# australia_newz077 - Putara - 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/3058 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: australia_newz077 - Putara - 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: Putara # Location: # Country: New Zealand # Northernmost_Latitude: -40.67 # Southernmost_Latitude: -40.67 # Easternmost_Longitude: 175.52 # Westernmost_Longitude: 175.52 # Elevation: 650 m #-------------------- # Data_Collection # Collection_Name: australia_newz077B # Earliest_Year: 1723 # Most_Recent_Year: 1993 # 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":"5.16615316053","T2":"17.0061052196","M1":"0.0222915755244","M2":"0.506018255025"}} #-------------------- # Species # Species_Name: pink pine # Species_Code: HABI #-------------------- # 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 1723 0.851 1724 0.997 1725 1.087 1726 1.062 1727 1.1 1728 1.296 1729 1.333 1730 1.47 1731 1.52 1732 1.328 1733 1.323 1734 1.474 1735 1.412 1736 1.337 1737 1.151 1738 1.187 1739 1.289 1740 1.096 1741 1.361 1742 1.316 1743 1.3 1744 1.148 1745 0.964 1746 0.877 1747 0.857 1748 0.914 1749 0.99 1750 0.741 1751 0.934 1752 1.086 1753 1.084 1754 1.058 1755 1.095 1756 1.202 1757 1.184 1758 1.084 1759 1.094 1760 1.001 1761 1.105 1762 1.12 1763 0.999 1764 0.932 1765 0.98 1766 1.103 1767 1.196 1768 0.947 1769 1.042 1770 0.977 1771 1.139 1772 1.234 1773 1.231 1774 1.353 1775 1.278 1776 1.358 1777 1.31 1778 1.414 1779 1.327 1780 1.444 1781 1.547 1782 1.367 1783 1.475 1784 1.398 1785 1.265 1786 1.399 1787 1.057 1788 0.961 1789 1.153 1790 1.073 1791 1.006 1792 0.974 1793 1.071 1794 1.232 1795 1.141 1796 1.148 1797 1.227 1798 1.045 1799 1.031 1800 1.192 1801 0.891 1802 1.077 1803 1.069 1804 0.999 1805 1.023 1806 0.959 1807 0.893 1808 0.987 1809 1.045 1810 0.967 1811 0.955 1812 0.974 1813 0.772 1814 0.885 1815 0.817 1816 0.794 1817 0.774 1818 0.808 1819 0.905 1820 0.907 1821 1.054 1822 0.975 1823 0.932 1824 0.967 1825 0.941 1826 0.733 1827 0.893 1828 0.909 1829 0.911 1830 1.025 1831 1.164 1832 0.956 1833 0.87 1834 0.664 1835 0.758 1836 0.865 1837 0.887 1838 0.864 1839 0.818 1840 0.8 1841 0.962 1842 0.789 1843 0.838 1844 0.758 1845 0.766 1846 0.68 1847 0.653 1848 0.782 1849 0.783 1850 0.89 1851 0.871 1852 0.829 1853 0.848 1854 0.773 1855 0.7 1856 0.707 1857 0.731 1858 0.749 1859 0.804 1860 0.76 1861 0.89 1862 1.022 1863 0.926 1864 1.03 1865 0.976 1866 1.156 1867 1.011 1868 0.936 1869 0.928 1870 0.886 1871 0.695 1872 0.64 1873 0.748 1874 0.798 1875 0.826 1876 0.952 1877 0.897 1878 0.686 1879 0.64 1880 0.637 1881 0.736 1882 0.773 1883 0.707 1884 0.766 1885 0.787 1886 0.564 1887 0.561 1888 0.625 1889 0.801 1890 0.963 1891 1.291 1892 1.212 1893 1.186 1894 1.145 1895 1.014 1896 0.834 1897 0.845 1898 0.858 1899 0.898 1900 0.865 1901 1.023 1902 0.786 1903 0.83 1904 0.7 1905 0.538 1906 0.711 1907 0.654 1908 0.801 1909 0.896 1910 1.14 1911 0.881 1912 0.782 1913 0.815 1914 0.77 1915 0.966 1916 1.05 1917 1.071 1918 0.95 1919 1.028 1920 0.977 1921 0.999 1922 0.99 1923 1.297 1924 1.129 1925 1.062 1926 0.86 1927 0.641 1928 0.714 1929 0.757 1930 0.654 1931 0.768 1932 0.865 1933 0.984 1934 1.016 1935 1.007 1936 0.973 1937 1.064 1938 0.926 1939 0.886 1940 1.085 1941 0.949 1942 0.964 1943 1.068 1944 1.028 1945 1.023 1946 0.793 1947 1.042 1948 1.036 1949 1.207 1950 1.328 1951 1.26 1952 1.283 1953 1.319 1954 1.443 1955 1.454 1956 1.466 1957 1.285 1958 1.429 1959 1.379 1960 1.386 1961 1.539 1962 1.387 1963 1.229 1964 1.228 1965 1.275 1966 1.29 1967 1.502 1968 1.171 1969 1.374 1970 1.295 1971 1.193 1972 1.155 1973 1.112 1974 0.941 1975 0.908 1976 0.864 1977 0.847 1978 0.915 1979 0.794 1980 0.977 1981 0.92 1982 0.912 1983 0.932 1984 0.92 1985 0.973 1986 0.862 1987 0.862 1988 0.962 1989 1.001 1990 0.939 1991 0.738 1992 0.715 1993 0.73