# europe_fran020 - Pic Aubas - 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/4585 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_fran020 - Pic Aubas - 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: Pic Aubas # Location: # Country: France # Northernmost_Latitude: 42.77 # Southernmost_Latitude: 42.77 # Easternmost_Longitude: 0.62 # Westernmost_Longitude: 0.62 # Elevation: 1800 m #-------------------- # Data_Collection # Collection_Name: europe_fran020B # Earliest_Year: 1797 # 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":"4.69220032085","T2":"15.7165069528","M1":"0.022296752545","M2":"0.458806479931"}} #-------------------- # 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 1797 0.937 1798 0.852 1799 0.785 1800 1.006 1801 1.319 1802 1.402 1803 1.334 1804 1.054 1805 1.388 1806 1.162 1807 1.163 1808 0.838 1809 0.864 1810 0.803 1811 0.901 1812 0.735 1813 0.644 1814 0.75 1815 0.623 1816 0.619 1817 0.783 1818 1.159 1819 1.094 1820 0.906 1821 0.94 1822 0.845 1823 1.006 1824 0.906 1825 1.174 1826 0.846 1827 0.883 1828 1.042 1829 1.073 1830 0.585 1831 1.166 1832 0.75 1833 0.73 1834 0.909 1835 1.137 1836 0.932 1837 0.692 1838 0.754 1839 0.883 1840 0.978 1841 0.945 1842 0.945 1843 0.856 1844 0.865 1845 1.036 1846 1.369 1847 0.853 1848 1.161 1849 0.869 1850 1.045 1851 0.948 1852 1.054 1853 1.022 1854 1.043 1855 0.996 1856 1.239 1857 1.2 1858 1.086 1859 1.311 1860 1.109 1861 1.333 1862 0.941 1863 1.116 1864 1.248 1865 1.132 1866 1.358 1867 1.106 1868 0.991 1869 1.028 1870 0.927 1871 0.881 1872 1.141 1873 1.203 1874 1.142 1875 0.846 1876 1.024 1877 1.059 1878 1.302 1879 1.135 1880 1.307 1881 1.29 1882 1.209 1883 1.067 1884 1.29 1885 1.109 1886 0.981 1887 1.081 1888 0.71 1889 0.874 1890 0.808 1891 0.737 1892 0.95 1893 1.016 1894 0.962 1895 1.016 1896 0.733 1897 0.846 1898 0.858 1899 0.672 1900 0.634 1901 0.749 1902 1.0 1903 1.211 1904 1.183 1905 1.216 1906 1.065 1907 1.055 1908 0.984 1909 0.984 1910 1.074 1911 1.033 1912 0.876 1913 1.248 1914 1.251 1915 1.215 1916 1.304 1917 1.162 1918 1.116 1919 1.029 1920 1.133 1921 1.092 1922 0.833 1923 1.15 1924 1.01 1925 1.062 1926 1.125 1927 1.079 1928 1.173 1929 1.089 1930 1.019 1931 0.864 1932 1.054 1933 0.955 1934 0.826 1935 0.953 1936 1.094 1937 1.143 1938 0.967 1939 0.909 1940 0.909 1941 0.99 1942 0.914 1943 1.007 1944 0.934 1945 0.854 1946 1.145 1947 0.955 1948 0.852 1949 0.784 1950 0.757 1951 0.807 1952 1.193 1953 1.165 1954 0.949 1955 1.111 1956 0.638 1957 0.774 1958 0.838 1959 0.925 1960 0.967 1961 1.071 1962 0.839 1963 0.7 1964 0.806 1965 0.709 1966 0.87 1967 0.929 1968 0.92 1969 0.825 1970 0.888 1971 0.902 1972 0.919 1973 1.203 1974 1.089 1975 0.932 1976 0.732 1977 0.66