# europe_fran027 - Col de Sorba Mount Renoso - 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/4389 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_fran027 - Col de Sorba Mount Renoso - 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: Col de Sorba Mount Renoso # Location: # Country: France # Northernmost_Latitude: 42.07 # Southernmost_Latitude: 42.07 # Easternmost_Longitude: 9.2 # Westernmost_Longitude: 9.2 # Elevation: 1400 m #-------------------- # Data_Collection # Collection_Name: europe_fran027B # Earliest_Year: 1700 # Most_Recent_Year: 1980 # 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":"4.3093298135","T2":"14.7406780389","M1":"0.0227711433729","M2":"0.55296293838"}} #-------------------- # Species # Species_Name: Austrian pine # Species_Code: PINI #-------------------- # 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 1700 1.167 1701 1.248 1702 1.045 1703 1.217 1704 1.133 1705 1.171 1706 1.069 1707 0.688 1708 0.904 1709 0.742 1710 0.753 1711 0.903 1712 0.998 1713 0.883 1714 0.971 1715 0.791 1716 0.601 1717 1.062 1718 1.024 1719 0.661 1720 0.57 1721 0.737 1722 0.761 1723 0.761 1724 0.681 1725 0.647 1726 0.792 1727 0.938 1728 1.007 1729 0.561 1730 0.439 1731 0.334 1732 0.546 1733 0.703 1734 0.977 1735 0.902 1736 0.979 1737 1.133 1738 1.006 1739 0.62 1740 0.587 1741 0.72 1742 0.528 1743 0.704 1744 0.723 1745 0.784 1746 0.717 1747 0.742 1748 0.908 1749 0.897 1750 0.801 1751 0.555 1752 0.736 1753 0.723 1754 0.79 1755 0.907 1756 0.657 1757 0.9 1758 1.078 1759 1.188 1760 1.163 1761 1.611 1762 1.597 1763 1.247 1764 1.045 1765 1.38 1766 1.238 1767 0.716 1768 0.724 1769 0.863 1770 0.778 1771 0.73 1772 0.646 1773 0.576 1774 0.748 1775 0.88 1776 0.778 1777 0.909 1778 0.884 1779 1.12 1780 1.422 1781 1.543 1782 0.797 1783 1.054 1784 1.162 1785 0.786 1786 0.664 1787 1.013 1788 0.971 1789 1.153 1790 1.27 1791 1.271 1792 0.885 1793 0.932 1794 1.056 1795 1.225 1796 1.169 1797 1.134 1798 1.134 1799 1.335 1800 1.352 1801 1.549 1802 1.046 1803 0.976 1804 0.845 1805 0.78 1806 0.848 1807 1.073 1808 1.189 1809 1.174 1810 1.4 1811 1.656 1812 1.324 1813 1.347 1814 1.572 1815 1.737 1816 1.138 1817 1.2 1818 1.543 1819 1.526 1820 1.218 1821 0.944 1822 0.993 1823 0.615 1824 0.556 1825 1.261 1826 1.7 1827 1.217 1828 1.223 1829 1.072 1830 1.346 1831 1.112 1832 0.99 1833 0.987 1834 1.5 1835 0.853 1836 0.779 1837 0.781 1838 0.76 1839 0.801 1840 0.791 1841 1.148 1842 0.984 1843 1.403 1844 1.35 1845 1.097 1846 1.29 1847 1.035 1848 0.953 1849 0.845 1850 0.998 1851 1.107 1852 1.226 1853 1.083 1854 1.119 1855 0.847 1856 0.76 1857 0.461 1858 0.648 1859 0.921 1860 0.757 1861 0.705 1862 0.776 1863 0.97 1864 0.756 1865 0.741 1866 0.755 1867 0.92 1868 0.863 1869 0.838 1870 0.904 1871 0.982 1872 0.922 1873 0.72 1874 0.672 1875 0.867 1876 0.847 1877 0.797 1878 0.73 1879 0.516 1880 0.63 1881 0.784 1882 0.881 1883 1.027 1884 1.337 1885 1.297 1886 1.448 1887 0.941 1888 1.236 1889 0.936 1890 1.123 1891 1.465 1892 1.388 1893 1.285 1894 1.065 1895 1.05 1896 1.113 1897 1.304 1898 1.397 1899 1.275 1900 1.233 1901 1.346 1902 1.677 1903 1.41 1904 1.119 1905 1.054 1906 0.922 1907 0.923 1908 1.071 1909 0.868 1910 0.869 1911 1.253 1912 1.532 1913 1.459 1914 1.283 1915 1.226 1916 1.093 1917 1.05 1918 0.815 1919 0.608 1920 0.795 1921 0.713 1922 0.645 1923 0.967 1924 1.043 1925 0.976 1926 1.198 1927 0.933 1928 0.613 1929 0.668 1930 0.803 1931 0.744 1932 0.987 1933 0.969 1934 0.987 1935 1.024 1936 1.086 1937 1.145 1938 0.902 1939 0.907 1940 1.085 1941 1.053 1942 1.06 1943 0.789 1944 0.74 1945 0.713 1946 0.582 1947 0.404 1948 0.815 1949 1.06 1950 0.774 1951 0.821 1952 0.941 1953 0.959 1954 0.701 1955 0.688 1956 0.873 1957 0.736 1958 0.805 1959 0.892 1960 0.886 1961 0.944 1962 0.708 1963 0.614 1964 0.694 1965 0.703 1966 0.87 1967 0.85 1968 0.91 1969 1.142 1970 0.838 1971 0.933 1972 0.887 1973 1.117 1974 0.922 1975 0.972 1976 1.027 1977 1.148 1978 1.081 1979 0.969 1980 0.852