# europe_spai009 - Boqueron - 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/3284 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_spai009 - Boqueron - 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: Boqueron # Location: # Country: Spain # Northernmost_Latitude: 40.35 # Southernmost_Latitude: 40.35 # Easternmost_Longitude: -2.13 # Westernmost_Longitude: -2.13 # Elevation: 1250 m #-------------------- # Data_Collection # Collection_Name: europe_spai009B # Earliest_Year: 1765 # Most_Recent_Year: 1988 # 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":"4.401931667","T2":"15.6906901711","M1":"0.0224287151604","M2":"0.427235245698"}} #-------------------- # Species # Species_Name: Austrian pine # Species_Code: PINI #-------------------- # 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 1765 1.256 1766 0.862 1767 0.727 1768 0.713 1769 0.578 1770 0.618 1771 0.728 1772 0.889 1773 0.941 1774 1.033 1775 0.984 1776 0.879 1777 1.034 1778 0.856 1779 0.828 1780 0.634 1781 0.826 1782 1.069 1783 1.114 1784 1.17 1785 1.135 1786 0.997 1787 1.107 1788 1.441 1789 0.886 1790 0.827 1791 1.48 1792 1.164 1793 0.978 1794 0.98 1795 1.027 1796 1.228 1797 0.747 1798 0.62 1799 0.729 1800 0.853 1801 0.929 1802 0.954 1803 0.436 1804 0.809 1805 0.561 1806 0.537 1807 0.665 1808 0.656 1809 0.685 1810 1.175 1811 1.385 1812 0.851 1813 1.131 1814 1.167 1815 0.869 1816 0.797 1817 0.925 1818 1.16 1819 1.248 1820 0.86 1821 0.879 1822 0.968 1823 0.975 1824 0.821 1825 1.286 1826 1.382 1827 1.082 1828 1.18 1829 1.265 1830 1.141 1831 1.18 1832 1.138 1833 1.175 1834 1.814 1835 1.202 1836 1.103 1837 1.059 1838 1.042 1839 0.488 1840 0.689 1841 1.124 1842 0.822 1843 1.115 1844 1.189 1845 1.172 1846 1.411 1847 0.882 1848 0.661 1849 0.767 1850 1.222 1851 1.156 1852 0.675 1853 0.562 1854 0.837 1855 0.997 1856 1.508 1857 1.368 1858 1.417 1859 1.506 1860 1.001 1861 1.183 1862 0.958 1863 0.939 1864 1.162 1865 1.136 1866 0.879 1867 0.789 1868 0.877 1869 1.172 1870 0.865 1871 0.962 1872 1.12 1873 1.041 1874 1.002 1875 1.058 1876 1.043 1877 1.389 1878 1.285 1879 0.655 1880 1.068 1881 1.326 1882 1.238 1883 1.37 1884 1.305 1885 1.456 1886 1.327 1887 0.995 1888 1.062 1889 1.083 1890 0.879 1891 0.813 1892 0.957 1893 0.8 1894 0.792 1895 0.869 1896 0.889 1897 1.109 1898 0.943 1899 0.853 1900 0.452 1901 0.539 1902 0.913 1903 1.262 1904 0.851 1905 0.879 1906 0.944 1907 1.086 1908 1.108 1909 0.936 1910 1.155 1911 1.173 1912 1.174 1913 1.016 1914 1.31 1915 0.816 1916 0.832 1917 0.856 1918 0.646 1919 0.834 1920 1.101 1921 0.772 1922 0.789 1923 1.198 1924 0.732 1925 0.75 1926 1.026 1927 0.783 1928 1.092 1929 1.075 1930 1.03 1931 0.784 1932 0.905 1933 1.033 1934 0.583 1935 0.534 1936 0.923 1937 0.942 1938 0.763 1939 0.939 1940 1.139 1941 0.831 1942 0.759 1943 0.812 1944 0.815 1945 0.823 1946 0.802 1947 0.692 1948 1.157 1949 0.721 1950 0.775 1951 1.02 1952 1.051 1953 1.012 1954 0.773 1955 0.911 1956 1.134 1957 0.906 1958 0.861 1959 1.249 1960 1.307 1961 1.291 1962 1.028 1963 0.624 1964 0.889 1965 0.731 1966 0.816 1967 0.665 1968 0.436 1969 0.7 1970 0.987 1971 0.944 1972 0.798 1973 1.285 1974 1.176 1975 1.221 1976 1.349 1977 1.449 1978 1.016 1979 1.21 1980 1.542 1981 1.057 1982 1.077 1983 1.041 1984 0.98 1985 1.069 1986 0.658 1987 1.024 1988 1.137