# asia_russ183 - Borovoi - 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/3978 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_russ183 - Borovoi - 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: Borovoi # Location: # Country: Russia # Northernmost_Latitude: 64.77 # Southernmost_Latitude: 64.77 # Easternmost_Longitude: 32.33 # Westernmost_Longitude: 32.33 # Elevation: nan m #-------------------- # Data_Collection # Collection_Name: asia_russ183B # Earliest_Year: 1707 # Most_Recent_Year: 2002 # 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":"4.78116731296","T2":"18.4920254074","M1":"0.0224183169738","M2":"0.278355240497"}} #-------------------- # 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 1707 1.28 1708 1.105 1709 0.899 1710 0.917 1711 0.927 1712 0.752 1713 0.67 1714 0.855 1715 1.116 1716 1.208 1717 1.013 1718 1.124 1719 0.897 1720 1.091 1721 0.833 1722 0.74 1723 0.889 1724 1.015 1725 1.211 1726 0.991 1727 1.164 1728 1.023 1729 1.149 1730 1.057 1731 0.801 1732 0.857 1733 0.947 1734 0.766 1735 0.721 1736 0.836 1737 0.689 1738 0.888 1739 0.873 1740 0.712 1741 0.496 1742 0.731 1743 0.769 1744 0.868 1745 0.744 1746 0.842 1747 0.679 1748 0.882 1749 0.785 1750 0.764 1751 0.721 1752 0.982 1753 1.159 1754 1.289 1755 1.248 1756 1.38 1757 1.734 1758 1.368 1759 1.184 1760 1.229 1761 1.219 1762 1.268 1763 1.189 1764 1.038 1765 1.118 1766 0.969 1767 0.905 1768 0.891 1769 0.69 1770 0.638 1771 0.729 1772 0.705 1773 0.572 1774 1.112 1775 0.949 1776 0.765 1777 0.831 1778 1.03 1779 0.96 1780 1.082 1781 0.924 1782 0.861 1783 0.978 1784 1.127 1785 0.979 1786 0.751 1787 0.857 1788 1.057 1789 1.13 1790 0.883 1791 1.12 1792 1.321 1793 1.202 1794 0.85 1795 0.741 1796 1.131 1797 1.097 1798 1.012 1799 1.199 1800 1.008 1801 1.121 1802 1.202 1803 1.015 1804 1.046 1805 0.964 1806 0.496 1807 0.844 1808 1.01 1809 0.95 1810 0.703 1811 0.866 1812 0.904 1813 0.67 1814 0.95 1815 0.788 1816 0.822 1817 0.885 1818 0.989 1819 1.017 1820 0.781 1821 0.687 1822 0.842 1823 1.038 1824 1.05 1825 0.895 1826 1.341 1827 1.144 1828 0.587 1829 1.163 1830 1.12 1831 1.236 1832 1.029 1833 1.313 1834 1.205 1835 0.872 1836 0.604 1837 0.593 1838 0.792 1839 0.867 1840 0.884 1841 0.822 1842 0.96 1843 0.871 1844 0.574 1845 0.783 1846 0.745 1847 0.758 1848 0.95 1849 1.21 1850 1.261 1851 1.303 1852 1.29 1853 1.109 1854 1.209 1855 1.258 1856 0.965 1857 0.838 1858 0.906 1859 0.819 1860 0.953 1861 1.084 1862 0.833 1863 0.956 1864 1.151 1865 1.099 1866 1.019 1867 0.845 1868 0.914 1869 0.928 1870 1.004 1871 0.832 1872 0.734 1873 0.851 1874 0.709 1875 0.894 1876 0.804 1877 1.028 1878 0.859 1879 0.751 1880 0.702 1881 0.773 1882 1.047 1883 0.949 1884 1.106 1885 1.287 1886 1.241 1887 1.14 1888 1.093 1889 1.233 1890 1.432 1891 1.317 1892 1.06 1893 1.368 1894 1.279 1895 1.019 1896 1.221 1897 1.258 1898 1.585 1899 1.35 1900 1.333 1901 1.608 1902 1.182 1903 1.012 1904 1.108 1905 1.221 1906 1.306 1907 1.247 1908 1.206 1909 1.268 1910 0.952 1911 1.062 1912 1.386 1913 1.002 1914 1.437 1915 1.496 1916 1.289 1917 1.193 1918 0.999 1919 0.907 1920 0.883 1921 1.123 1922 1.258 1923 1.398 1924 1.432 1925 1.125 1926 0.793 1927 1.213 1928 1.063 1929 1.058 1930 1.113 1931 1.016 1932 1.017 1933 0.925 1934 1.022 1935 0.84 1936 0.926 1937 0.966 1938 0.85 1939 1.314 1940 1.045 1941 1.014 1942 0.804 1943 0.93 1944 1.029 1945 1.003 1946 1.014 1947 1.139 1948 1.122 1949 1.003 1950 1.16 1951 1.134 1952 0.947 1953 0.916 1954 1.263 1955 1.23 1956 0.96 1957 0.963 1958 0.803 1959 0.925 1960 0.897 1961 0.743 1962 0.824 1963 0.728 1964 0.869 1965 0.605 1966 0.745 1967 0.828 1968 0.853 1969 0.76 1970 0.77 1971 0.647 1972 0.719 1973 0.832 1974 0.859 1975 0.798 1976 0.747 1977 0.722 1978 0.727 1979 0.712 1980 0.634 1981 0.706 1982 0.458 1983 0.919 1984 0.781 1985 0.741 1986 0.826 1987 0.849 1988 1.007 1989 0.951 1990 0.656 1991 0.775 1992 0.635 1993 0.426 1994 0.582 1995 0.698 1996 0.78 1997 0.7 1998 0.792 1999 0.777 2000 1.055 2001 1.005 2002 0.834