# asia_russ072w - Nyuchpas - 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/4570 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_russ072w - Nyuchpas - 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: Nyuchpas # Location: # Country: Russia # Northernmost_Latitude: 60.7 # Southernmost_Latitude: 60.7 # Easternmost_Longitude: 51.38 # Westernmost_Longitude: 51.38 # Elevation: 160 m #-------------------- # Data_Collection # Collection_Name: asia_russ072wB # Earliest_Year: 1741 # Most_Recent_Year: 1991 # Time_Unit: y_ad # Core_Length: # Notes: {"database":{"database1":"LMR","database2":"Breits"}} {"climateInterpretation":{"basis":"", "climateVariable":"M", "climateVariableDetail":"air", "interpDirection":"positive", "seasonality":"[6, 7, 8]"}}{"VSLite_parameters":{"T1":"3.88496746351","T2":"13.9392284831","M1":"0.023358565426","M2":"0.553528127618"}} #-------------------- # Species # Species_Name: Norway spruce # Species_Code: PCAB #-------------------- # 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 1741 0.96 1742 0.961 1743 1.189 1744 1.095 1745 0.984 1746 1.115 1747 1.028 1748 1.049 1749 0.918 1750 0.553 1751 0.647 1752 0.796 1753 0.817 1754 0.852 1755 0.669 1756 0.791 1757 0.816 1758 0.838 1759 0.766 1760 0.817 1761 0.816 1762 1.199 1763 0.714 1764 0.706 1765 0.733 1766 0.509 1767 0.781 1768 0.741 1769 0.726 1770 0.868 1771 0.894 1772 0.661 1773 0.596 1774 0.684 1775 0.699 1776 0.623 1777 0.746 1778 0.404 1779 0.479 1780 0.652 1781 0.867 1782 0.645 1783 0.74 1784 0.806 1785 0.794 1786 0.849 1787 0.906 1788 1.078 1789 0.886 1790 0.859 1791 0.745 1792 0.686 1793 0.707 1794 0.672 1795 0.618 1796 0.673 1797 0.568 1798 0.83 1799 0.817 1800 0.828 1801 0.671 1802 0.629 1803 0.868 1804 0.807 1805 0.93 1806 0.733 1807 0.807 1808 0.661 1809 0.926 1810 0.7 1811 0.706 1812 0.619 1813 0.652 1814 0.561 1815 0.594 1816 0.497 1817 0.556 1818 0.586 1819 0.656 1820 0.557 1821 0.388 1822 0.536 1823 0.915 1824 1.078 1825 1.439 1826 1.483 1827 0.961 1828 1.113 1829 1.502 1830 1.047 1831 1.088 1832 1.25 1833 1.328 1834 1.062 1835 0.831 1836 0.775 1837 0.893 1838 0.898 1839 1.133 1840 0.79 1841 1.095 1842 1.057 1843 1.208 1844 1.291 1845 1.463 1846 1.9 1847 1.45 1848 1.36 1849 1.326 1850 1.414 1851 1.477 1852 1.235 1853 1.136 1854 1.402 1855 1.428 1856 1.981 1857 1.11 1858 1.07 1859 1.328 1860 1.476 1861 1.552 1862 1.095 1863 1.075 1864 1.008 1865 0.871 1866 1.137 1867 1.036 1868 1.272 1869 1.325 1870 1.422 1871 1.185 1872 1.157 1873 1.041 1874 0.798 1875 0.92 1876 0.983 1877 0.822 1878 1.392 1879 1.305 1880 1.039 1881 0.655 1882 0.873 1883 1.003 1884 1.166 1885 1.156 1886 0.836 1887 1.025 1888 1.183 1889 1.575 1890 1.33 1891 1.274 1892 1.856 1893 1.147 1894 1.27 1895 0.904 1896 1.114 1897 1.312 1898 1.459 1899 1.072 1900 1.123 1901 1.094 1902 0.972 1903 0.796 1904 0.569 1905 0.893 1906 1.192 1907 1.497 1908 1.042 1909 1.135 1910 0.711 1911 0.888 1912 0.97 1913 0.869 1914 0.838 1915 0.932 1916 0.678 1917 0.693 1918 0.848 1919 0.637 1920 0.434 1921 0.571 1922 0.768 1923 0.682 1924 0.868 1925 0.96 1926 1.071 1927 1.415 1928 0.951 1929 0.953 1930 1.087 1931 1.135 1932 1.035 1933 1.101 1934 0.915 1935 0.824 1936 0.842 1937 1.007 1938 0.969 1939 1.022 1940 1.094 1941 0.813 1942 0.9 1943 0.843 1944 0.888 1945 1.072 1946 1.485 1947 1.126 1948 1.246 1949 1.278 1950 1.175 1951 1.206 1952 0.921 1953 0.976 1954 1.0 1955 0.785 1956 0.918 1957 0.659 1958 0.464 1959 0.692 1960 0.777 1961 0.737 1962 0.532 1963 0.419 1964 0.751 1965 0.732 1966 0.793 1967 0.693 1968 0.846 1969 0.349 1970 0.537 1971 0.505 1972 0.642 1973 0.485 1974 0.601 1975 0.614 1976 0.94 1977 0.951 1978 1.206 1979 1.321 1980 1.329 1981 1.314 1982 0.768 1983 0.82 1984 1.252 1985 0.929 1986 0.734 1987 1.079 1988 0.991 1989 0.817 1990 0.615 1991 1.087