# asia_russ040w - Nonburg - 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/4562 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_russ040w - Nonburg - 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: Nonburg # Location: # Country: Russia # Northernmost_Latitude: 65.6 # Southernmost_Latitude: 65.6 # Easternmost_Longitude: 50.63 # Westernmost_Longitude: 50.63 # Elevation: 70 m #-------------------- # Data_Collection # Collection_Name: asia_russ040wB # Earliest_Year: 1709 # 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":"7.50726851229","T2":"18.9949207275","M1":"0.0224841984989","M2":"0.226712869953"}} #-------------------- # 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 1709 1.138 1710 1.251 1711 0.858 1712 0.691 1713 0.583 1714 0.724 1715 0.537 1716 0.781 1717 0.769 1718 0.627 1719 0.974 1720 0.945 1721 0.995 1722 0.713 1723 0.981 1724 0.944 1725 1.051 1726 1.028 1727 1.183 1728 1.219 1729 0.991 1730 1.106 1731 1.097 1732 0.69 1733 0.723 1734 0.485 1735 0.662 1736 0.448 1737 0.725 1738 0.563 1739 0.697 1740 0.455 1741 0.576 1742 0.65 1743 0.656 1744 0.849 1745 0.994 1746 0.764 1747 0.635 1748 0.383 1749 0.868 1750 0.631 1751 0.683 1752 0.605 1753 1.062 1754 1.112 1755 0.904 1756 1.416 1757 1.126 1758 1.132 1759 1.014 1760 1.006 1761 1.28 1762 1.214 1763 0.852 1764 0.996 1765 0.878 1766 0.314 1767 0.86 1768 0.911 1769 1.038 1770 0.69 1771 0.933 1772 -0.051 1773 0.237 1774 0.208 1775 0.155 1776 0.368 1777 0.417 1778 0.194 1779 0.24 1780 0.29 1781 0.388 1782 0.509 1783 0.518 1784 0.489 1785 0.449 1786 0.358 1787 0.267 1788 0.481 1789 0.23 1790 0.567 1791 0.621 1792 0.446 1793 0.495 1794 0.323 1795 0.485 1796 0.632 1797 0.363 1798 0.653 1799 0.679 1800 0.864 1801 1.093 1802 0.88 1803 0.817 1804 0.765 1805 1.146 1806 0.955 1807 1.012 1808 0.75 1809 0.84 1810 0.457 1811 0.514 1812 0.589 1813 0.671 1814 0.381 1815 0.387 1816 0.414 1817 0.235 1818 0.347 1819 0.467 1820 0.491 1821 0.56 1822 0.642 1823 1.091 1824 0.987 1825 1.236 1826 1.194 1827 1.944 1828 2.014 1829 2.701 1830 2.377 1831 2.176 1832 2.086 1833 2.127 1834 1.828 1835 1.569 1836 1.195 1837 1.319 1838 1.099 1839 1.585 1840 0.962 1841 1.057 1842 1.312 1843 1.316 1844 1.694 1845 1.391 1846 1.547 1847 1.462 1848 1.197 1849 1.176 1850 1.126 1851 1.359 1852 1.085 1853 0.977 1854 1.062 1855 1.164 1856 1.64 1857 1.09 1858 0.844 1859 1.26 1860 0.823 1861 0.888 1862 0.836 1863 0.632 1864 1.065 1865 0.71 1866 0.896 1867 0.863 1868 0.783 1869 0.954 1870 0.728 1871 0.627 1872 1.043 1873 1.038 1874 0.717 1875 0.808 1876 0.837 1877 1.195 1878 1.629 1879 1.024 1880 1.349 1881 1.118 1882 1.024 1883 1.557 1884 1.431 1885 1.746 1886 1.447 1887 1.631 1888 1.09 1889 1.287 1890 1.659 1891 1.124 1892 2.0 1893 1.529 1894 1.3 1895 1.143 1896 1.267 1897 0.95 1898 1.097 1899 1.104 1900 1.251 1901 1.388 1902 1.133 1903 0.63 1904 1.032 1905 0.816 1906 1.134 1907 1.491 1908 1.194 1909 1.197 1910 0.708 1911 1.243 1912 1.242 1913 1.805 1914 1.398 1915 1.69 1916 1.386 1917 1.593 1918 1.511 1919 1.334 1920 0.858 1921 1.042 1922 1.258 1923 1.29 1924 0.91 1925 1.376 1926 1.282 1927 1.507 1928 1.239 1929 1.268 1930 0.882 1931 1.014 1932 0.665 1933 0.791 1934 0.812 1935 0.736 1936 1.107 1937 0.931 1938 1.254 1939 1.182 1940 1.23 1941 0.602 1942 0.839 1943 0.551 1944 0.564 1945 0.764 1946 0.673 1947 0.676 1948 0.878 1949 0.774 1950 0.496 1951 0.807 1952 1.235 1953 1.328 1954 1.245 1955 0.88 1956 1.259 1957 1.062 1958 0.809 1959 1.162 1960 0.79 1961 0.716 1962 0.201 1963 0.45 1964 0.879 1965 0.874 1966 0.733 1967 0.367 1968 0.748 1969 0.766 1970 0.833 1971 0.681 1972 0.582 1973 0.477 1974 0.681 1975 0.007 1976 0.554 1977 0.43 1978 0.392 1979 0.631 1980 0.484 1981 0.647 1982 0.077 1983 0.676 1984 0.779 1985 0.502 1986 0.46 1987 0.658 1988 0.775 1989 0.524 1990 0.562