# europe_norw006 - Veolia - 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/4713 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_norw006 - Veolia - 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: Veolia # Location: # Country: Norway # Northernmost_Latitude: 61.42 # Southernmost_Latitude: 61.42 # Easternmost_Longitude: 8.98 # Westernmost_Longitude: 8.98 # Elevation: 880 m #-------------------- # Data_Collection # Collection_Name: europe_norw006B # Earliest_Year: 1780 # Most_Recent_Year: 1978 # 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":"5.06353617926","T2":"17.9720817915","M1":"0.0222141859774","M2":"0.383804725459"}} #-------------------- # Species # Species_Name: Scots pine # Species_Code: PISY #-------------------- # 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 1780 0.862 1781 0.663 1782 0.618 1783 0.254 1784 0.355 1785 0.5 1786 0.55 1787 0.704 1788 0.683 1789 0.595 1790 0.666 1791 0.65 1792 0.907 1793 1.114 1794 1.252 1795 1.092 1796 0.875 1797 1.4 1798 1.211 1799 1.093 1800 0.792 1801 1.099 1802 0.722 1803 0.567 1804 0.931 1805 0.929 1806 0.733 1807 0.884 1808 0.802 1809 1.04 1810 0.813 1811 1.13 1812 0.798 1813 1.047 1814 1.073 1815 1.055 1816 1.067 1817 0.854 1818 0.893 1819 1.049 1820 0.934 1821 0.736 1822 1.137 1823 0.95 1824 0.886 1825 0.921 1826 1.209 1827 1.153 1828 1.378 1829 1.092 1830 1.132 1831 1.539 1832 0.855 1833 1.133 1834 1.614 1835 0.973 1836 0.78 1837 0.634 1838 0.807 1839 0.815 1840 0.753 1841 0.738 1842 1.01 1843 1.201 1844 0.814 1845 0.891 1846 1.023 1847 1.106 1848 0.958 1849 0.877 1850 1.065 1851 0.83 1852 1.06 1853 0.809 1854 1.295 1855 1.272 1856 0.979 1857 1.008 1858 1.227 1859 1.115 1860 1.114 1861 1.221 1862 1.161 1863 1.287 1864 1.136 1865 0.739 1866 0.969 1867 0.654 1868 0.74 1869 0.612 1870 0.85 1871 0.798 1872 0.81 1873 1.051 1874 1.009 1875 1.295 1876 1.075 1877 0.987 1878 1.237 1879 1.202 1880 1.175 1881 0.809 1882 1.231 1883 1.221 1884 1.171 1885 1.299 1886 0.919 1887 1.229 1888 0.872 1889 0.895 1890 0.837 1891 0.916 1892 1.004 1893 1.096 1894 1.28 1895 1.109 1896 1.362 1897 1.571 1898 1.171 1899 1.347 1900 1.367 1901 1.485 1902 0.999 1903 0.895 1904 1.1 1905 0.686 1906 0.675 1907 0.781 1908 0.828 1909 0.776 1910 1.023 1911 1.026 1912 1.058 1913 1.056 1914 1.585 1915 1.18 1916 1.197 1917 1.356 1918 1.256 1919 1.333 1920 0.946 1921 1.025 1922 0.954 1923 0.706 1924 0.654 1925 0.933 1926 0.771 1927 0.695 1928 0.355 1929 0.789 1930 0.935 1931 0.682 1932 0.622 1933 0.84 1934 1.074 1935 0.954 1936 1.091 1937 1.482 1938 1.366 1939 1.24 1940 0.936 1941 1.214 1942 1.042 1943 1.359 1944 1.395 1945 1.19 1946 1.039 1947 1.179 1948 0.999 1949 0.83 1950 0.805 1951 0.929 1952 1.149 1953 1.188 1954 1.177 1955 1.122 1956 0.74 1957 0.879 1958 0.635 1959 0.824 1960 0.802 1961 0.76 1962 0.885 1963 0.938 1964 0.879 1965 0.749 1966 0.797 1967 0.907 1968 0.864 1969 0.861 1970 0.699 1971 0.724 1972 1.105 1973 1.133 1974 0.77 1975 0.849 1976 0.834 1977 0.663 1978 0.695