# asia_russ073w - Zolotica - 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/4750 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_russ073w - Zolotica - 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: Zolotica # Location: # Country: Russia # Northernmost_Latitude: 65.33 # Southernmost_Latitude: 65.33 # Easternmost_Longitude: 41.12 # Westernmost_Longitude: 41.12 # Elevation: 130 m #-------------------- # Data_Collection # Collection_Name: asia_russ073wB # Earliest_Year: 1719 # 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":"5.00108731032","T2":"19.0233994762","M1":"0.0223134165373","M2":"0.331225163815"}} #-------------------- # 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 1719 0.954 1720 0.756 1721 0.254 1722 0.525 1723 0.677 1724 0.841 1725 0.974 1726 1.083 1727 0.679 1728 0.317 1729 0.496 1730 0.296 1731 0.337 1732 0.48 1733 0.663 1734 0.753 1735 0.872 1736 1.08 1737 1.087 1738 1.22 1739 1.145 1740 1.223 1741 1.627 1742 1.303 1743 1.321 1744 1.358 1745 1.443 1746 1.306 1747 1.354 1748 0.975 1749 0.918 1750 0.895 1751 0.984 1752 0.924 1753 1.284 1754 1.44 1755 1.483 1756 1.51 1757 1.394 1758 1.391 1759 1.081 1760 1.108 1761 1.208 1762 1.185 1763 0.871 1764 0.941 1765 1.066 1766 0.944 1767 1.134 1768 1.071 1769 0.873 1770 0.782 1771 1.27 1772 1.128 1773 0.791 1774 1.197 1775 1.137 1776 0.913 1777 1.144 1778 1.166 1779 0.928 1780 1.319 1781 0.817 1782 0.885 1783 0.894 1784 0.84 1785 0.886 1786 0.9 1787 0.944 1788 1.251 1789 1.008 1790 0.752 1791 1.098 1792 0.972 1793 1.142 1794 1.128 1795 1.316 1796 1.21 1797 1.177 1798 1.098 1799 1.103 1800 0.977 1801 1.005 1802 1.175 1803 0.823 1804 0.82 1805 1.174 1806 0.66 1807 0.773 1808 0.918 1809 0.958 1810 0.455 1811 0.488 1812 0.865 1813 0.445 1814 0.461 1815 0.565 1816 0.405 1817 0.31 1818 0.526 1819 0.642 1820 0.512 1821 0.739 1822 0.649 1823 0.861 1824 0.727 1825 0.683 1826 1.084 1827 1.137 1828 0.971 1829 1.118 1830 1.117 1831 1.162 1832 1.09 1833 0.968 1834 0.823 1835 0.763 1836 0.568 1837 0.422 1838 0.575 1839 0.552 1840 0.74 1841 0.788 1842 1.143 1843 0.842 1844 0.753 1845 0.802 1846 0.796 1847 0.86 1848 0.911 1849 1.346 1850 1.389 1851 1.732 1852 1.489 1853 1.237 1854 1.16 1855 1.273 1856 1.176 1857 0.991 1858 0.816 1859 1.162 1860 1.126 1861 1.275 1862 0.902 1863 0.806 1864 1.481 1865 0.914 1866 0.678 1867 0.661 1868 0.57 1869 1.029 1870 1.098 1871 0.89 1872 0.735 1873 0.745 1874 0.709 1875 0.719 1876 0.815 1877 0.953 1878 1.002 1879 0.703 1880 0.654 1881 0.822 1882 1.168 1883 1.066 1884 1.11 1885 1.492 1886 1.15 1887 1.116 1888 1.049 1889 1.097 1890 1.695 1891 1.564 1892 0.989 1893 1.5 1894 1.17 1895 0.744 1896 1.107 1897 0.826 1898 1.294 1899 1.108 1900 0.763 1901 1.009 1902 1.213 1903 0.414 1904 1.012 1905 1.153 1906 1.206 1907 1.416 1908 1.162 1909 1.238 1910 1.182 1911 1.042 1912 0.978 1913 0.945 1914 0.988 1915 1.172 1916 1.296 1917 1.069 1918 0.819 1919 0.907 1920 0.867 1921 1.284 1922 1.627 1923 1.492 1924 0.873 1925 1.46 1926 0.965 1927 0.98 1928 1.012 1929 0.929 1930 0.944 1931 1.188 1932 1.281 1933 1.189 1934 1.34 1935 1.128 1936 1.103 1937 1.339 1938 1.332 1939 1.209 1940 1.132 1941 0.955 1942 0.76 1943 1.246 1944 1.09 1945 0.988 1946 0.827 1947 1.103 1948 1.061 1949 1.161 1950 1.023 1951 1.263 1952 1.045 1953 0.893 1954 1.384 1955 1.255 1956 1.075 1957 1.221 1958 0.873 1959 0.839 1960 0.926 1961 0.919 1962 0.694 1963 0.372 1964 0.745 1965 0.647 1966 0.843 1967 0.666 1968 0.574 1969 0.329 1970 0.792 1971 0.712 1972 0.572 1973 0.739 1974 0.943 1975 0.651 1976 0.408 1977 0.469 1978 0.58 1979 0.554 1980 0.697 1981 1.063 1982 0.793 1983 0.735 1984 0.893 1985 0.638 1986 0.517 1987 0.423 1988 0.831 1989 0.795 1990 0.781