# southamerica_arge013 - Lonco Luan - 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/3542 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: southamerica_arge013 - Lonco Luan - 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: Lonco Luan # Location: # Country: Argentina # Northernmost_Latitude: -38.98 # Southernmost_Latitude: -38.98 # Easternmost_Longitude: -71.05 # Westernmost_Longitude: -71.05 # Elevation: 1110 m #-------------------- # Data_Collection # Collection_Name: southamerica_arge013B # Earliest_Year: 1610 # Most_Recent_Year: 1974 # Time_Unit: y_ad # Core_Length: # Notes: {"database":{"database1":"LMR","database2":"Breits"}} {"climateInterpretation":{"basis":"", "climateVariable":"M", "climateVariableDetail":"air", "interpDirection":"positive", "seasonality":"[-12, 1, 2]"}}{"VSLite_parameters":{"T1":"3.0252133278","T2":"13.5250363394","M1":"0.022656679548","M2":"0.524470493029"}} #-------------------- # Species # Species_Name: monkey puzzle # Species_Code: ARAR #-------------------- # 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 1610 1.038 1611 1.15 1612 0.808 1613 0.884 1614 0.788 1615 0.751 1616 0.802 1617 0.846 1618 1.06 1619 1.532 1620 1.46 1621 1.416 1622 1.146 1623 1.127 1624 0.986 1625 0.828 1626 1.302 1627 1.089 1628 1.268 1629 0.91 1630 1.002 1631 1.069 1632 1.082 1633 1.28 1634 1.361 1635 1.307 1636 1.455 1637 1.062 1638 1.157 1639 1.341 1640 1.022 1641 1.062 1642 1.114 1643 1.111 1644 0.984 1645 0.983 1646 1.169 1647 1.383 1648 1.37 1649 1.214 1650 1.351 1651 0.763 1652 1.011 1653 1.206 1654 1.039 1655 0.629 1656 0.684 1657 0.806 1658 0.644 1659 0.689 1660 0.8 1661 0.457 1662 0.423 1663 0.684 1664 0.658 1665 0.497 1666 0.639 1667 0.721 1668 0.766 1669 0.627 1670 0.639 1671 0.747 1672 0.887 1673 0.797 1674 0.717 1675 0.857 1676 0.856 1677 0.678 1678 1.125 1679 1.209 1680 1.159 1681 1.023 1682 0.845 1683 1.273 1684 1.137 1685 1.189 1686 0.806 1687 0.888 1688 0.919 1689 0.74 1690 0.584 1691 0.812 1692 0.822 1693 0.826 1694 1.284 1695 1.192 1696 0.949 1697 0.918 1698 0.94 1699 0.826 1700 0.958 1701 1.052 1702 1.033 1703 1.128 1704 1.049 1705 0.945 1706 0.856 1707 1.019 1708 1.13 1709 1.167 1710 1.105 1711 1.056 1712 0.856 1713 0.974 1714 0.944 1715 1.071 1716 0.933 1717 0.962 1718 1.047 1719 0.758 1720 1.071 1721 0.747 1722 0.878 1723 0.997 1724 0.965 1725 0.952 1726 1.029 1727 0.922 1728 1.198 1729 1.108 1730 0.991 1731 1.093 1732 0.994 1733 1.001 1734 0.922 1735 0.873 1736 1.138 1737 0.814 1738 0.892 1739 1.116 1740 1.21 1741 0.964 1742 1.034 1743 0.503 1744 0.74 1745 0.779 1746 0.939 1747 0.958 1748 0.819 1749 1.25 1750 1.127 1751 0.783 1752 0.862 1753 0.928 1754 1.086 1755 1.028 1756 0.947 1757 0.892 1758 1.107 1759 1.224 1760 1.206 1761 1.387 1762 0.964 1763 1.015 1764 1.051 1765 1.279 1766 1.242 1767 1.03 1768 0.981 1769 1.242 1770 1.109 1771 1.227 1772 0.986 1773 1.022 1774 0.907 1775 0.798 1776 0.859 1777 0.729 1778 0.775 1779 0.736 1780 0.763 1781 0.967 1782 0.812 1783 0.752 1784 0.964 1785 0.804 1786 0.745 1787 0.674 1788 1.075 1789 0.894 1790 1.059 1791 0.952 1792 0.782 1793 0.974 1794 1.159 1795 0.918 1796 1.174 1797 1.017 1798 0.953 1799 1.036 1800 1.102 1801 0.662 1802 0.74 1803 0.673 1804 0.81 1805 0.72 1806 0.898 1807 0.842 1808 0.893 1809 1.008 1810 0.815 1811 0.699 1812 0.843 1813 0.703 1814 0.902 1815 0.833 1816 0.952 1817 0.868 1818 0.731 1819 0.656 1820 0.861 1821 0.847 1822 0.83 1823 0.941 1824 0.968 1825 0.865 1826 0.979 1827 0.945 1828 1.02 1829 1.0 1830 1.001 1831 1.03 1832 1.127 1833 1.174 1834 1.152 1835 0.994 1836 0.943 1837 1.201 1838 1.323 1839 0.856 1840 1.152 1841 0.833 1842 0.774 1843 0.881 1844 0.857 1845 0.877 1846 0.96 1847 1.001 1848 0.98 1849 1.073 1850 1.08 1851 1.114 1852 1.305 1853 1.001 1854 1.004 1855 1.155 1856 1.243 1857 1.237 1858 1.065 1859 0.753 1860 0.935 1861 0.801 1862 0.815 1863 0.902 1864 0.893 1865 0.704 1866 0.947 1867 0.903 1868 1.318 1869 0.872 1870 0.835 1871 0.782 1872 0.989 1873 0.93 1874 0.792 1875 0.49 1876 1.077 1877 0.863 1878 0.865 1879 0.687 1880 0.989 1881 1.025 1882 1.017 1883 1.129 1884 1.268 1885 0.985 1886 0.973 1887 0.977 1888 0.795 1889 0.696 1890 0.722 1891 0.708 1892 0.891 1893 0.587 1894 0.824 1895 0.87 1896 0.851 1897 0.521 1898 0.918 1899 0.928 1900 0.904 1901 0.857 1902 0.653 1903 0.821 1904 0.864 1905 0.75 1906 0.616 1907 0.943 1908 0.863 1909 0.631 1910 0.847 1911 0.72 1912 0.847 1913 0.903 1914 1.029 1915 1.023 1916 0.997 1917 0.85 1918 1.069 1919 1.089 1920 0.97 1921 1.139 1922 1.23 1923 1.361 1924 1.101 1925 1.266 1926 1.365 1927 1.066 1928 1.206 1929 1.299 1930 1.077 1931 1.119 1932 1.094 1933 1.26 1934 1.286 1935 1.251 1936 0.895 1937 0.793 1938 1.422 1939 1.364 1940 1.606 1941 1.336 1942 1.055 1943 0.966 1944 0.993 1945 1.051 1946 1.487 1947 1.095 1948 1.019 1949 0.969 1950 1.22 1951 1.647 1952 0.998 1953 0.946 1954 1.007 1955 1.023 1956 1.219 1957 0.841 1958 0.889 1959 1.125 1960 1.03 1961 1.339 1962 0.863 1963 1.097 1964 1.262 1965 1.042 1966 0.921 1967 0.671 1968 0.962 1969 1.124 1970 0.838 1971 1.297 1972 0.888 1973 0.787 1974 0.99