# asia_russ115w - Lindulowo - 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/4510 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_russ115w - Lindulowo - 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: Lindulowo # Location: # Country: Russia # Northernmost_Latitude: 60.27 # Southernmost_Latitude: 60.27 # Easternmost_Longitude: 29.58 # Westernmost_Longitude: 29.58 # Elevation: 20 m #-------------------- # Data_Collection # Collection_Name: asia_russ115wB # Earliest_Year: 1763 # 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":"5.96648651992","T2":"18.4734745502","M1":"0.0220680424125","M2":"0.370507880977"}} #-------------------- # Species # Species_Name: Siberian larch # Species_Code: LASI #-------------------- # 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 1763 0.869 1764 0.97 1765 1.018 1766 0.894 1767 1.122 1768 1.175 1769 1.16 1770 0.689 1771 1.102 1772 0.919 1773 1.049 1774 1.0 1775 1.056 1776 0.992 1777 1.093 1778 0.923 1779 1.021 1780 0.845 1781 0.912 1782 0.93 1783 1.116 1784 1.028 1785 0.969 1786 0.896 1787 1.135 1788 0.888 1789 1.024 1790 1.114 1791 1.006 1792 1.053 1793 1.104 1794 1.081 1795 0.857 1796 0.84 1797 0.797 1798 0.927 1799 0.863 1800 1.071 1801 1.171 1802 0.953 1803 0.924 1804 1.03 1805 1.037 1806 1.036 1807 1.052 1808 0.806 1809 1.031 1810 0.959 1811 1.127 1812 1.08 1813 0.995 1814 0.879 1815 0.998 1816 1.01 1817 1.177 1818 1.221 1819 1.065 1820 0.791 1821 0.807 1822 0.609 1823 0.811 1824 0.791 1825 0.563 1826 0.834 1827 0.823 1828 0.777 1829 1.005 1830 0.797 1831 1.038 1832 0.682 1833 0.916 1834 1.079 1835 0.976 1836 0.436 1837 0.93 1838 1.199 1839 1.315 1840 1.257 1841 1.463 1842 1.308 1843 1.45 1844 1.436 1845 1.213 1846 0.763 1847 0.666 1848 0.65 1849 1.095 1850 1.609 1851 1.458 1852 1.179 1853 1.265 1854 1.005 1855 0.951 1856 1.1 1857 0.998 1858 0.944 1859 1.017 1860 1.095 1861 1.377 1862 1.219 1863 1.17 1864 1.186 1865 0.812 1866 1.343 1867 0.971 1868 0.924 1869 0.697 1870 0.893 1871 0.753 1872 1.114 1873 1.399 1874 1.033 1875 0.939 1876 0.946 1877 0.886 1878 0.982 1879 1.179 1880 1.242 1881 0.964 1882 1.047 1883 1.063 1884 1.084 1885 0.849 1886 0.888 1887 0.732 1888 0.723 1889 0.786 1890 1.144 1891 1.099 1892 0.677 1893 0.849 1894 0.692 1895 1.194 1896 0.969 1897 1.047 1898 1.068 1899 0.761 1900 0.89 1901 0.838 1902 0.796 1903 0.711 1904 0.711 1905 0.733 1906 1.11 1907 0.792 1908 0.729 1909 0.761 1910 0.801 1911 1.07 1912 0.898 1913 0.705 1914 0.778 1915 0.711 1916 0.761 1917 0.94 1918 0.5 1919 0.77 1920 0.808 1921 1.033 1922 1.23 1923 0.875 1924 0.88 1925 0.762 1926 1.169 1927 0.906 1928 0.577 1929 0.946 1930 1.362 1931 1.314 1932 1.166 1933 0.919 1934 1.336 1935 1.186 1936 0.975 1937 1.145 1938 1.239 1939 0.909 1940 0.871 1941 0.593 1942 0.77 1943 0.698 1944 0.934 1945 1.156 1946 0.945 1947 0.8 1948 0.793 1949 1.215 1950 1.106 1951 0.99 1952 0.936 1953 1.1 1954 1.099 1955 1.218 1956 0.791 1957 1.163 1958 1.136 1959 0.81 1960 0.907 1961 1.065 1962 1.052 1963 1.602 1964 1.156 1965 1.123 1966 1.047 1967 0.906 1968 0.649 1969 0.75 1970 0.925 1971 1.002 1972 1.067 1973 0.889 1974 0.796 1975 0.903 1976 0.949 1977 1.029 1978 0.991 1979 1.028 1980 0.756 1981 0.88 1982 0.79 1983 1.18 1984 1.028 1985 1.141 1986 1.067 1987 0.847 1988 1.095 1989 0.86 1990 0.778