# australia_newz030 - Snowslide Stream - 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/4070 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: australia_newz030 - Snowslide Stream - 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: Snowslide Stream # Location: # Country: New Zealand # Northernmost_Latitude: -43.05 # Southernmost_Latitude: -43.05 # Easternmost_Longitude: 171.72 # Westernmost_Longitude: 171.72 # Elevation: 1250 m #-------------------- # Data_Collection # Collection_Name: australia_newz030B # Earliest_Year: 1780 # Most_Recent_Year: 1979 # 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":"2.98203864676","T2":"11.4611081191","M1":"0.0228939917159","M2":"0.625921949266"}} #-------------------- # Species # Species_Name: mountain beech nothofagus # Species_Code: NOSO #-------------------- # 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 1780 1.387 1781 1.259 1782 0.99 1783 1.231 1784 1.131 1785 1.05 1786 1.358 1787 1.692 1788 1.097 1789 1.09 1790 0.873 1791 0.89 1792 1.304 1793 1.317 1794 1.184 1795 0.766 1796 0.214 1797 0.496 1798 0.866 1799 1.048 1800 1.009 1801 0.818 1802 0.962 1803 0.877 1804 1.001 1805 1.044 1806 0.871 1807 1.393 1808 1.403 1809 0.905 1810 1.289 1811 1.156 1812 1.12 1813 1.166 1814 0.953 1815 0.61 1816 0.771 1817 0.776 1818 0.968 1819 0.893 1820 0.914 1821 0.691 1822 1.036 1823 0.739 1824 0.152 1825 0.617 1826 0.882 1827 0.974 1828 0.35 1829 0.796 1830 0.946 1831 1.004 1832 0.065 1833 0.294 1834 0.403 1835 0.25 1836 0.592 1837 1.183 1838 0.571 1839 1.026 1840 1.33 1841 1.226 1842 0.978 1843 0.699 1844 0.302 1845 0.819 1846 1.405 1847 0.999 1848 0.937 1849 0.992 1850 0.669 1851 0.524 1852 0.517 1853 1.307 1854 1.199 1855 1.026 1856 1.148 1857 1.048 1858 1.361 1859 1.078 1860 1.199 1861 0.629 1862 0.019 1863 0.111 1864 0.915 1865 1.244 1866 1.208 1867 0.912 1868 0.871 1869 0.831 1870 0.717 1871 0.345 1872 0.069 1873 0.294 1874 0.842 1875 0.602 1876 0.742 1877 0.547 1878 0.708 1879 0.843 1880 0.888 1881 0.267 1882 0.591 1883 0.478 1884 0.951 1885 1.278 1886 1.705 1887 0.725 1888 1.055 1889 1.323 1890 1.24 1891 0.924 1892 1.448 1893 2.236 1894 2.196 1895 1.057 1896 1.633 1897 1.728 1898 1.603 1899 1.301 1900 1.559 1901 1.607 1902 1.38 1903 1.154 1904 0.622 1905 0.948 1906 1.672 1907 1.023 1908 1.076 1909 1.86 1910 1.552 1911 0.947 1912 1.599 1913 1.48 1914 1.243 1915 1.967 1916 1.24 1917 1.192 1918 1.065 1919 1.422 1920 1.216 1921 1.456 1922 1.116 1923 1.598 1924 1.176 1925 1.364 1926 1.286 1927 1.129 1928 1.245 1929 1.02 1930 1.192 1931 1.177 1932 1.193 1933 0.923 1934 0.715 1935 0.417 1936 0.649 1937 1.36 1938 0.367 1939 0.588 1940 0.984 1941 0.78 1942 0.73 1943 0.875 1944 0.673 1945 0.772 1946 1.027 1947 0.606 1948 0.679 1949 0.801 1950 0.894 1951 0.559 1952 0.868 1953 1.165 1954 0.877 1955 0.868 1956 0.847 1957 0.626 1958 0.669 1959 0.677 1960 0.937 1961 0.975 1962 0.971 1963 0.963 1964 1.124 1965 1.19 1966 1.147 1967 1.59 1968 1.034 1969 0.94 1970 0.696 1971 0.644 1972 0.786 1973 0.711 1974 0.762 1975 0.299 1976 0.675 1977 0.887 1978 0.85 1979 0.842