# europe_fran039 - Mont Risoux - 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/3922 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_fran039 - Mont Risoux - 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: Mont Risoux # Location: # Country: France # Northernmost_Latitude: 46.63 # Southernmost_Latitude: 46.63 # Easternmost_Longitude: 6.08 # Westernmost_Longitude: 6.08 # Elevation: 1100 m #-------------------- # Data_Collection # Collection_Name: europe_fran039B # Earliest_Year: 1762 # Most_Recent_Year: 1999 # 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":"6.39002340992","T2":"14.6198125942","M1":"0.0227813699508","M2":"0.575427599365"}} #-------------------- # Species # Species_Name: Norway spruce # Species_Code: PCAB #-------------------- # 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 1762 0.844 1763 0.87 1764 1.05 1765 0.935 1766 0.884 1767 0.858 1768 1.086 1769 1.103 1770 0.996 1771 1.037 1772 0.948 1773 0.985 1774 1.076 1775 1.2 1776 1.198 1777 1.101 1778 1.158 1779 0.929 1780 0.651 1781 0.88 1782 0.605 1783 0.843 1784 0.988 1785 1.053 1786 1.108 1787 0.892 1788 1.008 1789 0.866 1790 0.819 1791 0.974 1792 1.059 1793 0.734 1794 0.971 1795 1.025 1796 0.763 1797 0.793 1798 1.047 1799 0.944 1800 0.964 1801 0.915 1802 0.966 1803 0.873 1804 0.84 1805 1.082 1806 1.124 1807 1.063 1808 1.012 1809 1.222 1810 1.113 1811 1.21 1812 1.079 1813 1.068 1814 1.056 1815 1.047 1816 0.752 1817 0.949 1818 0.889 1819 0.858 1820 0.93 1821 0.89 1822 0.971 1823 0.988 1824 0.91 1825 1.037 1826 0.919 1827 0.751 1828 0.968 1829 1.233 1830 1.012 1831 1.209 1832 0.838 1833 0.874 1834 1.085 1835 0.779 1836 0.647 1837 0.493 1838 0.713 1839 0.609 1840 0.725 1841 1.001 1842 1.116 1843 0.988 1844 1.361 1845 1.265 1846 1.505 1847 1.348 1848 1.378 1849 1.187 1850 1.346 1851 1.253 1852 1.215 1853 1.176 1854 1.185 1855 1.174 1856 0.991 1857 0.978 1858 0.767 1859 0.791 1860 0.573 1861 0.689 1862 0.598 1863 0.744 1864 0.744 1865 0.656 1866 0.843 1867 1.007 1868 0.944 1869 0.993 1870 0.611 1871 0.849 1872 0.952 1873 1.106 1874 0.98 1875 1.276 1876 0.825 1877 1.06 1878 1.13 1879 1.017 1880 1.096 1881 1.216 1882 1.107 1883 1.058 1884 0.992 1885 1.019 1886 0.886 1887 0.829 1888 0.884 1889 0.943 1890 0.966 1891 0.927 1892 1.035 1893 1.0 1894 0.929 1895 1.074 1896 0.738 1897 0.927 1898 0.87 1899 0.822 1900 0.75 1901 0.893 1902 0.771 1903 0.932 1904 1.025 1905 0.785 1906 0.669 1907 0.639 1908 1.032 1909 0.845 1910 1.076 1911 0.985 1912 0.758 1913 1.007 1914 0.928 1915 1.227 1916 1.336 1917 1.474 1918 1.136 1919 1.167 1920 0.852 1921 0.949 1922 0.66 1923 0.787 1924 0.674 1925 0.861 1926 0.868 1927 1.096 1928 1.022 1929 0.87 1930 0.854 1931 1.0 1932 1.097 1933 0.911 1934 1.084 1935 1.115 1936 0.871 1937 0.987 1938 0.902 1939 1.171 1940 1.186 1941 0.996 1942 1.086 1943 1.138 1944 1.03 1945 0.857 1946 0.705 1947 1.026 1948 0.605 1949 0.538 1950 0.714 1951 1.068 1952 0.944 1953 0.768 1954 0.899 1955 1.373 1956 0.913 1957 0.849 1958 0.984 1959 0.979 1960 1.032 1961 0.924 1962 0.661 1963 0.938 1964 1.012 1965 0.944 1966 1.214 1967 1.16 1968 1.123 1969 1.566 1970 1.461 1971 1.388 1972 1.434 1973 1.339 1974 1.297 1975 1.299 1976 0.89 1977 1.165 1978 1.241 1979 1.009 1980 0.809 1981 1.097 1982 1.302 1983 1.282 1984 1.02 1985 1.211 1986 0.936 1987 0.992 1988 1.169 1989 1.182 1990 1.267 1991 1.016 1992 0.938 1993 1.092 1994 1.093 1995 0.975 1996 1.074 1997 1.118 1998 1.06 1999 1.403