# australia_newz039 - Cream Creek - 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/4049 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: australia_newz039 - Cream Creek - 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: Cream Creek # Location: # Country: New Zealand # Northernmost_Latitude: -43.08 # Southernmost_Latitude: -43.08 # Easternmost_Longitude: 170.98 # Westernmost_Longitude: 170.98 # Elevation: 800 m #-------------------- # Data_Collection # Collection_Name: australia_newz039B # Earliest_Year: 1684 # Most_Recent_Year: 1978 # 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":"3.50008220374","T2":"16.6005425792","M1":"0.0225600377483","M2":"0.405225619795"}} #-------------------- # 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 1684 0.961 1685 1.055 1686 0.847 1687 0.525 1688 0.723 1689 0.811 1690 1.142 1691 1.086 1692 0.838 1693 0.938 1694 1.023 1695 1.091 1696 1.038 1697 1.095 1698 1.081 1699 0.984 1700 1.053 1701 1.042 1702 0.805 1703 1.135 1704 1.109 1705 1.1 1706 1.151 1707 0.709 1708 0.584 1709 0.866 1710 0.738 1711 0.744 1712 0.915 1713 0.772 1714 1.078 1715 0.987 1716 0.902 1717 0.853 1718 0.526 1719 0.439 1720 0.704 1721 0.808 1722 0.962 1723 1.0 1724 1.0 1725 1.125 1726 0.97 1727 1.134 1728 1.42 1729 1.034 1730 1.211 1731 1.05 1732 0.944 1733 0.866 1734 0.742 1735 1.146 1736 1.144 1737 0.976 1738 0.871 1739 1.215 1740 1.024 1741 0.828 1742 0.823 1743 0.879 1744 1.035 1745 1.201 1746 1.246 1747 1.046 1748 1.216 1749 1.007 1750 0.748 1751 1.141 1752 1.009 1753 1.022 1754 0.915 1755 0.881 1756 1.042 1757 1.109 1758 1.021 1759 1.085 1760 0.9 1761 0.893 1762 0.971 1763 0.93 1764 1.028 1765 0.972 1766 0.912 1767 0.882 1768 1.024 1769 0.938 1770 0.522 1771 0.727 1772 0.547 1773 0.648 1774 0.677 1775 0.762 1776 0.69 1777 1.035 1778 1.121 1779 1.154 1780 1.216 1781 1.189 1782 1.017 1783 0.991 1784 1.04 1785 1.057 1786 1.259 1787 1.156 1788 1.156 1789 1.17 1790 0.997 1791 0.866 1792 0.964 1793 0.963 1794 0.965 1795 0.826 1796 0.865 1797 1.173 1798 0.953 1799 0.832 1800 1.348 1801 1.431 1802 1.488 1803 1.099 1804 1.561 1805 1.877 1806 1.103 1807 0.53 1808 0.629 1809 0.76 1810 0.9 1811 0.893 1812 1.239 1813 1.022 1814 1.144 1815 1.508 1816 1.482 1817 1.088 1818 0.87 1819 0.948 1820 1.051 1821 1.08 1822 1.124 1823 1.199 1824 1.316 1825 1.54 1826 1.067 1827 1.426 1828 1.413 1829 1.373 1830 1.026 1831 1.035 1832 0.764 1833 0.64 1834 0.974 1835 1.219 1836 1.325 1837 1.26 1838 1.309 1839 1.223 1840 1.467 1841 1.669 1842 1.418 1843 1.313 1844 1.147 1845 1.4 1846 1.287 1847 1.333 1848 1.226 1849 1.044 1850 0.71 1851 0.738 1852 0.78 1853 0.923 1854 0.982 1855 1.147 1856 0.84 1857 0.907 1858 0.723 1859 0.594 1860 0.501 1861 0.754 1862 0.75 1863 0.8 1864 1.053 1865 1.077 1866 1.161 1867 1.004 1868 1.126 1869 1.173 1870 1.257 1871 1.139 1872 1.114 1873 1.417 1874 1.476 1875 1.526 1876 1.205 1877 1.25 1878 0.858 1879 1.252 1880 1.093 1881 1.119 1882 1.09 1883 1.124 1884 1.157 1885 1.226 1886 1.22 1887 1.124 1888 1.036 1889 1.178 1890 1.103 1891 1.199 1892 1.452 1893 1.42 1894 0.99 1895 0.674 1896 1.345 1897 1.165 1898 0.769 1899 0.841 1900 0.9 1901 0.854 1902 0.889 1903 0.73 1904 0.682 1905 0.531 1906 0.585 1907 0.541 1908 0.682 1909 0.671 1910 0.715 1911 0.793 1912 0.731 1913 0.92 1914 0.825 1915 0.95 1916 0.767 1917 1.056 1918 0.869 1919 0.897 1920 0.87 1921 0.881 1922 0.808 1923 0.612 1924 0.715 1925 0.604 1926 0.632 1927 0.768 1928 0.668 1929 0.797 1930 0.841 1931 0.939 1932 1.037 1933 1.118 1934 0.998 1935 0.435 1936 0.383 1937 0.462 1938 0.245 1939 0.346 1940 0.699 1941 0.86 1942 0.791 1943 0.799 1944 0.831 1945 0.721 1946 0.753 1947 0.825 1948 1.021 1949 0.923 1950 1.215 1951 0.69 1952 0.883 1953 0.954 1954 1.001 1955 0.875 1956 0.845 1957 0.772 1958 0.497 1959 0.48 1960 0.847 1961 0.727 1962 0.623 1963 0.59 1964 0.538 1965 0.671 1966 0.594 1967 0.745 1968 0.459 1969 0.277 1970 0.725 1971 1.167 1972 1.589 1973 1.789 1974 1.654 1975 1.612 1976 1.581 1977 1.626 1978 1.232