# asia_russ095w - Ukyu - 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/4703 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_russ095w - Ukyu - 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: Ukyu # Location: # Country: Russia # Northernmost_Latitude: 62.6 # Southernmost_Latitude: 62.6 # Easternmost_Longitude: 58.8 # Westernmost_Longitude: 58.8 # Elevation: 340 m #-------------------- # Data_Collection # Collection_Name: asia_russ095wB # Earliest_Year: 1761 # 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":"4.65817417367","T2":"15.4729990656","M1":"0.023218238622","M2":"0.526950849655"}} #-------------------- # 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 1761 0.687 1762 0.786 1763 0.512 1764 0.971 1765 0.886 1766 0.853 1767 1.251 1768 1.382 1769 1.252 1770 1.07 1771 0.976 1772 0.839 1773 0.805 1774 1.044 1775 0.717 1776 0.577 1777 0.793 1778 0.608 1779 1.021 1780 0.828 1781 0.941 1782 1.122 1783 0.898 1784 1.185 1785 1.029 1786 0.834 1787 0.671 1788 0.742 1789 0.456 1790 0.863 1791 0.876 1792 0.909 1793 0.952 1794 1.004 1795 1.439 1796 1.356 1797 1.05 1798 1.122 1799 0.822 1800 1.08 1801 1.068 1802 0.805 1803 0.886 1804 0.923 1805 1.132 1806 1.002 1807 0.966 1808 1.102 1809 1.244 1810 0.936 1811 1.168 1812 1.25 1813 0.932 1814 0.838 1815 0.94 1816 0.827 1817 0.882 1818 0.973 1819 0.876 1820 1.072 1821 1.156 1822 1.124 1823 1.032 1824 0.865 1825 0.87 1826 0.877 1827 0.908 1828 0.739 1829 1.18 1830 1.091 1831 0.868 1832 1.122 1833 1.218 1834 1.045 1835 1.251 1836 1.077 1837 1.273 1838 0.873 1839 1.137 1840 0.951 1841 0.415 1842 0.165 1843 0.411 1844 0.582 1845 0.632 1846 0.906 1847 1.196 1848 0.896 1849 1.037 1850 0.813 1851 0.818 1852 0.891 1853 1.019 1854 0.981 1855 0.856 1856 1.374 1857 1.312 1858 0.628 1859 1.35 1860 1.114 1861 1.916 1862 1.074 1863 0.817 1864 1.429 1865 1.087 1866 1.572 1867 1.387 1868 1.87 1869 1.487 1870 0.799 1871 0.813 1872 0.836 1873 0.759 1874 0.85 1875 1.023 1876 1.155 1877 0.955 1878 1.129 1879 1.035 1880 1.078 1881 0.794 1882 0.734 1883 0.898 1884 1.13 1885 1.182 1886 1.065 1887 0.899 1888 0.987 1889 1.204 1890 1.013 1891 1.22 1892 1.66 1893 0.8 1894 0.692 1895 0.876 1896 0.893 1897 1.028 1898 1.103 1899 0.706 1900 1.062 1901 1.118 1902 1.075 1903 0.862 1904 0.862 1905 0.92 1906 1.095 1907 1.113 1908 0.842 1909 1.027 1910 0.6 1911 0.812 1912 0.701 1913 0.984 1914 0.672 1915 1.587 1916 0.703 1917 1.483 1918 1.514 1919 1.133 1920 0.949 1921 0.675 1922 0.669 1923 0.754 1924 0.859 1925 0.9 1926 0.896 1927 1.634 1928 1.577 1929 1.536 1930 1.695 1931 1.285 1932 1.315 1933 1.105 1934 0.823 1935 0.884 1936 0.919 1937 0.672 1938 1.009 1939 0.859 1940 1.088 1941 0.769 1942 1.579 1943 1.11 1944 0.923 1945 0.862 1946 0.762 1947 0.61 1948 0.917 1949 0.877 1950 1.011 1951 0.986 1952 0.858 1953 0.566 1954 0.339 1955 0.473 1956 0.728 1957 0.672 1958 0.466 1959 0.942 1960 0.556 1961 0.728 1962 0.351 1963 0.833 1964 0.941 1965 1.174 1966 1.046 1967 0.847 1968 1.191 1969 1.244 1970 1.299 1971 1.127 1972 1.357 1973 1.305 1974 1.439 1975 0.807 1976 0.858 1977 0.825 1978 0.743 1979 1.053 1980 1.025 1981 1.142 1982 1.003 1983 1.272 1984 1.172 1985 0.812 1986 0.621 1987 0.842 1988 0.51 1989 0.855 1990 0.706 1991 0.809