# southamerica_arge041 - Rio Horqueta Tucuman - 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: # # Original_Source_URL: # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: southamerica_arge041 - Rio Horqueta Tucuman - 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. #-------------------- # Funding_Agency # Funding_Agency_Name: Swiss National Science Foundation # Grant: #-------------------- # Site_Information # Site_Name: Rio Horqueta Tucuman # Location: # Country: Argentina # Northernmost_Latitude: -27.13 # Southernmost_Latitude: -27.13 # Easternmost_Longitude: -65.85 # Westernmost_Longitude: -65.85 # Elevation: 1850 m #-------------------- # Data_Collection # Collection_Name: southamerica_arge041B # Earliest_Year: 1862 # Most_Recent_Year: 1982 # Time_Unit: y_ad # Core_Length: # Notes: {"sensitivity":"temperature"}{"T1":"5.36229997285"}{"T2":"21.1099189665"}{"M1":"0.0222864617128"}{"M2":"0.194766696304"} #-------------------- # Species # Species_Name: Argentine walnut # Species_Code: JGAU #-------------------- # 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 1862 1.64 1863 0.993 1864 1.572 1865 1.056 1866 1.328 1867 1.413 1868 1.416 1869 0.982 1870 0.916 1871 0.892 1872 0.931 1873 0.927 1874 1.064 1875 1.132 1876 0.872 1877 1.104 1878 1.044 1879 0.777 1880 0.81 1881 1.029 1882 1.073 1883 1.305 1884 0.97 1885 1.336 1886 0.89 1887 0.734 1888 1.001 1889 0.703 1890 1.094 1891 0.756 1892 0.764 1893 0.975 1894 0.852 1895 0.862 1896 0.994 1897 1.389 1898 1.137 1899 1.595 1900 0.948 1901 1.16 1902 0.92 1903 0.358 1904 0.3 1905 0.252 1906 0.612 1907 0.798 1908 0.801 1909 0.832 1910 0.643 1911 1.414 1912 1.538 1913 0.831 1914 0.643 1915 0.867 1916 1.129 1917 1.526 1918 1.094 1919 1.159 1920 1.104 1921 0.702 1922 0.182 1923 0.566 1924 0.939 1925 1.034 1926 1.657 1927 1.069 1928 1.239 1929 1.249 1930 0.662 1931 0.168 1932 0.537 1933 0.57 1934 0.458 1935 0.992 1936 0.94 1937 1.414 1938 1.8 1939 1.268 1940 1.93 1941 1.765 1942 1.82 1943 1.004 1944 1.714 1945 1.259 1946 1.09 1947 1.589 1948 1.166 1949 1.483 1950 1.422 1951 1.26 1952 1.336 1953 1.264 1954 1.224 1955 1.076 1956 0.881 1957 1.263 1958 0.706 1959 0.442 1960 0.523 1961 0.639 1962 0.786 1963 0.22 1964 0.32 1965 0.372 1966 0.346 1967 0.69 1968 0.816 1969 0.917 1970 0.832 1971 0.92 1972 1.188 1973 1.051 1974 0.78 1975 1.235 1976 1.034 1977 0.917 1978 0.776 1979 0.224 1980 0.222 1981 0.212 1982 0.299