# europe_norw014 - Jondalen - 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/2826 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_norw014 - Jondalen - 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: Jondalen # Location: # Country: Norway # Northernmost_Latitude: 59.7 # Southernmost_Latitude: 59.7 # Easternmost_Longitude: 9.48 # Westernmost_Longitude: 9.48 # Elevation: 400 m #-------------------- # Data_Collection # Collection_Name: europe_norw014B # Earliest_Year: 1718 # Most_Recent_Year: 1981 # Time_Unit: y_ad # Core_Length: # Notes: {"database":{"database1":"LMR","database2":"Breits"}} {"climateInterpretation":{"basis":"", "climateVariable":"M", "climateVariableDetail":"air", "interpDirection":"positive", "seasonality":"[6, 7, 8]"}}{"VSLite_parameters":{"T1":"3.25029572162","T2":"12.4192695118","M1":"0.0222686140289","M2":"0.586943489494"}} #-------------------- # 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 1718 1.191 1719 1.047 1720 1.63 1721 1.839 1722 1.658 1723 0.931 1724 1.14 1725 1.428 1726 0.975 1727 1.163 1728 0.868 1729 0.83 1730 1.199 1731 1.314 1732 1.254 1733 1.384 1734 1.606 1735 1.178 1736 0.914 1737 0.957 1738 1.035 1739 1.039 1740 0.739 1741 0.552 1742 0.594 1743 0.964 1744 1.058 1745 1.26 1746 0.785 1747 1.012 1748 0.691 1749 0.711 1750 1.076 1751 1.066 1752 1.184 1753 0.955 1754 0.937 1755 0.692 1756 0.826 1757 0.876 1758 0.852 1759 1.282 1760 1.118 1761 1.259 1762 1.043 1763 1.423 1764 1.601 1765 1.217 1766 1.774 1767 1.614 1768 0.975 1769 0.975 1770 1.133 1771 0.879 1772 0.817 1773 1.194 1774 1.225 1775 0.665 1776 1.509 1777 1.225 1778 1.189 1779 0.933 1780 1.181 1781 0.327 1782 1.052 1783 0.846 1784 1.163 1785 0.855 1786 0.786 1787 0.969 1788 0.4 1789 0.989 1790 0.884 1791 0.887 1792 0.952 1793 1.034 1794 1.011 1795 0.641 1796 0.527 1797 0.846 1798 0.781 1799 0.819 1800 0.598 1801 0.573 1802 0.539 1803 0.557 1804 0.637 1805 0.574 1806 0.417 1807 0.783 1808 0.755 1809 0.797 1810 0.807 1811 0.912 1812 1.008 1813 0.87 1814 0.744 1815 0.756 1816 0.849 1817 1.127 1818 0.986 1819 0.973 1820 0.694 1821 0.517 1822 0.493 1823 0.592 1824 0.495 1825 0.698 1826 0.649 1827 0.808 1828 0.876 1829 0.791 1830 0.542 1831 0.521 1832 0.726 1833 0.777 1834 0.988 1835 0.723 1836 0.848 1837 0.72 1838 0.647 1839 0.622 1840 0.533 1841 0.55 1842 0.754 1843 0.685 1844 0.64 1845 0.711 1846 0.542 1847 0.774 1848 0.742 1849 0.332 1850 0.485 1851 0.582 1852 0.641 1853 0.613 1854 0.884 1855 0.813 1856 0.688 1857 0.674 1858 0.881 1859 0.793 1860 0.861 1861 0.797 1862 0.997 1863 0.794 1864 0.819 1865 0.748 1866 0.919 1867 0.658 1868 0.684 1869 0.782 1870 0.914 1871 0.776 1872 0.959 1873 0.928 1874 0.954 1875 0.98 1876 0.627 1877 0.751 1878 0.855 1879 0.924 1880 0.951 1881 0.817 1882 1.054 1883 0.864 1884 1.152 1885 1.086 1886 0.989 1887 0.665 1888 0.915 1889 0.771 1890 1.167 1891 1.098 1892 0.961 1893 0.874 1894 1.193 1895 1.091 1896 1.155 1897 1.16 1898 1.193 1899 0.956 1900 1.014 1901 0.945 1902 0.655 1903 0.991 1904 0.73 1905 0.979 1906 0.927 1907 0.974 1908 1.015 1909 1.061 1910 1.436 1911 1.022 1912 0.993 1913 1.161 1914 1.083 1915 0.662 1916 0.952 1917 0.878 1918 0.78 1919 0.885 1920 0.758 1921 0.869 1922 0.84 1923 0.828 1924 1.127 1925 1.151 1926 1.237 1927 1.204 1928 0.925 1929 1.013 1930 1.203 1931 0.84 1932 1.104 1933 0.934 1934 0.789 1935 0.909 1936 0.892 1937 1.126 1938 0.794 1939 1.241 1940 0.832 1941 0.961 1942 1.068 1943 1.24 1944 1.471 1945 1.659 1946 1.718 1947 0.898 1948 0.896 1949 1.576 1950 1.202 1951 1.494 1952 1.281 1953 1.684 1954 1.608 1955 1.056 1956 1.504 1957 1.614 1958 1.554 1959 0.904 1960 0.875 1961 0.909 1962 1.222 1963 1.358 1964 1.698 1965 1.715 1966 1.283 1967 1.575 1968 1.339 1969 1.136 1970 0.867 1971 1.047 1972 1.168 1973 1.17 1974 1.016 1975 0.827 1976 1.003 1977 0.737 1978 0.876 1979 1.104 1980 1.225 1981 1.358