# southamerica_arge100 - Paso de las Nubes 4 - 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/5176 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: southamerica_arge100 - Paso de las Nubes 4 - 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: Paso de las Nubes 4 # Location: # Country: Argentina # Northernmost_Latitude: -41.12 # Southernmost_Latitude: -41.12 # Easternmost_Longitude: -71.8 # Westernmost_Longitude: -71.8 # Elevation: 1230 m #-------------------- # Data_Collection # Collection_Name: southamerica_arge100B # Earliest_Year: 1749 # Most_Recent_Year: 1991 # 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":"5.99332369646","T2":"15.8933819856","M1":"0.0225270828516","M2":"0.361060256911"}} #-------------------- # Species # Species_Name: lenga nothofagus # Species_Code: NOPU #-------------------- # 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 1749 0.717 1750 0.853 1751 0.812 1752 0.361 1753 0.431 1754 0.592 1755 0.766 1756 0.743 1757 0.928 1758 0.716 1759 1.052 1760 0.771 1761 0.861 1762 1.078 1763 0.889 1764 0.877 1765 0.958 1766 0.734 1767 0.798 1768 0.777 1769 0.742 1770 0.458 1771 0.729 1772 0.944 1773 0.81 1774 0.487 1775 0.231 1776 0.419 1777 0.634 1778 0.845 1779 0.915 1780 0.901 1781 1.048 1782 1.101 1783 1.027 1784 0.909 1785 0.856 1786 1.207 1787 1.089 1788 0.733 1789 1.082 1790 0.608 1791 0.585 1792 0.975 1793 0.545 1794 0.938 1795 0.915 1796 0.722 1797 0.78 1798 0.612 1799 0.847 1800 0.814 1801 0.81 1802 0.77 1803 0.631 1804 1.216 1805 1.346 1806 1.296 1807 1.677 1808 1.337 1809 1.208 1810 1.041 1811 0.812 1812 1.032 1813 0.882 1814 0.554 1815 0.849 1816 1.019 1817 1.098 1818 0.728 1819 1.248 1820 0.836 1821 0.839 1822 1.512 1823 1.341 1824 1.472 1825 1.441 1826 1.062 1827 1.149 1828 1.621 1829 1.6 1830 1.432 1831 1.26 1832 1.172 1833 1.096 1834 1.098 1835 1.044 1836 1.292 1837 1.222 1838 1.006 1839 1.379 1840 0.913 1841 1.185 1842 1.172 1843 1.043 1844 1.305 1845 1.142 1846 1.532 1847 0.955 1848 1.033 1849 0.695 1850 0.591 1851 0.777 1852 1.129 1853 1.349 1854 1.146 1855 1.241 1856 1.245 1857 1.089 1858 1.13 1859 1.105 1860 1.023 1861 0.803 1862 0.994 1863 1.27 1864 1.129 1865 1.118 1866 0.993 1867 1.096 1868 1.141 1869 0.963 1870 0.565 1871 0.37 1872 0.74 1873 1.034 1874 1.196 1875 1.173 1876 1.076 1877 1.11 1878 1.328 1879 0.943 1880 1.139 1881 0.804 1882 1.015 1883 1.117 1884 1.335 1885 0.722 1886 1.174 1887 1.104 1888 1.102 1889 0.881 1890 1.138 1891 0.991 1892 0.965 1893 1.149 1894 1.486 1895 0.946 1896 0.793 1897 1.094 1898 1.08 1899 0.822 1900 0.981 1901 0.801 1902 0.697 1903 1.171 1904 1.006 1905 1.4 1906 1.262 1907 1.18 1908 1.02 1909 1.036 1910 1.173 1911 1.234 1912 0.878 1913 1.287 1914 0.931 1915 1.038 1916 0.975 1917 0.584 1918 0.801 1919 0.846 1920 0.935 1921 1.273 1922 0.961 1923 0.665 1924 1.194 1925 1.182 1926 0.754 1927 0.98 1928 0.836 1929 0.929 1930 0.89 1931 0.834 1932 1.093 1933 1.075 1934 1.121 1935 0.748 1936 1.061 1937 0.775 1938 0.688 1939 0.787 1940 0.644 1941 0.516 1942 1.164 1943 0.884 1944 1.005 1945 1.162 1946 0.701 1947 1.074 1948 0.88 1949 0.923 1950 0.687 1951 0.769 1952 0.571 1953 0.889 1954 1.038 1955 0.921 1956 0.625 1957 1.145 1958 1.279 1959 1.233 1960 0.967 1961 1.022 1962 0.952 1963 0.901 1964 1.144 1965 0.933 1966 0.824 1967 1.002 1968 0.622 1969 0.963 1970 0.589 1971 0.771 1972 1.055 1973 0.682 1974 0.71 1975 0.595 1976 0.709 1977 0.867 1978 0.82 1979 0.906 1980 0.922 1981 1.116 1982 0.884 1983 1.17 1984 0.931 1985 0.703 1986 0.768 1987 0.801 1988 1.042 1989 1.007 1990 0.901 1991 1.033