# europe_finl058 - Sompio - 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/2855 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_finl058 - Sompio - 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: Sompio # Location: # Country: Finland # Northernmost_Latitude: 68.13 # Southernmost_Latitude: 68.13 # Easternmost_Longitude: 27.45 # Westernmost_Longitude: 27.45 # Elevation: 330 m #-------------------- # Data_Collection # Collection_Name: europe_finl058B # Earliest_Year: 1627 # 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":"4.25844663722","T2":"17.8543692006","M1":"0.0227908283561","M2":"0.361305872407"}} #-------------------- # 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 1627 0.922 1628 0.974 1629 1.263 1630 0.843 1631 0.955 1632 1.256 1633 0.954 1634 0.904 1635 1.028 1636 1.376 1637 1.34 1638 1.034 1639 1.032 1640 0.812 1641 0.546 1642 0.415 1643 0.607 1644 0.452 1645 0.475 1646 0.67 1647 0.95 1648 1.013 1649 0.725 1650 0.541 1651 0.851 1652 1.015 1653 0.807 1654 0.894 1655 1.174 1656 1.056 1657 1.109 1658 1.259 1659 1.206 1660 1.313 1661 1.136 1662 1.151 1663 0.96 1664 1.134 1665 1.039 1666 0.75 1667 0.767 1668 1.077 1669 0.916 1670 1.049 1671 1.279 1672 0.846 1673 0.685 1674 0.709 1675 0.695 1676 0.688 1677 0.902 1678 0.779 1679 0.711 1680 0.449 1681 0.913 1682 1.197 1683 0.943 1684 0.982 1685 1.027 1686 1.489 1687 1.301 1688 1.115 1689 1.469 1690 0.94 1691 1.212 1692 1.209 1693 1.315 1694 1.566 1695 1.029 1696 0.569 1697 1.083 1698 1.037 1699 0.737 1700 0.698 1701 0.928 1702 1.128 1703 0.848 1704 1.008 1705 0.841 1706 0.793 1707 0.996 1708 0.904 1709 0.436 1710 0.779 1711 0.825 1712 0.869 1713 0.724 1714 0.964 1715 1.08 1716 0.799 1717 0.918 1718 1.124 1719 0.777 1720 0.914 1721 0.676 1722 0.871 1723 0.872 1724 0.627 1725 1.009 1726 0.899 1727 1.14 1728 1.008 1729 1.297 1730 1.115 1731 0.951 1732 0.874 1733 0.743 1734 0.398 1735 0.548 1736 0.94 1737 0.84 1738 1.152 1739 1.328 1740 0.926 1741 1.0 1742 1.126 1743 1.289 1744 1.148 1745 0.927 1746 1.199 1747 0.838 1748 1.104 1749 1.19 1750 1.163 1751 0.906 1752 1.356 1753 1.269 1754 1.519 1755 1.549 1756 1.541 1757 1.363 1758 1.388 1759 1.571 1760 1.568 1761 1.328 1762 1.316 1763 1.175 1764 1.186 1765 1.312 1766 1.278 1767 1.076 1768 1.101 1769 1.024 1770 1.03 1771 0.728 1772 0.835 1773 0.829 1774 0.968 1775 0.827 1776 0.887 1777 1.025 1778 1.15 1779 0.888 1780 1.12 1781 0.863 1782 0.993 1783 0.897 1784 1.052 1785 1.468 1786 1.102 1787 1.037 1788 1.048 1789 1.074 1790 0.775 1791 0.895 1792 0.784 1793 0.511 1794 0.439 1795 0.325 1796 0.411 1797 0.464 1798 0.563 1799 0.607 1800 0.421 1801 0.545 1802 0.621 1803 0.394 1804 0.594 1805 0.689 1806 0.253 1807 0.78 1808 0.776 1809 0.653 1810 0.673 1811 0.575 1812 0.668 1813 0.49 1814 0.568 1815 0.74 1816 0.632 1817 0.764 1818 0.715 1819 0.747 1820 0.584 1821 0.654 1822 0.599 1823 0.883 1824 0.868 1825 0.828 1826 1.214 1827 1.341 1828 1.016 1829 1.128 1830 1.278 1831 1.073 1832 1.114 1833 1.003 1834 1.066 1835 0.798 1836 0.896 1837 0.424 1838 0.987 1839 0.672 1840 1.034 1841 0.865 1842 0.903 1843 0.915 1844 0.803 1845 0.972 1846 0.814 1847 0.797 1848 0.8 1849 1.158 1850 1.052 1851 1.235 1852 1.451 1853 1.167 1854 1.269 1855 1.167 1856 1.031 1857 1.091 1858 1.153 1859 0.995 1860 0.971 1861 1.073 1862 1.087 1863 1.098 1864 1.339 1865 1.369 1866 1.047 1867 1.111 1868 1.197 1869 1.262 1870 1.304 1871 1.049 1872 0.935 1873 1.037 1874 0.766 1875 0.788 1876 0.941 1877 0.905 1878 0.803 1879 0.76 1880 0.546 1881 0.517 1882 0.817 1883 0.791 1884 0.716 1885 0.84 1886 0.952 1887 0.951 1888 0.769 1889 0.884 1890 1.066 1891 0.926 1892 0.72 1893 0.658 1894 0.819 1895 0.856 1896 0.88 1897 0.736 1898 1.011 1899 0.799 1900 0.59 1901 0.875 1902 0.607 1903 0.361 1904 0.564 1905 0.56 1906 0.743 1907 0.654 1908 0.738 1909 0.734 1910 0.472 1911 0.454 1912 0.715 1913 0.673 1914 0.83 1915 0.97 1916 1.005 1917 0.882 1918 0.957 1919 0.938 1920 1.068 1921 1.15 1922 1.24 1923 1.299 1924 1.226 1925 1.674 1926 1.1 1927 1.23 1928 0.862 1929 0.778 1930 1.198 1931 1.095 1932 1.087 1933 1.068 1934 1.325 1935 1.128 1936 0.922 1937 1.36 1938 1.502 1939 1.158 1940 1.012 1941 1.41 1942 1.05 1943 0.869 1944 0.908 1945 1.027 1946 0.816 1947 0.86 1948 1.086 1949 1.041 1950 1.068 1951 1.079 1952 1.117 1953 1.187 1954 1.391 1955 1.133 1956 1.055 1957 1.243 1958 1.026 1959 1.034 1960 1.249 1961 0.84 1962 1.158 1963 0.832 1964 1.541 1965 1.042 1966 1.084 1967 1.311 1968 1.071 1969 0.969 1970 1.09 1971 0.977 1972 1.084 1973 1.384 1974 0.938 1975 1.114 1976 1.149 1977 1.059 1978 0.883 1979 1.274 1980 1.127 1981 1.074 1982 1.191 1983 1.077