# europe_swit172w - Beatenberg, BE - 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/4343 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_swit172w - Beatenberg, BE - 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: Beatenberg, BE # Location: # Country: Switzerland # Northernmost_Latitude: 46.7 # Southernmost_Latitude: 46.7 # Easternmost_Longitude: 7.77 # Westernmost_Longitude: 7.77 # Elevation: 1560 m #-------------------- # Data_Collection # Collection_Name: europe_swit172wB # Earliest_Year: 1736 # Most_Recent_Year: 1988 # 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":"4.93822835862","T2":"19.1681050819","M1":"0.0225805774653","M2":"0.388751613558"}} #-------------------- # Species # Species_Name: Scots pine # Species_Code: PISY #-------------------- # 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 1736 0.914 1737 0.905 1738 0.892 1739 0.893 1740 0.805 1741 0.735 1742 0.796 1743 0.883 1744 1.072 1745 0.956 1746 0.982 1747 0.989 1748 1.038 1749 1.157 1750 0.858 1751 0.873 1752 0.735 1753 0.762 1754 0.905 1755 1.153 1756 1.136 1757 1.189 1758 0.928 1759 1.316 1760 1.066 1761 1.069 1762 0.823 1763 1.029 1764 1.074 1765 1.055 1766 1.052 1767 1.028 1768 0.903 1769 0.965 1770 0.789 1771 0.757 1772 0.84 1773 0.809 1774 0.864 1775 0.983 1776 0.877 1777 0.972 1778 1.023 1779 0.845 1780 1.022 1781 0.93 1782 0.865 1783 0.863 1784 1.084 1785 0.975 1786 0.91 1787 0.826 1788 0.825 1789 0.791 1790 0.768 1791 0.907 1792 0.845 1793 0.847 1794 0.891 1795 0.616 1796 0.752 1797 0.636 1798 0.746 1799 0.826 1800 0.771 1801 0.815 1802 0.744 1803 0.844 1804 0.887 1805 1.008 1806 0.916 1807 1.238 1808 0.978 1809 0.886 1810 0.745 1811 0.863 1812 0.74 1813 0.575 1814 0.776 1815 0.629 1816 0.608 1817 0.593 1818 0.642 1819 0.707 1820 0.641 1821 0.661 1822 0.866 1823 0.973 1824 1.013 1825 0.948 1826 0.889 1827 0.957 1828 1.036 1829 1.116 1830 0.991 1831 1.196 1832 1.057 1833 0.928 1834 1.342 1835 1.579 1836 1.189 1837 1.383 1838 1.338 1839 1.357 1840 1.119 1841 1.016 1842 1.238 1843 0.927 1844 1.042 1845 0.941 1846 1.346 1847 1.204 1848 1.153 1849 1.105 1850 0.997 1851 0.985 1852 1.236 1853 1.352 1854 1.129 1855 0.987 1856 1.081 1857 1.116 1858 1.001 1859 1.233 1860 0.93 1861 1.092 1862 1.119 1863 1.132 1864 1.143 1865 1.076 1866 0.974 1867 1.063 1868 1.076 1869 1.055 1870 0.887 1871 1.063 1872 1.038 1873 1.349 1874 1.161 1875 1.102 1876 1.02 1877 1.005 1878 0.936 1879 0.892 1880 0.802 1881 1.041 1882 0.943 1883 0.928 1884 1.069 1885 1.026 1886 0.742 1887 0.786 1888 0.62 1889 0.843 1890 0.807 1891 0.826 1892 0.778 1893 0.865 1894 0.861 1895 0.888 1896 0.871 1897 0.859 1898 0.923 1899 0.967 1900 0.848 1901 0.782 1902 0.814 1903 0.975 1904 1.093 1905 1.067 1906 0.823 1907 0.96 1908 1.072 1909 0.858 1910 0.875 1911 1.042 1912 0.844 1913 0.695 1914 0.894 1915 0.831 1916 0.71 1917 0.775 1918 0.669 1919 0.738 1920 0.67 1921 0.967 1922 0.895 1923 1.006 1924 1.056 1925 1.12 1926 0.968 1927 1.018 1928 1.017 1929 0.949 1930 1.091 1931 1.026 1932 1.102 1933 1.081 1934 0.844 1935 1.05 1936 0.998 1937 0.966 1938 0.84 1939 0.973 1940 0.722 1941 0.769 1942 0.631 1943 0.849 1944 0.933 1945 0.973 1946 1.097 1947 1.084 1948 0.816 1949 0.906 1950 1.073 1951 1.394 1952 1.553 1953 1.219 1954 1.017 1955 1.027 1956 0.848 1957 0.869 1958 0.902 1959 0.917 1960 0.772 1961 0.68 1962 0.797 1963 0.8 1964 1.052 1965 1.107 1966 1.142 1967 1.243 1968 1.086 1969 1.094 1970 1.15 1971 1.085 1972 0.994 1973 0.971 1974 0.787 1975 0.789 1976 0.867 1977 0.963 1978 0.929 1979 0.876 1980 0.947 1981 0.894 1982 1.194 1983 1.339 1984 1.09 1985 1.151 1986 1.166 1987 1.208 1988 1.228