# europe_germ040 - Falkenstein - 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/5266 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_germ040 - Falkenstein - 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: Falkenstein # Location: # Country: Germany # Northernmost_Latitude: 49.1 # Southernmost_Latitude: 49.1 # Easternmost_Longitude: 13.33 # Westernmost_Longitude: 13.33 # Elevation: 1325 m #-------------------- # Data_Collection # Collection_Name: europe_germ040B # Earliest_Year: 1755 # Most_Recent_Year: 1995 # 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":"6.41345525268","T2":"20.1016992266","M1":"0.0222399142755","M2":"0.256514270145"}} #-------------------- # Species # Species_Name: Norway spruce # Species_Code: PCAB #-------------------- # 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 1755 1.086 1756 1.168 1757 1.231 1758 0.908 1759 1.135 1760 1.184 1761 1.315 1762 1.393 1763 1.124 1764 1.101 1765 0.993 1766 1.204 1767 1.349 1768 1.209 1769 1.399 1770 1.214 1771 0.853 1772 0.969 1773 0.823 1774 0.933 1775 0.832 1776 0.993 1777 1.191 1778 1.265 1779 1.092 1780 1.085 1781 1.253 1782 0.891 1783 1.478 1784 1.162 1785 1.303 1786 1.297 1787 1.223 1788 1.222 1789 1.019 1790 1.04 1791 1.326 1792 1.291 1793 1.111 1794 1.439 1795 1.127 1796 1.022 1797 0.895 1798 1.457 1799 1.283 1800 1.313 1801 1.162 1802 0.973 1803 0.793 1804 0.947 1805 0.783 1806 0.81 1807 1.357 1808 0.987 1809 0.98 1810 1.039 1811 1.152 1812 0.75 1813 0.748 1814 0.932 1815 0.836 1816 0.68 1817 0.76 1818 0.588 1819 0.785 1820 0.515 1821 0.339 1822 0.753 1823 0.584 1824 0.765 1825 0.877 1826 0.758 1827 0.821 1828 1.005 1829 0.912 1830 0.699 1831 0.847 1832 0.745 1833 1.043 1834 1.116 1835 0.849 1836 0.907 1837 0.968 1838 0.808 1839 1.03 1840 0.922 1841 0.88 1842 1.113 1843 0.616 1844 0.841 1845 0.954 1846 1.121 1847 1.047 1848 0.907 1849 0.987 1850 1.044 1851 0.71 1852 1.055 1853 1.082 1854 0.985 1855 1.092 1856 0.973 1857 1.176 1858 1.261 1859 1.052 1860 0.963 1861 0.946 1862 0.998 1863 1.174 1864 1.048 1865 1.042 1866 1.292 1867 1.218 1868 1.194 1869 1.053 1870 1.262 1871 1.164 1872 1.156 1873 1.495 1874 1.438 1875 1.5 1876 1.177 1877 1.083 1878 1.179 1879 1.138 1880 1.195 1881 1.413 1882 0.989 1883 1.087 1884 1.284 1885 1.078 1886 0.943 1887 1.193 1888 1.097 1889 1.218 1890 0.963 1891 0.87 1892 1.044 1893 1.023 1894 1.034 1895 1.244 1896 1.045 1897 1.07 1898 0.944 1899 0.977 1900 0.863 1901 1.093 1902 0.988 1903 1.109 1904 1.202 1905 0.836 1906 0.739 1907 0.861 1908 1.101 1909 0.958 1910 1.009 1911 1.304 1912 1.046 1913 0.819 1914 0.981 1915 0.972 1916 1.07 1917 1.138 1918 0.752 1919 0.978 1920 0.855 1921 0.925 1922 0.92 1923 0.75 1924 1.05 1925 1.021 1926 1.008 1927 1.181 1928 1.169 1929 1.019 1930 0.945 1931 1.375 1932 1.148 1933 0.974 1934 1.249 1935 1.399 1936 1.148 1937 1.088 1938 1.148 1939 1.175 1940 1.066 1941 1.037 1942 0.723 1943 0.684 1944 0.721 1945 0.827 1946 1.238 1947 1.455 1948 0.724 1949 0.88 1950 1.098 1951 1.083 1952 1.164 1953 1.022 1954 0.299 1955 0.371 1956 0.305 1957 0.587 1958 0.547 1959 0.628 1960 0.806 1961 0.777 1962 0.94 1963 1.151 1964 0.903 1965 0.594 1966 1.051 1967 1.096 1968 1.041 1969 1.256 1970 1.157 1971 0.907 1972 0.927 1973 1.06 1974 0.518 1975 0.822 1976 0.464 1977 0.906 1978 0.664 1979 0.982 1980 0.454 1981 0.764 1982 0.922 1983 1.123 1984 0.836 1985 0.82 1986 1.041 1987 0.969 1988 1.216 1989 1.256 1990 1.144 1991 1.043 1992 1.187 1993 0.945 1994 1.146 1995 0.849