# australia_newz075 - Werberforce - 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/5378 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: australia_newz075 - Werberforce - 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: Werberforce # Location: # Country: New Zealand # Northernmost_Latitude: -43.07 # Southernmost_Latitude: -43.07 # Easternmost_Longitude: 171.28 # Westernmost_Longitude: 171.28 # Elevation: 780 m #-------------------- # Data_Collection # Collection_Name: australia_newz075B # Earliest_Year: 1756 # Most_Recent_Year: 1992 # 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":"4.91023034644","T2":"15.5417733695","M1":"0.0222975390942","M2":"0.407371472032"}} #-------------------- # 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 1756 1.304 1757 1.12 1758 1.063 1759 1.12 1760 0.653 1761 0.83 1762 0.827 1763 0.735 1764 0.666 1765 0.625 1766 0.764 1767 0.841 1768 1.116 1769 0.864 1770 1.285 1771 1.245 1772 1.13 1773 1.077 1774 1.111 1775 0.977 1776 1.276 1777 1.221 1778 1.25 1779 1.421 1780 1.216 1781 0.982 1782 1.039 1783 0.904 1784 0.907 1785 1.281 1786 1.276 1787 1.167 1788 1.325 1789 0.978 1790 0.718 1791 0.782 1792 0.678 1793 0.711 1794 0.798 1795 0.916 1796 1.407 1797 0.963 1798 0.752 1799 1.197 1800 1.156 1801 0.991 1802 0.999 1803 0.979 1804 0.911 1805 0.944 1806 1.073 1807 1.09 1808 0.999 1809 1.04 1810 1.178 1811 1.157 1812 1.373 1813 1.108 1814 1.182 1815 1.129 1816 1.006 1817 0.984 1818 0.905 1819 0.785 1820 0.809 1821 0.97 1822 0.923 1823 1.023 1824 1.116 1825 1.027 1826 0.865 1827 1.094 1828 1.185 1829 1.111 1830 0.958 1831 1.015 1832 0.825 1833 0.583 1834 0.629 1835 0.7 1836 0.792 1837 0.964 1838 1.123 1839 0.982 1840 0.858 1841 1.265 1842 1.045 1843 0.96 1844 0.784 1845 1.304 1846 1.104 1847 0.819 1848 0.883 1849 0.676 1850 1.008 1851 1.166 1852 1.125 1853 1.154 1854 0.865 1855 1.029 1856 0.914 1857 0.863 1858 0.893 1859 0.753 1860 0.873 1861 1.097 1862 0.98 1863 1.089 1864 1.102 1865 0.898 1866 1.185 1867 1.018 1868 1.074 1869 1.144 1870 0.968 1871 0.943 1872 0.677 1873 0.918 1874 1.001 1875 1.024 1876 0.789 1877 0.985 1878 0.829 1879 1.095 1880 1.034 1881 1.007 1882 0.889 1883 0.861 1884 0.921 1885 0.787 1886 0.845 1887 0.856 1888 0.886 1889 0.929 1890 0.934 1891 0.998 1892 1.191 1893 1.178 1894 0.937 1895 0.927 1896 2.177 1897 1.749 1898 1.249 1899 1.216 1900 1.309 1901 0.96 1902 1.059 1903 1.151 1904 0.808 1905 0.556 1906 0.655 1907 0.619 1908 0.696 1909 0.701 1910 0.668 1911 0.884 1912 0.909 1913 1.071 1914 0.803 1915 0.799 1916 0.532 1917 0.867 1918 0.853 1919 0.797 1920 0.848 1921 1.097 1922 1.037 1923 0.837 1924 0.756 1925 0.858 1926 0.9 1927 0.945 1928 1.16 1929 1.0 1930 0.844 1931 1.132 1932 1.279 1933 1.406 1934 1.229 1935 0.589 1936 0.69 1937 0.713 1938 0.503 1939 0.688 1940 1.175 1941 1.153 1942 0.946 1943 1.062 1944 1.288 1945 1.228 1946 1.216 1947 1.201 1948 1.244 1949 1.15 1950 1.222 1951 0.914 1952 1.018 1953 1.204 1954 1.085 1955 0.92 1956 0.669 1957 0.743 1958 1.066 1959 1.312 1960 1.309 1961 1.035 1962 0.894 1963 1.124 1964 1.163 1965 1.281 1966 1.139 1967 1.186 1968 0.93 1969 1.226 1970 1.031 1971 0.816 1972 0.95 1973 0.733 1974 0.69 1975 0.781 1976 0.827 1977 0.902 1978 0.77 1979 0.892 1980 1.093 1981 1.015 1982 1.098 1983 0.929 1984 0.924 1985 0.807 1986 0.637 1987 1.098 1988 0.886 1989 0.907 1990 0.759 1991 0.841 1992 0.923