# europe_turk019 - Katrandagi - 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/5132 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_turk019 - Katrandagi - 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: Katrandagi # Location: # Country: Turkey # Northernmost_Latitude: 37.38 # Southernmost_Latitude: 37.38 # Easternmost_Longitude: 30.6 # Westernmost_Longitude: 30.6 # Elevation: 1469 m #-------------------- # Data_Collection # Collection_Name: europe_turk019B # Earliest_Year: 1814 # Most_Recent_Year: 2000 # 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":"4.41048835592","T2":"15.4896880116","M1":"0.0218456909889","M2":"0.337715410312"}} #-------------------- # Species # Species_Name: cedar of Lebanone # Species_Code: CDLI #-------------------- # 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 1814 0.72 1815 0.741 1816 0.937 1817 0.596 1818 0.755 1819 0.587 1820 0.427 1821 0.607 1822 0.62 1823 0.796 1824 0.567 1825 0.844 1826 0.688 1827 1.258 1828 1.081 1829 1.037 1830 0.949 1831 1.184 1832 1.436 1833 1.643 1834 1.097 1835 1.121 1836 1.104 1837 1.257 1838 1.097 1839 0.919 1840 0.659 1841 1.196 1842 1.072 1843 1.16 1844 1.231 1845 1.315 1846 1.487 1847 1.213 1848 1.434 1849 0.839 1850 0.815 1851 0.88 1852 0.917 1853 1.262 1854 0.955 1855 1.164 1856 0.679 1857 0.67 1858 0.681 1859 1.068 1860 1.064 1861 0.743 1862 0.815 1863 0.905 1864 0.99 1865 1.063 1866 1.275 1867 1.065 1868 1.055 1869 0.924 1870 0.799 1871 0.911 1872 0.965 1873 0.91 1874 0.699 1875 0.822 1876 1.236 1877 1.144 1878 0.982 1879 0.949 1880 0.884 1881 0.944 1882 0.838 1883 1.015 1884 1.136 1885 1.495 1886 1.126 1887 0.649 1888 0.973 1889 1.139 1890 0.784 1891 0.94 1892 0.996 1893 0.779 1894 0.849 1895 0.899 1896 0.905 1897 0.967 1898 0.677 1899 0.691 1900 0.998 1901 1.298 1902 1.129 1903 1.266 1904 1.374 1905 1.16 1906 1.123 1907 0.93 1908 1.045 1909 0.773 1910 1.08 1911 0.919 1912 0.769 1913 1.099 1914 1.439 1915 1.212 1916 0.839 1917 0.958 1918 0.789 1919 0.74 1920 0.907 1921 1.066 1922 0.966 1923 0.663 1924 1.029 1925 0.841 1926 0.695 1927 0.702 1928 0.542 1929 0.741 1930 1.028 1931 0.971 1932 0.623 1933 0.591 1934 0.707 1935 0.545 1936 1.113 1937 0.802 1938 0.64 1939 0.934 1940 1.14 1941 0.813 1942 0.72 1943 0.646 1944 0.754 1945 0.72 1946 0.929 1947 0.8 1948 0.771 1949 0.766 1950 1.007 1951 0.838 1952 1.451 1953 1.402 1954 1.333 1955 1.109 1956 1.17 1957 1.253 1958 1.328 1959 1.616 1960 1.76 1961 1.22 1962 1.04 1963 1.293 1964 1.133 1965 1.126 1966 1.193 1967 1.211 1968 1.115 1969 1.083 1970 1.426 1971 1.278 1972 1.285 1973 1.176 1974 1.125 1975 1.075 1976 1.28 1977 1.179 1978 1.151 1979 1.316 1980 0.872 1981 1.066 1982 1.084 1983 1.203 1984 0.854 1985 0.923 1986 0.802 1987 0.861 1988 0.676 1989 0.693 1990 0.825 1991 0.896 1992 0.976 1993 0.94 1994 0.896 1995 0.654 1996 0.689 1997 0.83 1998 0.891 1999 0.468 2000 0.743