1.084 1604 1.101 1605 0.838 1606 1.077 1607 1.027 1608 1.145 1609 1.036 1610 1.202 1611 0.976 1612 1.22 1613 1.036 1614 1.017 1615 0.853 1616 0.987 1617 1.154 1618 1.06 1619 0.921 1620 0.806 1621 1.048 1622 0.759 1623 0.683 1624 1.044 1625 0.983 1626 0.85 1627 0.615 1628 0.819 1629 1.022 1630 0.91 1631 1.14 1632 1.131 1633 1.077 1634 1.412 1635 1.042 1636 0.806 1637 0.984 1638 1.091 1639 1.084 1640 1.003 1641 0.721 1642 0.822 1643 0.787 1644 0.656 1645 0.672 1646 0.596 1647 0.847 1648 1.148 1649 0.921 1650 0.734 1651 0.713 1652 0.785 1653 0.8 1654 0.91 1655 1.159 1656 0.958 1657 0.936 1658 0.996 1659 0.867 1660 0.815 1661 0.658 1662 0.626 1663 0.629 1664 0.621 1665 0.582 1666 0.311 1667 0.347 1668 0.439 1669 0.502 1670 0.603 1671 0.817 1672 0.852 1673 1.099 1674 0.972 1675 0.809 1676 1.076 1677 0.942 1678 1.12 1679 1.206 1680 1.08 1681 1.609 1682 1.456 1683 1.397 1684 1.915 1685 1.336 1686 1.793 1687 1.55 1688 1.427 1689 1.628 1690 1.442 1691 1.411 1692 1.42 1693 1.305 1694 1.315 1695 0.89 1696 0.513 1697 0.946 1698 1.006 1699 0.825 1700 1.041 1701 1.213 1702 1.392 1703 1.217 1704 1.367 1705 1.285 1706 1.353 1707 1.239 1708 1.182 1709 0.886 1710 0.9 1711 0.9 1712 0.888 1713 0.719 1714 0.882 1715 1.063 1716 1.19 1717 0.973 1718 0.926 1719 0.643 1720 0.887 1721 0.767 1722 0.724 1723 0.89 1724 0.917 1725 1.065 1726 0.914 1727 0.936 1728 0.925 1729 1.077 1730 0.967 1731 0.78 1732 0.784 1733 0.856 1734 0.738 1735 0.764 1736 0.993 1737 0.882 1738 1.147 1739 1.065 1740 0.826 1741 0.574 1742 0.702 1743 0.876 1744 1.007 1745 0.76 1746 0.832 1747 0.823 1748 0.96 1749 0.82 1750 0.738 1751 0.728 1752 1.101 1753 1.333 1754 1.436 1755 1.428 1756 1.068 1757 1.212 1758 1.126 1759 1.065 1760 0.995 1761 0.828 1762 0.915 1763 0.91 1764 0.851 1765 0.776 1766 0.655 1767 0.688 1768 0.774 1769 0.624 1770 0.515 1771 0.672 1772 0.683 1773 0.528 1774 0.832 1775 0.788 1776 0.606 1777 0.675 1778 0.616 1779 0.579 1780 0.819 1781 0.767 1782 0.782 1783 0.884 1784 0.891 1785 0.828 1786 0.77 1787 0.896 1788 0.959 1789 1.075 1790 0.722 1791 0.956 1792 1.351 1793 1.422 1794 1.134 1795 1.061 1796 1.304 1797 1.197 1798 1.167 1799 1.42 1800 1.013 1801 1.277 1802 1.184 1803 1.007 1804 1.166 1805 1.277 1806 0.673 1807 0.985 1808 1.142 1809 1.4 1810 1.01 1811 1.078 1812 1.032 1813 0.873 1814 0.982 1815 0.917 1816 0.97 1817 0.987 1818 1.019 1819 1.141 1820 0.81 1821 0.889 1822 1.095 1823 1.28 1824 1.181 1825 1.055 1826 1.371 1827 1.237 1828 1.04 1829 1.259 1830 1.366 1831 1.63 1832 1.338 1833 1.487 1834 1.517 1835 1.03 1836 0.944 1837 0.854 1838 1.095 1839 1.218 1840 1.241 1841 1.113 1842 1.17 1843 1.025 1844 0.826 1845 1.097 1846 1.019 1847 1.057 1848 1.161 1849 1.459 1850 1.501 1851 1.497 1852 1.406 1853 1.14 1854 1.231 1855 1.2 1856 1.115 1857 0.982 1858 1.048 1859 1.013 1860 0.903 1861 1.069 1862 0.865 1863 1.032 1864 1.225 1865 1.175 1866 1.102 1867 0.838 1868 1.001 1869 0.915 1870 0.802 1871 0.667 1872 0.626 1873 0.827 1874 0.704 1875 0.815 1876 0.826 1877 0.947 1878 0.883 1879 0.762 1880 0.654 1881 0.554 1882 0.783 1883 0.791 1884 0.888 1885 1.117 1886 1.014 1887 0.965 1888 0.816 1889 1.0 1890 1.244 1891 1.079 1892 0.9 1893 0.978 1894 0.868 1895 0.875 1896 0.996 1897 0.905 1898 1.127 1899 0.996 1900 0.946 1901 1.287 1902 0.895 1903 0.774 1904 0.991 1905 0.953 1906 0.841 1907 0.783 1908 0.703 1909 0.93 1910 0.766 1911 0.764 1912 1.008 1913 0.814 1914 1.127 1915 1.254 1916 1.119 1917 1.109 1918 0.989 1919 0.919 1920 0.915 1921 1.116 1922 1.177 1923 1.219 1924 1.125 1925 1.058 1926 0.799 1927 1.137 1928 0.907 1929 1.018 1930 1.176 1931 1.006 1932 1.017 1933 0.886 1934 1.186 1935 0.849 1936 0.895 1937 0.871 1938 0.862 1939 1.051 1940 1.031 1941 0.986 1942 0.761 1943 0.932 1944 0.926 1945 0.923 1946 0.852 1947 0.994 1948 0.956 1949 0.91 1950 0.94 1951 0.956 1952 0.841 1953 0.864 1954 1.207 1955 0.957 1956 0.803 1957 0.893 1958 0.777 1959 0.78 1960 0.775 1961 0.755 1962 0.803 1963 0.619 1964 0.792 1965 0.616 1966 0.652 1967 0.714 1968 0.75 1969 0.6 1970 0.725 1971 0.645 1972 0.806 1973 0.819 1974 0.908 1975 0.928 1976 0.921 1977 0.799 1978 0.875 1979 0.998 1980 0.803 1981 0.834 1982 0.518 1983 0.748 1984 0.761 1985 0.789 1986 0.856 1987 0.827 1988 1.001 1989 0.947 1990 1.05 1991 0.861 1992 0.734