# europe_swit102 - Grindelwald BE - 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/4428 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_swit102 - Grindelwald BE - 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 BE # Location: # Country: Switzerland # Northernmost_Latitude: 46.6 # Southernmost_Latitude: 46.6 # Easternmost_Longitude: 8.07 # Westernmost_Longitude: 8.07 # Elevation: 1370 m #-------------------- # Data_Collection # Collection_Name: europe_swit102B # Earliest_Year: 1812 # Most_Recent_Year: 1977 # 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":"5.57882969609","T2":"17.3274783672","M1":"0.0224310881306","M2":"0.389353047562"}} #-------------------- # 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 1812 0.655 1813 0.647 1814 0.864 1815 0.919 1816 0.665 1817 0.803 1818 1.019 1819 1.158 1820 0.778 1821 0.607 1822 0.928 1823 0.773 1824 0.841 1825 0.914 1826 0.932 1827 0.867 1828 1.098 1829 1.265 1830 1.021 1831 1.354 1832 1.134 1833 1.617 1834 1.553 1835 0.929 1836 1.056 1837 0.946 1838 0.609 1839 0.926 1840 0.998 1841 1.108 1842 1.505 1843 0.749 1844 0.822 1845 0.982 1846 1.108 1847 0.895 1848 0.918 1849 1.178 1850 1.13 1851 0.89 1852 0.797 1853 1.093 1854 1.191 1855 1.028 1856 0.772 1857 0.819 1858 0.658 1859 0.699 1860 0.763 1861 0.972 1862 0.897 1863 1.1 1864 1.164 1865 1.097 1866 1.013 1867 0.871 1868 0.999 1869 0.778 1870 0.841 1871 0.766 1872 0.989 1873 1.275 1874 1.009 1875 1.147 1876 0.98 1877 0.812 1878 1.036 1879 0.953 1880 1.235 1881 1.239 1882 1.207 1883 0.9 1884 1.112 1885 1.063 1886 0.97 1887 0.849 1888 0.916 1889 1.041 1890 1.145 1891 0.933 1892 1.149 1893 1.17 1894 1.168 1895 1.327 1896 1.146 1897 1.079 1898 0.928 1899 1.022 1900 0.913 1901 1.177 1902 0.829 1903 0.935 1904 0.987 1905 1.065 1906 0.867 1907 0.926 1908 1.159 1909 0.959 1910 1.114 1911 1.15 1912 0.773 1913 0.791 1914 0.919 1915 0.75 1916 0.986 1917 1.052 1918 0.915 1919 0.916 1920 0.846 1921 0.97 1922 0.959 1923 0.972 1924 1.289 1925 1.331 1926 1.026 1927 0.91 1928 0.982 1929 1.116 1930 1.055 1931 1.146 1932 1.127 1933 1.091 1934 1.31 1935 1.29 1936 1.127 1937 1.142 1938 0.941 1939 0.923 1940 0.896 1941 0.943 1942 0.836 1943 0.973 1944 0.967 1945 1.11 1946 1.072 1947 1.398 1948 0.751 1949 0.918 1950 0.847 1951 1.013 1952 1.132 1953 1.205 1954 0.887 1955 1.036 1956 0.788 1957 0.822 1958 0.745 1959 0.785 1960 0.748 1961 0.669 1962 0.623 1963 0.921 1964 0.906 1965 0.782 1966 1.114 1967 1.128 1968 1.142 1969 1.114 1970 1.083 1971 0.92 1972 0.869 1973 1.089 1974 0.681 1975 0.745 1976 0.477 1977 0.561