# southamerica_arge063 - Buenos Aires Santa Cruz - 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/3510 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: southamerica_arge063 - Buenos Aires Santa Cruz - 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: Buenos Aires Santa Cruz # Location: # Country: Argentina # Northernmost_Latitude: -50.37 # Southernmost_Latitude: -50.37 # Easternmost_Longitude: -72.78 # Westernmost_Longitude: -72.78 # Elevation: 870 m #-------------------- # Data_Collection # Collection_Name: southamerica_arge063B # Earliest_Year: 1770 # Most_Recent_Year: 1984 # Time_Unit: y_ad # Core_Length: # Notes: {"database":{"database1":"LMR","database2":"Breits"}} {"climateInterpretation":{"basis":"", "climateVariable":"M", "climateVariableDetail":"air", "interpDirection":"positive", "seasonality":"[-12, 1, 2]"}}{"VSLite_parameters":{"T1":"2.76614720335","T2":"14.8727140224","M1":"0.0231953506124","M2":"0.517734298734"}} #-------------------- # 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 1770 0.876 1771 0.868 1772 1.349 1773 1.348 1774 1.315 1775 1.191 1776 0.901 1777 0.775 1778 0.974 1779 1.084 1780 1.309 1781 1.165 1782 1.122 1783 1.075 1784 1.036 1785 1.098 1786 1.011 1787 1.059 1788 0.978 1789 1.014 1790 1.146 1791 1.032 1792 1.142 1793 1.066 1794 0.988 1795 1.167 1796 1.054 1797 1.138 1798 0.687 1799 0.746 1800 1.033 1801 0.812 1802 0.825 1803 0.908 1804 0.839 1805 0.54 1806 0.925 1807 0.812 1808 0.86 1809 0.922 1810 0.821 1811 0.788 1812 0.911 1813 0.721 1814 0.834 1815 1.016 1816 0.619 1817 0.609 1818 0.822 1819 1.428 1820 0.919 1821 0.771 1822 0.958 1823 1.249 1824 0.988 1825 1.489 1826 1.196 1827 1.461 1828 1.303 1829 1.104 1830 1.139 1831 0.724 1832 1.494 1833 1.008 1834 0.771 1835 1.446 1836 1.005 1837 0.824 1838 0.922 1839 1.022 1840 1.151 1841 0.743 1842 0.246 1843 0.761 1844 1.226 1845 1.188 1846 0.627 1847 0.871 1848 1.23 1849 0.702 1850 0.493 1851 0.255 1852 0.943 1853 1.18 1854 0.873 1855 1.054 1856 0.903 1857 1.078 1858 1.053 1859 0.997 1860 1.634 1861 1.515 1862 1.048 1863 1.376 1864 1.226 1865 1.071 1866 1.078 1867 0.961 1868 1.125 1869 0.963 1870 1.027 1871 0.903 1872 0.7 1873 0.776 1874 0.958 1875 1.214 1876 1.016 1877 0.734 1878 1.096 1879 1.043 1880 1.088 1881 0.988 1882 0.599 1883 0.741 1884 0.762 1885 0.873 1886 1.172 1887 1.007 1888 0.731 1889 0.716 1890 1.386 1891 0.849 1892 0.775 1893 1.079 1894 1.416 1895 1.057 1896 1.039 1897 1.053 1898 1.118 1899 1.03 1900 1.076 1901 1.065 1902 1.159 1903 1.126 1904 0.799 1905 1.248 1906 0.764 1907 0.719 1908 0.735 1909 0.898 1910 0.902 1911 0.772 1912 0.991 1913 1.134 1914 0.669 1915 0.372 1916 0.874 1917 0.858 1918 0.655 1919 0.431 1920 1.067 1921 0.921 1922 0.562 1923 0.818 1924 1.293 1925 1.406 1926 1.011 1927 1.078 1928 1.306 1929 1.094 1930 1.261 1931 1.065 1932 1.345 1933 1.325 1934 1.472 1935 1.394 1936 1.368 1937 1.403 1938 1.116 1939 1.483 1940 0.69 1941 0.478 1942 1.156 1943 0.941 1944 0.853 1945 0.775 1946 0.839 1947 0.94 1948 1.03 1949 1.071 1950 1.04 1951 1.016 1952 0.647 1953 0.783 1954 1.453 1955 1.216 1956 0.902 1957 1.083 1958 1.001 1959 1.162 1960 0.762 1961 1.446 1962 1.001 1963 1.035 1964 0.661 1965 0.96 1966 0.862 1967 0.793 1968 0.811 1969 0.699 1970 0.833 1971 1.108 1972 1.137 1973 0.847 1974 0.897 1975 1.046 1976 1.201 1977 0.985 1978 0.798 1979 0.807 1980 1.161 1981 0.668 1982 0.897 1983 0.79 1984 0.924