# europe_finl063 - Pyhatunturi - 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/2846 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_finl063 - Pyhatunturi - 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: Pyhatunturi # Location: # Country: Finland # Northernmost_Latitude: 67.0 # Southernmost_Latitude: 67.0 # Easternmost_Longitude: 27.25 # Westernmost_Longitude: 27.25 # Elevation: 260 m #-------------------- # Data_Collection # Collection_Name: europe_finl063B # Earliest_Year: 1681 # Most_Recent_Year: 1983 # 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":"3.54826041581","T2":"17.7883035755","M1":"0.0226623225257","M2":"0.367488699792"}} #-------------------- # 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 1681 0.828 1682 0.849 1683 0.797 1684 0.789 1685 0.766 1686 0.814 1687 0.954 1688 0.817 1689 0.939 1690 1.017 1691 1.11 1692 1.142 1693 1.043 1694 1.107 1695 0.886 1696 0.601 1697 0.851 1698 1.063 1699 1.121 1700 1.239 1701 1.093 1702 1.191 1703 1.16 1704 1.214 1705 1.179 1706 1.135 1707 1.316 1708 1.094 1709 0.894 1710 1.229 1711 1.164 1712 1.007 1713 0.757 1714 0.843 1715 1.075 1716 0.982 1717 0.974 1718 1.147 1719 0.944 1720 1.092 1721 1.02 1722 1.127 1723 1.09 1724 0.979 1725 1.037 1726 1.043 1727 1.259 1728 1.035 1729 1.366 1730 1.275 1731 0.904 1732 1.024 1733 0.934 1734 0.684 1735 0.838 1736 1.204 1737 0.955 1738 1.177 1739 1.299 1740 0.936 1741 0.969 1742 1.069 1743 1.147 1744 1.267 1745 1.066 1746 1.273 1747 0.965 1748 1.033 1749 0.975 1750 0.996 1751 1.016 1752 1.327 1753 1.214 1754 1.413 1755 1.282 1756 1.139 1757 1.179 1758 1.363 1759 1.3 1760 1.603 1761 1.202 1762 1.233 1763 1.051 1764 1.013 1765 1.079 1766 1.064 1767 0.916 1768 0.893 1769 0.76 1770 0.735 1771 0.651 1772 0.949 1773 0.971 1774 1.079 1775 1.003 1776 0.805 1777 1.046 1778 0.999 1779 1.056 1780 0.956 1781 0.779 1782 0.862 1783 0.715 1784 0.789 1785 1.047 1786 0.889 1787 0.887 1788 0.919 1789 1.029 1790 0.758 1791 0.899 1792 0.837 1793 0.705 1794 0.583 1795 0.612 1796 0.825 1797 0.865 1798 0.954 1799 0.996 1800 0.798 1801 0.927 1802 0.971 1803 0.876 1804 1.081 1805 0.995 1806 0.723 1807 1.08 1808 0.921 1809 0.829 1810 0.932 1811 0.904 1812 0.849 1813 0.622 1814 0.888 1815 0.921 1816 1.034 1817 1.109 1818 1.119 1819 1.216 1820 0.768 1821 0.795 1822 0.843 1823 1.091 1824 1.062 1825 1.155 1826 1.349 1827 1.191 1828 1.084 1829 1.191 1830 0.96 1831 0.939 1832 0.894 1833 0.895 1834 1.048 1835 0.814 1836 0.656 1837 0.48 1838 0.785 1839 0.717 1840 0.832 1841 0.75 1842 0.709 1843 0.877 1844 0.714 1845 0.836 1846 0.622 1847 0.683 1848 0.679 1849 0.829 1850 0.81 1851 0.909 1852 1.108 1853 0.994 1854 0.978 1855 0.932 1856 0.757 1857 0.75 1858 0.778 1859 0.663 1860 0.641 1861 0.688 1862 0.666 1863 0.679 1864 0.812 1865 0.928 1866 0.871 1867 0.895 1868 1.112 1869 0.948 1870 1.175 1871 0.993 1872 0.933 1873 0.873 1874 0.719 1875 0.885 1876 1.007 1877 1.033 1878 0.994 1879 0.861 1880 0.543 1881 0.578 1882 1.031 1883 0.824 1884 0.88 1885 0.985 1886 1.099 1887 1.0 1888 0.828 1889 1.012 1890 1.296 1891 1.167 1892 0.994 1893 0.923 1894 0.936 1895 1.027 1896 1.355 1897 0.969 1898 1.3 1899 1.238 1900 0.97 1901 1.078 1902 0.731 1903 0.624 1904 0.829 1905 0.889 1906 0.997 1907 0.864 1908 0.914 1909 0.853 1910 0.708 1911 0.787 1912 0.925 1913 0.838 1914 0.909 1915 1.038 1916 0.881 1917 0.828 1918 0.91 1919 0.95 1920 0.906 1921 1.141 1922 1.379 1923 1.435 1924 1.411 1925 1.494 1926 1.232 1927 1.305 1928 0.941 1929 0.94 1930 1.224 1931 1.16 1932 1.181 1933 0.901 1934 1.132 1935 0.942 1936 1.015 1937 1.337 1938 1.05 1939 0.993 1940 0.83 1941 1.204 1942 0.907 1943 0.99 1944 0.994 1945 0.936 1946 0.866 1947 1.213 1948 1.18 1949 1.232 1950 1.225 1951 1.12 1952 1.166 1953 1.433 1954 1.373 1955 1.276 1956 1.055 1957 1.27 1958 1.081 1959 1.417 1960 1.368 1961 0.898 1962 0.981 1963 0.87 1964 1.365 1965 1.009 1966 1.215 1967 1.245 1968 1.168 1969 0.82 1970 1.063 1971 0.995 1972 1.139 1973 1.331 1974 0.935 1975 1.057 1976 1.115 1977 0.974 1978 0.906 1979 1.153 1980 0.991 1981 0.928 1982 1.025 1983 1.123