# southamerica_arge089 - Río Horqueta - 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/5187 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: southamerica_arge089 - Río Horqueta - 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: Río Horqueta # Location: # Country: Argentina # Northernmost_Latitude: -41.83 # Southernmost_Latitude: -41.83 # Easternmost_Longitude: -71.77 # Westernmost_Longitude: -71.77 # Elevation: 950 m #-------------------- # Data_Collection # Collection_Name: southamerica_arge089B # Earliest_Year: 539 # Most_Recent_Year: 1993 # Time_Unit: y_ad # Core_Length: # Notes: {"database":{"database1":"LMR","database2":"Breits"}} {"climateInterpretation":{"basis":"", "climateVariable":"T", "climateVariableDetail":"air", "interpDirection":"positive", "seasonality":"[-12, 1, 2]"}}{"VSLite_parameters":{"T1":"2.82712427908","T2":"12.1250842646","M1":"0.0223376102608","M2":"0.589782178961"}} #-------------------- # Species # Species_Name: alerce cypress # Species_Code: FICU #-------------------- # 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 539 0.868 540 0.855 541 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1.276 1592 1.131 1593 1.505 1594 1.391 1595 1.427 1596 1.606 1597 1.122 1598 1.259 1599 0.757 1600 0.747 1601 1.019 1602 1.067 1603 1.111 1604 0.8 1605 0.884 1606 1.228 1607 0.992 1608 0.818 1609 1.403 1610 1.209 1611 1.155 1612 0.823 1613 1.07 1614 1.215 1615 1.201 1616 1.037 1617 1.031 1618 1.13 1619 1.166 1620 1.507 1621 1.208 1622 1.125 1623 1.13 1624 1.119 1625 1.333 1626 1.019 1627 0.884 1628 1.121 1629 1.049 1630 1.285 1631 1.082 1632 0.81 1633 1.124 1634 0.926 1635 0.981 1636 1.259 1637 1.2 1638 1.241 1639 0.962 1640 0.997 1641 1.124 1642 1.117 1643 1.085 1644 1.699 1645 1.373 1646 1.133 1647 1.156 1648 1.262 1649 1.399 1650 1.096 1651 0.865 1652 1.073 1653 0.757 1654 1.299 1655 0.861 1656 0.976 1657 0.911 1658 1.084 1659 1.144 1660 0.971 1661 0.929 1662 1.008 1663 1.214 1664 0.958 1665 0.455 1666 0.579 1667 0.796 1668 0.594 1669 0.646 1670 0.425 1671 0.721 1672 0.8 1673 0.701 1674 0.62 1675 0.801 1676 0.658 1677 0.866 1678 0.915 1679 0.845 1680 0.935 1681 1.129 1682 1.112 1683 1.081 1684 1.249 1685 0.998 1686 0.792 1687 1.042 1688 0.831 1689 0.698 1690 0.783 1691 1.119 1692 1.131 1693 0.511 1694 1.025 1695 0.703 1696 0.726 1697 0.841 1698 0.791 1699 0.431 1700 0.478 1701 0.589 1702 0.672 1703 0.824 1704 0.939 1705 1.159 1706 1.103 1707 1.131 1708 1.208 1709 1.296 1710 1.026 1711 1.087 1712 1.056 1713 1.348 1714 1.243 1715 1.218 1716 1.189 1717 1.114 1718 0.508 1719 0.704 1720 0.929 1721 0.83 1722 0.836 1723 0.884 1724 0.763 1725 1.042 1726 0.986 1727 1.047 1728 1.216 1729 1.049 1730 1.169 1731 1.202 1732 1.27 1733 1.039 1734 0.747 1735 1.316 1736 1.352 1737 0.779 1738 0.815 