# europe_fran5 - Bois De Vanclusie - 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/5105 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_fran5 - Bois De Vanclusie - 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: Bois De Vanclusie # Location: # Country: France # Northernmost_Latitude: 44.37 # Southernmost_Latitude: 44.37 # Easternmost_Longitude: 5.62 # Westernmost_Longitude: 5.62 # Elevation: 1100 m #-------------------- # Data_Collection # Collection_Name: europe_fran5B # Earliest_Year: 1810 # 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":"3.62056879164","T2":"13.24216865","M1":"0.0228469158346","M2":"0.601325424168"}} #-------------------- # 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 1810 1.001 1811 0.946 1812 0.834 1813 1.118 1814 1.264 1815 1.21 1816 1.093 1817 0.996 1818 1.197 1819 1.135 1820 0.845 1821 1.005 1822 0.738 1823 0.902 1824 0.733 1825 0.83 1826 0.851 1827 0.996 1828 0.882 1829 1.2 1830 0.978 1831 1.16 1832 0.885 1833 0.801 1834 0.986 1835 1.161 1836 0.897 1837 0.883 1838 0.957 1839 0.65 1840 0.834 1841 1.059 1842 1.057 1843 1.349 1844 1.136 1845 1.211 1846 1.394 1847 1.002 1848 1.079 1849 0.701 1850 0.991 1851 0.971 1852 1.119 1853 1.02 1854 1.499 1855 0.921 1856 1.124 1857 1.09 1858 0.895 1859 0.877 1860 0.876 1861 0.939 1862 0.911 1863 0.892 1864 0.919 1865 0.975 1866 1.069 1867 1.151 1868 1.099 1869 0.968 1870 0.598 1871 0.77 1872 0.981 1873 0.997 1874 1.073 1875 1.106 1876 0.987 1877 1.003 1878 1.372 1879 0.822 1880 1.109 1881 0.928 1882 1.015 1883 1.178 1884 1.072 1885 0.895 1886 0.92 1887 1.037 1888 1.112 1889 1.022 1890 0.921 1891 0.885 1892 0.972 1893 0.999 1894 1.043 1895 0.956 1896 1.067 1897 0.942 1898 0.874 1899 0.882 1900 0.787 1901 0.822 1902 0.766 1903 1.094 1904 1.135 1905 1.16 1906 0.725 1907 0.936 1908 1.122 1909 0.824 1910 1.033 1911 1.035 1912 1.136 1913 1.127 1914 1.579 1915 1.261 1916 1.101 1917 1.111 1918 0.759 1919 0.549 1920 0.802 1921 0.598 1922 0.623 1923 0.762 1924 0.792 1925 1.218 1926 1.175 1927 1.23 1928 1.111 1929 1.07 1930 1.511 1931 1.096 1932 1.43 1933 1.21 1934 1.085 1935 0.827 1936 0.876 1937 0.809 1938 0.953 1939 1.253 1940 1.294 1941 1.161 1942 0.706 1943 1.056 1944 1.135 1945 0.78 1946 0.95 1947 1.068 1948 1.189 1949 0.763 1950 0.492 1951 0.802 1952 0.595 1953 0.764 1954 0.848 1955 1.109 1956 0.9 1957 0.907 1958 1.002 1959 1.273 1960 0.957 1961 1.175 1962 0.678 1963 1.273 1964 1.126 1965 0.756 1966 1.034 1967 0.894 1968 1.03 1969 1.176 1970 0.836 1971 1.173 1972 1.008 1973 0.939 1974 0.617 1975 0.848 1976 0.762 1977 1.093 1978 0.935 1979 0.755