# northamerica_usa_nm556 - Cat Mesa - 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: # # Original_Source_URL: # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: northamerica_usa_nm556 - Cat Mesa - 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. #-------------------- # Funding_Agency # Funding_Agency_Name: Swiss National Science Foundation # Grant: #-------------------- # Site_Information # Site_Name: Cat Mesa # Location: # Country: United States # Northernmost_Latitude: 35.78 # Southernmost_Latitude: 35.78 # Easternmost_Longitude: -106.62 # Westernmost_Longitude: -106.62 # Elevation: 2515 m #-------------------- # Data_Collection # Collection_Name: northamerica_usa_nm556B # Earliest_Year: 1620 # Most_Recent_Year: 1986 # Time_Unit: y_ad # Core_Length: # Notes: {"sensitivity":"moisture"}{"T1":"4.40501453362"}{"T2":"16.3775229745"}{"M1":"0.0235279985091"}{"M2":"0.511606160505"} #-------------------- # Species # Species_Name: ponderosa pine # Species_Code: PIPO #-------------------- # 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 1620 0.897 1621 1.351 1622 1.007 1623 0.948 1624 0.743 1625 0.75 1626 1.145 1627 0.847 1628 0.725 1629 0.881 1630 1.197 1631 0.571 1632 0.541 1633 1.36 1634 1.229 1635 1.277 1636 1.329 1637 1.33 1638 0.711 1639 0.683 1640 0.723 1641 0.715 1642 0.841 1643 0.973 1644 1.215 1645 0.837 1646 1.191 1647 1.126 1648 0.688 1649 0.681 1650 0.873 1651 1.254 1652 1.337 1653 0.951 1654 0.588 1655 0.715 1656 0.733 1657 0.687 1658 0.78 1659 0.584 1660 1.002 1661 1.445 1662 1.603 1663 1.37 1664 0.542 1665 1.076 1666 0.897 1667 0.57 1668 0.607 1669 0.687 1670 0.709 1671 0.588 1672 0.944 1673 1.125 1674 1.279 1675 1.206 1676 0.721 1677 0.754 1678 0.954 1679 1.01 1680 1.469 1681 1.14 1682 1.353 1683 1.497 1684 1.095 1685 0.022 1686 0.983 1687 1.013 1688 1.187 1689 1.605 1690 1.181 1691 0.902 1692 1.808 1693 1.148 1694 1.247 1695 1.438 1696 0.562 1697 1.366 1698 0.531 1699 1.748 1700 0.965 1701 1.559 1702 0.721 1703 1.222 1704 0.312 1705 0.538 1706 1.061 1707 0.834 1708 1.102 1709 1.071 1710 1.502 1711 0.868 1712 1.25 1713 1.051 1714 0.73 1715 0.577 1716 0.528 1717 0.922 1718 1.233 1719 0.592 1720 1.54 1721 1.334 1722 1.374 1723 1.339 1724 0.892 1725 0.979 1726 1.201 1727 0.848 1728 1.144 1729 0.143 1730 0.655 1731 0.785 1732 0.753 1733 0.393 1734 0.968 1735 0.313 1736 0.538 1737 0.413 1738 0.534 1739 0.198 1740 0.734 1741 0.832 1742 0.823 1743 1.396 1744 1.291 1745 1.212 1746 1.681 1747 2.088 1748 0.19 1749 1.801 1750 0.8 1751 1.282 1752 0.452 1753 1.076 1754 1.407 1755 1.305 1756 0.696 1757 0.324 1758 1.481 1759 1.41 1760 0.979 1761 1.794 1762 1.676 1763 1.111 1764 1.61 1765 1.266 1766 1.798 1767 1.693 1768 1.504 1769 1.249 1770 1.394 1771 1.52 1772 1.116 1773 0.27 1774 0.965 1775 0.809 1776 0.955 1777 0.686 1778 0.922 1779 0.704 1780 0.612 1781 0.617 1782 0.428 1783 1.151 1784 1.45 1785 0.912 1786 0.513 1787 1.388 1788 0.926 1789 0.72 1790 1.381 1791 1.078 1792 1.142 1793 1.817 1794 1.289 1795 1.355 1796 1.158 1797 1.015 1798 0.965 1799 1.405 1800 1.516 1801 0.793 1802 1.083 1803 1.345 1804 1.27 1805 0.841 1806 0.63 1807 1.108 1808 1.196 1809 1.249 1810 1.025 1811 1.098 1812 1.192 1813 0.869 1814 0.831 1815 1.348 1816 1.239 1817 0.936 1818 0.489 1819 0.844 1820 0.691 1821 0.986 1822 0.337 1823 0.664 1824 0.814 1825 1.081 1826 1.175 1827 1.145 1828 1.261 1829 1.131 1830 1.378 1831 1.126 1832 1.369 1833 1.185 1834 1.091 1835 0.816 1836 1.21 1837 1.126 1838 1.172 1839 1.709 1840 1.859 1841 1.68 1842 0.985 1843 1.219 1844 1.385 1845 1.124 1846 1.088 1847 0.308 1848 0.774 1849 0.991 1850 0.854 1851 0.42 1852 1.136 1853 0.968 1854 1.118 1855 0.972 1856 1.104 1857 0.977 1858 1.397 1859 0.787 1860 1.065 1861 0.226 1862 0.615 1863 0.737 1864 0.537 1865 0.522 1866 0.879 1867 0.89 1868 1.06 1869 1.226 1870 0.933 1871 1.004 1872 1.362 1873 1.155 1874 1.023 1875 1.207 1876 0.72 1877 1.23 1878 1.12 1879 0.801 1880 0.317 1881 0.838 1882 1.107 1883 1.018 1884 1.11 1885 1.271 1886 1.061 1887 1.528 1888 1.409 1889 1.315 1890 1.026 1891 1.398 1892 1.449 1893 0.711 1894 1.133 1895 1.476 1896 0.676 1897 1.527 1898 1.522 1899 0.593 1900 0.277 1901 0.787 1902 0.479 1903 1.196 1904 0.491 1905 1.174 1906 0.838 1907 1.567 1908 1.732 1909 1.179 1910 0.863 1911 1.606 1912 1.261 1913 1.101 1914 1.749 1915 1.294 1916 1.329 1917 1.017 1918 1.371 1919 1.397 1920 1.337 1921 1.453 1922 0.739 1923 0.681 1924 1.219 1925 0.51 1926 1.076 1927 0.736 1928 0.641 1929 0.852 1930 0.871 1931 0.783 1932 0.754 1933 0.767 1934 0.722 1935 0.973 1936 0.991 1937 0.982 1938 0.848 1939 0.903 1940 0.921 1941 1.136 1942 1.117 1943 1.036 1944 0.978 1945 0.94 1946 0.303 1947 0.713 1948 0.824 1949 1.077 1950 0.442 1951 -0.017 1952 0.808 1953 0.32 1954 0.462 1955 0.078 1956 0.255 1957 0.462 1958 0.527 1959 0.502 1960 0.54 1961 0.626 1962 0.572 1963 0.363 1964 0.409 1965 0.697 1966 0.645 1967 -0.009 1968 0.73 1969 0.649 1970 0.901 1971 0.222 1972 0.943 1973 0.625 1974 0.301 1975 0.835 1976 0.385 1977 0.274 1978 0.647 1979 0.546 1980 0.55 1981 0.539 1982 0.654 1983 0.681 1984 0.681 1985 0.948 1986 1.013