# europe_swed017 - Arjeplog - 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/4312 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_swed017 - Arjeplog - 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: Arjeplog # Location: # Country: Sweden # Northernmost_Latitude: 66.07 # Southernmost_Latitude: 66.07 # Easternmost_Longitude: 17.98 # Westernmost_Longitude: 17.98 # Elevation: 600 m #-------------------- # Data_Collection # Collection_Name: europe_swed017B # Earliest_Year: 1747 # Most_Recent_Year: 1978 # 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":"6.36254887119","T2":"19.1407985757","M1":"0.0223435211205","M2":"0.270916266418"}} #-------------------- # Species # Species_Name: Norway spruce # Species_Code: PCAB #-------------------- # 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 1747 0.99 1748 1.126 1749 0.918 1750 1.112 1751 1.189 1752 1.32 1753 1.063 1754 1.15 1755 1.506 1756 1.08 1757 1.494 1758 1.226 1759 1.432 1760 1.677 1761 1.503 1762 1.427 1763 1.418 1764 1.032 1765 1.127 1766 1.418 1767 0.871 1768 0.806 1769 0.779 1770 0.81 1771 1.009 1772 0.983 1773 1.063 1774 1.04 1775 1.08 1776 1.264 1777 1.082 1778 1.211 1779 0.859 1780 0.961 1781 0.961 1782 0.827 1783 0.724 1784 0.799 1785 1.058 1786 0.751 1787 0.714 1788 1.068 1789 0.781 1790 0.287 1791 0.572 1792 0.657 1793 0.754 1794 0.568 1795 0.776 1796 0.778 1797 0.701 1798 0.874 1799 0.944 1800 0.632 1801 1.032 1802 0.779 1803 0.636 1804 0.908 1805 0.77 1806 0.464 1807 0.905 1808 0.992 1809 0.824 1810 0.782 1811 0.997 1812 0.544 1813 0.804 1814 0.947 1815 0.872 1816 1.243 1817 1.104 1818 1.307 1819 1.623 1820 1.162 1821 0.407 1822 0.747 1823 0.983 1824 1.022 1825 0.812 1826 1.375 1827 1.237 1828 1.577 1829 1.546 1830 1.254 1831 1.694 1832 1.03 1833 1.061 1834 0.981 1835 0.822 1836 0.738 1837 0.532 1838 0.827 1839 0.558 1840 0.747 1841 0.912 1842 1.067 1843 1.037 1844 0.852 1845 0.984 1846 1.15 1847 1.222 1848 0.854 1849 0.914 1850 0.913 1851 0.858 1852 1.286 1853 0.985 1854 1.118 1855 0.988 1856 0.73 1857 0.712 1858 0.963 1859 0.854 1860 1.222 1861 1.274 1862 1.015 1863 1.259 1864 1.166 1865 1.014 1866 1.15 1867 0.985 1868 1.055 1869 0.972 1870 1.06 1871 0.859 1872 1.27 1873 1.221 1874 0.829 1875 1.116 1876 1.091 1877 0.994 1878 1.019 1879 1.048 1880 0.704 1881 0.838 1882 0.998 1883 1.046 1884 0.949 1885 0.938 1886 1.065 1887 0.694 1888 0.942 1889 1.157 1890 1.026 1891 1.095 1892 0.91 1893 0.999 1894 0.815 1895 0.714 1896 0.919 1897 0.813 1898 1.014 1899 1.268 1900 1.013 1901 1.366 1902 0.588 1903 0.817 1904 0.838 1905 1.065 1906 0.895 1907 0.979 1908 1.029 1909 0.946 1910 0.77 1911 0.933 1912 1.237 1913 1.175 1914 1.358 1915 1.081 1916 1.386 1917 0.976 1918 1.014 1919 1.188 1920 0.837 1921 0.538 1922 0.902 1923 0.7 1924 0.966 1925 0.877 1926 0.859 1927 1.028 1928 0.505 1929 0.97 1930 1.203 1931 0.661 1932 1.146 1933 1.164 1934 1.064 1935 1.024 1936 1.605 1937 1.359 1938 1.329 1939 1.368 1940 1.444 1941 1.435 1942 0.893 1943 0.876 1944 0.773 1945 0.747 1946 0.65 1947 0.929 1948 0.441 1949 0.703 1950 0.853 1951 0.473 1952 0.738 1953 1.18 1954 0.89 1955 0.845 1956 0.848 1957 0.682 1958 0.779 1959 0.78 1960 0.942 1961 0.679 1962 0.891 1963 1.004 1964 0.886 1965 1.024 1966 1.367 1967 1.08 1968 1.145 1969 1.487 1970 1.299 1971 1.036 1972 1.416 1973 1.217 1974 1.118 1975 0.656 1976 1.222 1977 0.982 1978 1.145