# europe_gree005 - Olympos Oros - 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/4576 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_gree005 - Olympos Oros - 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: Olympos Oros # Location: # Country: Greece # Northernmost_Latitude: 40.08 # Southernmost_Latitude: 40.08 # Easternmost_Longitude: 22.42 # Westernmost_Longitude: 22.42 # Elevation: 2250 m #-------------------- # Data_Collection # Collection_Name: europe_gree005B # Earliest_Year: 1693 # Most_Recent_Year: 1981 # 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":"4.8624537676","T2":"15.7354792026","M1":"0.0224336600834","M2":"0.38406854713"}} #-------------------- # Species # Species_Name: Bosnian pine # Species_Code: PILE #-------------------- # 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 1693 1.408 1694 1.15 1695 1.057 1696 0.806 1697 0.865 1698 0.918 1699 1.175 1700 0.552 1701 0.776 1702 0.599 1703 0.794 1704 0.926 1705 0.813 1706 0.84 1707 0.994 1708 0.941 1709 1.221 1710 1.149 1711 1.006 1712 1.418 1713 1.343 1714 1.237 1715 0.943 1716 0.611 1717 0.799 1718 0.903 1719 1.219 1720 1.184 1721 1.019 1722 1.01 1723 0.882 1724 1.024 1725 0.63 1726 0.77 1727 0.828 1728 1.225 1729 1.164 1730 0.978 1731 1.202 1732 1.362 1733 1.56 1734 1.005 1735 1.183 1736 1.099 1737 1.247 1738 1.0 1739 0.848 1740 0.957 1741 0.82 1742 0.763 1743 0.811 1744 0.822 1745 0.961 1746 0.872 1747 0.798 1748 1.021 1749 1.146 1750 0.946 1751 1.064 1752 1.116 1753 1.098 1754 1.12 1755 1.05 1756 1.1 1757 1.209 1758 0.722 1759 0.969 1760 1.026 1761 1.028 1762 1.282 1763 1.177 1764 1.005 1765 1.283 1766 1.222 1767 1.261 1768 1.131 1769 1.065 1770 0.693 1771 1.058 1772 1.022 1773 0.825 1774 1.038 1775 1.03 1776 1.157 1777 1.009 1778 1.377 1779 0.98 1780 1.549 1781 1.247 1782 1.14 1783 1.003 1784 0.986 1785 0.801 1786 0.924 1787 0.638 1788 0.835 1789 0.861 1790 0.845 1791 1.122 1792 0.917 1793 0.896 1794 1.04 1795 0.802 1796 1.047 1797 0.993 1798 0.974 1799 0.979 1800 1.116 1801 1.015 1802 1.133 1803 1.18 1804 1.468 1805 1.333 1806 1.04 1807 1.174 1808 0.893 1809 0.854 1810 0.969 1811 1.106 1812 1.108 1813 0.659 1814 1.013 1815 0.964 1816 1.121 1817 0.981 1818 0.801 1819 0.922 1820 1.112 1821 0.915 1822 1.002 1823 0.934 1824 1.232 1825 1.232 1826 1.125 1827 1.244 1828 0.974 1829 0.796 1830 0.818 1831 1.006 1832 0.894 1833 0.588 1834 0.843 1835 0.862 1836 0.551 1837 0.937 1838 0.545 1839 0.792 1840 0.638 1841 0.853 1842 0.968 1843 0.866 1844 0.632 1845 0.958 1846 1.286 1847 0.969 1848 1.007 1849 1.014 1850 0.949 1851 1.084 1852 1.094 1853 1.127 1854 0.838 1855 1.107 1856 1.059 1857 0.989 1858 0.688 1859 0.884 1860 0.996 1861 0.567 1862 0.695 1863 0.817 1864 0.669 1865 0.976 1866 0.965 1867 0.798 1868 0.794 1869 0.946 1870 1.277 1871 1.226 1872 1.18 1873 1.497 1874 0.782 1875 1.018 1876 0.968 1877 1.232 1878 0.796 1879 0.639 1880 0.413 1881 0.958 1882 0.599 1883 0.774 1884 0.783 1885 0.807 1886 0.825 1887 0.825 1888 0.721 1889 0.873 1890 0.895 1891 0.871 1892 0.987 1893 0.88 1894 0.815 1895 0.931 1896 0.765 1897 1.039 1898 0.684 1899 1.11 1900 1.268 1901 1.313 1902 1.326 1903 1.163 1904 1.073 1905 1.168 1906 1.083 1907 0.958 1908 0.942 1909 0.935 1910 1.069 1911 0.65 1912 1.013 1913 0.952 1914 1.006 1915 1.114 1916 0.887 1917 1.239 1918 1.046 1919 1.005 1920 0.98 1921 0.935 1922 1.099 1923 0.94 1924 0.808 1925 0.931 1926 1.045 1927 1.041 1928 0.913 1929 0.539 1930 1.006 1931 1.021 1932 0.738 1933 0.917 1934 0.768 1935 0.905 1936 1.052 1937 0.792 1938 0.86 1939 1.107 1940 1.178 1941 1.336 1942 1.032 1943 1.462 1944 1.184 1945 1.124 1946 1.172 1947 1.095 1948 1.203 1949 0.946 1950 1.142 1951 1.28 1952 0.88 1953 0.858 1954 0.942 1955 1.034 1956 1.142 1957 0.735 1958 0.965 1959 1.027 1960 0.957 1961 1.055 1962 1.062 1963 0.923 1964 0.923 1965 1.018 1966 0.98 1967 1.031 1968 1.044 1969 1.002 1970 1.41 1971 1.172 1972 1.252 1973 1.132 1974 1.205 1975 1.203 1976 1.153 1977 1.112 1978 0.828 1979 0.825 1980 1.021 1981 1.163