# europe_swit171w - Suaiza, TI - 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/4665 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_swit171w - Suaiza, TI - 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: Suaiza, TI # Location: # Country: Switzerland # Northernmost_Latitude: 46.43 # Southernmost_Latitude: 46.43 # Easternmost_Longitude: 8.87 # Westernmost_Longitude: 8.87 # Elevation: 1520 m #-------------------- # Data_Collection # Collection_Name: europe_swit171wB # Earliest_Year: 1750 # 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":"5.10967357957","T2":"14.8332342153","M1":"0.0224783765164","M2":"0.417982940303"}} #-------------------- # 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 1750 0.948 1751 1.177 1752 1.194 1753 1.143 1754 1.068 1755 0.806 1756 1.017 1757 1.346 1758 1.391 1759 1.275 1760 1.079 1761 0.979 1762 0.878 1763 1.027 1764 0.929 1765 1.087 1766 1.176 1767 1.148 1768 1.005 1769 0.946 1770 1.131 1771 1.091 1772 0.98 1773 0.947 1774 0.943 1775 0.771 1776 0.791 1777 0.89 1778 0.932 1779 0.664 1780 0.903 1781 0.915 1782 0.733 1783 0.907 1784 1.016 1785 1.025 1786 1.147 1787 1.056 1788 1.113 1789 0.908 1790 0.773 1791 0.806 1792 0.806 1793 0.692 1794 0.884 1795 0.812 1796 0.707 1797 0.652 1798 0.588 1799 0.507 1800 0.617 1801 0.718 1802 0.841 1803 0.604 1804 0.621 1805 0.641 1806 0.562 1807 0.641 1808 0.545 1809 0.543 1810 0.622 1811 0.757 1812 0.843 1813 0.91 1814 1.111 1815 1.139 1816 0.908 1817 1.195 1818 1.025 1819 1.111 1820 1.021 1821 0.968 1822 0.959 1823 1.002 1824 0.821 1825 0.969 1826 0.83 1827 0.862 1828 0.877 1829 0.913 1830 0.745 1831 0.931 1832 0.661 1833 0.848 1834 0.749 1835 0.583 1836 0.64 1837 0.664 1838 0.625 1839 0.566 1840 0.525 1841 0.683 1842 0.98 1843 0.998 1844 1.151 1845 0.97 1846 0.984 1847 0.75 1848 1.117 1849 0.934 1850 0.861 1851 0.866 1852 0.853 1853 0.967 1854 0.933 1855 1.164 1856 1.053 1857 1.109 1858 1.058 1859 1.05 1860 0.71 1861 1.06 1862 0.759 1863 0.91 1864 1.046 1865 1.014 1866 1.06 1867 1.018 1868 1.074 1869 1.076 1870 0.871 1871 1.023 1872 0.941 1873 1.03 1874 0.993 1875 1.036 1876 0.877 1877 1.086 1878 1.164 1879 1.141 1880 1.062 1881 1.127 1882 0.992 1883 1.144 1884 0.979 1885 1.084 1886 0.899 1887 0.869 1888 0.88 1889 1.104 1890 1.177 1891 0.958 1892 1.283 1893 1.084 1894 0.739 1895 0.679 1896 0.688 1897 0.782 1898 0.796 1899 0.974 1900 1.084 1901 1.098 1902 0.865 1903 0.982 1904 1.294 1905 1.027 1906 0.971 1907 1.175 1908 1.272 1909 1.001 1910 1.306 1911 1.124 1912 1.174 1913 1.173 1914 1.221 1915 1.15 1916 1.174 1917 1.211 1918 1.239 1919 1.067 1920 1.247 1921 1.22 1922 1.048 1923 1.074 1924 1.179 1925 1.205 1926 1.086 1927 1.135 1928 0.978 1929 1.034 1930 1.006 1931 1.132 1932 1.083 1933 1.026 1934 0.998 1935 1.126 1936 1.161 1937 1.184 1938 1.022 1939 1.134 1940 1.089 1941 1.106 1942 0.933 1943 0.961 1944 1.028 1945 0.888 1946 1.027 1947 1.056 1948 0.94 1949 0.847 1950 0.77 1951 0.727 1952 0.95 1953 0.838 1954 0.915 1955 1.507 1956 1.168 1957 0.902 1958 0.976 1959 0.982 1960 0.977 1961 1.038 1962 0.855 1963 0.929 1964 1.11 1965 1.142 1966 1.07 1967 1.04 1968 1.163 1969 1.361 1970 1.17 1971 1.105 1972 1.092 1973 1.049 1974 0.932 1975 0.892 1976 0.641 1977 0.853 1978 0.914 1979 0.949 1980 0.929 1981 0.973 1982 1.32 1983 1.004 1984 0.73 1985 0.952 1986 0.822 1987 1.017 1988 0.959