# europe_norw007 - Karasjok - 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/3990 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_norw007 - Karasjok - 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: Karasjok # Location: # Country: Norway # Northernmost_Latitude: 69.42 # Southernmost_Latitude: 69.42 # Easternmost_Longitude: 25.63 # Westernmost_Longitude: 25.63 # Elevation: 350 m #-------------------- # Data_Collection # Collection_Name: europe_norw007B # Earliest_Year: 1719 # Most_Recent_Year: 2001 # 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":"6.68867105498","T2":"19.6224872486","M1":"0.0224927487915","M2":"0.310916667075"}} #-------------------- # 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 1719 0.841 1720 0.844 1721 1.0 1722 1.079 1723 0.818 1724 1.06 1725 1.139 1726 1.055 1727 1.134 1728 0.944 1729 1.143 1730 1.333 1731 1.029 1732 0.994 1733 0.892 1734 0.534 1735 0.723 1736 0.846 1737 0.877 1738 1.296 1739 1.404 1740 1.149 1741 1.117 1742 1.247 1743 0.998 1744 0.971 1745 0.91 1746 1.135 1747 0.891 1748 0.995 1749 1.012 1750 1.024 1751 1.002 1752 1.205 1753 1.243 1754 1.309 1755 1.385 1756 1.302 1757 1.417 1758 1.314 1759 1.273 1760 1.226 1761 1.414 1762 1.317 1763 1.177 1764 0.933 1765 0.926 1766 1.01 1767 0.758 1768 0.895 1769 0.633 1770 0.865 1771 0.692 1772 0.763 1773 0.734 1774 0.844 1775 0.904 1776 0.874 1777 1.038 1778 1.177 1779 1.141 1780 1.24 1781 0.979 1782 0.94 1783 0.899 1784 0.81 1785 0.946 1786 0.579 1787 0.545 1788 0.63 1789 0.669 1790 0.554 1791 0.616 1792 0.663 1793 0.627 1794 0.684 1795 0.699 1796 0.978 1797 1.19 1798 1.213 1799 1.498 1800 1.046 1801 1.071 1802 0.971 1803 0.777 1804 1.145 1805 1.071 1806 0.505 1807 0.877 1808 1.143 1809 0.85 1810 0.666 1811 0.591 1812 0.556 1813 0.382 1814 0.555 1815 0.576 1816 0.643 1817 0.811 1818 0.986 1819 0.932 1820 0.922 1821 0.709 1822 0.738 1823 1.111 1824 1.117 1825 0.81 1826 1.487 1827 1.601 1828 1.326 1829 1.65 1830 1.626 1831 1.533 1832 1.248 1833 1.048 1834 0.951 1835 0.857 1836 0.997 1837 0.488 1838 0.821 1839 0.67 1840 0.881 1841 0.821 1842 0.788 1843 1.003 1844 1.267 1845 1.1 1846 0.871 1847 0.95 1848 0.958 1849 1.037 1850 0.912 1851 0.958 1852 1.058 1853 0.943 1854 1.155 1855 1.198 1856 1.133 1857 1.21 1858 1.423 1859 1.123 1860 1.164 1861 1.165 1862 1.011 1863 1.112 1864 1.331 1865 1.236 1866 0.971 1867 0.869 1868 0.933 1869 0.941 1870 1.056 1871 1.005 1872 1.019 1873 1.157 1874 0.715 1875 0.8 1876 1.096 1877 1.003 1878 0.765 1879 0.694 1880 0.554 1881 0.56 1882 0.844 1883 0.887 1884 0.753 1885 0.677 1886 0.666 1887 0.791 1888 0.646 1889 0.837 1890 1.157 1891 1.024 1892 0.778 1893 0.696 1894 0.961 1895 1.17 1896 1.164 1897 1.003 1898 1.334 1899 1.065 1900 0.669 1901 1.028 1902 0.639 1903 0.395 1904 0.634 1905 0.595 1906 0.643 1907 0.567 1908 0.79 1909 0.634 1910 0.503 1911 0.604 1912 0.858 1913 0.837 1914 0.954 1915 0.918 1916 0.95 1917 0.682 1918 0.911 1919 0.866 1920 0.995 1921 1.099 1922 1.268 1923 1.277 1924 1.253 1925 1.46 1926 1.188 1927 1.17 1928 0.87 1929 0.774 1930 1.287 1931 1.168 1932 1.028 1933 1.12 1934 1.651 1935 1.254 1936 1.136 1937 1.542 1938 1.216 1939 1.094 1940 0.842 1941 1.135 1942 0.997 1943 0.844 1944 0.824 1945 0.923 1946 0.921 1947 0.924 1948 1.031 1949 1.122 1950 1.226 1951 1.012 1952 1.062 1953 1.461 1954 1.516 1955 1.332 1956 1.453 1957 1.698 1958 1.26 1959 1.343 1960 1.39 1961 0.935 1962 0.922 1963 0.69 1964 1.186 1965 0.894 1966 0.947 1967 1.117 1968 0.917 1969 1.007 1970 1.135 1971 1.016 1972 1.071 1973 1.28 1974 0.97 1975 1.027 1976 1.078 1977 1.036 1978 0.803 1979 1.054 1980 0.928 1981 0.813 1982 0.861 1983 0.903 1984 0.672 1985 0.915 1986 0.766 1987 0.666 1988 0.811 1989 0.888 1990 0.835 1991 0.842 1992 0.843 1993 1.013 1994 0.926 1995 0.76 1996 0.744 1997 0.926 1998 0.903 1999 0.882 2000 0.981 2001 0.704