# europe_germ003 - Koln Abt. 48 - 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/4288 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_germ003 - Koln Abt. 48 - 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: Koln Abt. 48 # Location: # Country: Germany # Northernmost_Latitude: 50.92 # Southernmost_Latitude: 50.92 # Easternmost_Longitude: 7.15 # Westernmost_Longitude: 7.15 # Elevation: 131 m #-------------------- # Data_Collection # Collection_Name: europe_germ003B # Earliest_Year: 1802 # 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":"4.82741651484","T2":"19.1879546771","M1":"0.0225735009581","M2":"0.439854703302"}} #-------------------- # Species # Species_Name: English oak # Species_Code: QURO #-------------------- # 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 1802 1.057 1803 0.809 1804 1.194 1805 1.064 1806 1.076 1807 0.941 1808 1.263 1809 1.107 1810 0.94 1811 1.152 1812 1.167 1813 1.145 1814 1.033 1815 1.017 1816 1.193 1817 1.118 1818 1.02 1819 0.915 1820 0.741 1821 0.917 1822 0.884 1823 1.054 1824 1.281 1825 0.828 1826 0.828 1827 1.044 1828 1.123 1829 1.185 1830 1.058 1831 1.027 1832 0.899 1833 0.809 1834 1.119 1835 0.905 1836 0.843 1837 1.009 1838 0.806 1839 0.823 1840 0.94 1841 0.796 1842 0.936 1843 1.001 1844 0.907 1845 0.82 1846 0.813 1847 0.869 1848 1.031 1849 0.929 1850 0.985 1851 0.987 1852 0.891 1853 0.979 1854 0.791 1855 0.841 1856 0.86 1857 0.781 1858 0.582 1859 0.817 1860 1.0 1861 0.962 1862 0.866 1863 0.952 1864 0.942 1865 0.759 1866 0.969 1867 1.169 1868 0.895 1869 0.596 1870 0.557 1871 0.559 1872 0.62 1873 0.839 1874 0.916 1875 1.202 1876 0.938 1877 0.956 1878 1.344 1879 1.238 1880 0.94 1881 1.079 1882 1.264 1883 0.963 1884 1.083 1885 0.969 1886 1.023 1887 1.015 1888 0.781 1889 0.706 1890 0.689 1891 0.733 1892 0.906 1893 0.815 1894 1.085 1895 1.024 1896 0.983 1897 1.072 1898 1.213 1899 0.974 1900 1.097 1901 1.081 1902 1.05 1903 1.289 1904 1.326 1905 1.153 1906 0.748 1907 0.585 1908 0.634 1909 0.422 1910 0.6 1911 0.885 1912 1.28 1913 1.05 1914 1.17 1915 0.957 1916 1.0 1917 1.029 1918 1.218 1919 1.152 1920 1.146 1921 0.82 1922 0.795 1923 0.698 1924 0.703 1925 0.655 1926 0.899 1927 1.142 1928 1.032 1929 0.89 1930 0.996 1931 1.255 1932 1.127 1933 1.086 1934 0.924 1935 1.028 1936 1.205 1937 0.99 1938 0.927 1939 0.662 1940 0.675 1941 0.698 1942 0.628 1943 0.905 1944 0.995 1945 1.204 1946 1.171 1947 0.997 1948 1.226 1949 1.488 1950 1.526 1951 1.43 1952 1.358 1953 1.378 1954 1.307 1955 1.518 1956 0.844 1957 0.913 1958 0.883 1959 0.635 1960 1.029 1961 1.059 1962 1.104 1963 1.031 1964 1.071 1965 0.99 1966 0.998 1967 1.14 1968 0.913 1969 1.184 1970 1.324 1971 1.521