# asia_russ050w - Zhigansk - 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/4749 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_russ050w - Zhigansk - 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: Zhigansk # Location: # Country: Russia # Northernmost_Latitude: 66.52 # Southernmost_Latitude: 66.52 # Easternmost_Longitude: 122.33 # Westernmost_Longitude: 122.33 # Elevation: 180 m #-------------------- # Data_Collection # Collection_Name: asia_russ050wB # Earliest_Year: 1736 # 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":"6.40724889038","T2":"18.9627670236","M1":"0.0226659763322","M2":"0.302402791489"}} #-------------------- # 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 1736 0.997 1737 1.004 1738 1.185 1739 1.274 1740 1.145 1741 0.837 1742 1.063 1743 0.997 1744 1.343 1745 1.232 1746 1.131 1747 1.46 1748 1.101 1749 1.18 1750 1.135 1751 0.81 1752 0.965 1753 1.01 1754 0.738 1755 1.271 1756 0.936 1757 1.156 1758 1.127 1759 0.703 1760 1.166 1761 1.029 1762 0.739 1763 0.941 1764 0.922 1765 0.817 1766 1.096 1767 0.963 1768 1.214 1769 1.178 1770 0.935 1771 0.978 1772 0.977 1773 0.877 1774 0.957 1775 1.083 1776 0.772 1777 0.693 1778 1.037 1779 0.943 1780 0.957 1781 1.03 1782 1.073 1783 0.929 1784 1.147 1785 0.969 1786 0.934 1787 0.801 1788 0.557 1789 0.809 1790 0.778 1791 0.661 1792 0.829 1793 0.813 1794 1.074 1795 1.334 1796 1.06 1797 1.337 1798 1.099 1799 1.345 1800 1.008 1801 1.14 1802 1.336 1803 1.356 1804 1.051 1805 1.001 1806 1.097 1807 0.987 1808 0.969 1809 0.736 1810 0.958 1811 1.247 1812 0.814 1813 0.794 1814 0.885 1815 0.934 1816 0.689 1817 0.412 1818 0.692 1819 0.448 1820 0.698 1821 0.755 1822 0.798 1823 0.343 1824 0.917 1825 0.597 1826 0.941 1827 1.145 1828 0.883 1829 1.196 1830 0.758 1831 0.977 1832 0.933 1833 0.92 1834 1.212 1835 1.485 1836 1.068 1837 0.906 1838 0.855 1839 1.172 1840 1.011 1841 1.109 1842 0.915 1843 1.107 1844 1.108 1845 1.254 1846 1.013 1847 0.988 1848 0.774 1849 1.02 1850 1.136 1851 0.844 1852 1.092 1853 1.201 1854 1.111 1855 0.972 1856 1.143 1857 1.218 1858 0.882 1859 0.525 1860 0.773 1861 0.858 1862 0.694 1863 0.695 1864 0.79 1865 0.877 1866 0.883 1867 1.076 1868 1.295 1869 0.918 1870 0.819 1871 1.04 1872 1.059 1873 1.226 1874 0.934 1875 0.775 1876 0.962 1877 0.983 1878 1.229 1879 1.067 1880 1.093 1881 1.062 1882 1.056 1883 1.091 1884 1.126 1885 1.045 1886 0.886 1887 1.159 1888 0.963 1889 0.558 1890 0.799 1891 0.896 1892 0.707 1893 0.885 1894 0.935 1895 0.67 1896 0.875 1897 0.866 1898 0.865 1899 0.848 1900 0.493 1901 1.04 1902 1.148 1903 1.046 1904 0.973 1905 0.836 1906 1.443 1907 1.201 1908 1.583 1909 1.294 1910 0.873 1911 1.091 1912 0.708 1913 0.907 1914 1.372 1915 1.074 1916 1.168 1917 0.94 1918 1.096 1919 1.121 1920 1.318 1921 0.742 1922 1.343 1923 0.856 1924 0.859 1925 0.86 1926 1.076 1927 0.768 1928 1.137 1929 1.185 1930 1.177 1931 1.331 1932 1.362 1933 0.916 1934 1.046 1935 1.279 1936 1.09 1937 0.817 1938 1.048 1939 0.922 1940 1.053 1941 1.114 1942 1.122 1943 0.928 1944 1.189 1945 1.094 1946 1.183 1947 1.002 1948 1.075 1949 0.928 1950 0.865 1951 0.975 1952 1.138 1953 0.962 1954 0.879 1955 0.77 1956 0.861 1957 0.955 1958 0.428 1959 1.017 1960 0.844 1961 1.024 1962 0.771 1963 0.755 1964 0.881 1965 1.029 1966 0.997 1967 0.91 1968 1.067 1969 0.963 1970 0.787 1971 0.714 1972 0.771 1973 0.59 1974 0.682 1975 0.76 1976 0.721 1977 0.597 1978 0.939 1979 1.245 1980 0.948 1981 0.703 1982 1.256 1983 1.103 1984 0.703 1985 0.947 1986 1.274 1987 1.259 1988 1.166 1989 1.265 1990 1.057 1991 1.318