# europe_neth025 - Landgoed Hillenraad - 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/3912 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_neth025 - Landgoed Hillenraad - 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: Landgoed Hillenraad # Location: # Country: Netherlands # Northernmost_Latitude: 51.22 # Southernmost_Latitude: 51.22 # Easternmost_Longitude: 6.05 # Westernmost_Longitude: 6.05 # Elevation: 27 m #-------------------- # Data_Collection # Collection_Name: europe_neth025B # Earliest_Year: 1807 # Most_Recent_Year: 1986 # 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":"4.68920995345","T2":"16.0297377668","M1":"0.0225988955726","M2":"0.533171051716"}} #-------------------- # 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 1807 1.076 1808 0.962 1809 1.124 1810 1.091 1811 1.027 1812 1.134 1813 1.009 1814 0.97 1815 1.038 1816 1.017 1817 1.034 1818 0.882 1819 0.857 1820 0.847 1821 0.868 1822 0.911 1823 0.966 1824 0.987 1825 1.023 1826 1.106 1827 1.019 1828 1.072 1829 1.069 1830 1.093 1831 1.074 1832 1.066 1833 1.049 1834 1.051 1835 1.045 1836 1.058 1837 1.04 1838 1.063 1839 1.086 1840 1.158 1841 1.216 1842 1.244 1843 1.174 1844 0.991 1845 0.876 1846 0.802 1847 0.768 1848 0.766 1849 0.798 1850 0.929 1851 0.999 1852 1.023 1853 1.067 1854 1.091 1855 0.974 1856 0.943 1857 0.836 1858 0.842 1859 0.808 1860 0.86 1861 0.81 1862 0.827 1863 0.894 1864 0.853 1865 0.876 1866 0.855 1867 0.843 1868 0.891 1869 0.922 1870 0.939 1871 0.964 1872 0.983 1873 1.024 1874 1.063 1875 1.058 1876 1.036 1877 1.054 1878 1.044 1879 0.956 1880 0.928 1881 0.907 1882 0.963 1883 0.987 1884 0.957 1885 0.967 1886 0.944 1887 0.883 1888 0.799 1889 0.768 1890 0.731 1891 0.8 1892 0.868 1893 0.937 1894 0.98 1895 1.065 1896 1.029 1897 1.01 1898 0.945 1899 1.047 1900 1.047 1901 1.094 1902 1.225 1903 1.219 1904 1.344 1905 1.176 1906 1.124 1907 1.05 1908 1.022 1909 1.027 1910 0.954 1911 0.976 1912 0.971 1913 0.938 1914 1.029 1915 1.061 1916 1.105 1917 1.036 1918 0.99 1919 1.02 1920 0.953 1921 0.862 1922 0.772 1923 0.776 1924 0.843 1925 0.881 1926 0.96 1927 1.074 1928 1.071 1929 1.103 1930 1.009 1931 1.075 1932 1.104 1933 1.058 1934 0.977 1935 0.973 1936 0.9 1937 0.961 1938 0.95 1939 0.929 1940 0.806 1941 0.748 1942 0.782 1943 0.792 1944 0.89 1945 0.955 1946 0.965 1947 1.02 1948 1.117 1949 1.165 1950 1.316 1951 1.331 1952 1.277 1953 1.265 1954 1.144 1955 1.101 1956 1.055 1957 1.174 1958 1.128 1959 0.96 1960 1.002 1961 1.047 1962 1.008 1963 0.953 1964 0.962 1965 1.136 1966 1.344 1967 1.243 1968 1.017 1969 0.972 1970 0.891 1971 0.875 1972 0.906 1973 0.87 1974 0.899 1975 0.644 1976 0.586 1977 0.564 1978 0.588 1979 0.64 1980 0.66 1981 0.729 1982 0.628 1983 0.627 1984 0.635 1985 0.66 1986 0.382