# europe_germ018 - Oberer Bannwald B - 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/2705 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_germ018 - Oberer Bannwald B - 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: Oberer Bannwald B # Location: # Country: Germany # Northernmost_Latitude: 48.57 # Southernmost_Latitude: 48.57 # Easternmost_Longitude: 9.08 # Westernmost_Longitude: 9.08 # Elevation: 750 m #-------------------- # Data_Collection # Collection_Name: europe_germ018B # Earliest_Year: 1790 # Most_Recent_Year: 1971 # 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":"4.98696978654","T2":"16.0542282844","M1":"0.022268183659","M2":"0.287729862903"}} #-------------------- # Species # Species_Name: Scots pine # Species_Code: PISY #-------------------- # 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 1790 1.008 1791 1.002 1792 1.504 1793 1.138 1794 1.215 1795 1.181 1796 1.316 1797 1.286 1798 1.407 1799 1.204 1800 1.249 1801 1.136 1802 1.165 1803 1.148 1804 0.948 1805 0.941 1806 0.943 1807 0.941 1808 1.008 1809 0.89 1810 1.054 1811 0.93 1812 0.687 1813 0.903 1814 1.015 1815 0.737 1816 0.747 1817 0.779 1818 0.917 1819 1.072 1820 0.829 1821 0.903 1822 1.413 1823 1.166 1824 0.993 1825 0.963 1826 0.89 1827 0.798 1828 1.079 1829 1.079 1830 0.971 1831 1.108 1832 0.968 1833 0.986 1834 1.204 1835 0.883 1836 0.942 1837 1.017 1838 0.82 1839 0.73 1840 0.963 1841 1.018 1842 0.944 1843 0.919 1844 0.879 1845 0.692 1846 0.97 1847 0.694 1848 1.195 1849 0.733 1850 0.557 1851 0.792 1852 0.686 1853 1.032 1854 0.67 1855 0.631 1856 0.81 1857 0.735 1858 0.63 1859 0.819 1860 0.801 1861 0.995 1862 1.16 1863 1.09 1864 1.328 1865 1.001 1866 0.926 1867 1.05 1868 0.979 1869 0.901 1870 0.655 1871 0.919 1872 0.737 1873 0.998 1874 1.145 1875 1.153 1876 1.036 1877 0.995 1878 1.1 1879 1.11 1880 0.924 1881 1.28 1882 1.422 1883 1.059 1884 1.287 1885 1.267 1886 0.919 1887 0.732 1888 0.623 1889 0.419 1890 0.876 1891 0.572 1892 0.693 1893 0.846 1894 0.92 1895 1.024 1896 1.026 1897 1.375 1898 1.109 1899 1.107 1900 0.928 1901 1.107 1902 1.14 1903 1.079 1904 1.219 1905 1.325 1906 0.969 1907 1.025 1908 0.937 1909 0.805 1910 0.709 1911 0.626 1912 0.937 1913 0.905 1914 0.914 1915 0.873 1916 0.979 1917 0.617 1918 0.665 1919 0.757 1920 0.918 1921 0.799 1922 0.873 1923 0.805 1924 1.145 1925 1.422 1926 0.746 1927 1.332 1928 1.42 1929 1.177 1930 1.074 1931 0.94 1932 0.883 1933 0.709 1934 0.612 1935 0.55 1936 0.792 1937 0.822 1938 1.075 1939 1.168 1940 0.744 1941 0.687 1942 0.868 1943 1.324 1944 1.233 1945 1.151 1946 1.188 1947 1.345 1948 1.307 1949 1.305 1950 1.401 1951 1.221 1952 1.002 1953 1.184 1954 0.934 1955 1.065 1956 0.951 1957 0.9 1958 1.085 1959 1.268 1960 1.032 1961 1.097 1962 1.019 1963 0.8 1964 0.823 1965 1.321 1966 1.159 1967 1.345 1968 1.162 1969 1.095 1970 1.233 1971 1.648