# europe_swit178w - Krauchthal 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/4483 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_swit178w - Krauchthal 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: Krauchthal BE # Location: # Country: Switzerland # Northernmost_Latitude: 47.0 # Southernmost_Latitude: 47.0 # Easternmost_Longitude: 7.57 # Westernmost_Longitude: 7.57 # Elevation: 550 m #-------------------- # Data_Collection # Collection_Name: europe_swit178wB # Earliest_Year: 1785 # Most_Recent_Year: 1976 # 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":"2.92799896707","T2":"12.7359143815","M1":"0.0234719723274","M2":"0.628633228363"}} #-------------------- # 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 1785 0.829 1786 0.945 1787 0.861 1788 0.958 1789 1.223 1790 1.311 1791 1.052 1792 1.385 1793 0.967 1794 1.212 1795 1.164 1796 0.908 1797 1.055 1798 0.593 1799 1.165 1800 1.025 1801 1.072 1802 1.087 1803 0.846 1804 0.984 1805 0.881 1806 0.784 1807 0.706 1808 1.144 1809 0.949 1810 0.936 1811 0.759 1812 0.924 1813 1.104 1814 0.8 1815 1.052 1816 1.046 1817 0.955 1818 0.784 1819 1.01 1820 0.885 1821 1.077 1822 0.875 1823 1.088 1824 1.117 1825 0.92 1826 0.769 1827 0.965 1828 0.94 1829 0.61 1830 1.158 1831 0.896 1832 0.909 1833 0.88 1834 0.326 1835 0.557 1836 0.859 1837 0.86 1838 1.008 1839 1.016 1840 1.093 1841 1.103 1842 0.977 1843 1.478 1844 0.668 1845 1.028 1846 1.344 1847 0.92 1848 1.04 1849 0.882 1850 1.073 1851 0.905 1852 0.652 1853 1.058 1854 0.975 1855 1.056 1856 1.168 1857 0.984 1858 0.624 1859 1.025 1860 1.13 1861 1.071 1862 0.806 1863 0.793 1864 1.126 1865 0.55 1866 1.071 1867 1.071 1868 0.811 1869 1.146 1870 0.405 1871 0.864 1872 0.732 1873 0.744 1874 0.746 1875 0.846 1876 0.973 1877 1.112 1878 1.408 1879 1.267 1880 1.171 1881 1.144 1882 1.201 1883 1.319 1884 1.032 1885 0.822 1886 1.231 1887 0.784 1888 0.901 1889 0.94 1890 0.935 1891 1.135 1892 0.808 1893 0.505 1894 0.714 1895 0.745 1896 1.129 1897 0.892 1898 1.04 1899 0.945 1900 1.191 1901 0.746 1902 0.675 1903 1.025 1904 0.971 1905 1.535 1906 1.054 1907 1.235 1908 0.9 1909 0.56 1910 1.042 1911 0.731 1912 1.043 1913 0.754 1914 1.099 1915 1.516 1916 1.735 1917 1.332 1918 0.862 1919 0.844 1920 1.13 1921 0.713 1922 0.927 1923 0.796 1924 1.165 1925 0.801 1926 1.126 1927 1.052 1928 0.889 1929 0.978 1930 1.832 1931 1.33 1932 1.638 1933 0.8 1934 0.703 1935 1.106 1936 1.037 1937 0.887 1938 0.951 1939 1.329 1940 1.27 1941 1.348 1942 0.927 1943 0.52 1944 0.636 1945 0.654 1946 1.068 1947 0.52 1948 0.994 1949 0.819 1950 0.78 1951 1.327 1952 0.999 1953 0.608 1954 0.969 1955 1.322 1956 1.038 1957 0.862 1958 1.22 1959 0.919 1960 0.93 1961 0.875 1962 0.521 1963 0.941 1964 1.009 1965 0.979 1966 0.947 1967 0.909 1968 0.904 1969 0.894 1970 0.867 1971 0.864 1972 1.093 1973 1.174 1974 0.848 1975 1.048 1976 0.648