# europe_turk041 - Silpisli - 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/5558 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_turk041 - Silpisli - 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: Silpisli # Location: # Country: Turkey # Northernmost_Latitude: 37.27 # Southernmost_Latitude: 37.27 # Easternmost_Longitude: 34.55 # Westernmost_Longitude: 34.55 # Elevation: 1790 m #-------------------- # Data_Collection # Collection_Name: europe_turk041B # Earliest_Year: 1752 # Most_Recent_Year: 2001 # 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":"3.97584099254","T2":"14.3099386296","M1":"0.0218471490242","M2":"0.181605094646"}} #-------------------- # Species # Species_Name: Greek juniper # Species_Code: JUEX #-------------------- # 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 1752 1.321 1753 1.24 1754 1.243 1755 1.534 1756 0.828 1757 0.766 1758 0.974 1759 0.77 1760 1.064 1761 1.576 1762 1.399 1763 1.085 1764 0.933 1765 1.073 1766 1.415 1767 1.203 1768 1.036 1769 0.929 1770 0.623 1771 0.761 1772 0.872 1773 0.979 1774 1.031 1775 0.852 1776 0.842 1777 0.884 1778 1.316 1779 0.737 1780 1.255 1781 1.113 1782 0.661 1783 1.277 1784 1.043 1785 0.93 1786 1.228 1787 1.035 1788 1.509 1789 0.932 1790 1.069 1791 0.998 1792 1.05 1793 0.956 1794 0.509 1795 0.906 1796 0.557 1797 0.541 1798 0.899 1799 0.76 1800 0.924 1801 1.088 1802 0.782 1803 1.298 1804 1.49 1805 1.688 1806 1.134 1807 0.9 1808 0.933 1809 1.348 1810 1.478 1811 1.352 1812 1.099 1813 0.752 1814 0.814 1815 0.759 1816 1.508 1817 1.533 1818 1.205 1819 0.436 1820 0.703 1821 1.121 1822 0.786 1823 0.856 1824 1.293 1825 1.222 1826 0.878 1827 1.591 1828 1.401 1829 1.475 1830 0.829 1831 1.198 1832 1.351 1833 0.947 1834 1.017 1835 1.392 1836 1.01 1837 0.856 1838 0.932 1839 0.673 1840 0.646 1841 1.014 1842 1.095 1843 0.884 1844 0.772 1845 0.925 1846 0.893 1847 1.001 1848 1.026 1849 0.967 1850 0.806 1851 0.407 1852 0.773 1853 1.023 1854 0.988 1855 1.378 1856 1.336 1857 1.165 1858 0.842 1859 1.313 1860 1.271 1861 0.893 1862 0.997 1863 0.493 1864 1.001 1865 1.278 1866 1.359 1867 1.286 1868 0.79 1869 0.853 1870 0.706 1871 1.014 1872 1.108 1873 0.991 1874 0.33 1875 0.703 1876 0.996 1877 0.768 1878 0.588 1879 0.533 1880 0.573 1881 1.169 1882 0.988 1883 0.981 1884 0.795 1885 1.206 1886 0.971 1887 0.787 1888 0.962 1889 1.353 1890 1.057 1891 0.835 1892 0.727 1893 0.561 1894 0.55 1895 0.502 1896 0.701 1897 1.329 1898 0.711 1899 0.798 1900 1.09 1901 1.329 1902 1.199 1903 0.957 1904 0.94 1905 0.7 1906 1.027 1907 0.794 1908 0.641 1909 0.441 1910 0.931 1911 0.334 1912 0.661 1913 0.748 1914 1.215 1915 0.965 1916 0.565 1917 0.812 1918 0.824 1919 1.201 1920 1.087 1921 1.027 1922 1.286 1923 1.0 1924 1.223 1925 1.196 1926 0.997 1927 0.58 1928 0.813 1929 1.042 1930 1.748 1931 1.543 1932 0.955 1933 0.692 1934 1.199 1935 0.822 1936 1.54 1937 1.185 1938 0.764 1939 0.878 1940 1.042 1941 0.857 1942 0.58 1943 0.868 1944 1.066 1945 0.568 1946 0.801 1947 1.63 1948 0.817 1949 0.487 1950 0.684 1951 1.404 1952 1.127 1953 0.668 1954 0.661 1955 0.897 1956 0.831 1957 1.046 1958 1.364 1959 1.06 1960 1.052 1961 0.885 1962 0.934 1963 1.457 1964 1.268 1965 0.857 1966 0.783 1967 0.773 1968 1.064 1969 0.935 1970 1.129 1971 0.927 1972 1.04 1973 0.891 1974 0.698 1975 1.049 1976 1.003 1977 0.871 1978 0.819 1979 1.189 1980 0.704 1981 0.989 1982 1.019 1983 1.077 1984 0.605 1985 1.028 1986 1.459 1987 1.024 1988 0.975 1989 0.85 1990 1.018 1991 1.34 1992 1.274 1993 0.994 1994 0.797 1995 1.096 1996 0.954 1997 1.255 1998 1.427 1999 1.6 2000 0.862 2001 1.157