# australia_newz012 - Mangawhero R.B. - 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/3136 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: australia_newz012 - Mangawhero R.B. - 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: Mangawhero R.B. # Location: # Country: New Zealand # Northernmost_Latitude: -39.35 # Southernmost_Latitude: -39.35 # Easternmost_Longitude: 175.48 # Westernmost_Longitude: 175.48 # Elevation: 1000 m #-------------------- # Data_Collection # Collection_Name: australia_newz012B # Earliest_Year: 1720 # 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":"6.03401090168","T2":"18.268657331","M1":"0.0227530835482","M2":"0.385937590619"}} #-------------------- # Species # Species_Name: New Zealand cedar # Species_Code: LIBI #-------------------- # 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 1720 0.5 1721 0.592 1722 0.543 1723 0.846 1724 0.994 1725 0.947 1726 0.81 1727 0.848 1728 1.007 1729 0.769 1730 0.846 1731 0.683 1732 0.554 1733 0.717 1734 0.707 1735 0.646 1736 0.758 1737 0.711 1738 0.728 1739 0.73 1740 0.725 1741 0.705 1742 0.881 1743 0.955 1744 0.942 1745 1.103 1746 1.044 1747 1.184 1748 1.169 1749 1.19 1750 0.962 1751 0.989 1752 0.841 1753 0.961 1754 1.087 1755 0.978 1756 0.923 1757 1.068 1758 0.917 1759 0.854 1760 1.218 1761 1.359 1762 1.227 1763 1.267 1764 1.189 1765 1.03 1766 1.261 1767 1.038 1768 1.058 1769 1.402 1770 1.122 1771 1.444 1772 1.408 1773 1.175 1774 1.051 1775 1.039 1776 0.918 1777 1.156 1778 1.18 1779 1.083 1780 1.014 1781 0.992 1782 0.864 1783 0.886 1784 0.828 1785 0.865 1786 0.907 1787 0.964 1788 0.98 1789 1.172 1790 1.299 1791 1.294 1792 1.162 1793 1.428 1794 1.164 1795 1.068 1796 1.106 1797 1.673 1798 1.344 1799 1.704 1800 1.681 1801 1.609 1802 1.556 1803 0.982 1804 1.117 1805 1.296 1806 1.098 1807 0.986 1808 0.788 1809 0.73 1810 0.75 1811 0.631 1812 0.686 1813 0.767 1814 0.932 1815 1.095 1816 0.854 1817 0.82 1818 0.991 1819 0.93 1820 0.844 1821 0.843 1822 0.842 1823 0.909 1824 1.008 1825 1.075 1826 0.89 1827 1.177 1828 1.052 1829 0.947 1830 0.774 1831 0.783 1832 0.64 1833 0.57 1834 0.612 1835 0.634 1836 0.95 1837 0.991 1838 1.107 1839 1.038 1840 0.686 1841 0.961 1842 0.959 1843 1.031 1844 0.812 1845 0.968 1846 0.697 1847 0.526 1848 0.764 1849 0.513 1850 0.517 1851 0.788 1852 0.957 1853 1.004 1854 0.925 1855 0.919 1856 0.986 1857 1.001 1858 0.872 1859 0.875 1860 0.746 1861 0.924 1862 0.955 1863 1.197 1864 1.233 1865 1.047 1866 1.18 1867 0.948 1868 1.103 1869 1.139 1870 1.067 1871 1.112 1872 0.54 1873 0.836 1874 0.931 1875 1.027 1876 1.088 1877 1.074 1878 1.136 1879 1.135 1880 0.957 1881 1.045 1882 0.913 1883 0.833 1884 0.914 1885 0.97 1886 0.909 1887 0.823 1888 0.908 1889 1.059 1890 1.333 1891 1.275 1892 1.535 1893 1.813 1894 1.787 1895 1.877 1896 1.969 1897 1.69 1898 1.641 1899 1.557 1900 1.504 1901 1.332 1902 1.011 1903 0.919 1904 0.748 1905 0.962 1906 0.856 1907 0.407 1908 0.576 1909 0.789 1910 0.82 1911 1.024 1912 0.928 1913 0.993 1914 0.976 1915 0.859 1916 0.606 1917 0.732 1918 0.601 1919 0.638 1920 0.556 1921 0.705 1922 0.68 1923 0.677 1924 0.68 1925 0.705 1926 0.894 1927 0.963 1928 1.157 1929 1.052 1930 0.752 1931 0.93 1932 1.332 1933 1.382 1934 1.303 1935 0.733 1936 0.823 1937 0.953 1938 0.624 1939 0.619 1940 0.697 1941 0.582 1942 0.724 1943 0.74 1944 0.72 1945 0.617 1946 0.564 1947 0.63 1948 0.553 1949 0.548 1950 0.556 1951 0.52 1952 0.521 1953 0.607 1954 0.582 1955 0.54 1956 0.605 1957 0.851 1958 1.076 1959 1.211 1960 1.299 1961 1.026 1962 1.174 1963 1.453 1964 1.462 1965 1.282 1966 1.247 1967 1.739 1968 1.263 1969 1.28 1970 1.25 1971 1.454 1972 1.383 1973 1.36 1974 1.214 1975 1.257 1976 1.347