# europe_fran001 - Chambord - 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/4211 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_fran001 - Chambord - 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: Chambord # Location: # Country: France # Northernmost_Latitude: 47.57 # Southernmost_Latitude: 47.57 # Easternmost_Longitude: 1.5 # Westernmost_Longitude: 1.5 # Elevation: 100 m #-------------------- # Data_Collection # Collection_Name: europe_fran001B # Earliest_Year: 1756 # Most_Recent_Year: 1979 # 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":"4.42718082323","T2":"15.6354790248","M1":"0.0232762509507","M2":"0.533841440256"}} #-------------------- # Species # Species_Name: English oak # Species_Code: QURO #-------------------- # 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 1756 0.831 1757 0.958 1758 0.96 1759 0.876 1760 0.669 1761 0.619 1762 0.707 1763 1.297 1764 0.98 1765 1.171 1766 1.424 1767 0.85 1768 1.527 1769 1.599 1770 1.906 1771 1.403 1772 1.262 1773 1.388 1774 1.52 1775 1.03 1776 1.112 1777 1.26 1778 0.877 1779 0.645 1780 0.888 1781 1.064 1782 0.949 1783 1.065 1784 0.815 1785 0.593 1786 0.801 1787 0.813 1788 1.043 1789 0.992 1790 0.695 1791 0.952 1792 1.078 1793 1.003 1794 0.957 1795 1.308 1796 1.07 1797 1.114 1798 1.061 1799 1.019 1800 0.899 1801 0.864 1802 0.737 1803 0.588 1804 0.551 1805 0.959 1806 0.961 1807 0.737 1808 0.669 1809 0.8 1810 0.772 1811 0.88 1812 1.011 1813 1.013 1814 1.033 1815 0.735 1816 0.994 1817 1.009 1818 0.859 1819 0.758 1820 1.095 1821 1.274 1822 0.856 1823 1.184 1824 1.137 1825 0.907 1826 0.855 1827 0.841 1828 1.086 1829 1.373 1830 1.379 1831 1.412 1832 0.902 1833 0.79 1834 0.593 1835 0.535 1836 0.943 1837 1.106 1838 1.158 1839 1.199 1840 1.076 1841 1.293 1842 1.113 1843 1.388 1844 1.103 1845 1.588 1846 1.094 1847 0.951 1848 1.031 1849 0.891 1850 1.098 1851 0.93 1852 1.051 1853 1.45 1854 0.989 1855 1.308 1856 1.289 1857 0.753 1858 0.667 1859 1.069 1860 1.35 1861 1.203 1862 1.035 1863 0.915 1864 1.056 1865 0.951 1866 1.05 1867 1.497 1868 1.123 1869 1.185 1870 0.541 1871 0.769 1872 0.822 1873 1.056 1874 0.523 1875 0.598 1876 0.896 1877 0.983 1878 1.226 1879 0.988 1880 0.604 1881 0.866 1882 0.749 1883 1.176 1884 0.854 1885 0.922 1886 1.078 1887 0.832 1888 1.035 1889 0.906 1890 0.891 1891 0.824 1892 0.7 1893 0.7 1894 0.932 1895 0.87 1896 0.598 1897 1.273 1898 0.982 1899 0.718 1900 0.676 1901 0.722 1902 0.814 1903 0.777 1904 0.915 1905 0.731 1906 0.687 1907 0.873 1908 0.917 1909 0.857 1910 1.26 1911 0.94 1912 1.091 1913 1.158 1914 1.028 1915 0.87 1916 1.137 1917 1.195 1918 0.857 1919 0.949 1920 1.002 1921 0.496 1922 0.756 1923 1.01 1924 1.065 1925 1.171 1926 1.263 1927 1.343 1928 1.179 1929 0.985 1930 1.215 1931 1.371 1932 1.239 1933 0.882 1934 0.724 1935 1.041 1936 1.014 1937 1.055 1938 0.64 1939 1.074 1940 0.974 1941 0.922 1942 0.785 1943 0.751 1944 0.599 1945 0.825 1946 0.88 1947 1.171 1948 1.12 1949 0.644 1950 1.028 1951 1.344 1952 0.959 1953 0.99 1954 0.955 1955 0.795 1956 0.724 1957 0.9 1958 1.512 1959 0.943 1960 0.945 1961 1.021 1962 1.063 1963 1.157 1964 1.012 1965 1.089 1966 1.38 1967 1.395 1968 1.453 1969 1.265 1970 1.242 1971 1.248 1972 0.744 1973 0.957 1974 0.863 1975 0.953 1976 0.773 1977 0.999 1978 1.148 1979 1.069