# europe_spai013 - Navafria I - 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/5399 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_spai013 - Navafria I - 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: Navafria I # Location: # Country: Spain # Northernmost_Latitude: 40.02 # Southernmost_Latitude: 40.02 # Easternmost_Longitude: -0.12 # Westernmost_Longitude: -0.12 # Elevation: 1900 m #-------------------- # Data_Collection # Collection_Name: europe_spai013B # Earliest_Year: 1764 # Most_Recent_Year: 1992 # 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":"5.69054156566","T2":"17.6586326456","M1":"0.0224021498546","M2":"0.418984912349"}} #-------------------- # Species # Species_Name: Scots pine # Species_Code: PISY #-------------------- # 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 1764 1.241 1765 1.17 1766 0.899 1767 0.965 1768 0.978 1769 0.7 1770 0.484 1771 0.428 1772 0.559 1773 0.841 1774 0.838 1775 0.785 1776 0.9 1777 0.917 1778 0.946 1779 1.187 1780 1.423 1781 1.376 1782 1.072 1783 0.923 1784 0.697 1785 0.737 1786 1.178 1787 1.253 1788 1.552 1789 1.354 1790 1.179 1791 1.28 1792 1.039 1793 1.427 1794 1.286 1795 1.056 1796 1.006 1797 0.98 1798 1.315 1799 1.036 1800 0.579 1801 0.415 1802 0.459 1803 0.524 1804 0.54 1805 1.068 1806 0.789 1807 0.938 1808 0.773 1809 0.674 1810 0.83 1811 1.038 1812 1.107 1813 1.26 1814 1.108 1815 0.968 1816 0.849 1817 0.944 1818 0.929 1819 1.079 1820 0.922 1821 1.207 1822 1.274 1823 1.144 1824 1.02 1825 1.098 1826 0.875 1827 0.79 1828 0.943 1829 0.87 1830 1.029 1831 0.816 1832 0.739 1833 0.835 1834 1.135 1835 0.879 1836 0.836 1837 1.088 1838 0.972 1839 1.015 1840 1.037 1841 1.205 1842 0.967 1843 1.027 1844 0.894 1845 0.895 1846 1.132 1847 1.008 1848 0.776 1849 0.899 1850 1.011 1851 0.987 1852 0.961 1853 0.926 1854 1.083 1855 0.853 1856 0.9 1857 0.82 1858 1.093 1859 1.367 1860 1.115 1861 1.129 1862 0.898 1863 0.928 1864 1.219 1865 0.987 1866 1.178 1867 1.34 1868 1.257 1869 1.392 1870 1.204 1871 1.265 1872 1.122 1873 1.159 1874 1.057 1875 0.956 1876 0.877 1877 1.0 1878 1.215 1879 0.783 1880 0.877 1881 1.042 1882 1.087 1883 0.972 1884 1.076 1885 1.068 1886 0.968 1887 1.019 1888 1.127 1889 1.153 1890 1.02 1891 0.904 1892 1.044 1893 1.183 1894 0.751 1895 0.721 1896 0.706 1897 0.968 1898 0.999 1899 1.046 1900 0.949 1901 0.81 1902 0.991 1903 1.278 1904 1.407 1905 1.382 1906 1.178 1907 0.965 1908 0.759 1909 0.78 1910 0.895 1911 0.856 1912 1.012 1913 1.055 1914 1.19 1915 1.067 1916 1.078 1917 0.95 1918 1.036 1919 0.972 1920 0.793 1921 0.656 1922 0.882 1923 1.175 1924 0.792 1925 0.854 1926 1.106 1927 1.151 1928 0.945 1929 1.028 1930 0.929 1931 1.153 1932 1.182 1933 1.41 1934 1.024 1935 0.736 1936 0.949 1937 1.213 1938 0.89 1939 0.853 1940 0.869 1941 0.468 1942 0.55 1943 0.909 1944 1.35 1945 1.43 1946 1.031 1947 1.39 1948 1.185 1949 1.052 1950 1.08 1951 1.212 1952 1.105 1953 1.013 1954 0.671 1955 0.809 1956 0.836 1957 0.919 1958 1.229 1959 1.264 1960 0.955 1961 0.884 1962 0.648 1963 0.552 1964 0.918 1965 0.753 1966 0.715 1967 0.713 1968 0.75 1969 0.772 1970 0.885 1971 0.803 1972 0.698 1973 0.995 1974 0.868 1975 0.778 1976 1.123 1977 0.843 1978 0.869 1979 0.837 1980 1.031 1981 0.991 1982 1.055 1983 1.0 1984 0.864 1985 1.029 1986 0.736 1987 0.731 1988 0.76 1989 0.982 1990 0.967 1991 0.769 1992 1.078