# europe_cypr016 - Armiantos - 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/5545 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_cypr016 - Armiantos - 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: Armiantos # Location: # Country: Cyprus # Northernmost_Latitude: 34.92 # Southernmost_Latitude: 34.92 # Easternmost_Longitude: 32.9 # Westernmost_Longitude: 32.9 # Elevation: 1550 m #-------------------- # Data_Collection # Collection_Name: europe_cypr016B # Earliest_Year: 1711 # Most_Recent_Year: 2002 # 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":"7.37020539015","T2":"14.4475711492","M1":"0.0214628493231","M2":"0.366285480417"}} #-------------------- # 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 1711 0.788 1712 0.727 1713 0.603 1714 0.738 1715 0.583 1716 0.748 1717 0.742 1718 0.782 1719 0.786 1720 0.938 1721 1.205 1722 1.233 1723 0.889 1724 0.968 1725 0.774 1726 0.544 1727 0.936 1728 0.985 1729 1.108 1730 0.921 1731 0.924 1732 0.876 1733 1.034 1734 1.018 1735 1.057 1736 1.159 1737 0.859 1738 0.724 1739 0.763 1740 0.823 1741 0.917 1742 0.897 1743 0.691 1744 0.657 1745 0.618 1746 0.798 1747 0.938 1748 1.072 1749 0.906 1750 0.769 1751 1.014 1752 1.038 1753 1.039 1754 1.233 1755 1.282 1756 1.155 1757 0.993 1758 1.034 1759 0.832 1760 0.833 1761 0.778 1762 1.069 1763 1.051 1764 1.177 1765 1.09 1766 1.104 1767 1.029 1768 0.934 1769 1.022 1770 0.943 1771 1.14 1772 1.186 1773 1.406 1774 1.205 1775 0.972 1776 1.046 1777 1.336 1778 0.828 1779 0.712 1780 0.982 1781 0.86 1782 0.893 1783 1.044 1784 0.831 1785 0.781 1786 1.138 1787 0.823 1788 1.159 1789 1.251 1790 0.965 1791 1.189 1792 1.482 1793 1.056 1794 1.096 1795 1.177 1796 1.043 1797 1.093 1798 0.939 1799 1.014 1800 1.162 1801 1.193 1802 1.096 1803 0.913 1804 1.05 1805 1.276 1806 1.472 1807 1.034 1808 1.112 1809 1.041 1810 1.077 1811 1.374 1812 1.104 1813 1.04 1814 1.171 1815 0.953 1816 0.973 1817 1.03 1818 1.158 1819 0.961 1820 1.022 1821 1.018 1822 0.767 1823 0.904 1824 1.061 1825 0.937 1826 0.745 1827 1.29 1828 1.423 1829 1.521 1830 1.194 1831 1.142 1832 1.111 1833 0.787 1834 0.794 1835 1.089 1836 1.062 1837 1.296 1838 1.43 1839 1.159 1840 0.962 1841 1.191 1842 1.18 1843 1.021 1844 0.829 1845 0.917 1846 1.026 1847 1.1 1848 1.084 1849 0.883 1850 0.693 1851 0.731 1852 0.698 1853 0.964 1854 0.75 1855 0.753 1856 0.799 1857 0.931 1858 0.915 1859 0.909 1860 0.761 1861 0.831 1862 0.793 1863 0.684 1864 0.703 1865 0.793 1866 0.78 1867 0.936 1868 0.55 1869 0.713 1870 0.769 1871 1.026 1872 1.037 1873 1.018 1874 0.509 1875 0.589 1876 0.712 1877 0.883 1878 0.624 1879 0.65 1880 0.773 1881 0.85 1882 0.757 1883 0.851 1884 0.7 1885 0.736 1886 0.892 1887 0.804 1888 1.002 1889 1.09 1890 0.981 1891 0.835 1892 0.954 1893 0.743 1894 0.481 1895 0.703 1896 0.641 1897 0.95 1898 0.658 1899 0.52 1900 0.842 1901 0.866 1902 0.995 1903 0.816 1904 0.861 1905 0.617 1906 0.491 1907 0.444 1908 0.737 1909 0.488 1910 0.769 1911 0.618 1912 1.007 1913 0.971 1914 1.304 1915 1.592 1916 1.502 1917 1.011 1918 1.255 1919 1.759 1920 0.859 1921 1.195 1922 1.421 1923 1.182 1924 0.971 1925 1.144 1926 1.26 1927 0.938 1928 0.789 1929 0.557 1930 0.942 1931 1.174 1932 1.071 1933 1.391 1934 1.112 1935 1.14 1936 1.524 1937 1.019 1938 1.1 1939 1.104 1940 1.027 1941 0.997 1942 0.347 1943 0.769 1944 0.953 1945 0.776 1946 0.594 1947 0.667 1948 0.695 1949 0.505 1950 0.854 1951 1.258 1952 1.139 1953 0.907 1954 0.88 1955 1.175 1956 1.025 1957 0.757 1958 1.263 1959 1.169 1960 1.205 1961 0.802 1962 0.879 1963 0.89 1964 1.125 1965 1.093 1966 1.146 1967 0.973 1968 0.948 1969 1.354 1970 1.286 1971 1.138 1972 1.667 1973 1.467 1974 1.215 1975 1.36 1976 1.396 1977 1.574 1978 1.369 1979 1.593 1980 1.344 1981 1.122 1982 1.25 1983 1.027 1984 1.085 1985 0.852 1986 1.228 1987 1.203 1988 1.132 1989 0.934 1990 0.939 1991 0.85 1992 0.403 1993 0.521 1994 0.898 1995 1.001 1996 0.879 1997 0.93 1998 1.172 1999 1.26 2000 0.966 2001 1.319 2002 1.019