# europe_aust112 - Weinerwald - 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/5059 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_aust112 - Weinerwald - 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: Weinerwald # 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_aust112B # Earliest_Year: 1812 # 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":"5.34661543503","T2":"15.9575160011","M1":"0.0225719200291","M2":"0.511237065133"}} #-------------------- # Species # Species_Name: durmast oak # Species_Code: QUPE #-------------------- # 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 1812 1.383 1813 1.283 1814 1.14 1815 1.132 1816 0.867 1817 0.632 1818 0.784 1819 0.713 1820 0.784 1821 0.936 1822 0.523 1823 1.023 1824 0.949 1825 0.715 1826 0.959 1827 0.951 1828 1.015 1829 0.846 1830 0.537 1831 0.695 1832 0.627 1833 0.602 1834 0.548 1835 0.56 1836 0.533 1837 0.692 1838 0.659 1839 0.76 1840 0.944 1841 1.058 1842 1.2 1843 1.623 1844 1.446 1845 1.28 1846 1.032 1847 1.668 1848 1.454 1849 1.037 1850 1.418 1851 1.226 1852 1.026 1853 1.305 1854 1.155 1855 1.009 1856 1.134 1857 0.924 1858 0.923 1859 1.009 1860 1.211 1861 1.375 1862 1.191 1863 0.831 1864 1.066 1865 0.954 1866 0.935 1867 1.258 1868 0.945 1869 0.827 1870 1.238 1871 1.289 1872 0.811 1873 1.074 1874 0.988 1875 1.082 1876 0.767 1877 0.615 1878 0.975 1879 0.873 1880 0.899 1881 0.926 1882 0.78 1883 1.029 1884 1.069 1885 0.822 1886 0.964 1887 0.845 1888 0.875 1889 0.763 1890 0.801 1891 1.128 1892 1.163 1893 1.004 1894 1.032 1895 1.121 1896 1.194 1897 1.274 1898 1.303 1899 1.203 1900 0.991 1901 0.715 1902 1.086 1903 1.083 1904 0.957 1905 0.947 1906 1.107 1907 0.972 1908 0.868 1909 0.797 1910 0.973 1911 1.068 1912 1.176 1913 0.796 1914 1.104 1915 0.77 1916 0.802 1917 0.595 1918 0.661 1919 0.909 1920 0.882 1921 0.757 1922 0.557 1923 0.745 1924 0.831 1925 0.789 1926 1.285 1927 1.042 1928 0.919 1929 0.767 1930 0.625 1931 0.736 1932 0.974 1933 0.902 1934 0.784 1935 0.946 1936 0.989 1937 0.853 1938 0.893 1939 0.821 1940 0.896 1941 1.111 1942 1.123 1943 1.076 1944 1.073 1945 0.714 1946 0.705 1947 0.801 1948 0.793 1949 1.085 1950 0.773 1951 1.088 1952 1.045 1953 1.108 1954 1.074 1955 1.315 1956 1.041 1957 0.865 1958 1.305 1959 0.994 1960 1.282 1961 1.198 1962 0.975 1963 0.887 1964 0.891 1965 1.166 1966 1.153 1967 1.108 1968 0.977 1969 1.119 1970 0.962 1971 0.902 1972 1.002 1973 0.822 1974 0.865 1975 1.171 1976 0.859 1977 0.758 1978 1.005 1979 0.947 1980 0.877 1981 0.654 1982 1.064 1983 0.949 1984 1.134 1985 0.935 1986 0.967 1987 1.096 1988 1.136 1989 1.309 1990 1.27 1991 1.207 1992 1.165 1993 0.916 1994 1.331 1995 1.107