# europe_finl062 - Jurmarova - 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/2827 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_finl062 - Jurmarova - 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: Jurmarova # Location: # Country: Finland # Northernmost_Latitude: 68.87 # Southernmost_Latitude: 68.87 # Easternmost_Longitude: 26.88 # Westernmost_Longitude: 26.88 # Elevation: 250 m #-------------------- # Data_Collection # Collection_Name: europe_finl062B # Earliest_Year: 1560 # 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":"7.27523594596","T2":"20.2485744525","M1":"0.0226713659884","M2":"0.238771811962"}} #-------------------- # 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 1560 0.854 1561 0.85 1562 0.987 1563 0.838 1564 0.845 1565 1.007 1566 0.933 1567 0.73 1568 1.072 1569 1.16 1570 1.11 1571 0.883 1572 0.743 1573 0.974 1574 0.675 1575 1.258 1576 1.173 1577 1.166 1578 0.97 1579 1.197 1580 0.875 1581 0.98 1582 1.277 1583 1.274 1584 1.015 1585 1.23 1586 1.199 1587 0.91 1588 0.974 1589 0.917 1590 0.837 1591 0.975 1592 1.262 1593 1.049 1594 1.375 1595 0.997 1596 0.946 1597 1.053 1598 0.98 1599 1.115 1600 1.007 1601 0.421 1602 0.866 1603 1.018 1604 0.962 1605 0.961 1606 1.052 1607 0.534 1608 0.574 1609 0.534 1610 0.62 1611 0.741 1612 0.694 1613 0.691 1614 0.681 1615 0.731 1616 0.954 1617 1.018 1618 1.098 1619 1.171 1620 0.761 1621 1.203 1622 1.21 1623 1.282 1624 1.183 1625 0.996 1626 1.333 1627 1.168 1628 1.343 1629 1.592 1630 1.176 1631 1.137 1632 1.27 1633 1.065 1634 1.409 1635 0.86 1636 1.072 1637 1.296 1638 1.26 1639 1.333 1640 1.508 1641 0.803 1642 0.935 1643 1.04 1644 0.681 1645 0.743 1646 0.85 1647 0.845 1648 1.092 1649 0.964 1650 0.816 1651 0.956 1652 0.97 1653 1.04 1654 1.207 1655 1.366 1656 1.248 1657 1.297 1658 1.448 1659 1.105 1660 1.252 1661 0.991 1662 1.145 1663 1.103 1664 1.249 1665 1.308 1666 1.021 1667 0.767 1668 1.076 1669 0.864 1670 0.937 1671 1.23 1672 1.065 1673 1.059 1674 0.851 1675 0.595 1676 0.703 1677 0.735 1678 0.728 1679 0.902 1680 0.339 1681 0.58 1682 0.811 1683 0.786 1684 0.915 1685 0.828 1686 0.952 1687 0.869 1688 0.744 1689 1.24 1690 0.998 1691 1.198 1692 1.062 1693 1.338 1694 1.361 1695 0.711 1696 0.527 1697 0.525 1698 0.446 1699 0.608 1700 0.59 1701 0.653 1702 0.876 1703 0.669 1704 0.968 1705 0.795 1706 0.891 1707 1.017 1708 0.815 1709 0.391 1710 0.881 1711 0.839 1712 0.751 1713 0.74 1714 0.747 1715 0.873 1716 0.644 1717 0.573 1718 0.874 1719 0.622 1720 0.698 1721 0.705 1722 0.682 1723 0.555 1724 0.647 1725 0.888 1726 0.737 1727 0.916 1728 0.741 1729 1.129 1730 1.134 1731 0.819 1732 0.931 1733 0.969 1734 0.509 1735 0.931 1736 1.124 1737 0.916 1738 1.353 1739 