# europe_turk036 - Göller - 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/5553 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_turk036 - Göller - 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: Göller # Location: # Country: Turkey # Northernmost_Latitude: 37.08 # Southernmost_Latitude: 37.08 # Easternmost_Longitude: 30.52 # Westernmost_Longitude: 30.52 # Elevation: 1047 m #-------------------- # Data_Collection # Collection_Name: europe_turk036B # Earliest_Year: 1760 # Most_Recent_Year: 2001 # 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":"4.47332214214","T2":"14.6650949904","M1":"0.0229001811734","M2":"0.415422366093"}} #-------------------- # Species # Species_Name: Calabrian pine # Species_Code: PIBR #-------------------- # 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 1760 0.902 1761 0.935 1762 0.793 1763 0.619 1764 0.762 1765 0.655 1766 0.847 1767 0.962 1768 0.935 1769 1.118 1770 1.168 1771 0.981 1772 1.059 1773 1.12 1774 1.264 1775 1.203 1776 1.049 1777 1.103 1778 1.213 1779 0.82 1780 1.256 1781 1.186 1782 1.033 1783 1.269 1784 1.072 1785 1.192 1786 1.172 1787 0.893 1788 1.031 1789 0.98 1790 0.868 1791 1.08 1792 1.111 1793 0.9 1794 0.97 1795 1.229 1796 1.034 1797 1.069 1798 1.038 1799 0.66 1800 0.674 1801 0.755 1802 0.865 1803 0.888 1804 0.826 1805 0.768 1806 0.964 1807 0.912 1808 0.783 1809 0.939 1810 0.926 1811 0.902 1812 0.981 1813 0.864 1814 0.798 1815 0.875 1816 1.026 1817 1.076 1818 1.254 1819 1.046 1820 0.912 1821 0.988 1822 0.826 1823 0.781 1824 0.767 1825 0.668 1826 0.795 1827 1.2 1828 1.027 1829 0.979 1830 0.998 1831 1.089 1832 1.084 1833 1.141 1834 0.917 1835 1.562 1836 1.283 1837 1.227 1838 1.433 1839 1.204 1840 0.864 1841 1.031 1842 0.954 1843 1.138 1844 1.051 1845 0.997 1846 1.073 1847 0.884 1848 1.111 1849 0.906 1850 0.89 1851 0.83 1852 0.855 1853 1.075 1854 0.802 1855 1.361 1856 0.818 1857 1.37 1858 0.942 1859 0.945 1860 0.736 1861 0.871 1862 0.899 1863 0.8 1864 0.881 1865 1.067 1866 1.015 1867 0.788 1868 0.97 1869 0.848 1870 0.816 1871 0.917 1872 1.092 1873 1.068 1874 0.857 1875 0.917 1876 1.582 1877 1.204 1878 0.863 1879 0.744 1880 0.98 1881 1.001 1882 1.049 1883 1.106 1884 1.088 1885 1.235 1886 1.034 1887 0.904 1888 0.957 1889 1.291 1890 0.958 1891 0.864 1892 0.878 1893 0.658 1894 0.718 1895 0.736 1896 0.876 1897 0.929 1898 0.747 1899 0.853 1900 1.361 1901 1.211 1902 1.069 1903 1.505 1904 1.204 1905 1.07 1906 0.925 1907 0.398 1908 0.529 1909 0.64 1910 0.946 1911 0.89 1912 0.9 1913 1.267 1914 1.468 1915 1.212 1916 0.999 1917 1.13 1918 0.994 1919 1.409 1920 1.021 1921 0.881 1922 1.036 1923 1.041 1924 1.23 1925 1.337 1926 1.203 1927 0.735 1928 0.672 1929 0.821 1930 1.123 1931 1.052 1932 0.747 1933 1.024 1934 1.048 1935 0.679 1936 1.195 1937 0.963 1938 0.776 1939 0.914 1940 0.965 1941 0.83 1942 0.848 1943 1.085 1944 0.958 1945 0.654 1946 0.783 1947 0.821 1948 1.043 1949 0.79 1950 0.852 1951 0.977 1952 1.213 1953 0.691 1954 0.8 1955 0.825 1956 0.715 1957 0.774 1958 1.171 1959 0.832 1960 1.11 1961 0.769 1962 0.885 1963 0.932 1964 0.847 1965 0.82 1966 1.418 1967 0.863 1968 1.38 1969 1.143 1970 1.103 1971 0.86 1972 1.494 1973 0.873 1974 1.073 1975 1.165 1976 1.114 1977 1.11 1978 1.132 1979 1.347 1980 0.856 1981 1.022 1982 1.382 1983 1.03 1984 1.027 1985 0.716 1986 0.948 1987 0.933 1988 1.004 1989 0.974 1990 1.249 1991 1.143 1992 1.36 1993 1.079 1994 0.935 1995 1.136 1996 0.924 1997 1.114 1998 0.926 1999 0.727 2000 0.634 2001 0.796