# europe_swit175w - Grindelwald Süd (S3) - 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/4430 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_swit175w - Grindelwald Süd (S3) - 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: Grindelwald Süd (S3) # Location: # Country: Switzerland # Northernmost_Latitude: 46.65 # Southernmost_Latitude: 46.65 # Easternmost_Longitude: 8.02 # Westernmost_Longitude: 8.02 # Elevation: 1960 m #-------------------- # Data_Collection # Collection_Name: europe_swit175wB # Earliest_Year: 1786 # Most_Recent_Year: 1995 # 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":"5.61303351807","T2":"17.1818317652","M1":"0.0229374849436","M2":"0.392390798191"}} #-------------------- # Species # Species_Name: Norway spruce # Species_Code: PCAB #-------------------- # 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 1786 1.05 1787 1.009 1788 1.058 1789 1.023 1790 0.827 1791 0.801 1792 1.014 1793 0.848 1794 0.978 1795 0.8 1796 1.039 1797 0.999 1798 1.093 1799 1.132 1800 1.019 1801 1.004 1802 1.01 1803 1.024 1804 0.819 1805 0.887 1806 0.988 1807 1.412 1808 1.343 1809 1.206 1810 0.767 1811 0.84 1812 0.803 1813 0.639 1814 0.727 1815 0.605 1816 0.447 1817 0.484 1818 0.386 1819 0.54 1820 0.667 1821 0.557 1822 0.768 1823 0.727 1824 1.034 1825 0.836 1826 1.002 1827 1.085 1828 1.056 1829 1.086 1830 1.022 1831 1.107 1832 0.969 1833 0.952 1834 0.988 1835 0.927 1836 0.936 1837 0.956 1838 0.835 1839 0.939 1840 0.76 1841 0.922 1842 1.202 1843 1.019 1844 1.114 1845 0.974 1846 1.189 1847 0.846 1848 1.083 1849 1.07 1850 1.094 1851 0.871 1852 0.811 1853 0.973 1854 0.679 1855 0.895 1856 0.835 1857 0.915 1858 0.786 1859 1.067 1860 0.758 1861 0.86 1862 0.717 1863 0.913 1864 0.865 1865 0.781 1866 0.769 1867 1.004 1868 0.861 1869 0.884 1870 1.004 1871 0.951 1872 0.952 1873 1.07 1874 1.015 1875 0.829 1876 1.003 1877 1.037 1878 0.976 1879 1.007 1880 0.829 1881 1.205 1882 0.939 1883 0.852 1884 0.801 1885 0.962 1886 0.707 1887 0.966 1888 0.677 1889 0.861 1890 0.681 1891 0.769 1892 0.919 1893 0.823 1894 0.985 1895 1.153 1896 1.303 1897 1.214 1898 1.22 1899 1.481 1900 1.667 1901 1.815 1902 1.536 1903 1.602 1904 1.659 1905 1.529 1906 1.145 1907 1.378 1908 1.626 1909 1.024 1910 1.234 1911 1.191 1912 1.071 1913 0.987 1914 1.181 1915 1.024 1916 1.01 1917 1.144 1918 0.951 1919 1.091 1920 0.895 1921 1.298 1922 0.995 1923 1.105 1924 1.023 1925 1.024 1926 0.855 1927 1.095 1928 1.144 1929 0.943 1930 0.952 1931 1.133 1932 0.923 1933 0.797 1934 0.788 1935 1.005 1936 0.764 1937 0.929 1938 0.891 1939 0.941 1940 0.801 1941 1.108 1942 1.228 1943 1.16 1944 1.04 1945 1.139 1946 0.946 1947 1.159 1948 0.538 1949 0.97 1950 0.905 1951 0.922 1952 0.952 1953 0.808 1954 0.871 1955 1.036 1956 0.987 1957 0.968 1958 1.037 1959 1.143 1960 0.994 1961 1.118 1962 1.077 1963 1.049 1964 1.066 1965 0.845 1966 0.847 1967 0.888 1968 0.791 1969 0.883 1970 0.96 1971 1.021 1972 1.038 1973 1.1 1974 0.77 1975 0.815 1976 1.039 1977 0.97 1978 0.944 1979 1.139 1980 0.957 1981 1.005 1982 1.211 1983 1.196 1984 1.041 1985 1.126 1986 0.774 1987 0.746 1988 0.666 1989 0.835 1990 0.765 1991 0.848 1992 0.606 1993 0.86 1994 0.931 1995 0.889