# asia_russ045w - Voroney - 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/4727 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_russ045w - Voroney - 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: Voroney # Location: # Country: Russia # Northernmost_Latitude: 63.43 # Southernmost_Latitude: 63.43 # Easternmost_Longitude: 43.55 # Westernmost_Longitude: 43.55 # Elevation: 120 m #-------------------- # Data_Collection # Collection_Name: asia_russ045wB # Earliest_Year: 1771 # Most_Recent_Year: 1991 # 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":"4.34327027819","T2":"18.1949730164","M1":"0.022094455269","M2":"0.39359912694"}} #-------------------- # 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 1771 0.829 1772 0.833 1773 0.915 1774 1.117 1775 1.197 1776 0.955 1777 0.993 1778 1.026 1779 1.059 1780 1.093 1781 0.97 1782 1.165 1783 1.011 1784 1.176 1785 1.113 1786 0.977 1787 1.106 1788 1.153 1789 1.012 1790 1.015 1791 1.124 1792 1.238 1793 1.435 1794 1.506 1795 1.684 1796 1.586 1797 1.381 1798 1.294 1799 1.146 1800 1.081 1801 1.127 1802 1.209 1803 1.112 1804 1.112 1805 1.098 1806 0.775 1807 0.918 1808 1.071 1809 1.39 1810 0.829 1811 0.717 1812 0.809 1813 0.595 1814 0.606 1815 0.705 1816 0.701 1817 0.657 1818 0.727 1819 0.706 1820 0.847 1821 1.101 1822 0.946 1823 0.903 1824 0.954 1825 1.015 1826 1.132 1827 1.242 1828 0.955 1829 1.101 1830 1.068 1831 1.081 1832 1.081 1833 1.065 1834 0.94 1835 0.881 1836 0.768 1837 0.73 1838 0.705 1839 0.739 1840 0.619 1841 0.944 1842 1.173 1843 0.932 1844 1.048 1845 0.882 1846 0.926 1847 0.839 1848 0.995 1849 1.251 1850 1.623 1851 1.517 1852 1.324 1853 1.187 1854 1.076 1855 1.228 1856 1.254 1857 0.97 1858 0.717 1859 0.822 1860 0.867 1861 0.845 1862 0.823 1863 0.741 1864 1.083 1865 0.789 1866 0.856 1867 0.68 1868 0.701 1869 0.78 1870 0.792 1871 0.777 1872 0.624 1873 0.71 1874 0.823 1875 0.921 1876 0.96 1877 1.101 1878 1.013 1879 0.948 1880 1.001 1881 1.027 1882 1.019 1883 0.927 1884 0.995 1885 1.186 1886 0.913 1887 0.806 1888 0.728 1889 0.86 1890 1.152 1891 1.013 1892 0.595 1893 0.787 1894 0.724 1895 0.867 1896 1.012 1897 0.8 1898 1.072 1899 1.111 1900 0.896 1901 1.099 1902 1.22 1903 0.677 1904 1.015 1905 1.03 1906 1.139 1907 1.306 1908 1.077 1909 0.914 1910 0.74 1911 0.884 1912 0.957 1913 0.831 1914 1.04 1915 1.144 1916 0.993 1917 1.075 1918 0.88 1919 1.004 1920 1.021 1921 1.323 1922 1.616 1923 1.523 1924 1.173 1925 1.39 1926 0.964 1927 1.189 1928 0.914 1929 0.928 1930 1.042 1931 1.109 1932 1.175 1933 1.267 1934 1.093 1935 1.185 1936 1.167 1937 1.221 1938 1.179 1939 0.995 1940 1.124 1941 0.817 1942 0.743 1943 0.999 1944 0.828 1945 1.006 1946 0.957 1947 0.971 1948 1.129 1949 1.234 1950 1.2 1951 1.341 1952 1.173 1953 1.094 1954 1.23 1955 1.26 1956 1.283 1957 1.398 1958 0.922 1959 1.021 1960 1.195 1961 1.065 1962 0.788 1963 0.7 1964 0.934 1965 0.903 1966 1.241 1967 1.019 1968 0.925 1969 0.652 1970 0.999 1971 0.839 1972 0.596 1973 0.786 1974 0.94 1975 0.9 1976 0.959 1977 0.894 1978 0.873 1979 0.72 1980 0.835 1981 0.985 1982 0.827 1983 0.693 1984 0.816 1985 0.802 1986 0.832 1987 0.813 1988 0.998 1989 1.068 1990 1.193 1991 0.993