# europe_fran035 - Lac Miroir - 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/3923 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_fran035 - Lac Miroir - 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: Lac Miroir # Location: # Country: France # Northernmost_Latitude: 44.63 # Southernmost_Latitude: 44.63 # Easternmost_Longitude: 6.78 # Westernmost_Longitude: 6.78 # Elevation: 2300 m #-------------------- # Data_Collection # Collection_Name: europe_fran035B # Earliest_Year: 1716 # Most_Recent_Year: 2000 # 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":"4.88109926936","T2":"17.0177973607","M1":"0.0225814817913","M2":"0.399114114799"}} #-------------------- # Species # Species_Name: Swiss stone pine # Species_Code: PICE #-------------------- # 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 1716 1.024 1717 1.038 1718 0.985 1719 1.147 1720 1.118 1721 1.059 1722 1.022 1723 0.992 1724 0.878 1725 1.225 1726 1.175 1727 1.416 1728 1.0 1729 1.158 1730 1.014 1731 1.016 1732 0.819 1733 0.994 1734 0.949 1735 0.996 1736 1.051 1737 1.199 1738 1.302 1739 1.316 1740 1.228 1741 1.051 1742 0.982 1743 0.976 1744 0.841 1745 0.894 1746 1.071 1747 1.177 1748 1.06 1749 1.113 1750 1.038 1751 0.996 1752 1.031 1753 1.076 1754 1.0 1755 0.969 1756 1.028 1757 1.064 1758 0.961 1759 0.957 1760 0.841 1761 0.833 1762 0.954 1763 0.941 1764 0.891 1765 0.847 1766 0.801 1767 0.918 1768 0.97 1769 0.751 1770 0.913 1771 0.841 1772 0.886 1773 0.958 1774 0.949 1775 0.945 1776 0.871 1777 0.871 1778 0.897 1779 0.951 1780 0.921 1781 0.976 1782 0.969 1783 1.099 1784 1.107 1785 1.205 1786 1.25 1787 1.219 1788 1.192 1789 1.268 1790 1.107 1791 1.086 1792 0.987 1793 1.093 1794 1.142 1795 1.048 1796 1.107 1797 1.155 1798 1.07 1799 1.01 1800 1.036 1801 1.137 1802 1.093 1803 0.994 1804 1.055 1805 0.977 1806 0.98 1807 1.027 1808 0.954 1809 0.941 1810 0.841 1811 0.99 1812 0.968 1813 0.829 1814 0.807 1815 0.867 1816 0.865 1817 0.822 1818 0.671 1819 0.705 1820 0.608 1821 0.565 1822 0.567 1823 0.474 1824 0.542 1825 0.503 1826 0.579 1827 0.589 1828 0.546 1829 0.593 1830 0.549 1831 0.594 1832 0.585 1833 0.631 1834 0.679 1835 0.566 1836 0.584 1837 0.622 1838 0.649 1839 0.742 1840 0.655 1841 0.763 1842 0.761 1843 0.867 1844 0.762 1845 0.818 1846 0.973 1847 0.939 1848 0.979 1849 0.96 1850 0.855 1851 0.98 1852 0.956 1853 1.036 1854 0.869 1855 0.844 1856 1.028 1857 1.059 1858 0.987 1859 0.803 1860 1.009 1861 0.942 1862 0.939 1863 0.778 1864 0.845 1865 0.953 1866 1.062 1867 0.961 1868 1.071 1869 1.144 1870 1.373 1871 1.327 1872 1.299 1873 1.35 1874 1.316 1875 1.374 1876 1.307 1877 1.538 1878 1.34 1879 1.411 1880 1.284 1881 1.188 1882 0.989 1883 1.148 1884 1.161 1885 1.048 1886 1.189 1887 0.883 1888 1.149 1889 1.039 1890 1.137 1891 1.023 1892 1.048 1893 1.081 1894 1.111 1895 0.962 1896 1.014 1897 0.982 1898 0.9 1899 0.933 1900 0.952 1901 0.961 1902 1.022 1903 0.915 1904 1.046 1905 0.936 1906 0.914 1907 0.892 1908 0.822 1909 0.755 1910 0.817 1911 0.887 1912 0.881 1913 0.979 1914 0.866 1915 0.819 1916 0.838 1917 0.714 1918 0.804 1919 0.708 1920 0.834 1921 0.731 1922 0.828 1923 0.916 1924 0.829 1925 0.86 1926 0.826 1927 0.973 1928 0.984 1929 0.932 1930 0.891 1931 0.957 1932 1.124 1933 0.799 1934 0.814 1935 1.016 1936 0.887 1937 0.878 1938 1.053 1939 1.1 1940 0.998 1941 0.804 1942 0.951 1943 0.901 1944 0.958 1945 1.003 1946 0.981 1947 1.056 1948 1.009 1949 1.057 1950 1.067 1951 1.167 1952 1.183 1953 1.198 1954 1.108 1955 1.068 1956 1.215 1957 1.027 1958 1.015 1959 1.092 1960 1.154 1961 1.213 1962 0.998 1963 1.186 1964 1.077 1965 1.119 1966 1.057 1967 1.188 1968 1.173 1969 1.055 1970 1.133 1971 1.11 1972 0.958 1973 1.11 1974 1.026 1975 1.087 1976 0.861 1977 1.099 1978 0.887 1979 1.032 1980 1.095 1981 0.872 1982 0.842 1983 0.955 1984 0.962 1985 0.89 1986 1.002 1987 1.205 1988 1.131 1989 1.062 1990 1.052 1991 1.202 1992 1.22 1993 1.042 1994 1.212 1995 1.506 1996 1.526 1997 1.375 1998 1.121 1999 1.163 2000 1.343