# europe_spai026 - Puerto Llano - 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/4261 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_spai026 - Puerto Llano - 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: Puerto Llano # Location: # Country: Spain # Northernmost_Latitude: 37.82 # Southernmost_Latitude: 37.82 # Easternmost_Longitude: -2.95 # Westernmost_Longitude: -2.95 # Elevation: 1800 m #-------------------- # Data_Collection # Collection_Name: europe_spai026B # Earliest_Year: 1601 # Most_Recent_Year: 1985 # 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":"5.29706760779","T2":"16.9174056209","M1":"0.0226139645353","M2":"0.280040526185"}} #-------------------- # Species # Species_Name: Austrian pine # Species_Code: PINI #-------------------- # 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 1601 0.865 1602 1.141 1603 0.85 1604 1.018 1605 1.041 1606 0.94 1607 1.111 1608 0.858 1609 1.01 1610 1.025 1611 1.027 1612 1.403 1613 1.253 1614 0.778 1615 0.945 1616 1.026 1617 1.165 1618 1.007 1619 1.107 1620 1.01 1621 1.039 1622 1.035 1623 0.624 1624 0.899 1625 1.053 1626 1.031 1627 0.843 1628 0.988 1629 1.128 1630 0.888 1631 1.011 1632 0.912 1633 0.942 1634 0.972 1635 0.979 1636 0.858 1637 0.743 1638 0.645 1639 0.796 1640 0.637 1641 0.69 1642 0.951 1643 1.188 1644 1.422 1645 1.106 1646 1.155 1647 1.02 1648 0.805 1649 0.882 1650 1.301 1651 0.928 1652 0.966 1653 1.024 1654 0.896 1655 0.932 1656 1.149 1657 1.312 1658 0.919 1659 1.102 1660 0.896 1661 1.427 1662 1.358 1663 1.092 1664 1.095 1665 1.035 1666 1.123 1667 0.858 1668 0.751 1669 0.828 1670 1.264 1671 1.071 1672 0.649 1673 0.794 1674 0.934 1675 0.962 1676 1.228 1677 1.458 1678 0.798 1679 0.597 1680 1.064 1681 0.977 1682 0.79 1683 0.68 1684 0.958 1685 1.333 1686 0.996 1687 0.738 1688 0.831 1689 1.002 1690 0.89 1691 1.098 1692 0.878 1693 0.991 1694 0.908 1695 0.824 1696 1.069 1697 0.923 1698 0.956 1699 1.259 1700 1.361 1701 1.201 1702 1.272 1703 0.965 1704 0.931 1705 0.98 1706 1.034 1707 0.904 1708 1.254 1709 1.195 1710 1.092 1711 0.788 1712 0.835 1713 0.781 1714 1.063 1715 1.298 1716 0.661 1717 0.681 1718 0.887 1719 0.948 1720 0.787 1721 1.101 1722 1.157 1723 1.14 1724 1.314 1725 0.626 1726 0.716 1727 0.943 1728 1.064 1729 0.728 1730 1.032 1731 1.086 1732 1.261 1733 1.087 1734 1.276 1735 0.824 1736 0.968 1737 1.317 1738 1.179 1739 1.097 1740 1.053 1741 0.96 1742 0.721 1743 0.8 1744 0.8 1745 1.003 1746 0.902 1747 1.365 1748 1.337 1749 1.094 1750 1.495 1751 1.034 1752 0.766 1753 0.791 1754 0.816 1755 1.191 1756 1.256 1757 1.326 1758 1.156 1759 1.42 1760 1.086 1761 1.089 1762 1.392 1763 1.383 1764 1.273 1765 1.049 1766 1.054 1767 0.98 1768 0.766 1769 0.586 1770 0.862 1771 0.831 1772 0.915 1773 1.068 1774 0.789 1775 0.938 1776 0.946 1777 0.908 1778 0.698 1779 0.705 1780 0.628 1781 0.953 1782 0.999 1783 0.599 1784 0.622 1785 0.644 1786 0.617 1787 0.688 1788 0.798 1789 0.644 1790 0.866 1791 1.262 1792 1.388 1793 1.028 1794 0.955 1795 1.274 1796 1.193 1797 0.89 1798 1.192 1799 0.974 1800 0.748 1801 1.123 1802 0.941 1803 0.971 1804 1.263 1805 0.665 1806 0.359 1807 0.706 1808 0.691 1809 0.955 1810 1.122 1811 1.33 1812 0.883 1813 0.818 1814 1.093 1815 1.28 1816 0.934 1817 0.86 1818 1.085 1819 1.08 1820 1.004 1821 0.941 1822 0.837 1823 0.842 1824 0.7 1825 0.831 1826 0.97 1827 1.046 1828 1.083 1829 1.064 1830 1.209 1831 0.743 1832 0.789 1833 1.093 1834 1.639 1835 1.398 1836 1.091 1837 1.316 1838 1.092 1839 1.028 1840 1.087 1841 1.32 1842 0.941 1843 1.205 1844 1.096 1845 1.118 1846 1.605 1847 1.248 1848 0.989 1849 1.154 1850 1.421 1851 1.404 1852 1.132 1853 1.282 1854 1.416 1855 1.338 1856 1.434 1857 0.738 1858 0.726 1859 0.843 1860 0.788 1861 0.995 1862 0.893 1863 0.907 1864 1.326 1865 1.027 1866 0.997 1867 1.02 1868 0.932 1869 1.276 1870 0.891 1871 0.956 1872 1.097 1873 1.152 1874 1.063 1875 1.03 1876 0.929 1877 1.222 1878 1.133 1879 0.605 1880 0.834 1881 1.074 1882 0.937 1883 1.208 1884 1.301 1885 1.421 1886 1.21 1887 0.789 1888 0.957 1889 1.148 1890 0.965 1891 1.173 1892 1.449 1893 1.293 1894 0.911 1895 0.817 1896 0.995 1897 0.904 1898 0.781 1899 0.991 1900 0.839 1901 0.752 1902 0.86 1903 1.148 1904 0.981 1905 1.012 1906 0.857 1907 0.879 1908 1.074 1909 0.822 1910 0.792 1911 0.877 1912 1.012 1913 1.037 1914 1.147 1915 0.831 1916 0.728 1917 0.802 1918 0.887 1919 0.947 1920 1.082 1921 0.844 1922 0.866 1923 1.037 1924 0.911 1925 0.949 1926 1.202 1927 0.747 1928 0.64 1929 0.987 1930 1.173 1931 0.973 1932 0.968 1933 1.331 1934 0.633 1935 0.613 1936 0.698 1937 0.911 1938 0.598 1939 0.793 1940 1.112 1941 0.923 1942 0.728 1943 0.715 1944 0.895 1945 0.8 1946 0.527 1947 0.642 1948 0.799 1949 0.611 1950 0.575 1951 0.432 1952 0.651 1953 0.843 1954 0.821 1955 0.93 1956 0.805 1957 0.929 1958 0.879 1959 0.532 1960 0.661 1961 0.892 1962 0.922 1963 0.538 1964 0.725 1965 0.577 1966 0.549 1967 0.668 1968 0.77 1969 1.032 1970 1.117 1971 0.871 1972 0.726 1973 1.016 1974 0.706 1975 0.73 1976 0.988 1977 1.229 1978 1.232 1979 1.013 1980 1.257 1981 1.0 1982 0.929 1983 0.948 1984 0.773 1985 0.823