# europe_swit193 - Vals GR Riefawald - 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/8499 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_swit193 - Vals GR Riefawald - 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: Vals GR Riefawald # Location: # Country: Switzerland # Northernmost_Latitude: 46.62 # Southernmost_Latitude: 46.62 # Easternmost_Longitude: 9.2 # Westernmost_Longitude: 9.2 # Elevation: 1900 m #-------------------- # Data_Collection # Collection_Name: europe_swit193B # Earliest_Year: 1802 # Most_Recent_Year: 2008 # 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":"4.44819853489","T2":"16.9931182713","M1":"0.02278164975","M2":"0.391842905179"}} #-------------------- # 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 1802 1.082 1803 1.02 1804 0.901 1805 0.902 1806 0.986 1807 1.245 1808 1.093 1809 1.074 1810 1.073 1811 1.45 1812 1.156 1813 0.804 1814 0.941 1815 0.664 1816 0.671 1817 0.708 1818 0.425 1819 0.381 1820 0.459 1821 0.413 1822 0.811 1823 0.692 1824 0.863 1825 0.809 1826 1.024 1827 1.07 1828 1.279 1829 1.401 1830 1.025 1831 1.224 1832 1.037 1833 1.016 1834 1.248 1835 1.219 1836 1.004 1837 0.915 1838 0.726 1839 0.919 1840 0.927 1841 1.001 1842 1.191 1843 0.798 1844 0.992 1845 1.025 1846 1.381 1847 0.862 1848 0.973 1849 0.843 1850 0.829 1851 0.826 1852 0.729 1853 0.981 1854 0.761 1855 0.995 1856 0.991 1857 0.956 1858 0.808 1859 0.958 1860 0.804 1861 0.909 1862 0.821 1863 1.043 1864 0.927 1865 0.817 1866 0.984 1867 1.082 1868 1.031 1869 1.049 1870 1.005 1871 0.994 1872 0.957 1873 1.011 1874 0.967 1875 1.235 1876 1.195 1877 1.075 1878 0.92 1879 0.846 1880 0.886 1881 1.204 1882 1.052 1883 1.082 1884 0.991 1885 0.975 1886 0.791 1887 1.076 1888 0.75 1889 1.055 1890 0.997 1891 1.006 1892 1.095 1893 0.92 1894 1.003 1895 1.079 1896 0.934 1897 1.001 1898 0.915 1899 0.897 1900 1.029 1901 1.252 1902 1.033 1903 1.166 1904 1.429 1905 1.198 1906 0.926 1907 0.845 1908 1.225 1909 0.811 1910 1.064 1911 1.015 1912 0.792 1913 0.74 1914 0.924 1915 1.128 1916 1.089 1917 1.298 1918 0.882 1919 1.182 1920 1.104 1921 1.281 1922 1.196 1923 1.326 1924 1.133 1925 1.072 1926 0.878 1927 1.083 1928 1.143 1929 0.962 1930 0.971 1931 1.176 1932 1.003 1933 0.73 1934 0.738 1935 0.882 1936 0.925 1937 1.042 1938 0.931 1939 1.004 1940 0.906 1941 1.045 1942 1.163 1943 1.095 1944 1.052 1945 1.106 1946 1.114 1947 1.117 1948 0.629 1949 0.912 1950 0.856 1951 0.963 1952 1.173 1953 0.83 1954 0.875 1955 1.238 1956 0.993 1957 0.904 1958 1.123 1959 1.103 1960 1.156 1961 1.246 1962 1.111 1963 1.109 1964 1.213 1965 0.971 1966 1.037 1967 1.123 1968 1.143 1969 1.242 1970 1.109 1971 1.11 1972 0.997 1973 1.092 1974 0.767 1975 0.722 1976 0.797 1977 0.824 1978 0.726 1979 0.921 1980 0.639 1981 0.721 1982 1.019 1983 0.937 1984 0.794 1985 0.887 1986 0.89 1987 0.671 1988 0.809 1989 0.9 1990 0.768 1991 0.877 1992 0.864 1993 1.082 1994 0.977 1995 1.088 1996 0.804 1997 0.728 1998 0.89 1999 0.811 2000 0.988 2001 1.35 2002 1.241 2003 1.157 2004 1.195 2005 1.266 2006 1.278 2007 1.293 2008 1.258