# europe_fran002 - Foret de Chinon - 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/4214 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_fran002 - Foret de Chinon - 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: Foret de Chinon # Location: # Country: France # Northernmost_Latitude: 47.23 # Southernmost_Latitude: 47.23 # Easternmost_Longitude: 0.37 # Westernmost_Longitude: 0.37 # Elevation: 110 m #-------------------- # Data_Collection # Collection_Name: europe_fran002B # Earliest_Year: 1813 # Most_Recent_Year: 1979 # 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":"4.16830778077","T2":"15.7340854796","M1":"0.0231322084077","M2":"0.522111254273"}} #-------------------- # Species # Species_Name: durmast oak # Species_Code: QUPE #-------------------- # 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 1813 1.253 1814 1.148 1815 0.778 1816 1.101 1817 0.822 1818 0.55 1819 0.537 1820 0.844 1821 1.094 1822 0.99 1823 1.166 1824 1.344 1825 0.79 1826 0.708 1827 0.833 1828 1.231 1829 1.517 1830 1.283 1831 1.093 1832 0.776 1833 0.835 1834 0.85 1835 0.56 1836 0.845 1837 0.726 1838 1.436 1839 1.207 1840 1.211 1841 1.444 1842 1.091 1843 1.101 1844 0.657 1845 0.689 1846 0.405 1847 0.366 1848 0.728 1849 0.701 1850 0.802 1851 0.714 1852 0.868 1853 1.05 1854 0.802 1855 1.069 1856 0.818 1857 0.689 1858 0.627 1859 0.8 1860 1.088 1861 1.559 1862 1.361 1863 1.047 1864 1.017 1865 1.031 1866 1.244 1867 1.2 1868 1.077 1869 1.137 1870 0.581 1871 1.286 1872 1.094 1873 0.916 1874 0.563 1875 0.741 1876 0.903 1877 0.826 1878 0.897 1879 0.896 1880 0.659 1881 0.764 1882 1.087 1883 1.033 1884 1.038 1885 0.946 1886 1.063 1887 0.775 1888 1.188 1889 0.955 1890 0.907 1891 0.768 1892 0.711 1893 0.619 1894 0.968 1895 1.07 1896 0.901 1897 1.124 1898 0.796 1899 0.869 1900 0.964 1901 0.695 1902 0.823 1903 0.882 1904 1.041 1905 0.907 1906 0.692 1907 0.963 1908 1.219 1909 0.799 1910 1.167 1911 1.022 1912 1.615 1913 1.204 1914 1.192 1915 1.245 1916 1.16 1917 1.374 1918 1.027 1919 0.944 1920 1.203 1921 0.712 1922 0.802 1923 0.869 1924 1.165 1925 1.0 1926 1.302 1927 1.372 1928 1.037 1929 1.156 1930 1.323 1931 1.348 1932 1.251 1933 0.874 1934 0.691 1935 0.722 1936 0.945 1937 0.919 1938 0.973 1939 1.1 1940 1.073 1941 0.899 1942 0.927 1943 0.773 1944 0.754 1945 0.894 1946 0.982 1947 0.784 1948 0.954 1949 0.873 1950 0.962 1951 0.915 1952 0.639 1953 0.993 1954 0.932 1955 0.764 1956 0.736 1957 0.813 1958 0.974 1959 0.677 1960 0.859 1961 0.939 1962 0.901 1963 0.973 1964 0.869 1965 1.051 1966 0.953 1967 1.248 1968 0.908 1969 1.114 1970 1.092 1971 1.291 1972 1.081 1973 1.185 1974 1.084 1975 1.39 1976 0.986 1977 1.028 1978 1.477 1979 1.337