# europe_turk011 - Mugla 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/3809 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_turk011 - Mugla 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: Mugla Forest # Location: # Country: Turkey # Northernmost_Latitude: 37.23 # Southernmost_Latitude: 37.23 # Easternmost_Longitude: 28.38 # Westernmost_Longitude: 28.38 # Elevation: 1200 m #-------------------- # Data_Collection # Collection_Name: europe_turk011B # Earliest_Year: 1785 # Most_Recent_Year: 1999 # 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":"4.94048640423","T2":"12.6504981785","M1":"0.022499611548","M2":"0.444713934832"}} #-------------------- # 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 1785 0.761 1786 0.798 1787 0.843 1788 1.248 1789 0.957 1790 0.654 1791 0.889 1792 1.115 1793 0.817 1794 0.731 1795 0.928 1796 0.897 1797 0.95 1798 0.906 1799 0.982 1800 1.11 1801 0.922 1802 0.878 1803 0.946 1804 0.94 1805 0.849 1806 0.909 1807 0.972 1808 0.934 1809 1.025 1810 1.029 1811 1.076 1812 0.916 1813 0.81 1814 0.918 1815 0.911 1816 1.073 1817 1.054 1818 1.124 1819 0.772 1820 0.757 1821 0.756 1822 0.767 1823 0.773 1824 0.89 1825 0.969 1826 1.094 1827 1.174 1828 0.976 1829 1.117 1830 0.837 1831 0.988 1832 0.949 1833 0.997 1834 0.974 1835 1.132 1836 1.181 1837 1.084 1838 1.081 1839 1.042 1840 0.801 1841 0.946 1842 1.059 1843 0.848 1844 0.835 1845 1.083 1846 1.331 1847 1.073 1848 0.992 1849 0.852 1850 0.853 1851 0.753 1852 0.497 1853 0.735 1854 0.729 1855 1.234 1856 0.877 1857 1.004 1858 0.975 1859 0.876 1860 0.933 1861 1.032 1862 1.089 1863 0.915 1864 1.027 1865 1.209 1866 1.19 1867 1.052 1868 0.896 1869 1.037 1870 0.843 1871 0.951 1872 0.938 1873 0.87 1874 0.707 1875 0.751 1876 1.177 1877 0.952 1878 0.681 1879 0.805 1880 1.038 1881 1.162 1882 1.159 1883 1.117 1884 1.164 1885 1.301 1886 1.144 1887 0.952 1888 1.068 1889 1.17 1890 0.983 1891 1.093 1892 1.027 1893 0.644 1894 0.834 1895 0.905 1896 1.001 1897 1.274 1898 0.961 1899 0.885 1900 1.128 1901 1.183 1902 1.079 1903 1.305 1904 1.446 1905 1.202 1906 1.175 1907 1.272 1908 1.231 1909 1.196 1910 1.353 1911 1.123 1912 1.225 1913 1.318 1914 1.532 1915 1.798 1916 1.289 1917 1.245 1918 1.053 1919 1.291 1920 1.108 1921 1.227 1922 1.139 1923 1.188 1924 0.901 1925 1.219 1926 1.03 1927 0.842 1928 0.794 1929 0.867 1930 1.129 1931 0.856 1932 0.754 1933 1.047 1934 1.048 1935 0.899 1936 1.325 1937 1.077 1938 0.894 1939 1.08 1940 1.173 1941 0.998 1942 0.819 1943 0.926 1944 0.881 1945 0.746 1946 0.728 1947 0.903 1948 0.705 1949 0.548 1950 0.794 1951 1.062 1952 0.807 1953 0.819 1954 1.027 1955 1.017 1956 0.884 1957 0.838 1958 0.904 1959 0.74 1960 1.104 1961 0.857 1962 0.888 1963 0.964 1964 0.803 1965 0.855 1966 1.067 1967 0.854 1968 0.709 1969 0.833 1970 0.707 1971 0.885 1972 0.987 1973 0.897 1974 0.913 1975 1.264 1976 1.051 1977 0.917 1978 0.952 1979 1.146 1980 1.013 1981 0.927 1982 1.043 1983 0.946 1984 0.817 1985 0.692 1986 0.859 1987 0.822 1988 0.797 1989 0.883 1990 0.798 1991 0.858 1992 0.894 1993 0.806 1994 0.957 1995 0.741 1996 0.709 1997 0.811 1998 0.84 1999 0.82