# europe_brit024 - Glen Affric - 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/4423 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_brit024 - Glen Affric - 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: Glen Affric # Location: # Country: United Kingdom # Northernmost_Latitude: 57.28 # Southernmost_Latitude: 57.28 # Easternmost_Longitude: -4.92 # Westernmost_Longitude: -4.92 # Elevation: 300 m #-------------------- # Data_Collection # Collection_Name: europe_brit024B # Earliest_Year: 1776 # Most_Recent_Year: 1976 # 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":"6.20702520088","T2":"18.2269795181","M1":"0.0220853752986","M2":"0.398793168905"}} #-------------------- # 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 1776 0.642 1777 0.678 1778 0.61 1779 0.57 1780 0.589 1781 0.509 1782 0.338 1783 0.618 1784 0.739 1785 0.524 1786 0.557 1787 0.638 1788 0.585 1789 0.614 1790 0.57 1791 0.439 1792 0.483 1793 0.423 1794 0.365 1795 0.364 1796 0.305 1797 0.248 1798 0.359 1799 0.249 1800 0.309 1801 0.249 1802 0.349 1803 0.464 1804 0.564 1805 0.322 1806 0.34 1807 0.432 1808 0.454 1809 0.495 1810 0.761 1811 1.283 1812 1.095 1813 0.898 1814 0.666 1815 0.728 1816 0.804 1817 1.065 1818 0.88 1819 0.994 1820 0.983 1821 0.841 1822 0.758 1823 0.952 1824 0.978 1825 1.077 1826 0.784 1827 1.207 1828 1.298 1829 1.347 1830 1.482 1831 1.138 1832 1.184 1833 1.095 1834 1.053 1835 1.205 1836 1.071 1837 0.977 1838 1.044 1839 1.011 1840 1.106 1841 1.181 1842 1.26 1843 1.339 1844 1.161 1845 1.295 1846 1.225 1847 1.199 1848 1.457 1849 1.531 1850 1.615 1851 1.378 1852 1.252 1853 0.862 1854 1.414 1855 1.299 1856 1.272 1857 1.518 1858 1.686 1859 1.389 1860 1.379 1861 1.176 1862 1.234 1863 1.367 1864 1.232 1865 1.212 1866 0.99 1867 0.949 1868 1.212 1869 1.272 1870 1.314 1871 1.076 1872 1.078 1873 0.985 1874 1.328 1875 1.36 1876 1.188 1877 1.021 1878 1.032 1879 0.931 1880 1.389 1881 0.897 1882 1.079 1883 0.943 1884 1.08 1885 0.889 1886 0.833 1887 0.928 1888 0.866 1889 0.792 1890 1.026 1891 1.018 1892 1.034 1893 1.086 1894 0.964 1895 0.825 1896 1.022 1897 1.03 1898 1.223 1899 0.961 1900 0.946 1901 0.996 1902 0.894 1903 1.047 1904 1.2 1905 1.148 1906 1.183 1907 1.19 1908 1.047 1909 0.927 1910 1.173 1911 1.245 1912 0.966 1913 1.108 1914 0.975 1915 0.96 1916 1.031 1917 0.973 1918 1.187 1919 1.292 1920 1.082 1921 1.19 1922 1.252 1923 1.196 1924 1.057 1925 1.179 1926 1.155 1927 1.049 1928 0.781 1929 0.852 1930 0.907 1931 0.938 1932 1.085 1933 1.114 1934 1.017 1935 1.351 1936 1.034 1937 0.967 1938 1.12 1939 0.958 1940 0.767 1941 0.835 1942 0.737 1943 1.075 1944 0.947 1945 0.857 1946 0.731 1947 0.869 1948 0.813 1949 1.097 1950 0.818 1951 0.779 1952 0.745 1953 0.807 1954 0.735 1955 0.795 1956 0.622 1957 0.688 1958 0.71 1959 0.783 1960 0.67 1961 0.528 1962 0.56 1963 0.689 1964 0.918 1965 0.852 1966 0.767 1967 0.907 1968 0.811 1969 0.679 1970 0.616 1971 0.725 1972 0.66 1973 0.622 1974 0.52 1975 0.658 1976 0.675