# europe_fran7 - Mt. Ventoux - 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/4754 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_fran7 - Mt. Ventoux - 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: Mt. Ventoux # Location: # Country: France # Northernmost_Latitude: 44.17 # Southernmost_Latitude: 44.17 # Easternmost_Longitude: 5.25 # Westernmost_Longitude: 5.25 # Elevation: 1775 m #-------------------- # Data_Collection # Collection_Name: europe_fran7B # Earliest_Year: 1720 # Most_Recent_Year: 1975 # 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":"4.76964574057","T2":"14.7496946677","M1":"0.022741682712","M2":"0.611940676491"}} #-------------------- # Species # Species_Name: silver fir # Species_Code: ABAL #-------------------- # 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 1720 0.721 1721 1.288 1722 0.933 1723 1.036 1724 0.994 1725 0.992 1726 1.306 1727 0.955 1728 1.148 1729 0.729 1730 0.952 1731 0.625 1732 1.701 1733 1.575 1734 1.419 1735 1.313 1736 1.564 1737 1.247 1738 1.376 1739 0.872 1740 1.271 1741 1.196 1742 0.917 1743 1.128 1744 1.104 1745 0.966 1746 0.952 1747 1.21 1748 0.963 1749 1.085 1750 1.11 1751 0.719 1752 0.797 1753 0.866 1754 0.737 1755 0.839 1756 0.98 1757 1.114 1758 1.104 1759 1.273 1760 1.036 1761 1.088 1762 1.059 1763 1.178 1764 0.784 1765 0.866 1766 0.928 1767 0.672 1768 0.696 1769 0.412 1770 0.788 1771 0.666 1772 0.606 1773 0.704 1774 0.709 1775 0.759 1776 0.862 1777 0.876 1778 0.922 1779 0.871 1780 0.373 1781 0.603 1782 0.656 1783 0.656 1784 0.571 1785 0.582 1786 0.686 1787 0.821 1788 0.754 1789 0.929 1790 0.805 1791 0.841 1792 0.672 1793 0.64 1794 0.865 1795 0.827 1796 0.641 1797 0.643 1798 0.811 1799 0.906 1800 1.146 1801 1.063 1802 1.125 1803 0.483 1804 0.485 1805 0.84 1806 0.817 1807 1.012 1808 0.735 1809 1.348 1810 1.391 1811 1.376 1812 1.089 1813 1.048 1814 1.374 1815 1.19 1816 1.112 1817 1.399 1818 1.022 1819 1.077 1820 0.785 1821 0.913 1822 0.639 1823 0.565 1824 0.586 1825 0.823 1826 0.973 1827 1.059 1828 0.973 1829 1.277 1830 1.371 1831 0.929 1832 0.901 1833 0.64 1834 0.903 1835 0.922 1836 0.837 1837 0.605 1838 0.809 1839 0.729 1840 0.61 1841 0.658 1842 0.91 1843 0.937 1844 0.937 1845 0.975 1846 1.352 1847 0.769 1848 1.074 1849 0.883 1850 0.997 1851 1.051 1852 1.191 1853 1.011 1854 1.411 1855 1.017 1856 0.99 1857 1.003 1858 1.093 1859 1.253 1860 0.977 1861 1.325 1862 0.809 1863 0.884 1864 1.029 1865 0.99 1866 0.987 1867 1.296 1868 0.767 1869 0.89 1870 0.728 1871 1.071 1872 1.022 1873 0.974 1874 0.993 1875 1.334 1876 1.255 1877 0.965 1878 1.098 1879 1.012 1880 1.261 1881 0.975 1882 0.915 1883 1.323 1884 1.668 1885 1.3 1886 1.177 1887 1.048 1888 0.939 1889 1.37 1890 1.05 1891 0.972 1892 1.025 1893 1.062 1894 0.836 1895 1.068 1896 1.027 1897 1.076 1898 0.919 1899 0.937 1900 0.821 1901 1.151 1902 1.324 1903 1.353 1904 1.241 1905 1.039 1906 0.934 1907 0.827 1908 1.114 1909 1.147 1910 1.315 1911 1.177 1912 0.943 1913 0.976 1914 1.51 1915 1.482 1916 1.18 1917 1.303 1918 0.832 1919 0.742 1920 0.675 1921 0.896 1922 0.61 1923 0.544 1924 0.44 1925 0.675 1926 0.656 1927 0.806 1928 0.677 1929 0.617 1930 0.577 1931 0.487 1932 1.233 1933 1.114 1934 1.05 1935 0.832 1936 1.105 1937 0.999 1938 0.904 1939 1.209 1940 1.479 1941 1.388 1942 0.838 1943 0.588 1944 1.119 1945 1.031 1946 0.903 1947 0.854 1948 0.877 1949 0.858 1950 0.632 1951 0.522 1952 0.695 1953 1.03 1954 0.845 1955 1.303 1956 0.764 1957 0.972 1958 1.047 1959 1.162 1960 1.203 1961 1.239 1962 0.656 1963 0.915 1964 1.174 1965 0.897 1966 1.119 1967 0.889 1968 0.859 1969 1.046 1970 0.808 1971 0.811 1972 0.74 1973 0.969 1974 0.564 1975 0.7