# europe_ital012 - Ceppo Bosque di Martense - 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/4374 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_ital012 - Ceppo Bosque di Martense - 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: Ceppo Bosque di Martense # Location: # Country: Italy # Northernmost_Latitude: 42.68 # Southernmost_Latitude: 42.68 # Easternmost_Longitude: 13.43 # Westernmost_Longitude: 13.43 # Elevation: 1700 m #-------------------- # Data_Collection # Collection_Name: europe_ital012B # Earliest_Year: 1734 # Most_Recent_Year: 1980 # Time_Unit: y_ad # Core_Length: # Notes: {"database":{"database1":"LMR","database2":"Breits"}} {"climateInterpretation":{"basis":"", "climateVariable":"T", "climateVariableDetail":"air", "interpDirection":"positive", "seasonality":"[6, 7, 8]"}}{"VSLite_parameters":{"T1":"4.54460982691","T2":"16.1123947215","M1":"0.0230474677536","M2":"0.523915737015"}} #-------------------- # Species # Species_Name: silver fir # Species_Code: ABAL #-------------------- # 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 1734 0.845 1735 0.897 1736 1.107 1737 1.251 1738 1.037 1739 0.941 1740 0.87 1741 0.733 1742 0.591 1743 0.773 1744 0.682 1745 0.689 1746 0.877 1747 0.684 1748 0.815 1749 0.845 1750 0.725 1751 0.758 1752 0.585 1753 0.729 1754 0.785 1755 0.817 1756 0.897 1757 0.94 1758 0.964 1759 1.292 1760 1.03 1761 1.086 1762 1.034 1763 0.87 1764 0.928 1765 1.093 1766 0.931 1767 1.035 1768 0.892 1769 0.802 1770 0.819 1771 0.938 1772 0.938 1773 0.873 1774 1.114 1775 1.033 1776 1.025 1777 1.038 1778 0.998 1779 0.764 1780 0.963 1781 1.21 1782 0.963 1783 1.063 1784 1.07 1785 1.13 1786 1.032 1787 1.089 1788 0.949 1789 0.946 1790 1.075 1791 1.222 1792 1.201 1793 1.222 1794 1.095 1795 1.149 1796 1.204 1797 1.026 1798 1.155 1799 1.27 1800 1.258 1801 1.535 1802 1.127 1803 0.976 1804 1.203 1805 1.136 1806 1.246 1807 1.172 1808 0.86 1809 1.003 1810 0.936 1811 1.047 1812 0.937 1813 0.862 1814 1.227 1815 1.06 1816 1.306 1817 1.073 1818 0.991 1819 1.074 1820 1.036 1821 0.942 1822 0.962 1823 0.614 1824 0.739 1825 0.734 1826 0.858 1827 0.927 1828 1.009 1829 0.875 1830 0.824 1831 1.177 1832 1.276 1833 0.878 1834 1.081 1835 0.877 1836 0.898 1837 0.855 1838 0.833 1839 0.704 1840 0.699 1841 0.805 1842 0.929 1843 0.99 1844 0.856 1845 0.853 1846 0.837 1847 0.479 1848 0.8 1849 0.728 1850 0.736 1851 0.847 1852 0.897 1853 0.868 1854 0.863 1855 0.842 1856 0.787 1857 0.734 1858 0.879 1859 1.033 1860 0.74 1861 0.726 1862 0.584 1863 0.509 1864 0.66 1865 0.538 1866 0.758 1867 0.792 1868 0.809 1869 0.913 1870 0.886 1871 0.99 1872 0.946 1873 1.012 1874 0.766 1875 0.959 1876 0.987 1877 1.102 1878 0.882 1879 0.739 1880 0.826 1881 1.025 1882 0.946 1883 1.147 1884 1.207 1885 1.642 1886 1.423 1887 1.349 1888 1.239 1889 1.297 1890 1.169 1891 0.973 1892 0.969 1893 1.112 1894 1.272 1895 1.071 1896 1.083 1897 1.46 1898 1.418 1899 1.294 1900 1.385 1901 1.246 1902 1.461 1903 1.14 1904 1.161 1905 1.259 1906 1.286 1907 0.926 1908 0.772 1909 0.92 1910 1.172 1911 1.103 1912 1.016 1913 0.94 1914 1.233 1915 1.105 1916 1.082 1917 1.047 1918 1.002 1919 1.023 1920 1.048 1921 0.967 1922 0.864 1923 0.769 1924 0.86 1925 1.052 1926 1.135 1927 1.031 1928 0.794 1929 0.727 1930 1.076 1931 0.817 1932 0.917 1933 0.838 1934 1.03 1935 1.084 1936 1.109 1937 1.132 1938 0.982 1939 0.989 1940 1.114 1941 1.323 1942 1.028 1943 0.914 1944 0.833 1945 0.97 1946 0.992 1947 0.792 1948 1.003 1949 1.192 1950 1.087 1951 0.812 1952 1.038 1953 0.773 1954 0.982 1955 1.117 1956 1.148 1957 0.844 1958 0.782 1959 1.046 1960 1.028 1961 0.982 1962 0.851 1963 0.644 1964 1.091 1965 0.977 1966 1.013 1967 0.896 1968 0.726 1969 0.829 1970 1.103 1971 0.743 1972 0.722 1973 0.832 1974 0.691 1975 0.588 1976 0.574 1977 0.595 1978 0.614 1979 0.56 1980 0.454