# europe_brit044 - Castle Coole - 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/2671 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_brit044 - Castle Coole - 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: Castle Coole # Location: # Country: United Kingdom # Northernmost_Latitude: 54.33 # Southernmost_Latitude: 54.33 # Easternmost_Longitude: -7.6 # Westernmost_Longitude: -7.6 # Elevation: 60 m #-------------------- # Data_Collection # Collection_Name: europe_brit044B # Earliest_Year: 1740 # Most_Recent_Year: 1983 # 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":"6.0115276215","T2":"18.2075400162","M1":"0.0220781500542","M2":"0.371926462629"}} #-------------------- # Species # Species_Name: oak # Species_Code: QUSP #-------------------- # 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 1740 0.657 1741 0.588 1742 0.429 1743 0.654 1744 0.779 1745 0.554 1746 0.702 1747 1.0 1748 0.912 1749 1.197 1750 1.058 1751 1.005 1752 1.099 1753 1.001 1754 1.028 1755 1.121 1756 0.924 1757 0.73 1758 1.056 1759 1.044 1760 0.943 1761 0.912 1762 0.793 1763 0.769 1764 0.802 1765 0.87 1766 0.895 1767 0.703 1768 1.058 1769 0.945 1770 0.764 1771 0.567 1772 0.863 1773 0.99 1774 0.958 1775 0.731 1776 0.921 1777 0.699 1778 0.792 1779 1.036 1780 0.988 1781 1.083 1782 0.946 1783 0.955 1784 1.247 1785 1.069 1786 0.965 1787 0.736 1788 0.971 1789 1.045 1790 0.843 1791 0.815 1792 1.078 1793 0.86 1794 0.872 1795 1.187 1796 1.058 1797 0.963 1798 1.316 1799 1.317 1800 1.199 1801 1.122 1802 0.798 1803 0.817 1804 0.923 1805 1.302 1806 1.3 1807 1.249 1808 1.317 1809 1.1 1810 0.876 1811 1.138 1812 1.104 1813 1.077 1814 1.091 1815 1.121 1816 0.785 1817 0.683 1818 1.193 1819 1.392 1820 1.151 1821 0.972 1822 1.192 1823 1.102 1824 1.055 1825 1.26 1826 1.192 1827 1.098 1828 0.955 1829 1.278 1830 1.062 1831 1.088 1832 1.192 1833 1.404 1834 1.611 1835 1.297 1836 1.046 1837 0.983 1838 1.372 1839 1.065 1840 0.638 1841 0.797 1842 0.844 1843 0.889 1844 1.041 1845 1.349 1846 1.288 1847 1.2 1848 1.23 1849 0.961 1850 1.112 1851 0.96 1852 1.081 1853 0.849 1854 1.075 1855 1.099 1856 0.968 1857 1.009 1858 1.031 1859 1.107 1860 0.934 1861 1.23 1862 1.032 1863 0.863 1864 0.931 1865 0.998 1866 0.948 1867 1.009 1868 0.948 1869 0.729 1870 0.995 1871 1.136 1872 0.792 1873 0.706 1874 0.842 1875 0.745 1876 0.678 1877 0.627 1878 0.785 1879 0.878 1880 0.674 1881 0.747 1882 1.163 1883 0.919 1884 0.844 1885 0.785 1886 0.829 1887 0.797 1888 0.893 1889 0.793 1890 1.023 1891 0.956 1892 0.975 1893 0.952 1894 0.757 1895 1.076 1896 1.123 1897 1.389 1898 0.987 1899 0.993 1900 1.062 1901 1.021 1902 1.015 1903 1.346 1904 1.161 1905 0.935 1906 0.902 1907 0.957 1908 0.962 1909 0.997 1910 1.041 1911 1.058 1912 1.22 1913 1.449 1914 1.232 1915 1.007 1916 1.102 1917 1.074 1918 1.052 1919 0.974 1920 0.938 1921 1.098 1922 0.95 1923 0.717 1924 0.717 1925 0.929 1926 0.807 1927 0.834 1928 0.596 1929 0.607 1930 0.652 1931 0.687 1932 0.668 1933 0.754 1934 0.783 1935 1.068 1936 0.981 1937 0.88 1938 0.763 1939 1.135 1940 1.134 1941 1.118 1942 1.041 1943 0.854 1944 0.861 1945 1.171 1946 0.957 1947 1.323 1948 1.011 1949 0.867 1950 1.094 1951 0.994 1952 1.062 1953 0.864 1954 0.843 1955 0.97 1956 0.811 1957 0.795 1958 0.944 1959 1.114 1960 1.111 1961 0.922 1962 0.993 1963 0.745 1964 0.881 1965 0.827 1966 0.886 1967 0.754 1968 1.006 1969 1.073 1970 0.937 1971 0.959 1972 0.837 1973 0.937 1974 1.028 1975 0.997 1976 1.002 1977 0.924 1978 0.976 1979 1.103 1980 1.1 1981 1.144 1982 1.449 1983 1.407