# europe_spai053 - Sant Maurici - 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: # # Original_Source_URL: # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_spai053 - Sant Maurici - 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. #-------------------- # Funding_Agency # Funding_Agency_Name: Swiss National Science Foundation # Grant: #-------------------- # Site_Information # Site_Name: Sant Maurici # Location: # Country: Spain # Northernmost_Latitude: 42.5 # Southernmost_Latitude: 42.5 # Easternmost_Longitude: 1.5 # Westernmost_Longitude: 1.5 # Elevation: 2000 m #-------------------- # Data_Collection # Collection_Name: europe_spai053B # Earliest_Year: 1821 # Most_Recent_Year: 1996 # Time_Unit: y_ad # Core_Length: # Notes: {"sensitivity":"moisture"}{"T1":"4.39803397983"}{"T2":"13.6139183043"}{"M1":"0.0226990190966"}{"M2":"0.599334369977"} #-------------------- # Species # Species_Name: mountain pine # Species_Code: PIUN #-------------------- # 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 1821 0.956 1822 0.815 1823 1.087 1824 0.978 1825 1.157 1826 0.777 1827 1.269 1828 1.066 1829 0.925 1830 0.951 1831 0.983 1832 0.987 1833 1.071 1834 1.29 1835 1.256 1836 0.827 1837 1.176 1838 1.143 1839 0.805 1840 1.064 1841 1.215 1842 1.014 1843 1.166 1844 1.086 1845 0.838 1846 1.166 1847 0.801 1848 1.007 1849 0.88 1850 1.106 1851 0.883 1852 1.132 1853 0.666 1854 1.001 1855 0.769 1856 0.783 1857 0.869 1858 0.812 1859 1.09 1860 0.761 1861 0.969 1862 0.789 1863 0.925 1864 1.069 1865 0.829 1866 0.825 1867 1.089 1868 0.771 1869 0.991 1870 0.954 1871 0.945 1872 0.885 1873 0.844 1874 0.954 1875 0.981 1876 0.901 1877 0.966 1878 1.053 1879 0.531 1880 0.843 1881 0.881 1882 0.843 1883 0.864 1884 1.131 1885 1.109 1886 0.946 1887 0.873 1888 1.054 1889 1.13 1890 0.874 1891 1.063 1892 1.073 1893 1.156 1894 1.016 1895 1.315 1896 1.107 1897 1.214 1898 1.193 1899 1.268 1900 1.161 1901 1.179 1902 1.215 1903 1.193 1904 1.283 1905 1.161 1906 0.863 1907 0.876 1908 0.784 1909 0.641 1910 0.827 1911 1.143 1912 0.912 1913 0.917 1914 1.267 1915 1.124 1916 0.973 1917 0.95 1918 1.094 1919 1.141 1920 1.479 1921 1.23 1922 0.993 1923 1.042 1924 0.999 1925 1.066 1926 0.823 1927 1.02 1928 0.908 1929 0.9 1930 1.227 1931 0.738 1932 0.99 1933 0.916 1934 0.798 1935 0.881 1936 1.013 1937 0.994 1938 1.033 1939 1.313 1940 1.154 1941 1.017 1942 0.872 1943 0.894 1944 0.775 1945 0.817 1946 0.829 1947 0.689 1948 0.937 1949 0.805 1950 0.842 1951 1.08 1952 1.073 1953 1.127 1954 0.962 1955 1.095 1956 1.13 1957 0.949 1958 1.065 1959 1.263 1960 1.266 1961 1.423 1962 0.847 1963 0.905 1964 1.185 1965 0.696 1966 0.88 1967 0.541 1968 0.779 1969 1.069 1970 1.039 1971 1.095 1972 1.078 1973 1.217 1974 1.188 1975 0.955 1976 0.832 1977 0.776 1978 1.025 1979 0.862 1980 0.923 1981 0.902 1982 1.132 1983 1.028 1984 0.684 1985 0.963 1986 0.599 1987 0.811 1988 0.962 1989 0.812 1990 1.13 1991 0.663 1992 0.98 1993 1.204 1994 1.093 1995 1.04 1996 1.322