# europe_swit128 - Jolimont Ju - 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/4448 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_swit128 - Jolimont Ju - 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: Jolimont Ju # Location: # Country: Switzerland # Northernmost_Latitude: 47.32 # Southernmost_Latitude: 47.32 # Easternmost_Longitude: 7.22 # Westernmost_Longitude: 7.22 # Elevation: 660 m #-------------------- # Data_Collection # Collection_Name: europe_swit128B # Earliest_Year: 1780 # Most_Recent_Year: 1982 # 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":"3.38497829459","T2":"12.9052497084","M1":"0.0229666878608","M2":"0.634884773415"}} #-------------------- # 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 1780 0.804 1781 1.032 1782 0.938 1783 1.03 1784 0.717 1785 0.739 1786 1.032 1787 1.087 1788 1.036 1789 1.089 1790 1.163 1791 1.21 1792 1.099 1793 0.945 1794 0.986 1795 0.708 1796 0.756 1797 0.892 1798 0.983 1799 1.158 1800 0.972 1801 1.326 1802 0.658 1803 0.561 1804 0.809 1805 0.902 1806 0.771 1807 0.675 1808 1.04 1809 0.576 1810 0.552 1811 0.59 1812 0.901 1813 1.05 1814 1.071 1815 1.013 1816 1.117 1817 1.102 1818 1.247 1819 1.019 1820 1.099 1821 1.313 1822 1.199 1823 1.464 1824 1.125 1825 1.149 1826 1.333 1827 1.25 1828 1.49 1829 1.525 1830 1.437 1831 1.931 1832 0.803 1833 0.778 1834 0.724 1835 0.816 1836 0.811 1837 1.142 1838 1.05 1839 1.007 1840 1.401 1841 1.505 1842 0.836 1843 1.198 1844 0.95 1845 1.377 1846 1.126 1847 0.925 1848 1.174 1849 0.763 1850 1.012 1851 0.813 1852 0.804 1853 1.404 1854 1.312 1855 0.979 1856 0.959 1857 1.035 1858 0.842 1859 0.909 1860 0.943 1861 0.869 1862 0.617 1863 0.45 1864 0.717 1865 0.454 1866 0.951 1867 0.943 1868 1.109 1869 1.168 1870 0.259 1871 0.783 1872 0.974 1873 0.782 1874 0.9 1875 0.648 1876 0.766 1877 1.11 1878 1.278 1879 1.524 1880 1.113 1881 1.212 1882 1.399 1883 1.311 1884 1.079 1885 1.21 1886 1.031 1887 0.678 1888 0.709 1889 0.954 1890 1.179 1891 1.307 1892 0.799 1893 0.15 1894 0.945 1895 1.087 1896 1.157 1897 0.945 1898 0.767 1899 0.557 1900 0.838 1901 0.764 1902 0.475 1903 0.813 1904 1.012 1905 1.208 1906 0.778 1907 0.833 1908 0.758 1909 0.461 1910 0.831 1911 0.783 1912 0.995 1913 1.063 1914 0.952 1915 1.027 1916 1.044 1917 1.352 1918 0.761 1919 0.72 1920 0.896 1921 0.532 1922 0.835 1923 0.728 1924 1.342 1925 1.073 1926 1.118 1927 1.314 1928 0.923 1929 1.417 1930 1.644 1931 1.354 1932 1.599 1933 1.21 1934 0.494 1935 0.912 1936 1.089 1937 1.093 1938 0.933 1939 1.186 1940 1.018 1941 1.315 1942 1.12 1943 0.804 1944 0.656 1945 0.869 1946 0.932 1947 0.713 1948 0.936 1949 0.758 1950 0.981 1951 1.061 1952 0.532 1953 0.719 1954 0.743 1955 1.004 1956 0.812 1957 0.735 1958 0.972 1959 0.928 1960 1.102 1961 0.869 1962 0.615 1963 1.157 1964 0.985 1965 1.133 1966 1.167 1967 1.539 1968 1.519 1969 1.263 1970 1.442 1971 1.092 1972 1.012 1973 0.707 1974 0.745 1975 0.953 1976 0.602 1977 1.041 1978 0.774 1979 1.019 1980 1.127 1981 0.891 1982 1.106