# europe_finl061 - Suojanpera - 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/2857 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_finl061 - Suojanpera - 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: Suojanpera # Location: # Country: Finland # Northernmost_Latitude: 69.32 # Southernmost_Latitude: 69.32 # Easternmost_Longitude: 28.13 # Westernmost_Longitude: 28.13 # Elevation: 140 m #-------------------- # Data_Collection # Collection_Name: europe_finl061B # Earliest_Year: 1621 # 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":"7.117347322","T2":"20.4322789305","M1":"0.0220392755508","M2":"0.202136387035"}} #-------------------- # 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 1621 1.025 1622 0.997 1623 1.193 1624 1.216 1625 1.241 1626 1.429 1627 1.161 1628 1.182 1629 1.545 1630 1.069 1631 1.259 1632 1.361 1633 1.073 1634 1.275 1635 1.01 1636 1.15 1637 1.453 1638 1.248 1639 1.126 1640 1.159 1641 0.821 1642 0.815 1643 0.882 1644 0.555 1645 0.712 1646 0.872 1647 0.909 1648 1.176 1649 0.894 1650 0.951 1651 1.003 1652 0.982 1653 0.988 1654 1.059 1655 1.182 1656 1.073 1657 1.032 1658 1.329 1659 1.099 1660 1.268 1661 0.952 1662 1.03 1663 0.981 1664 0.916 1665 1.238 1666 0.865 1667 0.667 1668 1.164 1669 0.946 1670 0.904 1671 1.178 1672 0.887 1673 0.895 1674 0.764 1675 0.53 1676 0.551 1677 0.628 1678 0.734 1679 0.835 1680 0.175 1681 0.572 1682 0.686 1683 0.662 1684 0.773 1685 0.807 1686 0.935 1687 0.699 1688 0.807 1689 1.267 1690 0.781 1691 0.882 1692 0.969 1693 1.303 1694 1.304 1695 0.714 1696 0.377 1697 0.418 1698 0.397 1699 0.479 1700 0.608 1701 0.617 1702 0.762 1703 0.598 1704 1.025 1705 0.823 1706 0.846 1707 1.113 1708 0.891 1709 0.399 1710 0.815 1711 0.797 1712 0.71 1713 0.712 1714 0.743 1715 1.061 1716 0.914 1717 0.624 1718 0.954 1719 0.466 1720 0.652 1721 0.562 1722 0.629 1723 0.569 1724 0.653 1725 0.816 1726 0.857 1727 1.283 1728 0.813 1729 1.138 1730 1.263 1731 0.877 1732 0.856 1733 0.982 1734 0.504 1735 1.153 1736 1.361 1737 1.055 1738 1.401 1739 1.569 1740 1.126 1741 1.063 1742 1.238 1743 0.981 1744 1.184 1745 0.864 1746 1.342 1747 0.999 1748 1.105 1749 1.182 1750 1.539 1751 1.234 1752 1.291 1753 1.7 1754 1.741 1755 1.737 1756 1.972 1757 1.776 1758 1.625 1759 1.479 1760 1.412 1761 1.583 1762 1.841 1763 1.517 1764 1.265 1765 1.586 1766 1.714 1767 1.185 1768 1.164 1769 0.781 1770 0.905 1771 0.952 1772 1.0 1773 1.109 1774 1.146 1775 1.125 1776 1.077 1777 1.228 1778 1.113 1779 1.105 1780 1.494 1781 0.931 1782 1.201 1783 1.065 1784 1.084 1785 1.289 1786 1.148 1787 1.042 1788 1.323 1789 1.187 1790 0.878 1791 1.198 1792 1.163 1793 0.996 1794 0.856 1795 0.932 1796 1.237 1797 1.176 1798 0.966 1799 1.526 1800 0.898 1801 0.975 1802 1.153 1803 0.845 1804 1.105 1805 1.296 1806 0.431 1807 0.955 1808 1.177 1809 1.043 1810 0.75 1811 0.736 1812 0.661 1813 0.521 1814 0.632 1815 0.622 1816 0.578 1817 0.642 1818 1.086 1819 1.25 1820 0.822 1821 0.75 1822 0.745 1823 1.324 1824 1.204 1825 0.751 1826 1.543 1827 1.547 1828 1.053 1829 1.275 1830 1.313 1831 1.225 1832 1.066 1833 0.999 1834 1.079 1835 1.002 1836 0.917 1837 0.404 1838 0.789 1839 0.541 1840 0.89 1841 0.618 1842 0.423 1843 0.656 1844 0.729 1845 0.989 1846 0.843 1847 0.879 1848 0.74 1849 1.051 1850 0.986 1851 1.063 1852 1.143 1853 1.035 1854 1.15 1855 0.945 1856 0.979 1857 0.98 1858 1.153 1859 1.053 1860 0.996 1861 0.907 1862 0.719 1863 0.888 1864 1.111 1865 1.069 1866 0.813 1867 0.837 1868 0.823 1869 1.051 1870 1.019 1871 0.866 1872 0.861 1873 1.135 1874 0.659 1875 0.797 1876 1.135 1877 0.959 1878 0.743 1879 0.567 1880 0.504 1881 0.528 1882 0.742 1883 0.762 1884 0.636 1885 0.669 1886 0.745 1887 0.757 1888 0.557 1889 0.746 1890 0.897 1891 0.742 1892 0.427 1893 0.44 1894 0.682 1895 0.788 1896 0.913 1897 0.642 1898 1.098 1899 0.794 1900 0.463 1901 0.842 1902 0.429 1903 0.31 1904 0.463 1905 0.446 1906 0.635 1907 0.587 1908 0.564 1909 0.551 1910 0.26 1911 0.408 1912 0.71 1913 0.745 1914 0.93 1915 1.056 1916 1.012 1917 0.84 1918 0.927 1919 0.898 1920 1.119 1921 1.13 1922 1.166 1923 1.205 1924 1.213 1925 1.54 1926 0.888 1927 1.401 1928 1.0 1929 0.787 1930 1.493 1931 1.583 1932 1.407 1933 1.551 1934 1.922 1935 1.665 1936 1.331 1937 1.856 1938 1.634 1939 1.338 1940 0.922 1941 1.418 1942 1.045 1943 1.015 1944 1.085 1945 1.294 1946 0.997 1947 1.011 1948 1.121 1949 1.139 1950 1.063 1951 0.925 1952 0.998 1953 1.289 1954 1.341 1955 0.903 1956 0.873 1957 1.203 1958 1.072 1959 1.204 1960 1.409 1961 1.055 1962 0.925 1963 0.586 1964 1.358 1965 0.843 1966 0.916 1967 1.103 1968 0.884 1969 0.768 1970 1.158 1971 0.956 1972 1.093 1973 1.515 1974 0.965 1975 1.051 1976 0.979 1977 0.959 1978 0.871 1979 1.155 1980 0.983 1981 0.91 1982 0.926 1983 0.981