# europe_finl008 - Lieksa Patvinsuo N - 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/3207 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_finl008 - Lieksa Patvinsuo N - 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: Lieksa Patvinsuo N # Location: # Country: Finland # Northernmost_Latitude: 63.1 # Southernmost_Latitude: 63.1 # Easternmost_Longitude: 30.63 # Westernmost_Longitude: 30.63 # Elevation: 165 m #-------------------- # Data_Collection # Collection_Name: europe_finl008B # Earliest_Year: 1727 # Most_Recent_Year: 1985 # 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":"5.29461381432","T2":"19.173560062","M1":"0.0221524089663","M2":"0.222600711819"}} #-------------------- # 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 1727 1.081 1728 1.03 1729 0.985 1730 0.914 1731 0.959 1732 0.943 1733 0.978 1734 0.915 1735 1.045 1736 0.988 1737 0.911 1738 1.314 1739 0.988 1740 1.07 1741 0.687 1742 0.805 1743 0.852 1744 0.811 1745 0.744 1746 0.653 1747 0.762 1748 0.711 1749 0.632 1750 0.656 1751 0.699 1752 0.945 1753 1.15 1754 1.285 1755 1.233 1756 1.103 1757 1.031 1758 1.213 1759 1.159 1760 1.087 1761 1.093 1762 1.193 1763 1.097 1764 0.942 1765 0.801 1766 0.886 1767 0.714 1768 0.764 1769 0.91 1770 0.786 1771 0.701 1772 0.772 1773 0.965 1774 1.217 1775 1.302 1776 1.315 1777 1.256 1778 1.342 1779 1.185 1780 1.316 1781 1.218 1782 1.301 1783 1.311 1784 1.21 1785 1.016 1786 0.847 1787 0.951 1788 1.128 1789 1.262 1790 0.856 1791 0.935 1792 1.124 1793 1.177 1794 1.122 1795 0.874 1796 0.942 1797 0.843 1798 0.96 1799 0.914 1800 0.869 1801 0.778 1802 0.734 1803 0.577 1804 0.728 1805 0.93 1806 0.636 1807 0.772 1808 0.802 1809 1.056 1810 0.842 1811 0.96 1812 0.968 1813 0.863 1814 0.889 1815 0.687 1816 0.848 1817 0.957 1818 0.955 1819 1.165 1820 1.161 1821 1.148 1822 0.972 1823 0.95 1824 0.997 1825 1.008 1826 1.295 1827 1.207 1828 1.01 1829 1.337 1830 1.205 1831 1.339 1832 0.765 1833 0.955 1834 0.641 1835 0.418 1836 0.544 1837 0.532 1838 0.633 1839 0.644 1840 0.679 1841 0.711 1842 0.818 1843 0.682 1844 0.77 1845 0.778 1846 0.811 1847 0.934 1848 1.101 1849 1.256 1850 1.423 1851 1.41 1852 1.333 1853 1.166 1854 1.415 1855 1.314 1856 1.53 1857 1.269 1858 1.377 1859 1.234 1860 1.356 1861 1.593 1862 1.239 1863 1.442 1864 1.591 1865 1.624 1866 1.4 1867 1.004 1868 1.39 1869 1.331 1870 1.126 1871 1.028 1872 1.249 1873 1.291 1874 0.971 1875 1.042 1876 1.02 1877 1.204 1878 0.997 1879 0.858 1880 0.92 1881 0.934 1882 1.255 1883 1.01 1884 1.012 1885 0.938 1886 0.918 1887 0.798 1888 0.854 1889 0.945 1890 1.008 1891 0.932 1892 0.984 1893 1.152 1894 1.016 1895 0.994 1896 1.013 1897 0.96 1898 0.94 1899 0.887 1900 0.993 1901 0.984 1902 0.708 1903 0.898 1904 0.8 1905 0.703 1906 0.732 1907 0.802 1908 0.928 1909 0.883 1910 0.546 1911 0.641 1912 1.102 1913 0.965 1914 1.211 1915 1.451 1916 1.173 1917 1.152 1918 0.841 1919 0.819 1920 0.811 1921 1.058 1922 1.059 1923 1.139 1924 0.973 1925 0.808 1926 0.67 1927 0.948 1928 0.884 1929 1.01 1930 0.953 1931 0.67 1932 0.877 1933 0.752 1934 0.876 1935 0.716 1936 0.837 1937 0.701 1938 0.849 1939 1.02 1940 0.863 1941 0.974 1942 0.841 1943 1.003 1944 0.981 1945 1.103 1946 1.32 1947 1.516 1948 1.282 1949 1.039 1950 0.952 1951 0.968 1952 0.905 1953 1.073 1954 1.291 1955 0.944 1956 0.853 1957 0.84 1958 0.908 1959 0.89 1960 0.925 1961 0.785 1962 0.907 1963 0.764 1964 0.899 1965 0.557 1966 0.914 1967 0.878 1968 0.848 1969 0.639 1970 0.722 1971 0.678 1972 0.891 1973 0.952 1974 0.85 1975 0.726 1976 0.717 1977 0.786 1978 0.907 1979 1.066 1980 0.737 1981 0.839 1982 0.699 1983 0.736 1984 0.71 1985 0.765