# australia_newz022 - Waipoua - 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/3148 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: australia_newz022 - Waipoua - 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: Waipoua # Location: # Country: New Zealand # Northernmost_Latitude: -35.68 # Southernmost_Latitude: -35.68 # Easternmost_Longitude: 173.55 # Westernmost_Longitude: 173.55 # Elevation: 244 m #-------------------- # Data_Collection # Collection_Name: australia_newz022B # Earliest_Year: 1676 # Most_Recent_Year: 1976 # 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":"3.53729591918","T2":"14.2750894303","M1":"0.0229244707471","M2":"0.585143064426"}} #-------------------- # Species # Species_Name: tanekaha celery top pine # Species_Code: PHTR #-------------------- # 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 1676 1.024 1677 0.974 1678 0.843 1679 0.797 1680 0.804 1681 0.804 1682 0.486 1683 0.761 1684 0.813 1685 0.679 1686 0.873 1687 0.772 1688 0.841 1689 0.809 1690 0.739 1691 0.827 1692 0.979 1693 0.703 1694 0.965 1695 1.155 1696 0.596 1697 0.748 1698 1.026 1699 0.809 1700 1.101 1701 0.696 1702 0.794 1703 1.042 1704 0.829 1705 0.731 1706 0.835 1707 0.562 1708 0.79 1709 0.797 1710 0.844 1711 0.776 1712 0.786 1713 0.765 1714 1.045 1715 0.747 1716 0.949 1717 0.759 1718 0.741 1719 0.92 1720 0.542 1721 0.779 1722 0.791 1723 0.721 1724 0.385 1725 0.89 1726 0.861 1727 0.635 1728 0.739 1729 0.615 1730 0.552 1731 0.649 1732 0.753 1733 0.774 1734 0.862 1735 0.724 1736 1.085 1737 1.013 1738 0.668 1739 0.831 1740 0.757 1741 0.508 1742 0.863 1743 0.605 1744 0.865 1745 0.736 1746 0.763 1747 1.109 1748 0.794 1749 0.89 1750 0.711 1751 0.868 1752 0.638 1753 0.739 1754 0.815 1755 0.743 1756 0.631 1757 0.958 1758 0.857 1759 0.892 1760 0.637 1761 1.019 1762 0.855 1763 0.807 1764 0.944 1765 0.652 1766 0.941 1767 0.664 1768 1.087 1769 1.083 1770 0.697 1771 0.989 1772 0.994 1773 0.876 1774 0.723 1775 0.911 1776 0.653 1777 1.005 1778 0.757 1779 1.145 1780 0.962 1781 0.866 1782 1.059 1783 1.005 1784 0.677 1785 1.112 1786 1.033 1787 0.963 1788 1.354 1789 1.161 1790 0.798 1791 1.275 1792 1.191 1793 1.231 1794 1.11 1795 1.419 1796 1.102 1797 1.34 1798 1.158 1799 1.466 1800 0.918 1801 1.117 1802 1.105 1803 1.422 1804 0.971 1805 0.877 1806 1.246 1807 1.057 1808 0.831 1809 1.305 1810 1.203 1811 1.045 1812 1.27 1813 1.036 1814 1.427 1815 1.226 1816 1.363 1817 1.197 1818 1.502 1819 0.989 1820 1.588 1821 1.221 1822 1.447 1823 1.089 1824 1.275 1825 1.029 1826 1.386 1827 1.182 1828 1.289 1829 1.504 1830 0.97 1831 1.431 1832 1.038 1833 1.368 1834 0.551 1835 1.008 1836 0.996 1837 0.995 1838 0.684 1839 1.128 1840 0.872 1841 1.26 1842 1.311 1843 1.548 1844 1.178 1845 1.688 1846 1.101 1847 0.661 1848 1.174 1849 0.841 1850 1.085 1851 0.824 1852 1.366 1853 1.341 1854 0.654 1855 1.435 1856 1.358 1857 1.12 1858 1.483 1859 1.062 1860 1.153 1861 0.832 1862 0.926 1863 0.496 1864 1.076 1865 0.767 1866 0.927 1867 0.564 1868 1.365 1869 1.003 1870 1.556 1871 1.715 1872 1.183 1873 1.636 1874 1.26 1875 1.416 1876 0.757 1877 1.691 1878 1.176 1879 0.817 1880 1.16 1881 1.343 1882 0.944 1883 1.255 1884 1.569 1885 0.816 1886 0.867 1887 0.545 1888 1.115 1889 0.765 1890 0.965 1891 1.031 1892 1.021 1893 0.828 1894 1.459 1895 0.975 1896 1.17 1897 0.996 1898 1.206 1899 1.064 1900 1.261 1901 1.576 1902 0.747 1903 1.215 1904 0.638 1905 1.387 1906 1.169 1907 0.396 1908 1.201 1909 0.897 1910 0.494 1911 0.968 1912 1.037 1913 0.299 1914 0.872 1915 0.677 1916 0.243 1917 0.856 1918 0.753 1919 1.023 1920 0.495 1921 0.967 1922 0.643 1923 1.019 1924 0.281 1925 1.062 1926 0.911 1927 0.558 1928 0.78 1929 0.922 1930 1.195 1931 0.735 1932 1.086 1933 0.972 1934 1.342 1935 0.44 1936 0.885 1937 0.725 1938 0.381 1939 1.103 1940 1.101 1941 0.438 1942 0.983 1943 0.792 1944 1.085 1945 1.126 1946 0.499 1947 1.085 1948 0.646 1949 1.0 1950 0.448 1951 1.283 1952 1.154 1953 0.741 1954 0.766 1955 0.831 1956 0.862 1957 1.013 1958 0.852 1959 1.033 1960 0.796 1961 1.019 1962 0.308 1963 1.015 1964 0.538 1965 0.937 1966 0.42 1967 1.051 1968 0.346 1969 0.994 1970 0.153 1971 0.824 1972 0.8 1973 0.727 1974 0.432 1975 0.812 1976 0.801