# southamerica_arge024 - Bahia York - 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/3677 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: southamerica_arge024 - Bahia York - 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: Bahia York # Location: # Country: Argentina # Northernmost_Latitude: -54.83 # Southernmost_Latitude: -54.83 # Easternmost_Longitude: -64.33 # Westernmost_Longitude: -64.33 # Elevation: 60 m #-------------------- # Data_Collection # Collection_Name: southamerica_arge024B # Earliest_Year: 1748 # Most_Recent_Year: 1986 # 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":"4.66150663668","T2":"17.1848606046","M1":"0.0224099096122","M2":"0.380387865832"}} #-------------------- # Species # Species_Name: coihue de Magallanes # Species_Code: NOBE #-------------------- # 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 1748 0.598 1749 0.925 1750 1.276 1751 1.301 1752 0.875 1753 0.958 1754 0.979 1755 0.877 1756 0.995 1757 0.96 1758 0.913 1759 0.959 1760 1.246 1761 1.113 1762 0.999 1763 0.854 1764 0.992 1765 1.193 1766 0.719 1767 0.787 1768 0.652 1769 1.202 1770 0.948 1771 1.062 1772 1.081 1773 1.111 1774 0.783 1775 1.242 1776 1.358 1777 1.112 1778 1.021 1779 1.137 1780 1.026 1781 1.141 1782 1.268 1783 1.08 1784 0.966 1785 0.935 1786 0.902 1787 0.764 1788 1.086 1789 1.14 1790 0.693 1791 1.042 1792 0.804 1793 0.801 1794 0.701 1795 0.651 1796 0.678 1797 0.623 1798 0.661 1799 0.765 1800 0.853 1801 0.715 1802 0.464 1803 0.685 1804 0.619 1805 0.697 1806 0.673 1807 0.717 1808 0.418 1809 0.478 1810 0.366 1811 0.519 1812 0.622 1813 0.635 1814 0.59 1815 0.526 1816 0.729 1817 0.956 1818 0.966 1819 1.05 1820 0.875 1821 0.879 1822 0.921 1823 1.142 1824 0.935 1825 1.041 1826 1.115 1827 0.913 1828 0.939 1829 1.042 1830 1.09 1831 1.036 1832 1.111 1833 1.19 1834 0.951 1835 0.946 1836 0.622 1837 0.879 1838 0.649 1839 0.904 1840 0.73 1841 0.919 1842 0.922 1843 0.903 1844 1.174 1845 1.088 1846 1.106 1847 1.114 1848 0.944 1849 0.936 1850 1.045 1851 1.091 1852 0.785 1853 0.993 1854 0.628 1855 1.021 1856 0.637 1857 1.255 1858 1.213 1859 1.374 1860 1.772 1861 1.869 1862 1.561 1863 1.694 1864 1.144 1865 1.397 1866 1.163 1867 0.953 1868 1.28 1869 1.363 1870 1.581 1871 1.356 1872 0.839 1873 1.141 1874 0.821 1875 1.049 1876 1.199 1877 1.303 1878 1.052 1879 1.014 1880 1.013 1881 0.908 1882 0.935 1883 0.884 1884 0.881 1885 0.992 1886 0.832 1887 1.26 1888 0.867 1889 0.951 1890 0.909 1891 1.301 1892 0.942 1893 1.122 1894 0.965 1895 1.586 1896 1.285 1897 1.69 1898 1.23 1899 1.191 1900 1.402 1901 1.414 1902 1.104 1903 1.417 1904 1.275 1905 1.418 1906 0.993 1907 1.156 1908 0.997 1909 1.137 1910 0.962 1911 1.094 1912 0.73 1913 0.952 1914 0.708 1915 1.001 1916 0.857 1917 1.424 1918 1.03 1919 1.27 1920 1.221 1921 1.732 1922 1.599 1923 1.265 1924 1.364 1925 1.021 1926 1.145 1927 0.973 1928 1.031 1929 0.922 1930 1.211 1931 0.952 1932 0.939 1933 1.001 1934 0.711 1935 0.962 1936 0.702 1937 0.926 1938 0.89 1939 1.009 1940 1.04 1941 1.253 1942 1.008 1943 1.029 1944 1.193 1945 1.265 1946 1.118 1947 0.991 1948 0.475 1949 0.556 1950 0.519 1951 0.905 1952 0.328 1953 0.602 1954 0.786 1955 0.657 1956 0.576 1957 0.672 1958 0.312 1959 0.456 1960 0.23 1961 0.672 1962 0.476 1963 0.885 1964 0.615 1965 0.802 1966 0.828 1967 0.961 1968 0.722 1969 0.745 1970 0.69 1971 0.629 1972 0.68 1973 0.637 1974 0.707 1975 0.688 1976 0.371 1977 0.662 1978 0.53 1979 0.684 1980 0.488 1981 0.847 1982 0.631 1983 0.646 1984 0.298 1985 0.37 1986 0.268