# europe_swit189 - Glarus GL - 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/8495 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_swit189 - Glarus GL - 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: Glarus GL # Location: # Country: Switzerland # Northernmost_Latitude: 47.03 # Southernmost_Latitude: 47.03 # Easternmost_Longitude: 9.07 # Westernmost_Longitude: 9.07 # Elevation: 1500 m #-------------------- # Data_Collection # Collection_Name: europe_swit189B # Earliest_Year: 1841 # Most_Recent_Year: 2007 # 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":"5.57222059241","T2":"20.0251098004","M1":"0.0221168344488","M2":"0.360372149731"}} #-------------------- # 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 1841 0.843 1842 1.275 1843 0.79 1844 0.954 1845 0.952 1846 1.211 1847 1.025 1848 1.059 1849 1.271 1850 1.075 1851 0.997 1852 1.09 1853 0.996 1854 1.0 1855 0.935 1856 0.961 1857 1.161 1858 1.007 1859 1.0 1860 0.756 1861 0.92 1862 0.787 1863 1.076 1864 1.092 1865 1.183 1866 1.076 1867 1.287 1868 1.186 1869 1.297 1870 1.212 1871 1.131 1872 1.05 1873 1.157 1874 1.022 1875 1.055 1876 0.947 1877 0.902 1878 1.003 1879 0.98 1880 1.052 1881 1.433 1882 1.168 1883 1.039 1884 1.016 1885 1.001 1886 0.814 1887 1.071 1888 0.816 1889 1.048 1890 0.856 1891 0.734 1892 0.859 1893 0.903 1894 0.96 1895 1.023 1896 0.876 1897 0.954 1898 0.861 1899 0.916 1900 0.883 1901 1.065 1902 0.877 1903 0.889 1904 1.219 1905 1.119 1906 0.877 1907 0.888 1908 1.156 1909 0.745 1910 0.968 1911 1.153 1912 0.842 1913 0.723 1914 0.793 1915 0.88 1916 0.863 1917 1.101 1918 0.769 1919 0.866 1920 0.881 1921 1.017 1922 0.921 1923 1.174 1924 1.204 1925 1.203 1926 0.959 1927 0.991 1928 1.127 1929 0.903 1930 0.88 1931 1.004 1932 0.872 1933 0.692 1934 0.758 1935 0.888 1936 0.873 1937 0.95 1938 1.003 1939 1.019 1940 1.017 1941 1.053 1942 1.142 1943 1.243 1944 1.26 1945 1.379 1946 1.249 1947 1.357 1948 0.737 1949 1.073 1950 0.949 1951 1.083 1952 1.297 1953 1.094 1954 0.876 1955 1.013 1956 0.796 1957 0.753 1958 0.784 1959 0.84 1960 0.762 1961 0.838 1962 0.774 1963 0.887 1964 1.048 1965 0.852 1966 0.976 1967 1.073 1968 1.033 1969 1.228 1970 1.105 1971 0.96 1972 0.929 1973 1.057 1974 0.737 1975 0.767 1976 0.848 1977 0.952 1978 0.843 1979 0.957 1980 0.756 1981 0.942 1982 1.205 1983 1.221 1984 0.933 1985 1.114 1986 1.0 1987 0.787 1988 1.102 1989 1.032 1990 0.922 1991 0.894 1992 0.856 1993 0.894 1994 1.113 1995 0.948 1996 0.802 1997 0.766 1998 0.887 1999 0.955 2000 1.137 2001 1.318 2002 1.111 2003 1.109 2004 0.869 2005 1.04 2006 1.236 2007 1.089