# australia_newz021 - Waiomu - 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/3147 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: australia_newz021 - Waiomu - 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: Waiomu # Location: # Country: New Zealand # Northernmost_Latitude: -37.03 # Southernmost_Latitude: -37.03 # Easternmost_Longitude: 175.53 # Westernmost_Longitude: 175.53 # Elevation: 61 m #-------------------- # Data_Collection # Collection_Name: australia_newz021B # Earliest_Year: 1701 # 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":"4.55818605281","T2":"11.7899262175","M1":"0.022568823217","M2":"0.493114743853"}} #-------------------- # 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 1701 0.478 1702 0.445 1703 0.548 1704 0.495 1705 0.388 1706 0.653 1707 0.447 1708 0.625 1709 0.399 1710 0.491 1711 0.41 1712 0.646 1713 0.496 1714 0.695 1715 0.386 1716 0.822 1717 0.5 1718 0.708 1719 0.578 1720 0.713 1721 0.434 1722 0.556 1723 0.558 1724 0.403 1725 0.614 1726 0.677 1727 0.638 1728 0.669 1729 0.626 1730 0.707 1731 0.649 1732 0.915 1733 1.011 1734 0.608 1735 0.519 1736 0.951 1737 0.858 1738 0.798 1739 0.627 1740 0.916 1741 0.698 1742 0.974 1743 0.771 1744 1.047 1745 1.002 1746 1.201 1747 0.956 1748 0.783 1749 0.813 1750 0.771 1751 0.851 1752 0.812 1753 0.918 1754 1.132 1755 1.288 1756 1.125 1757 1.517 1758 1.248 1759 1.107 1760 0.963 1761 1.27 1762 1.071 1763 1.163 1764 1.059 1765 1.059 1766 1.021 1767 1.044 1768 1.306 1769 1.193 1770 1.099 1771 0.96 1772 1.158 1773 0.932 1774 1.209 1775 1.119 1776 1.06 1777 1.433 1778 1.029 1779 1.413 1780 1.151 1781 1.333 1782 1.394 1783 1.264 1784 1.352 1785 1.351 1786 1.359 1787 1.293 1788 1.678 1789 1.337 1790 1.166 1791 1.56 1792 1.318 1793 1.602 1794 1.228 1795 1.58 1796 1.148 1797 1.498 1798 1.361 1799 1.596 1800 1.081 1801 1.27 1802 0.778 1803 1.41 1804 1.094 1805 1.214 1806 1.351 1807 1.034 1808 1.001 1809 1.075 1810 1.053 1811 0.954 1812 1.237 1813 0.947 1814 1.22 1815 1.11 1816 1.279 1817 1.039 1818 1.125 1819 0.736 1820 1.043 1821 0.826 1822 1.18 1823 0.984 1824 0.727 1825 0.902 1826 0.769 1827 1.001 1828 0.673 1829 1.267 1830 0.838 1831 1.253 1832 0.805 1833 1.248 1834 0.724 1835 1.118 1836 1.018 1837 1.199 1838 0.835 1839 0.999 1840 0.663 1841 1.075 1842 0.912 1843 1.268 1844 0.833 1845 1.162 1846 0.577 1847 0.523 1848 0.885 1849 0.554 1850 1.015 1851 0.882 1852 1.35 1853 1.029 1854 1.042 1855 1.205 1856 0.972 1857 1.077 1858 1.016 1859 0.664 1860 0.928 1861 0.838 1862 0.954 1863 0.824 1864 1.228 1865 0.743 1866 1.21 1867 0.679 1868 1.01 1869 0.893 1870 0.989 1871 0.83 1872 0.505 1873 0.841 1874 0.79 1875 1.065 1876 0.819 1877 1.245 1878 0.575 1879 1.23 1880 0.946 1881 1.283 1882 0.737 1883 1.264 1884 1.354 1885 0.895 1886 1.039 1887 0.959 1888 1.196 1889 0.823 1890 1.027 1891 0.973 1892 1.497 1893 1.179 1894 1.545 1895 1.213 1896 1.241 1897 1.042 1898 1.246 1899 1.088 1900 0.593 1901 1.293 1902 0.715 1903 0.979 1904 0.529 1905 1.075 1906 0.788 1907 0.869 1908 0.69 1909 0.827 1910 0.337 1911 0.825 1912 0.752 1913 0.497 1914 0.554 1915 0.514 1916 0.693 1917 0.695 1918 1.274 1919 1.272 1920 0.896 1921 1.111 1922 0.627 1923 0.983 1924 0.364 1925 1.052 1926 0.803 1927 1.044 1928 0.552 1929 0.677 1930 0.7 1931 0.69 1932 0.712 1933 0.733 1934 0.873 1935 0.552 1936 0.806 1937 0.782 1938 0.763 1939 1.14 1940 1.14 1941 1.015 1942 0.929 1943 0.995 1944 0.923 1945 0.991 1946 0.86 1947 1.062 1948 0.652 1949 0.931 1950 0.456 1951 0.896 1952 0.515 1953 0.945 1954 0.559 1955 0.6 1956 0.958 1957 0.98 1958 0.934 1959 1.185 1960 1.26 1961 1.161 1962 0.996 1963 1.419 1964 1.348 1965 1.516 1966 1.527 1967 1.273 1968 1.282 1969 1.208 1970 0.547 1971 0.706 1972 0.911 1973 0.612 1974 0.829 1975 1.267 1976 1.349