# southamerica_arge059 - Rio Malenguena - 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/2784 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: southamerica_arge059 - Rio Malenguena - 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: Rio Malenguena # Location: # Country: Argentina # Northernmost_Latitude: -54.52 # Southernmost_Latitude: -54.52 # Easternmost_Longitude: -66.17 # Westernmost_Longitude: -66.17 # Elevation: 15 m #-------------------- # Data_Collection # Collection_Name: southamerica_arge059B # Earliest_Year: 1789 # 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":"8.25082058531","T2":"17.4005390754","M1":"0.0226506531407","M2":"0.392588656146"}} #-------------------- # 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 1789 1.039 1790 0.817 1791 0.604 1792 1.235 1793 1.352 1794 1.204 1795 1.259 1796 0.964 1797 1.056 1798 0.86 1799 1.109 1800 1.176 1801 0.795 1802 0.609 1803 1.061 1804 0.575 1805 0.573 1806 1.029 1807 0.834 1808 0.82 1809 0.977 1810 0.852 1811 0.682 1812 0.933 1813 0.939 1814 1.051 1815 1.011 1816 0.609 1817 1.143 1818 0.974 1819 1.302 1820 1.045 1821 0.948 1822 0.809 1823 0.896 1824 1.01 1825 0.885 1826 0.353 1827 1.027 1828 1.55 1829 1.097 1830 0.981 1831 1.108 1832 1.023 1833 0.898 1834 0.853 1835 1.616 1836 1.428 1837 1.044 1838 1.019 1839 0.936 1840 0.276 1841 0.883 1842 1.061 1843 1.132 1844 0.859 1845 0.676 1846 0.551 1847 0.36 1848 1.326 1849 1.259 1850 1.203 1851 0.925 1852 0.456 1853 0.488 1854 1.093 1855 0.238 1856 0.438 1857 1.05 1858 0.927 1859 0.662 1860 0.494 1861 0.202 1862 1.028 1863 1.553 1864 0.878 1865 0.784 1866 0.802 1867 1.076 1868 1.322 1869 1.206 1870 1.149 1871 1.266 1872 0.929 1873 0.953 1874 0.697 1875 1.097 1876 1.607 1877 1.035 1878 0.849 1879 1.012 1880 1.154 1881 0.769 1882 0.65 1883 1.103 1884 1.156 1885 1.079 1886 0.99 1887 0.851 1888 0.829 1889 0.695 1890 1.159 1891 0.852 1892 0.81 1893 0.898 1894 0.905 1895 1.102 1896 0.919 1897 1.116 1898 1.332 1899 1.381 1900 1.143 1901 0.687 1902 0.18 1903 0.737 1904 1.472 1905 0.978 1906 0.881 1907 1.023 1908 1.239 1909 1.441 1910 0.994 1911 1.175 1912 1.407 1913 1.487 1914 1.029 1915 1.144 1916 1.259 1917 0.949 1918 1.118 1919 0.895 1920 1.532 1921 1.068 1922 0.161 1923 0.184 1924 1.033 1925 1.277 1926 0.849 1927 1.017 1928 1.337 1929 0.897 1930 1.018 1931 1.273 1932 0.969 1933 0.722 1934 0.566 1935 0.898 1936 1.043 1937 1.415 1938 1.506 1939 1.369 1940 1.019 1941 0.901 1942 1.113 1943 0.597 1944 1.049 1945 1.142 1946 1.19 1947 1.179 1948 1.405 1949 0.822 1950 1.239 1951 1.64 1952 0.967 1953 1.082 1954 1.168 1955 1.155 1956 1.172 1957 0.797 1958 0.518 1959 0.861 1960 0.808 1961 0.698 1962 0.63 1963 1.131 1964 1.319 1965 1.096 1966 1.404 1967 1.081 1968 0.707 1969 0.981 1970 0.356 1971 0.095 1972 0.601 1973 0.896 1974 0.818 1975 0.837 1976 0.868 1977 1.045 1978 0.91 1979 1.119 1980 1.132 1981 0.829 1982 1.072 1983 0.559 1984 0.61 1985 0.664 1986 0.843