# europe_gree009 - Taygetos Forest - 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/3814 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_gree009 - Taygetos Forest - 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: Taygetos Forest # Location: # Country: Greece # Northernmost_Latitude: 36.92 # Southernmost_Latitude: 36.92 # Easternmost_Longitude: 22.35 # Westernmost_Longitude: 22.35 # Elevation: 1400 m #-------------------- # Data_Collection # Collection_Name: europe_gree009B # Earliest_Year: 1707 # Most_Recent_Year: 1999 # 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":"5.84703661502","T2":"13.8977883784","M1":"0.022321748045","M2":"0.198008162376"}} #-------------------- # Species # Species_Name: Austrian pine # Species_Code: PINI #-------------------- # 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 1707 0.882 1708 0.845 1709 1.09 1710 0.897 1711 0.692 1712 0.921 1713 0.831 1714 0.836 1715 0.66 1716 0.495 1717 0.715 1718 0.76 1719 0.863 1720 0.874 1721 1.25 1722 1.25 1723 1.109 1724 1.203 1725 0.728 1726 0.666 1727 0.957 1728 0.973 1729 1.04 1730 0.917 1731 1.23 1732 1.223 1733 1.132 1734 0.942 1735 0.971 1736 1.158 1737 0.998 1738 0.887 1739 1.135 1740 0.994 1741 1.275 1742 1.035 1743 1.12 1744 1.302 1745 1.188 1746 1.204 1747 1.417 1748 1.463 1749 1.121 1750 1.098 1751 1.268 1752 0.86 1753 0.812 1754 0.784 1755 1.052 1756 0.891 1757 0.997 1758 0.893 1759 0.885 1760 0.914 1761 0.892 1762 1.192 1763 1.006 1764 0.837 1765 0.986 1766 1.079 1767 0.851 1768 0.813 1769 0.663 1770 0.716 1771 0.823 1772 0.775 1773 0.616 1774 0.747 1775 0.954 1776 1.004 1777 0.828 1778 0.943 1779 0.642 1780 1.042 1781 1.037 1782 0.979 1783 1.011 1784 0.956 1785 0.944 1786 1.172 1787 0.967 1788 1.03 1789 0.876 1790 0.742 1791 0.985 1792 0.863 1793 0.711 1794 0.631 1795 0.877 1796 0.852 1797 0.986 1798 0.988 1799 1.164 1800 0.944 1801 0.763 1802 0.925 1803 0.962 1804 1.234 1805 0.879 1806 0.779 1807 0.91 1808 0.836 1809 0.714 1810 0.867 1811 0.903 1812 0.893 1813 0.949 1814 0.86 1815 1.098 1816 1.151 1817 1.036 1818 1.182 1819 1.158 1820 0.88 1821 1.037 1822 1.04 1823 0.87 1824 0.557 1825 0.639 1826 1.022 1827 1.312 1828 1.191 1829 1.54 1830 1.003 1831 1.151 1832 1.128 1833 0.938 1834 0.84 1835 1.119 1836 1.167 1837 1.297 1838 1.195 1839 1.021 1840 0.806 1841 0.884 1842 0.916 1843 0.915 1844 0.886 1845 1.039 1846 0.999 1847 0.932 1848 0.996 1849 0.932 1850 0.8 1851 0.928 1852 0.868 1853 0.98 1854 0.904 1855 1.281 1856 0.851 1857 0.741 1858 1.047 1859 1.4 1860 1.149 1861 0.777 1862 1.158 1863 0.908 1864 0.849 1865 0.765 1866 0.85 1867 0.889 1868 0.812 1869 0.89 1870 0.707 1871 0.801 1872 0.971 1873 1.08 1874 0.916 1875 0.827 1876 1.02 1877 0.992 1878 0.83 1879 1.051 1880 1.016 1881 1.293 1882 1.203 1883 1.284 1884 1.254 1885 1.235 1886 1.025 1887 0.934 1888 1.008 1889 1.178 1890 0.941 1891 1.005 1892 1.141 1893 0.575 1894 -0.061 1895 0.284 1896 0.366 1897 0.551 1898 0.609 1899 0.745 1900 1.021 1901 1.049 1902 1.289 1903 1.34 1904 1.352 1905 1.316 1906 1.526 1907 1.064 1908 0.964 1909 0.988 1910 0.99 1911 0.995 1912 1.456 1913 1.714 1914 1.447 1915 1.098 1916 1.134 1917 1.1 1918 0.996 1919 1.354 1920 1.27 1921 1.045 1922 1.029 1923 0.872 1924 0.869 1925 0.945 1926 1.266 1927 1.077 1928 0.876 1929 0.819 1930 1.214 1931 1.075 1932 0.95 1933 1.083 1934 1.092 1935 0.958 1936 1.063 1937 1.174 1938 0.932 1939 0.96 1940 1.114 1941 1.15 1942 1.098 1943 0.758 1944 0.699 1945 0.832 1946 1.03 1947 0.906 1948 0.915 1949 0.718 1950 0.926 1951 0.988 1952 0.874 1953 1.049 1954 0.964 1955 0.978 1956 0.823 1957 0.86 1958 1.243 1959 1.22 1960 1.2 1961 1.019 1962 0.942 1963 1.143 1964 1.142 1965 1.053 1966 0.983 1967 1.279 1968 1.007 1969 0.779 1970 0.89 1971 1.044 1972 1.146 1973 0.925 1974 0.954 1975 1.224 1976 0.984 1977 0.801 1978 0.974 1979 1.05 1980 0.937 1981 1.144 1982 0.894 1983 0.934 1984 0.896 1985 0.776 1986 0.89 1987 0.67 1988 0.748 1989 0.697 1990 0.668 1991 0.867 1992 0.718 1993 0.953 1994 1.001 1995 0.79 1996 0.829 1997 0.883 1998 0.929 1999 0.806