# europe_fran021 - Pic d'Anie - 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/4586 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_fran021 - Pic d'Anie - 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: Pic d'Anie # Location: # Country: France # Northernmost_Latitude: 42.97 # Southernmost_Latitude: 42.97 # Easternmost_Longitude: 0.73 # Westernmost_Longitude: 0.73 # Elevation: 1750 m #-------------------- # Data_Collection # Collection_Name: europe_fran021B # Earliest_Year: 1711 # Most_Recent_Year: 1977 # 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":"5.1729010579","T2":"17.7683608094","M1":"0.0229661550445","M2":"0.368278224139"}} #-------------------- # Species # Species_Name: krummholz pine # Species_Code: PIMU #-------------------- # 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 1711 1.122 1712 0.831 1713 0.928 1714 0.812 1715 0.936 1716 0.772 1717 0.667 1718 0.613 1719 0.81 1720 0.892 1721 1.244 1722 1.231 1723 1.22 1724 1.189 1725 1.134 1726 1.283 1727 1.285 1728 1.23 1729 0.975 1730 1.422 1731 1.102 1732 1.119 1733 0.949 1734 1.112 1735 0.802 1736 0.943 1737 0.927 1738 0.846 1739 0.807 1740 1.025 1741 0.806 1742 1.17 1743 0.939 1744 0.944 1745 0.915 1746 1.046 1747 1.262 1748 1.152 1749 1.009 1750 0.909 1751 0.955 1752 0.834 1753 0.84 1754 1.054 1755 0.982 1756 1.025 1757 1.104 1758 0.91 1759 0.869 1760 0.733 1761 0.61 1762 0.842 1763 0.937 1764 0.974 1765 0.755 1766 0.941 1767 1.04 1768 1.095 1769 1.097 1770 0.861 1771 0.865 1772 1.08 1773 0.987 1774 1.118 1775 1.393 1776 1.121 1777 1.242 1778 1.264 1779 1.078 1780 1.17 1781 1.305 1782 0.998 1783 1.078 1784 1.512 1785 1.195 1786 1.339 1787 0.945 1788 1.035 1789 1.107 1790 0.913 1791 1.172 1792 1.038 1793 0.754 1794 0.947 1795 0.918 1796 1.165 1797 1.054 1798 1.306 1799 1.294 1800 1.207 1801 1.055 1802 1.04 1803 0.512 1804 0.766 1805 0.87 1806 0.862 1807 1.131 1808 0.852 1809 0.888 1810 0.798 1811 0.95 1812 0.908 1813 0.811 1814 0.825 1815 0.731 1816 0.592 1817 0.747 1818 0.995 1819 1.033 1820 0.938 1821 0.801 1822 0.94 1823 1.103 1824 0.71 1825 1.119 1826 0.93 1827 1.061 1828 1.226 1829 1.097 1830 0.751 1831 1.05 1832 0.582 1833 0.725 1834 0.931 1835 0.782 1836 0.494 1837 1.118 1838 0.975 1839 0.807 1840 0.982 1841 1.057 1842 1.077 1843 0.962 1844 0.798 1845 0.962 1846 1.304 1847 0.87 1848 0.966 1849 0.683 1850 0.815 1851 0.736 1852 0.898 1853 0.915 1854 0.949 1855 0.863 1856 0.802 1857 0.926 1858 0.829 1859 0.974 1860 0.939 1861 1.018 1862 1.213 1863 1.351 1864 1.644 1865 1.512 1866 1.429 1867 1.653 1868 1.306 1869 1.149 1870 1.007 1871 1.21 1872 1.034 1873 1.209 1874 1.259 1875 1.264 1876 0.829 1877 1.042 1878 1.439 1879 1.05 1880 0.933 1881 1.157 1882 1.22 1883 0.99 1884 0.952 1885 0.858 1886 0.919 1887 0.953 1888 0.877 1889 1.156 1890 0.762 1891 0.814 1892 1.02 1893 1.08 1894 0.929 1895 0.969 1896 0.931 1897 0.821 1898 0.92 1899 0.784 1900 0.917 1901 0.927 1902 0.871 1903 1.009 1904 1.206 1905 1.13 1906 0.872 1907 1.252 1908 1.305 1909 0.94 1910 0.894 1911 1.111 1912 0.878 1913 1.13 1914 1.128 1915 0.909 1916 0.826 1917 1.037 1918 0.866 1919 0.84 1920 0.859 1921 0.864 1922 0.933 1923 0.936 1924 1.046 1925 1.329 1926 0.98 1927 1.261 1928 1.169 1929 1.216 1930 1.232 1931 1.184 1932 1.135 1933 0.826 1934 0.815 1935 0.88 1936 0.901 1937 0.842 1938 0.646 1939 0.726 1940 0.641 1941 0.589 1942 0.663 1943 0.785 1944 0.797 1945 0.575 1946 0.859 1947 0.654 1948 0.824 1949 1.003 1950 0.614 1951 0.796 1952 1.135 1953 0.869 1954 0.774 1955 0.977 1956 0.625 1957 0.503 1958 1.044 1959 0.989 1960 0.893 1961 0.861 1962 0.81 1963 0.79 1964 0.986 1965 0.882 1966 1.168 1967 1.012 1968 1.204 1969 1.496 1970 1.655 1971 1.686 1972 1.181 1973 1.45 1974 1.307 1975 0.976 1976 1.285 1977 0.972