# southamerica_arge050 - Paso Cordova Neuquen - 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/4273 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: southamerica_arge050 - Paso Cordova Neuquen - 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 Cordova Neuquen # Location: # Country: Argentina # Northernmost_Latitude: -40.67 # Southernmost_Latitude: -40.67 # Easternmost_Longitude: -71.25 # Westernmost_Longitude: -71.25 # Elevation: 1890 m #-------------------- # Data_Collection # Collection_Name: southamerica_arge050B # Earliest_Year: 1770 # 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":"3.58110290559","T2":"13.5224010567","M1":"0.0228518037851","M2":"0.58499975417"}} #-------------------- # 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 0.825 1771 1.282 1772 1.041 1773 1.192 1774 1.154 1775 1.042 1776 0.994 1777 0.735 1778 0.764 1779 0.809 1780 0.799 1781 1.095 1782 1.114 1783 1.204 1784 0.995 1785 0.816 1786 0.917 1787 0.793 1788 0.542 1789 0.862 1790 0.791 1791 1.031 1792 1.125 1793 0.93 1794 1.093 1795 0.988 1796 1.015 1797 1.134 1798 1.137 1799 1.014 1800 1.004 1801 1.042 1802 1.018 1803 0.937 1804 1.347 1805 1.131 1806 0.961 1807 1.078 1808 0.974 1809 1.13 1810 0.894 1811 0.842 1812 0.893 1813 0.409 1814 0.448 1815 1.061 1816 1.101 1817 0.909 1818 0.794 1819 1.208 1820 0.646 1821 0.472 1822 0.85 1823 0.694 1824 0.868 1825 0.875 1826 0.809 1827 0.899 1828 1.072 1829 0.954 1830 0.908 1831 0.846 1832 0.914 1833 0.664 1834 1.125 1835 1.293 1836 1.491 1837 1.319 1838 1.282 1839 1.35 1840 0.93 1841 0.867 1842 1.024 1843 1.255 1844 0.81 1845 0.46 1846 0.823 1847 0.937 1848 1.118 1849 1.368 1850 0.993 1851 0.647 1852 1.189 1853 1.245 1854 0.679 1855 0.824 1856 1.464 1857 1.198 1858 1.298 1859 1.072 1860 1.023 1861 0.9 1862 1.108 1863 1.359 1864 1.112 1865 1.043 1866 0.993 1867 1.103 1868 1.453 1869 1.064 1870 1.438 1871 0.9 1872 0.772 1873 1.095 1874 0.782 1875 0.927 1876 0.928 1877 0.863 1878 0.92 1879 1.034 1880 1.496 1881 0.74 1882 0.955 1883 1.034 1884 0.932 1885 0.822 1886 1.278 1887 0.858 1888 0.792 1889 1.007 1890 1.23 1891 1.115 1892 1.334 1893 1.405 1894 1.034 1895 1.178 1896 0.682 1897 0.854 1898 1.017 1899 0.789 1900 0.791 1901 1.264 1902 1.154 1903 0.954 1904 0.898 1905 0.923 1906 0.75 1907 0.884 1908 0.573 1909 0.729 1910 1.431 1911 0.494 1912 0.67 1913 0.737 1914 0.587 1915 1.036 1916 0.889 1917 1.035 1918 1.057 1919 0.937 1920 1.101 1921 1.396 1922 1.252 1923 0.679 1924 1.412 1925 1.229 1926 0.71 1927 1.181 1928 1.028 1929 1.018 1930 1.178 1931 1.217 1932 0.889 1933 1.042 1934 1.469 1935 1.132 1936 1.256 1937 1.317 1938 1.592 1939 1.227 1940 1.108 1941 1.122 1942 1.582 1943 0.862 1944 0.754 1945 1.225 1946 1.092 1947 1.193 1948 1.26 1949 1.386 1950 0.894 1951 1.162 1952 1.13 1953 1.142 1954 1.095 1955 1.147 1956 1.097 1957 0.591 1958 1.116 1959 1.134 1960 0.691 1961 0.848 1962 0.902 1963 0.754 1964 1.149 1965 0.885 1966 0.712 1967 1.11 1968 0.545 1969 1.004 1970 0.554 1971 0.707 1972 1.148 1973 0.826 1974 1.104 1975 0.674 1976 0.92 1977 0.604 1978 0.911 1979 0.545 1980 0.582 1981 0.662 1982 0.546 1983 1.053 1984 0.884 1985 0.7 1986 0.428