1.329 1740 0.976 1741 1.031 1742 1.191 1743 1.036 1744 1.159 1745 0.81 1746 1.204 1747 0.845 1748 1.089 1749 1.169 1750 1.327 1751 1.173 1752 1.177 1753 1.222 1754 1.259 1755 1.323 1756 1.414 1757 1.171 1758 1.097 1759 1.338 1760 1.268 1761 1.345 1762 1.386 1763 1.202 1764 1.053 1765 1.256 1766 1.316 1767 0.932 1768 0.987 1769 0.768 1770 0.829 1771 0.833 1772 1.131 1773 0.963 1774 1.047 1775 1.063 1776 1.048 1777 1.109 1778 1.125 1779 1.041 1780 1.404 1781 0.916 1782 1.108 1783 1.16 1784 1.091 1785 1.488 1786 1.071 1787 1.07 1788 1.139 1789 1.182 1790 0.879 1791 1.064 1792 1.103 1793 0.914 1794 0.938 1795 1.026 1796 1.145 1797 1.14 1798 1.044 1799 1.453 1800 1.076 1801 1.101 1802 1.182 1803 0.983 1804 1.216 1805 1.314 1806 0.453 1807 0.951 1808 1.107 1809 0.954 1810 0.767 1811 0.865 1812 0.728 1813 0.725 1814 0.678 1815 0.668 1816 0.731 1817 0.672 1818 0.942 1819 0.961 1820 0.729 1821 0.592 1822 0.539 1823 0.996 1824 1.029 1825 0.829 1826 1.576 1827 1.463 1828 1.059 1829 1.321 1830 1.367 1831 1.217 1832 1.05 1833 0.917 1834 1.161 1835 0.884 1836 0.863 1837 0.287 1838 0.889 1839 0.587 1840 0.943 1841 0.656 1842 0.41 1843 0.599 1844 0.558 1845 0.954 1846 0.788 1847 0.769 1848 0.606 1849 1.046 1850 0.919 1851 1.212 1852 1.261 1853 1.092 1854 1.363 1855 1.192 1856 1.154 1857 1.118 1858 1.358 1859 1.143 1860 1.194 1861 1.178 1862 0.903 1863 0.994 1864 1.22 1865 1.242 1866 0.926 1867 0.91 1868 0.893 1869 0.99 1870 0.982 1871 0.856 1872 0.849 1873 1.135 1874 0.807 1875 0.805 1876 1.086 1877 0.953 1878 0.82 1879 0.893 1880 0.705 1881 0.737 1882 1.01 1883 0.941 1884 0.972 1885 1.125 1886 1.362 1887 1.083 1888 0.706 1889 0.912 1890 1.17 1891 0.991 1892 0.515 1893 0.623 1894 0.782 1895 0.888 1896 0.947 1897 0.71 1898 1.084 1899 0.944 1900 0.589 1901 1.064 1902 0.652 1903 0.512 1904 0.759 1905 0.621 1906 0.713 1907 0.61 1908 0.591 1909 0.616 1910 0.272 1911 0.286 1912 0.659 1913 0.842 1914 1.096 1915 1.133 1916 1.043 1917 0.799 1918 0.993 1919 0.922 1920 1.093 1921 1.157 1922 1.302 1923 1.458 1924 1.339 1925 1.674 1926 1.089 1927 1.457 1928 0.987 1929 0.79 1930 1.372 1931 1.272 1932 1.224 1933 1.286 1934 1.579 1935 1.352 1936 1.007 1937 1.425 1938 1.267 1939 1.095 1940 0.821 1941 1.115 1942 0.972 1943 0.953 1944 1.083 1945 1.159 1946 0.887 1947 0.866 1948 0.987 1949 0.896 1950 1.005 1951 0.797 1952 0.994 1953 1.064 1954 1.125 1955 1.058 1956 0.949 1957 1.128 1958 1.012 1959 1.148 1960 1.307 1961 0.82 1962 0.859 1963 0.578 1964 1.258 1965 0.757 1966 0.932 1967 1.087 1968 0.911 1969 0.977 1970 0.977 1971 0.921 1972 1.132 1973 1.357 1974 0.99 1975 0.921 1976 1.025 1977 0.905 1978 0.791 1979 1.166 1980 0.913 1981 1.004 1982 1.113 1983 1.098