# asia_russ188 - Allayka - 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/3561 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_russ188 - Allayka - 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: Allayka # Location: # Country: Russia # Northernmost_Latitude: 70.05 # Southernmost_Latitude: 70.05 # Easternmost_Longitude: 146.45 # Westernmost_Longitude: 146.45 # Elevation: 80 m #-------------------- # Data_Collection # Collection_Name: asia_russ188B # Earliest_Year: 1676 # Most_Recent_Year: 1994 # 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":"5.60207452515","T2":"17.7170743482","M1":"0.0212043857429","M2":"0.333285541983"}} #-------------------- # 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 1676 0.768 1677 0.905 1678 0.688 1679 0.678 1680 0.069 1681 0.537 1682 1.173 1683 0.886 1684 0.7 1685 0.83 1686 0.904 1687 0.697 1688 0.72 1689 0.823 1690 0.464 1691 0.755 1692 0.7 1693 1.319 1694 1.021 1695 0.234 1696 0.56 1697 1.53 1698 0.443 1699 1.254 1700 1.053 1701 1.556 1702 1.259 1703 1.374 1704 1.13 1705 1.052 1706 0.878 1707 1.3 1708 1.103 1709 0.885 1710 1.152 1711 0.673 1712 0.623 1713 0.86 1714 0.667 1715 0.995 1716 1.407 1717 0.532 1718 0.71 1719 1.319 1720 1.297 1721 1.19 1722 1.644 1723 1.498 1724 0.786 1725 0.543 1726 0.897 1727 1.154 1728 1.203 1729 1.197 1730 0.439 1731 0.747 1732 1.498 1733 1.13 1734 1.173 1735 0.742 1736 1.006 1737 0.593 1738 0.772 1739 1.117 1740 0.514 1741 0.672 1742 0.985 1743 0.731 1744 0.547 1745 1.051 1746 0.821 1747 0.989 1748 1.066 1749 1.256 1750 1.287 1751 0.867 1752 1.209 1753 0.784 1754 0.711 1755 1.285 1756 0.708 1757 1.436 1758 1.084 1759 0.871 1760 0.783 1761 0.82 1762 0.291 1763 1.49 1764 0.76 1765 1.098 1766 1.079 1767 0.847 1768 0.673 1769 0.504 1770 0.567 1771 1.216 1772 0.693 1773 0.924 1774 0.805 1775 1.131 1776 0.657 1777 1.123 1778 1.204 1779 0.674 1780 0.467 1781 1.08 1782 1.251 1783 1.373 1784 1.059 1785 1.237 1786 1.023 1787 0.877 1788 0.793 1789 1.375 1790 1.137 1791 1.036 1792 1.256 1793 1.048 1794 0.664 1795 1.017 1796 0.633 1797 0.918 1798 0.838 1799 0.896 1800 0.8 1801 0.144 1802 1.258 1803 0.844 1804 0.456 1805 1.245 1806 1.01 1807 0.979 1808 1.069 1809 0.896 1810 1.112 1811 1.268 1812 0.659 1813 0.679 1814 0.846 1815 0.849 1816 1.015 1817 0.12 1818 0.472 1819 1.199 1820 1.028 1821 0.95 1822 0.315 1823 0.654 1824 0.934 1825 0.738 1826 0.786 1827 0.277 1828 0.582 1829 0.664 1830 0.564 1831 0.883 1832 0.847 1833 1.205 1834 1.116 1835 1.332 1836 1.63 1837 0.242 1838 0.717 1839 0.384 1840 0.525 1841 0.144 1842 0.553 1843 0.641 1844 0.489 1845 0.846 1846 0.86 1847 0.944 1848 0.485 1849 0.328 1850 0.671 1851 0.337 1852 0.54 1853 0.715 1854 0.985 1855 0.904 1856 0.703 1857 0.482 1858 1.886 1859 0.791 1860 1.253 1861 1.558 1862 0.937 1863 0.466 1864 0.595 1865 1.256 1866 1.289 1867 1.353 1868 1.273 1869 1.508 1870 1.834 1871 1.193 1872 1.195 1873 1.314 1874 1.24 1875 0.806 1876 1.53 1877 1.137 1878 1.423 1879 1.408 1880 1.272 1881 1.012 1882 1.055 1883 1.313 1884 1.011 1885 1.104 1886 0.937 1887 0.758 1888 1.006 1889 0.832 1890 1.168 1891 1.239 1892 0.644 1893 0.892 1894 0.923 1895 0.973 1896 0.628 1897 0.994 1898 1.032 1899 0.724 1900 0.692 1901 1.055 1902 1.558 1903 1.2 1904 0.904 1905 0.755 1906 0.893 1907 1.016 1908 0.752 1909 1.031 1910 1.059 1911 1.134 1912 1.593 1913 1.306 1914 1.687 1915 0.732 1916 0.815 1917 1.148 1918 0.726 1919 0.703 1920 0.893 1921 0.863 1922 1.032 1923 0.762 1924 1.013 1925 1.036 1926 0.806 1927 0.835 1928 0.917 1929 1.079 1930 1.31 1931 0.939 1932 1.225 1933 1.762 1934 1.283 1935 1.216 1936 1.261 1937 0.766 1938 1.681 1939 1.482 1940 1.699 1941 0.699 1942 1.377 1943 1.407 1944 1.668 1945 0.481 1946 0.936 1947 1.411 1948 1.363 1949 0.955 1950 1.045 1951 1.262 1952 1.318 1953 1.034 1954 0.911 1955 1.277 1956 1.408 1957 0.705 1958 1.041 1959 0.828 1960 1.545 1961 1.473 1962 0.568 1963 0.866 1964 0.978 1965 1.065 1966 0.988 1967 1.015 1968 1.241 1969 1.014 1970 0.977 1971 0.684 1972 0.474 1973 1.166 1974 1.247 1975 0.862 1976 0.774 1977 0.905 1978 0.473 1979 0.332 1980 0.64 1981 0.439 1982 0.677 1983 0.662 1984 0.35 1985 0.845 1986 0.969 1987 0.694 1988 0.585 1989 0.616 1990 0.687 1991 0.572 1992 0.235 1993 0.88 1994 0.713