# southamerica_arge035 - Dique Escaba 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: # # Online_Resource: https://www.ncdc.noaa.gov/paleo/study/24611 # # Original_Source_URL:https://www.ncdc.noaa.gov/paleo/study/5156 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: southamerica_arge035 - Dique Escaba 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. #-------------------- # 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: Dique Escaba Tucuman # Location: # Country: Argentina # Northernmost_Latitude: -27.7 # Southernmost_Latitude: -27.7 # Easternmost_Longitude: -65.78 # Westernmost_Longitude: -65.78 # Elevation: 900 m #-------------------- # Data_Collection # Collection_Name: southamerica_arge035B # Earliest_Year: 1862 # Most_Recent_Year: 1985 # 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":"4.99233417811","T2":"17.7760276001","M1":"0.0224269521423","M2":"0.457482676227"}} #-------------------- # 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 0.963 1863 0.765 1864 1.313 1865 0.81 1866 0.879 1867 0.673 1868 0.926 1869 0.533 1870 0.59 1871 1.186 1872 1.14 1873 1.593 1874 1.655 1875 1.192 1876 0.971 1877 1.001 1878 0.59 1879 0.797 1880 1.101 1881 1.521 1882 0.541 1883 0.246 1884 0.18 1885 0.608 1886 0.792 1887 0.596 1888 1.205 1889 0.91 1890 0.486 1891 0.879 1892 0.686 1893 0.906 1894 0.643 1895 0.757 1896 1.28 1897 2.234 1898 1.351 1899 0.874 1900 0.588 1901 0.351 1902 0.583 1903 0.962 1904 1.694 1905 1.659 1906 1.45 1907 0.595 1908 1.083 1909 0.076 1910 1.068 1911 1.211 1912 0.881 1913 1.298 1914 1.379 1915 1.273 1916 0.122 1917 0.216 1918 0.533 1919 0.618 1920 1.397 1921 1.285 1922 1.49 1923 1.56 1924 0.981 1925 1.297 1926 0.976 1927 1.042 1928 1.86 1929 0.752 1930 1.286 1931 1.972 1932 1.125 1933 0.713 1934 0.828 1935 0.666 1936 0.349 1937 0.133 1938 0.185 1939 0.752 1940 1.764 1941 0.678 1942 0.783 1943 1.231 1944 0.956 1945 0.816 1946 0.32 1947 0.618 1948 0.179 1949 0.721 1950 0.212 1951 0.335 1952 0.617 1953 0.441 1954 0.298 1955 0.274 1956 0.683 1957 0.4 1958 1.239 1959 1.561 1960 1.766 1961 1.505 1962 0.652 1963 1.354 1964 1.385 1965 1.516 1966 1.713 1967 1.111 1968 1.601 1969 0.876 1970 0.752 1971 0.825 1972 0.229 1973 0.563 1974 0.991 1975 1.619 1976 1.896 1977 1.974 1978 1.913 1979 1.243 1980 0.808 1981 0.396 1982 0.799 1983 1.301 1984 0.808 1985 1.135