# asia_russ041w - Nonburg - 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/4563 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_russ041w - Nonburg - 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: Nonburg # Location: # Country: Russia # Northernmost_Latitude: 65.6 # Southernmost_Latitude: 65.6 # Easternmost_Longitude: 50.63 # Westernmost_Longitude: 50.63 # Elevation: 70 m #-------------------- # Data_Collection # Collection_Name: asia_russ041wB # Earliest_Year: 1723 # 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":"6.24577086109","T2":"19.6794589101","M1":"0.0221778085714","M2":"0.261174487783"}} #-------------------- # 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 1723 0.77 1724 0.811 1725 1.164 1726 1.209 1727 1.0 1728 0.931 1729 0.991 1730 0.794 1731 0.689 1732 0.621 1733 0.7 1734 0.618 1735 0.692 1736 0.773 1737 0.696 1738 0.898 1739 0.905 1740 0.721 1741 1.036 1742 0.914 1743 1.036 1744 1.074 1745 1.185 1746 0.901 1747 0.967 1748 0.839 1749 0.855 1750 1.122 1751 0.915 1752 0.676 1753 0.894 1754 1.131 1755 1.283 1756 1.327 1757 1.273 1758 1.43 1759 1.151 1760 1.085 1761 1.115 1762 1.178 1763 0.974 1764 0.984 1765 1.002 1766 0.88 1767 1.231 1768 1.182 1769 0.953 1770 0.719 1771 1.32 1772 0.893 1773 1.082 1774 1.452 1775 1.403 1776 0.913 1777 0.967 1778 0.93 1779 0.789 1780 1.023 1781 0.889 1782 0.992 1783 0.883 1784 0.848 1785 1.032 1786 0.755 1787 0.716 1788 0.907 1789 0.839 1790 1.028 1791 1.124 1792 1.241 1793 1.464 1794 1.161 1795 1.207 1796 1.198 1797 0.94 1798 0.878 1799 0.801 1800 1.082 1801 0.94 1802 1.224 1803 1.031 1804 0.949 1805 1.118 1806 0.92 1807 0.992 1808 0.976 1809 0.901 1810 0.5 1811 0.691 1812 0.883 1813 0.668 1814 0.61 1815 0.574 1816 0.431 1817 0.202 1818 0.488 1819 0.642 1820 0.577 1821 0.753 1822 0.721 1823 0.748 1824 0.791 1825 0.771 1826 0.824 1827 1.081 1828 0.843 1829 1.21 1830 1.417 1831 1.348 1832 1.665 1833 1.439 1834 1.162 1835 0.894 1836 0.874 1837 0.629 1838 0.456 1839 0.808 1840 1.034 1841 0.915 1842 1.221 1843 0.951 1844 1.408 1845 0.938 1846 0.974 1847 0.968 1848 0.965 1849 1.171 1850 1.236 1851 1.29 1852 1.179 1853 1.103 1854 0.989 1855 0.917 1856 1.031 1857 0.788 1858 0.461 1859 0.87 1860 0.853 1861 0.682 1862 0.49 1863 0.257 1864 0.963 1865 0.512 1866 0.584 1867 0.443 1868 0.315 1869 0.62 1870 0.731 1871 0.55 1872 0.57 1873 0.526 1874 0.664 1875 0.557 1876 0.671 1877 0.836 1878 1.124 1879 1.063 1880 0.963 1881 0.79 1882 0.696 1883 0.871 1884 1.078 1885 1.19 1886 0.856 1887 0.676 1888 0.538 1889 0.564 1890 0.893 1891 0.897 1892 0.491 1893 1.172 1894 0.833 1895 0.656 1896 0.956 1897 0.942 1898 1.373 1899 0.96 1900 1.119 1901 1.124 1902 1.312 1903 0.396 1904 1.015 1905 1.444 1906 1.624 1907 1.617 1908 1.584 1909 1.592 1910 1.384 1911 1.522 1912 1.511 1913 1.734 1914 1.209 1915 1.537 1916 1.34 1917 1.323 1918 1.213 1919 1.106 1920 1.075 1921 1.142 1922 1.383 1923 1.524 1924 1.607 1925 2.032 1926 1.3 1927 1.467 1928 1.375 1929 0.995 1930 0.955 1931 0.811 1932 0.964 1933 1.208 1934 1.328 1935 1.238 1936 1.343 1937 1.393 1938 1.236 1939 1.271 1940 1.572 1941 0.802 1942 0.881 1943 0.963 1944 0.942 1945 0.873 1946 0.741 1947 0.655 1948 0.909 1949 1.082 1950 1.147 1951 1.196 1952 1.259 1953 0.899 1954 1.366 1955 1.141 1956 1.304 1957 1.526 1958 0.872 1959 0.813 1960 1.034 1961 0.933 1962 0.651 1963 0.654 1964 0.926 1965 1.003 1966 1.016 1967 0.988 1968 0.849 1969 0.448 1970 0.755 1971 0.727 1972 0.73 1973 0.679 1974 0.855 1975 0.552 1976 0.783 1977 0.864 1978 0.838 1979 0.76 1980 0.702 1981 0.894 1982 0.517 1983 0.752 1984 1.072 1985 0.626 1986 0.578 1987 0.651 1988 0.974 1989 0.967 1990 0.881