# asia_russ038w - Kotuy River - 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/4474 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_russ038w - Kotuy River - 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: Kotuy River # Location: # Country: Russia # Northernmost_Latitude: 70.27 # Southernmost_Latitude: 70.27 # Easternmost_Longitude: 103.52 # Westernmost_Longitude: 103.52 # Elevation: 130 m #-------------------- # Data_Collection # Collection_Name: asia_russ038wB # Earliest_Year: 1776 # 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":"4.28115629801","T2":"19.4922572544","M1":"0.0217939647651","M2":"0.178637298425"}} #-------------------- # Species # Species_Name: Siberian spruce # Species_Code: PCOB #-------------------- # 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 1776 0.925 1777 1.065 1778 1.096 1779 0.904 1780 1.043 1781 0.719 1782 0.92 1783 0.549 1784 1.235 1785 0.92 1786 0.964 1787 0.826 1788 0.608 1789 0.958 1790 0.701 1791 0.743 1792 0.301 1793 0.714 1794 0.935 1795 0.984 1796 0.856 1797 0.834 1798 0.659 1799 1.057 1800 0.557 1801 0.846 1802 0.932 1803 1.092 1804 0.759 1805 0.931 1806 1.135 1807 0.436 1808 1.022 1809 0.805 1810 0.861 1811 0.848 1812 0.45 1813 0.683 1814 0.896 1815 0.497 1816 0.827 1817 1.26 1818 1.626 1819 0.689 1820 1.071 1821 1.059 1822 1.014 1823 1.15 1824 0.804 1825 0.478 1826 1.141 1827 1.19 1828 1.28 1829 1.35 1830 1.21 1831 1.499 1832 1.034 1833 0.705 1834 1.316 1835 1.114 1836 0.86 1837 0.753 1838 0.867 1839 0.372 1840 1.284 1841 1.455 1842 1.039 1843 1.127 1844 0.986 1845 0.798 1846 0.898 1847 0.629 1848 1.012 1849 0.59 1850 0.848 1851 0.739 1852 1.129 1853 0.826 1854 0.524 1855 0.739 1856 0.861 1857 0.808 1858 1.086 1859 0.938 1860 1.458 1861 1.044 1862 1.152 1863 1.333 1864 1.36 1865 1.482 1866 0.975 1867 1.096 1868 1.454 1869 0.56 1870 1.806 1871 1.144 1872 1.289 1873 0.854 1874 0.96 1875 1.295 1876 0.904 1877 1.264 1878 1.389 1879 0.884 1880 1.171 1881 1.158 1882 1.095 1883 1.207 1884 0.979 1885 1.048 1886 1.228 1887 1.004 1888 1.177 1889 0.695 1890 0.76 1891 1.264 1892 1.283 1893 1.234 1894 1.199 1895 0.572 1896 1.348 1897 1.057 1898 0.592 1899 1.061 1900 0.739 1901 1.137 1902 0.988 1903 1.487 1904 0.846 1905 0.676 1906 0.973 1907 0.548 1908 1.585 1909 1.024 1910 0.616 1911 0.703 1912 0.649 1913 0.77 1914 1.207 1915 0.98 1916 1.293 1917 0.945 1918 0.965 1919 1.097 1920 0.918 1921 1.107 1922 0.879 1923 0.794 1924 1.129 1925 0.788 1926 1.18 1927 0.645 1928 1.266 1929 0.879 1930 1.159 1931 0.999 1932 1.135 1933 1.013 1934 1.676 1935 1.472 1936 1.33 1937 1.102 1938 1.282 1939 1.252 1940 1.372 1941 1.639 1942 1.224 1943 1.147 1944 1.037 1945 1.156 1946 1.242 1947 0.916 1948 1.45 1949 0.834 1950 1.202 1951 0.963 1952 1.159 1953 1.286 1954 0.781 1955 1.231 1956 1.293 1957 1.305 1958 1.27 1959 1.5 1960 0.775 1961 0.756 1962 0.725 1963 0.416 1964 0.863 1965 0.84 1966 0.756 1967 1.142 1968 0.777 1969 1.091 1970 1.078 1971 0.862 1972 0.622 1973 0.531 1974 0.302 1975 0.795 1976 0.697 1977 0.745 1978 0.734 1979 0.872 1980 0.417 1981 0.37 1982 0.647 1983 0.577 1984 0.692 1985 0.341 1986 1.085 1987 0.669 1988 0.462 1989 0.245 1990 0.978