# europe_finl059 - Riukuselka - 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/2848 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_finl059 - Riukuselka - 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: Riukuselka # Location: # Country: Finland # Northernmost_Latitude: 68.45 # Southernmost_Latitude: 68.45 # Easternmost_Longitude: 28.07 # Westernmost_Longitude: 28.07 # Elevation: 320 m #-------------------- # Data_Collection # Collection_Name: europe_finl059B # Earliest_Year: 1681 # 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":"5.07803477074","T2":"19.8505714981","M1":"0.0225851416078","M2":"0.241953871839"}} #-------------------- # 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 1681 0.731 1682 0.88 1683 0.992 1684 1.074 1685 0.904 1686 1.039 1687 1.258 1688 1.213 1689 1.565 1690 1.533 1691 1.794 1692 1.593 1693 1.803 1694 1.644 1695 0.995 1696 0.666 1697 0.705 1698 0.598 1699 0.566 1700 0.75 1701 0.815 1702 1.038 1703 0.868 1704 1.056 1705 0.92 1706 0.888 1707 0.839 1708 0.629 1709 0.381 1710 0.475 1711 0.613 1712 0.73 1713 0.672 1714 0.689 1715 0.743 1716 0.568 1717 0.529 1718 0.541 1719 0.446 1720 0.455 1721 0.367 1722 0.499 1723 0.517 1724 0.567 1725 0.675 1726 0.592 1727 0.706 1728 0.655 1729 1.041 1730 1.163 1731 0.833 1732 0.862 1733 0.899 1734 0.481 1735 0.978 1736 1.089 1737 0.836 1738 1.11 1739 1.153 1740 0.754 1741 0.703 1742 0.857 1743 0.817 1744 0.935 1745 0.767 1746 0.966 1747 0.697 1748 0.787 1749 0.764 1750 0.813 1751 0.786 1752 1.023 1753 1.111 1754 1.284 1755 1.418 1756 1.562 1757 1.557 1758 1.413 1759 1.481 1760 1.479 1761 1.46 1762 1.444 1763 1.377 1764 1.227 1765 1.398 1766 1.428 1767 1.065 1768 1.143 1769 0.809 1770 1.078 1771 0.894 1772 0.889 1773 0.663 1774 0.901 1775 0.975 1776 0.953 1777 1.138 1778 1.113 1779 1.1 1780 1.418 1781 1.12 1782 1.04 1783 0.958 1784 0.972 1785 1.297 1786 0.903 1787 1.013 1788 1.246 1789 1.443 1790 0.765 1791 0.641 1792 0.877 1793 0.747 1794 0.921 1795 1.088 1796 1.062 1797 1.07 1798 1.289 1799 1.51 1800 0.926 1801 0.888 1802 0.828 1803 0.765 1804 0.912 1805 1.104 1806 0.537 1807 1.096 1808 1.255 1809 1.148 1810 0.936 1811 0.791 1812 0.855 1813 0.817 1814 0.858 1815 0.941 1816 0.995 1817 0.961 1818 0.995 1819 1.084 1820 0.898 1821 0.956 1822 0.676 1823 1.111 1824 1.176 1825 0.969 1826 1.405 1827 1.372 1828 1.219 1829 1.351 1830 1.309 1831 1.318 1832 1.132 1833 0.944 1834 0.974 1835 0.869 1836 1.046 1837 0.401 1838 0.848 1839 0.514 1840 0.939 1841 0.643 1842 0.524 1843 0.551 1844 0.611 1845 0.935 1846 0.862 1847 0.796 1848 0.622 1849 0.955 1850 0.832 1851 1.076 1852 1.022 1853 1.02 1854 1.226 1855 1.217 1856 1.128 1857 1.207 1858 1.262 1859 1.112 1860 1.096 1861 1.172 1862 0.891 1863 0.801 1864 1.154 1865 1.151 1866 0.847 1867 0.893 1868 0.957 1869 0.983 1870 1.15 1871 0.949 1872 0.934 1873 1.152 1874 0.831 1875 0.758 1876 1.161 1877 1.092 1878 0.923 1879 1.082 1880 0.87 1881 0.984 1882 1.143 1883 1.063 1884 1.039 1885 1.273 1886 1.555 1887 1.259 1888 0.991 1889 1.123 1890 1.247 1891 1.114 1892 0.723 1893 0.754 1894 1.007 1895 0.985 1896 1.041 1897 0.681 1898 1.082 1899 0.903 1900 0.527 1901 0.96 1902 0.605 1903 0.475 1904 0.586 1905 0.505 1906 0.596 1907 0.521 1908 0.604 1909 0.492 1910 0.238 1911 0.254 1912 0.508 1913 0.506 1914 0.718 1915 0.736 1916 0.787 1917 0.666 1918 0.722 1919 0.81 1920 0.965 1921 1.005 1922 0.959 1923 1.083 1924 1.01 1925 1.073 1926 0.684 1927 1.065 1928 0.803 1929 0.71 1930 1.366 1931 1.275 1932 1.054 1933 1.075 1934 1.135 1935 0.982 1936 0.975 1937 1.338 1938 1.363 1939 1.039 1940 1.111 1941 1.492 1942 1.317 1943 1.298 1944 1.326 1945 1.347 1946 1.143 1947 0.909 1948 1.086 1949 0.976 1950 0.997 1951 0.913 1952 1.027 1953 1.291 1954 1.348 1955 1.131 1956 1.099 1957 1.406 1958 1.175 1959 1.332 1960 1.724 1961 1.151 1962 1.268 1963 0.878 1964 1.377 1965 0.69 1966 0.716 1967 0.882 1968 0.707 1969 0.794 1970 0.972 1971 0.906 1972 1.042 1973 1.081 1974 0.82 1975 0.903 1976 1.005 1977 0.99 1978 0.943 1979 1.416 1980 1.22 1981 1.181 1982 1.104 1983 1.153