# europe_ital013 - Aetna Linguaglossa - 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/4304 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_ital013 - Aetna Linguaglossa - 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: Aetna Linguaglossa # Location: # Country: Italy # Northernmost_Latitude: 37.78 # Southernmost_Latitude: 37.78 # Easternmost_Longitude: 15.05 # Westernmost_Longitude: 15.05 # Elevation: 1800 m #-------------------- # Data_Collection # Collection_Name: europe_ital013B # Earliest_Year: 1812 # Most_Recent_Year: 1980 # Time_Unit: y_ad # Core_Length: # Notes: {"database":{"database1":"LMR","database2":"Breits"}} {"climateInterpretation":{"basis":"", "climateVariable":"M", "climateVariableDetail":"air", "interpDirection":"positive", "seasonality":"[6, 7, 8]"}}{"VSLite_parameters":{"T1":"4.49182844119","T2":"15.7846387048","M1":"0.022327879831","M2":"0.446451960453"}} #-------------------- # Species # Species_Name: Austrian pine # Species_Code: PINI #-------------------- # 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 1812 0.571 1813 0.734 1814 0.758 1815 0.877 1816 0.742 1817 0.87 1818 1.07 1819 1.036 1820 0.847 1821 0.916 1822 1.221 1823 1.131 1824 0.943 1825 1.483 1826 1.471 1827 1.163 1828 0.953 1829 1.146 1830 0.894 1831 0.846 1832 0.664 1833 0.442 1834 0.878 1835 0.959 1836 0.85 1837 1.004 1838 0.858 1839 0.755 1840 0.852 1841 1.009 1842 0.956 1843 1.511 1844 0.957 1845 0.905 1846 0.704 1847 0.925 1848 1.008 1849 1.157 1850 1.07 1851 1.302 1852 1.291 1853 0.869 1854 0.421 1855 0.866 1856 1.246 1857 0.904 1858 1.127 1859 1.607 1860 1.66 1861 0.882 1862 1.106 1863 1.155 1864 0.747 1865 0.712 1866 1.265 1867 1.259 1868 1.198 1869 1.06 1870 1.268 1871 1.03 1872 1.01 1873 1.132 1874 0.782 1875 0.889 1876 1.321 1877 1.884 1878 0.859 1879 1.025 1880 1.067 1881 0.819 1882 0.447 1883 0.422 1884 0.919 1885 1.326 1886 1.128 1887 0.998 1888 0.197 1889 0.245 1890 0.554 1891 1.014 1892 0.858 1893 0.658 1894 1.055 1895 0.932 1896 0.766 1897 1.573 1898 1.596 1899 1.597 1900 1.224 1901 0.954 1902 1.181 1903 1.365 1904 0.87 1905 0.813 1906 0.807 1907 0.651 1908 0.957 1909 0.88 1910 0.695 1911 0.776 1912 0.683 1913 0.576 1914 0.387 1915 0.442 1916 0.663 1917 0.995 1918 0.775 1919 0.414 1920 0.801 1921 0.668 1922 0.555 1923 0.419 1924 0.487 1925 0.882 1926 0.765 1927 0.821 1928 0.783 1929 0.4 1930 0.742 1931 0.768 1932 0.474 1933 0.601 1934 1.278 1935 1.023 1936 1.014 1937 0.827 1938 1.168 1939 0.95 1940 0.936 1941 1.814 1942 2.025 1943 1.325 1944 0.867 1945 1.271 1946 0.976 1947 0.529 1948 1.055 1949 1.455 1950 0.89 1951 0.736 1952 1.54 1953 1.239 1954 1.078 1955 1.47 1956 1.698 1957 1.092 1958 0.822 1959 1.268 1960 1.405 1961 1.615 1962 2.029 1963 0.881 1964 1.168 1965 1.17 1966 0.761 1967 0.841 1968 0.89 1969 0.806 1970 0.844 1971 0.84 1972 0.965 1973 0.761 1974 1.04 1975 0.848 1976 0.588 1977 0.863 1978 1.197 1979 1.264 1980 1.135