# northamerica_canada_cana213 - Chenal des Quatre Fourches Recollection - 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/3936 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: northamerica_canada_cana213 - Chenal des Quatre Fourches Recollection - 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: Chenal des Quatre Fourches Recollection # Location: # Country: Canada # Northernmost_Latitude: 58.78 # Southernmost_Latitude: 58.78 # Easternmost_Longitude: -111.45 # Westernmost_Longitude: -111.45 # Elevation: 70 m #-------------------- # Data_Collection # Collection_Name: northamerica_canada_cana213B # Earliest_Year: 1771 # Most_Recent_Year: 2000 # 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":"4.68391780522","T2":"15.6105211418","M1":"0.0236969949696","M2":"0.496415922376"}} #-------------------- # Species # Species_Name: white spruce # Species_Code: PCGL #-------------------- # 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 1771 1.05 1772 0.763 1773 1.149 1774 0.742 1775 1.128 1776 0.951 1777 0.69 1778 0.75 1779 0.751 1780 1.06 1781 0.73 1782 0.853 1783 1.232 1784 1.372 1785 1.144 1786 1.214 1787 1.147 1788 0.966 1789 0.86 1790 0.584 1791 1.105 1792 0.764 1793 0.615 1794 0.711 1795 0.385 1796 0.634 1797 0.788 1798 0.773 1799 1.176 1800 1.261 1801 1.016 1802 0.678 1803 1.078 1804 1.423 1805 1.46 1806 1.271 1807 1.001 1808 0.777 1809 0.961 1810 1.331 1811 1.344 1812 1.476 1813 1.463 1814 0.994 1815 0.974 1816 0.629 1817 0.863 1818 1.045 1819 1.104 1820 1.04 1821 0.921 1822 0.866 1823 0.832 1824 0.7 1825 0.734 1826 0.572 1827 0.627 1828 0.592 1829 0.614 1830 0.544 1831 0.743 1832 0.815 1833 0.882 1834 0.727 1835 0.673 1836 1.034 1837 0.955 1838 1.057 1839 1.113 1840 0.997 1841 0.914 1842 1.179 1843 1.114 1844 0.93 1845 0.917 1846 0.411 1847 0.696 1848 0.792 1849 0.957 1850 0.986 1851 1.049 1852 1.137 1853 1.222 1854 0.979 1855 1.056 1856 1.025 1857 0.948 1858 1.082 1859 1.011 1860 0.933 1861 0.891 1862 0.619 1863 0.72 1864 0.919 1865 0.806 1866 1.001 1867 0.884 1868 0.842 1869 0.579 1870 0.796 1871 1.003 1872 0.841 1873 0.915 1874 1.026 1875 1.169 1876 0.899 1877 1.166 1878 0.958 1879 0.672 1880 0.859 1881 1.141 1882 1.336 1883 1.33 1884 1.139 1885 0.844 1886 0.851 1887 0.997 1888 1.018 1889 1.002 1890 1.051 1891 1.054 1892 0.887 1893 0.804 1894 0.715 1895 0.878 1896 0.788 1897 0.796 1898 0.865 1899 0.914 1900 0.955 1901 1.085 1902 1.053 1903 1.099 1904 1.151 1905 1.254 1906 1.148 1907 0.864 1908 0.909 1909 0.72 1910 0.837 1911 1.026 1912 0.763 1913 0.788 1914 0.936 1915 0.783 1916 0.664 1917 0.771 1918 0.945 1919 1.099 1920 0.848 1921 1.433 1922 1.521 1923 1.377 1924 0.981 1925 1.181 1926 1.089 1927 1.176 1928 0.599 1929 0.632 1930 1.012 1931 0.994 1932 1.346 1933 1.296 1934 1.557 1935 1.802 1936 1.607 1937 1.44 1938 0.971 1939 0.758 1940 0.728 1941 0.893 1942 0.638 1943 0.333 1944 0.446 1945 0.231 1946 0.423 1947 0.785 1948 0.842 1949 1.109 1950 0.608 1951 0.673 1952 0.46 1953 0.523 1954 0.687 1955 0.586 1956 1.011 1957 1.048 1958 1.435 1959 1.622 1960 1.561 1961 1.285 1962 1.344 1963 1.695 1964 1.539 1965 1.726 1966 1.533 1967 1.265 1968 1.429 1969 1.226 1970 0.829 1971 1.006 1972 0.956 1973 0.869 1974 1.273 1975 1.36 1976 1.176 1977 1.001 1978 0.89 1979 0.822 1980 0.423 1981 0.607 1982 0.331 1983 0.579 1984 0.587 1985 0.564 1986 0.717 1987 0.704 1988 0.808 1989 0.933 1990 0.731 1991 0.937 1992 0.881 1993 0.874 1994 0.936 1995 0.716 1996 1.003 1997 1.112 1998 0.999 1999 0.933 2000 0.867