1739 1.053 1740 1.027 1741 1.024 1742 0.839 1743 0.812 1744 0.816 1745 0.747 1746 0.826 1747 0.672 1748 0.463 1749 0.761 1750 0.771 1751 0.581 1752 0.772 1753 0.934 1754 1.01 1755 0.477 1756 0.64 1757 0.958 1758 0.943 1759 1.072 1760 0.9 1761 0.997 1762 0.975 1763 1.007 1764 1.134 1765 0.903 1766 0.661 1767 0.818 1768 0.722 1769 0.644 1770 0.501 1771 0.574 1772 0.437 1773 0.551 1774 0.817 1775 0.662 1776 0.634 1777 0.615 1778 1 1779 0.651 1780 0.967 1781 0.985 1782 0.948 1783 0.949 1784 1.151 1785 0.988 1786 0.977 1787 1.161 1788 1.077 1789 1.032 1790 1.058 1791 0.871 1792 0.753 1793 0.885 1794 0.981 1795 0.941 1796 0.993 1797 1.261 1798 1.046 1799 1.084 1800 1.275 1801 1.478 1802 1.431 1803 1.424 1804 1.174 1805 1.041 1806 1.245 1807 1.013 1808 1.33 1809 1.221 1810 1.06 1811 0.834 1812 0.921 1813 0.866 1814 0.68 1815 0.488 1816 0.714 1817 0.825 1818 0.602 1819 0.593 1820 0.674 1821 0.467 1822 0.81 1823 1.003 1824 0.476 1825 0.431 1826 0.787 1827 0.892 1828 1.084 1829 1.2 1830 0.886 1831 1.136 1832 1.328 1833 0.721 1834 0.795 1835 1.144 1836 0.991 1837 1.029 1838 1.167 1839 0.976 1840 0.613 1841 0.692 1842 0.987 1843 0.574 1844 0.777 1845 0.728 1846 0.872 1847 0.953 1848 0.926 1849 1.326 1850 0.859 1851 0.318 1852 0.551 1853 0.806 1854 0.803 1855 0.835 1856 1.029 1857 0.962 1858 0.974 1859 0.821 1860 0.681 1861 1.073 1862 0.891 1863 1.186 1864 1.111 1865 0.774 1866 0.917 1867 0.892 1868 1.295 1869 1.055 1870 1.225 1871 0.836 1872 1.134 1873 1.178 1874 0.985 1875 1.3 1876 1.201 1877 0.532 1878 0.828 1879 0.751 1880 0.952 1881 0.809 1882 0.773 1883 0.726 1884 1.106 1885 0.893 1886 1.115 1887 1.06 1888 0.861 1889 1.081 1890 1.015 1891 1.033 1892 1.073 1893 1.125 1894 1.2 1895 1.167 1896 1.414 1897 0.721 1898 0.865 1899 0.924 1900 0.884 1901 1.105 1902 1.094 1903 1.281 1904 1.444 1905 1.222 1906 0.993 1907 1.21 1908 1.235 1909 1.188 1910 1.248 1911 0.989 1912 1.118 1913 1.23 1914 0.946 1915 0.986 1916 0.986 1917 1.317 1918 1.002 1919 0.574 1920 0.811 1921 1.097 1922 1.219 1923 0.863 1924 1.231 1925 1.17 1926 1.363 1927 0.796 1928 1.108 1929 1.443 1930 1.204 1931 1.1 1932 1.227 1933 1.235 1934 1.232 1935 1.422 1936 0.887 1937 0.999 1938 0.983 1939 1.171 1940 0.92 1941 1.191 1942 1.02 1943 0.897 1944 0.779 1945 0.97 1946 1.081 1947 1.171 1948 1.077 1949 0.965 1950 1.178 1951 0.983 1952 0.932 1953 0.927 1954 0.971 1955 0.604 1956 0.905 1957 0.671 1958 0.878 1959 0.937 1960 0.468 1961 0.592 1962 0.793 1963 0.859 1964 0.99 1965 0.79 1966 1.016 1967 0.863 1968 1.138 1969 0.995 1970 1.019 1971 1.144 1972 1.175 1973 0.881 1974 1.28 1975 0.793 1976 1.23 1977 1.403 1978 0.942 1979 1.061 1980 1.224 1981 1.147 1982 1.008 1983 0.909 1984 0.924 1985 1.174 1986 1.021 1987 1.081 1988 0.777 1989 0.866 1990 0.961 1991 0.855 1992 0.492 1993 0.798