# europe_swed325 - Tannsjö - 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/6141 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_swed325 - Tannsjö - 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: Tannsjö # Location: # Country: Sweden # Northernmost_Latitude: 63.98 # Southernmost_Latitude: 63.98 # Easternmost_Longitude: 16.53 # Westernmost_Longitude: 16.53 # Elevation: 270 m #-------------------- # Data_Collection # Collection_Name: europe_swed325B # Earliest_Year: 1702 # Most_Recent_Year: 1999 # 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":"4.66956763741","T2":"17.0144655534","M1":"0.0224033400073","M2":"0.452154232978"}} #-------------------- # 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 1702 1.335 1703 1.3 1704 1.004 1705 1.032 1706 0.875 1707 1.04 1708 0.743 1709 0.778 1710 0.995 1711 1.022 1712 1.006 1713 0.827 1714 1.089 1715 1.01 1716 1.224 1717 1.193 1718 1.146 1719 1.064 1720 1.146 1721 0.992 1722 1.099 1723 1.262 1724 1.149 1725 1.136 1726 1.127 1727 1.057 1728 0.862 1729 0.998 1730 1.104 1731 1.004 1732 1.109 1733 0.949 1734 0.893 1735 0.706 1736 0.776 1737 0.862 1738 1.078 1739 1.05 1740 0.927 1741 0.733 1742 0.832 1743 0.837 1744 0.922 1745 0.789 1746 0.757 1747 0.814 1748 0.931 1749 0.838 1750 0.947 1751 1.134 1752 1.511 1753 1.096 1754 1.166 1755 1.253 1756 0.943 1757 0.959 1758 0.964 1759 1.079 1760 1.002 1761 0.994 1762 1.179 1763 1.321 1764 1.314 1765 1.14 1766 1.312 1767 0.974 1768 0.999 1769 0.938 1770 0.814 1771 0.82 1772 0.829 1773 0.773 1774 0.925 1775 0.895 1776 0.818 1777 0.937 1778 1.1 1779 1.043 1780 0.83 1781 0.833 1782 0.793 1783 0.767 1784 1.097 1785 1.082 1786 0.807 1787 0.829 1788 0.912 1789 0.819 1790 0.55 1791 0.804 1792 0.747 1793 0.715 1794 0.778 1795 0.667 1796 0.633 1797 0.59 1798 0.701 1799 0.914 1800 0.791 1801 0.874 1802 0.837 1803 0.803 1804 0.96 1805 0.986 1806 0.864 1807 0.846 1808 0.723 1809 0.785 1810 0.659 1811 0.848 1812 0.718 1813 0.745 1814 0.842 1815 0.893 1816 1.136 1817 1.245 1818 1.388 1819 1.636 1820 1.211 1821 1.043 1822 1.201 1823 1.262 1824 0.986 1825 1.247 1826 1.657 1827 1.459 1828 1.561 1829 1.265 1830 1.128 1831 1.142 1832 0.806 1833 1.035 1834 1.053 1835 0.647 1836 0.802 1837 0.742 1838 0.833 1839 0.686 1840 0.61 1841 0.709 1842 0.607 1843 0.426 1844 0.372 1845 0.564 1846 0.581 1847 0.512 1848 0.627 1849 0.486 1850 0.523 1851 0.742 1852 0.724 1853 0.679 1854 1.105 1855 1.064 1856 0.974 1857 1.05 1858 1.452 1859 1.128 1860 1.35 1861 1.583 1862 1.15 1863 1.38 1864 1.466 1865 1.121 1866 1.486 1867 1.303 1868 1.67 1869 1.516 1870 1.559 1871 1.502 1872 1.476 1873 1.394 1874 1.406 1875 1.425 1876 1.406 1877 1.369 1878 1.219 1879 1.14 1880 1.019 1881 0.839 1882 1.363 1883 1.093 1884 1.254 1885 1.353 1886 1.023 1887 1.058 1888 0.871 1889 1.046 1890 1.138 1891 1.32 1892 1.11 1893 1.061 1894 1.167 1895 1.068 1896 1.219 1897 1.041 1898 1.124 1899 1.105 1900 1.128 1901 1.358 1902 0.883 1903 0.799 1904 0.752 1905 0.95 1906 1.02 1907 0.91 1908 1.031 1909 0.891 1910 0.833 1911 0.672 1912 0.787 1913 0.791 1914 1.212 1915 1.295 1916 1.214 1917 1.107 1918 1.143 1919 0.985 1920 0.953 1921 1.024 1922 1.413 1923 1.382 1924 1.231 1925 1.407 1926 0.939 1927 1.06 1928 0.791 1929 1.128 1930 1.316 1931 0.957 1932 0.999 1933 1.143 1934 1.173 1935 0.809 1936 0.765 1937 0.848 1938 0.749 1939 1.048 1940 1.004 1941 1.089 1942 0.877 1943 1.125 1944 1.121 1945 1.001 1946 1.087 1947 1.239 1948 1.113 1949 1.151 1950 1.103 1951 0.998 1952 0.897 1953 1.221 1954 1.272 1955 1.187 1956 0.975 1957 0.965 1958 0.998 1959 1.012 1960 1.028 1961 0.664 1962 0.78 1963 0.825 1964 0.833 1965 0.783 1966 0.75 1967 0.863 1968 0.821 1969 0.592 1970 0.699 1971 0.723 1972 0.821 1973 0.996 1974 0.871 1975 0.91 1976 0.747 1977 0.651 1978 0.777 1979 0.82 1980 0.751 1981 0.515 1982 0.526 1983 0.596 1984 0.629 1985 0.937 1986 0.887 1987 0.77 1988 0.871 1989 1.008 1990 0.94 1991 1.021 1992 0.996 1993 0.684 1994 0.792 1995 0.712 1996 0.7 1997 0.829 1998 0.736 1999 0.439