# europe_fran024 - Formigueres - 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/4413 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_fran024 - Formigueres - 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: Formigueres # Location: # Country: France # Northernmost_Latitude: 42.6 # Southernmost_Latitude: 42.6 # Easternmost_Longitude: 2.07 # Westernmost_Longitude: 2.07 # Elevation: 1700 m #-------------------- # Data_Collection # Collection_Name: europe_fran024B # Earliest_Year: 1795 # Most_Recent_Year: 1977 # 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":"4.83568996461","T2":"19.5893576981","M1":"0.021829362033","M2":"0.275054126046"}} #-------------------- # 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 1795 1.508 1796 1.299 1797 1.33 1798 1.842 1799 1.686 1800 1.33 1801 1.335 1802 1.351 1803 1.034 1804 0.954 1805 1.382 1806 1.072 1807 1.074 1808 0.723 1809 1.11 1810 1.017 1811 1.005 1812 1.001 1813 0.989 1814 1.293 1815 1.127 1816 1.088 1817 1.2 1818 1.52 1819 1.357 1820 1.646 1821 1.782 1822 1.453 1823 1.352 1824 1.377 1825 1.559 1826 1.031 1827 1.302 1828 1.452 1829 1.361 1830 0.751 1831 1.477 1832 1.173 1833 1.202 1834 1.097 1835 1.126 1836 0.95 1837 0.97 1838 0.992 1839 0.902 1840 0.865 1841 0.944 1842 0.974 1843 1.31 1844 1.257 1845 1.165 1846 1.456 1847 1.076 1848 1.154 1849 1.044 1850 1.098 1851 1.082 1852 0.939 1853 0.801 1854 0.857 1855 0.774 1856 0.959 1857 0.743 1858 0.687 1859 0.973 1860 0.78 1861 1.028 1862 0.751 1863 0.785 1864 0.947 1865 0.633 1866 0.722 1867 0.678 1868 0.906 1869 0.909 1870 0.734 1871 0.719 1872 0.709 1873 0.691 1874 0.577 1875 0.521 1876 0.753 1877 0.753 1878 0.612 1879 0.495 1880 0.667 1881 0.702 1882 0.476 1883 0.662 1884 0.77 1885 0.659 1886 0.519 1887 0.478 1888 0.499 1889 0.711 1890 0.603 1891 0.661 1892 0.569 1893 0.444 1894 0.573 1895 0.485 1896 0.427 1897 0.557 1898 0.614 1899 0.485 1900 0.486 1901 0.56 1902 0.664 1903 0.752 1904 0.667 1905 0.705 1906 0.721 1907 0.694 1908 0.649 1909 0.682 1910 0.896 1911 1.018 1912 0.962 1913 1.159 1914 1.003 1915 0.985 1916 0.946 1917 0.975 1918 0.878 1919 0.842 1920 0.897 1921 0.936 1922 0.742 1923 0.819 1924 0.681 1925 0.767 1926 0.754 1927 0.728 1928 0.726 1929 0.618 1930 0.69 1931 0.709 1932 0.878 1933 0.677 1934 0.776 1935 0.992 1936 1.187 1937 1.006 1938 1.035 1939 1.188 1940 1.253 1941 1.119 1942 1.049 1943 1.16 1944 1.208 1945 1.087 1946 1.044 1947 1.134 1948 1.338 1949 1.557 1950 1.709 1951 1.55 1952 1.63 1953 1.569 1954 1.377 1955 1.549 1956 1.117 1957 1.163 1958 1.407 1959 1.511 1960 1.505 1961 1.22 1962 1.093 1963 0.865 1964 1.301 1965 1.162 1966 1.34 1967 1.261 1968 1.168 1969 0.979 1970 1.039 1971 1.083 1972 1.086 1973 1.198 1974 1.366 1975 1.421 1976 1.376 1977 1.011