# europe_aust111 - Parapluiberg - 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/5058 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_aust111 - Parapluiberg - 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: Parapluiberg # Location: # Country: Austria # Northernmost_Latitude: 48.12 # Southernmost_Latitude: 48.12 # Easternmost_Longitude: 16.25 # Westernmost_Longitude: 16.25 # Elevation: 450 m #-------------------- # Data_Collection # Collection_Name: europe_aust111B # Earliest_Year: 1781 # Most_Recent_Year: 1995 # 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":"4.26180437316","T2":"15.6802855106","M1":"0.0227411286701","M2":"0.574703135584"}} #-------------------- # 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 1781 1.011 1782 0.954 1783 1.021 1784 1.017 1785 1.333 1786 1.129 1787 1.003 1788 1.052 1789 0.575 1790 0.522 1791 1.21 1792 1.083 1793 1.373 1794 1.003 1795 0.98 1796 1.101 1797 0.603 1798 1.033 1799 0.804 1800 0.6 1801 1.087 1802 0.422 1803 0.728 1804 0.817 1805 0.724 1806 0.432 1807 0.72 1808 0.657 1809 0.872 1810 0.94 1811 0.755 1812 1.103 1813 1.331 1814 1.336 1815 1.326 1816 1.404 1817 1.328 1818 1.094 1819 1.243 1820 1.258 1821 1.875 1822 1.053 1823 1.547 1824 1.94 1825 1.492 1826 1.683 1827 0.983 1828 1.282 1829 1.811 1830 1.134 1831 1.754 1832 1.039 1833 0.852 1834 0.769 1835 0.515 1836 0.728 1837 1.332 1838 0.759 1839 0.761 1840 1.231 1841 0.789 1842 0.823 1843 1.443 1844 0.879 1845 1.255 1846 1.343 1847 1.211 1848 1.114 1849 0.667 1850 0.944 1851 1.238 1852 0.639 1853 1.081 1854 0.816 1855 0.888 1856 0.777 1857 0.541 1858 0.491 1859 0.696 1860 0.734 1861 1.057 1862 0.792 1863 0.435 1864 0.922 1865 0.493 1866 0.583 1867 0.98 1868 0.689 1869 0.478 1870 0.81 1871 1.109 1872 0.689 1873 0.644 1874 0.702 1875 0.534 1876 0.877 1877 0.719 1878 0.999 1879 1.015 1880 0.794 1881 0.837 1882 0.695 1883 0.822 1884 1.238 1885 0.989 1886 0.879 1887 0.661 1888 0.811 1889 0.562 1890 0.708 1891 0.515 1892 0.904 1893 0.61 1894 0.828 1895 0.929 1896 0.776 1897 1.248 1898 1.208 1899 1.217 1900 1.067 1901 0.557 1902 1.351 1903 1.698 1904 0.962 1905 0.753 1906 1.297 1907 0.774 1908 0.858 1909 0.805 1910 1.103 1911 1.124 1912 1.826 1913 1.571 1914 1.754 1915 0.938 1916 1.686 1917 0.823 1918 1.291 1919 1.632 1920 1.764 1921 1.027 1922 0.482 1923 0.98 1924 0.745 1925 0.94 1926 1.396 1927 1.075 1928 1.093 1929 0.707 1930 0.561 1931 0.858 1932 1.26 1933 0.899 1934 0.513 1935 0.708 1936 1.151 1937 0.828 1938 0.873 1939 1.534 1940 1.364 1941 1.823 1942 1.438 1943 1.326 1944 1.088 1945 0.361 1946 0.552 1947 0.554 1948 0.494 1949 0.776 1950 0.696 1951 0.935 1952 0.865 1953 1.126 1954 1.021 1955 0.914 1956 0.831 1957 0.736 1958 1.202 1959 1.739 1960 1.265 1961 1.418 1962 0.926 1963 0.861 1964 0.804 1965 1.687 1966 1.305 1967 1.052 1968 0.552 1969 0.904 1970 1.245 1971 0.893 1972 1.367 1973 1.689 1974 0.857 1975 0.889 1976 0.589 1977 0.414 1978 0.846 1979 0.407 1980 0.6 1981 0.671 1982 0.862 1983 0.616 1984 0.541 1985 0.831 1986 0.813 1987 0.768 1988 0.485 1989 1.033 1990 0.968 1991 1.124 1992 1.013 1993 0.661 1994 1.668 1995 1.381