# europe_norw004 - Skibotn - 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/4655 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_norw004 - Skibotn - 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: Skibotn # Location: # Country: Norway # Northernmost_Latitude: 69.25 # Southernmost_Latitude: 69.25 # Easternmost_Longitude: 20.58 # Westernmost_Longitude: 20.58 # Elevation: 80 m #-------------------- # Data_Collection # Collection_Name: europe_norw004B # Earliest_Year: 1797 # 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":"4.175637286","T2":"16.9760695911","M1":"0.0223134266446","M2":"0.394390356011"}} #-------------------- # 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 1797 1.259 1798 1.258 1799 1.248 1800 0.965 1801 1.258 1802 1.198 1803 1.119 1804 1.299 1805 1.307 1806 0.807 1807 0.512 1808 0.529 1809 0.823 1810 0.829 1811 0.987 1812 0.814 1813 1.095 1814 0.962 1815 0.853 1816 0.733 1817 0.937 1818 0.981 1819 1.044 1820 0.748 1821 0.733 1822 1.023 1823 1.218 1824 1.122 1825 1.02 1826 1.33 1827 1.263 1828 1.575 1829 0.737 1830 0.936 1831 1.347 1832 1.049 1833 0.813 1834 0.793 1835 0.708 1836 1.141 1837 1.187 1838 1.402 1839 1.219 1840 1.183 1841 0.621 1842 0.445 1843 0.746 1844 1.003 1845 0.987 1846 1.104 1847 1.289 1848 1.295 1849 1.341 1850 1.521 1851 1.61 1852 1.262 1853 0.661 1854 0.611 1855 0.642 1856 0.8 1857 0.977 1858 1.418 1859 1.011 1860 0.949 1861 0.621 1862 0.644 1863 0.906 1864 0.938 1865 1.009 1866 1.169 1867 1.078 1868 1.034 1869 1.12 1870 1.313 1871 1.129 1872 1.135 1873 0.654 1874 0.565 1875 1.041 1876 1.146 1877 1.164 1878 1.048 1879 0.954 1880 0.533 1881 0.367 1882 0.768 1883 1.103 1884 1.291 1885 0.986 1886 1.08 1887 1.239 1888 1.281 1889 1.482 1890 1.746 1891 1.37 1892 1.054 1893 1.091 1894 1.251 1895 0.891 1896 0.731 1897 0.908 1898 0.649 1899 0.366 1900 0.449 1901 0.781 1902 0.674 1903 0.638 1904 0.685 1905 0.62 1906 0.709 1907 0.862 1908 0.876 1909 0.69 1910 1.103 1911 1.02 1912 0.864 1913 0.907 1914 0.978 1915 1.026 1916 1.206 1917 0.949 1918 0.963 1919 1.104 1920 1.346 1921 1.09 1922 0.756 1923 0.657 1924 0.856 1925 0.856 1926 0.681 1927 0.796 1928 0.632 1929 0.78 1930 1.343 1931 0.784 1932 0.8 1933 0.692 1934 0.805 1935 0.779 1936 0.9 1937 1.012 1938 0.851 1939 1.044 1940 1.137 1941 1.244 1942 0.88 1943 0.852 1944 0.719 1945 1.018 1946 1.039 1947 1.123 1948 1.422 1949 1.789 1950 1.762 1951 1.347 1952 1.197 1953 1.426 1954 0.944 1955 0.631 1956 0.644 1957 0.859 1958 0.856 1959 0.76 1960 0.662 1961 0.736 1962 0.986 1963 1.211 1964 1.508 1965 1.282 1966 1.144 1967 1.174 1968 1.045 1969 0.773 1970 0.879 1971 0.89 1972 0.912 1973 1.049 1974 1.1 1975 0.98 1976 1.074 1977 0.965 1978 0.871