# europe_fran013 - L'Orgere B - 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/5108 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_fran013 - L'Orgere B - 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: L'Orgere B # Location: # Country: France # Northernmost_Latitude: 45.22 # Southernmost_Latitude: 45.22 # Easternmost_Longitude: 6.68 # Westernmost_Longitude: 6.68 # Elevation: 2100 m #-------------------- # Data_Collection # Collection_Name: europe_fran013B # Earliest_Year: 1798 # Most_Recent_Year: 1973 # 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":"5.2368544211","T2":"15.5873989548","M1":"0.0227975837064","M2":"0.439549205742"}} #-------------------- # Species # Species_Name: Norway spruce # Species_Code: PCAB #-------------------- # 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 1798 1.022 1799 1.102 1800 1.003 1801 0.952 1802 0.951 1803 0.946 1804 0.827 1805 0.703 1806 0.853 1807 1.017 1808 1.049 1809 1.049 1810 0.921 1811 1.183 1812 1.06 1813 0.886 1814 1.057 1815 0.997 1816 0.937 1817 1.12 1818 0.979 1819 0.974 1820 1.075 1821 0.971 1822 0.982 1823 0.976 1824 1.046 1825 1.156 1826 1.026 1827 1.048 1828 1.032 1829 0.978 1830 0.9 1831 1.135 1832 0.982 1833 1.076 1834 1.049 1835 0.922 1836 0.872 1837 0.927 1838 0.703 1839 0.694 1840 0.791 1841 0.79 1842 1.089 1843 0.895 1844 1.116 1845 1.09 1846 1.523 1847 1.373 1848 1.326 1849 0.93 1850 0.919 1851 1.026 1852 0.956 1853 1.068 1854 0.953 1855 1.026 1856 1.097 1857 1.089 1858 0.869 1859 1.027 1860 0.772 1861 0.97 1862 0.62 1863 1.045 1864 0.857 1865 0.844 1866 0.905 1867 1.055 1868 1.091 1869 1.269 1870 0.671 1871 1.014 1872 0.926 1873 0.849 1874 0.964 1875 1.007 1876 1.188 1877 1.054 1878 1.07 1879 1.183 1880 0.883 1881 1.185 1882 1.212 1883 1.076 1884 1.191 1885 0.957 1886 0.769 1887 0.765 1888 0.469 1889 0.916 1890 0.943 1891 0.819 1892 1.139 1893 1.306 1894 0.852 1895 1.001 1896 0.87 1897 1.048 1898 0.932 1899 0.922 1900 0.95 1901 1.188 1902 0.915 1903 0.886 1904 0.928 1905 0.74 1906 0.582 1907 0.574 1908 0.901 1909 0.559 1910 0.849 1911 0.931 1912 0.729 1913 0.756 1914 0.98 1915 1.133 1916 1.004 1917 1.129 1918 0.875 1919 0.97 1920 1.065 1921 0.884 1922 0.804 1923 1.017 1924 0.867 1925 0.964 1926 0.947 1927 1.071 1928 0.896 1929 0.814 1930 0.806 1931 0.957 1932 1.098 1933 0.934 1934 0.918 1935 1.032 1936 1.082 1937 1.159 1938 1.062 1939 1.071 1940 1.061 1941 1.071 1942 0.977 1943 1.03 1944 0.823 1945 0.764 1946 1.034 1947 1.095 1948 0.669 1949 1.16 1950 0.905 1951 0.987 1952 1.023 1953 0.795 1954 0.95 1955 1.181 1956 0.874 1957 0.985 1958 1.198 1959 1.19 1960 1.235 1961 1.063 1962 0.921 1963 0.899 1964 1.329 1965 0.981 1966 1.282 1967 1.205 1968 0.914 1969 1.3 1970 1.245 1971 1.215 1972 0.98 1973 1.172