# europe_swed306 - Muddas South - 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/2840 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_swed306 - Muddas South - 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: Muddas South # Location: # Country: Sweden # Northernmost_Latitude: 66.78 # Southernmost_Latitude: 66.78 # Easternmost_Longitude: 20.13 # Westernmost_Longitude: 20.13 # Elevation: 270 m #-------------------- # Data_Collection # Collection_Name: europe_swed306B # Earliest_Year: 1750 # 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":"6.70865933301","T2":"20.0897403463","M1":"0.022241426919","M2":"0.221613224851"}} #-------------------- # 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 1750 0.896 1751 1.172 1752 1.181 1753 1.154 1754 1.239 1755 1.3 1756 1.141 1757 1.109 1758 0.985 1759 1.112 1760 1.237 1761 1.116 1762 1.304 1763 1.358 1764 1.295 1765 0.984 1766 1.184 1767 0.943 1768 0.864 1769 0.809 1770 0.831 1771 0.867 1772 0.866 1773 0.888 1774 0.878 1775 1.006 1776 1.094 1777 1.066 1778 1.149 1779 1.029 1780 0.903 1781 0.986 1782 0.989 1783 0.946 1784 0.952 1785 1.136 1786 0.836 1787 0.695 1788 0.987 1789 1.013 1790 0.837 1791 0.889 1792 0.711 1793 0.643 1794 0.689 1795 0.757 1796 0.74 1797 0.793 1798 0.901 1799 0.907 1800 0.592 1801 0.744 1802 0.845 1803 0.847 1804 1.023 1805 1.12 1806 0.698 1807 0.912 1808 0.863 1809 0.873 1810 0.866 1811 1.042 1812 0.716 1813 0.745 1814 0.838 1815 0.894 1816 1.04 1817 1.175 1818 1.322 1819 1.282 1820 1.13 1821 0.568 1822 0.745 1823 0.801 1824 0.71 1825 0.757 1826 1.287 1827 1.315 1828 1.13 1829 1.097 1830 0.909 1831 1.087 1832 0.938 1833 0.931 1834 1.028 1835 0.889 1836 1.014 1837 0.596 1838 0.919 1839 0.84 1840 0.832 1841 0.831 1842 1.081 1843 1.311 1844 1.166 1845 1.445 1846 1.404 1847 1.307 1848 1.363 1849 1.179 1850 1.275 1851 1.08 1852 1.118 1853 1.106 1854 1.591 1855 1.416 1856 1.235 1857 0.943 1858 1.298 1859 1.284 1860 1.049 1861 1.455 1862 1.19 1863 1.026 1864 1.062 1865 0.883 1866 1.156 1867 1.032 1868 1.329 1869 0.993 1870 1.084 1871 1.074 1872 1.16 1873 1.344 1874 1.087 1875 1.162 1876 1.028 1877 0.96 1878 0.79 1879 0.816 1880 0.839 1881 0.727 1882 1.051 1883 1.108 1884 1.13 1885 1.161 1886 1.015 1887 1.054 1888 0.63 1889 0.805 1890 0.904 1891 0.741 1892 0.749 1893 0.815 1894 0.98 1895 1.104 1896 0.921 1897 0.993 1898 1.238 1899 1.012 1900 1.048 1901 1.179 1902 1.206 1903 0.882 1904 0.802 1905 1.023 1906 1.111 1907 1.012 1908 1.069 1909 0.977 1910 1.134 1911 1.085 1912 1.143 1913 1.356 1914 1.556 1915 1.9 1916 1.706 1917 1.195 1918 1.213 1919 1.24 1920 1.47 1921 1.395 1922 1.27 1923 1.436 1924 1.296 1925 1.414 1926 1.117 1927 0.917 1928 0.574 1929 0.593 1930 0.805 1931 0.653 1932 0.658 1933 0.724 1934 0.76 1935 0.667 1936 0.683 1937 0.947 1938 0.77 1939 0.672 1940 0.616 1941 1.195 1942 0.868 1943 0.859 1944 0.859 1945 0.9 1946 0.744 1947 1.027 1948 0.89 1949 0.986 1950 0.822 1951 0.775 1952 0.833 1953 1.101 1954 1.19 1955 0.864 1956 0.59 1957 0.793 1958 0.81 1959 0.869 1960 0.797 1961 0.586 1962 0.793 1963 0.63 1964 0.829 1965 0.686 1966 0.758 1967 0.957 1968 0.903 1969 0.91 1970 0.8 1971 0.93 1972 0.914 1973 1.243 1974 0.94 1975 0.941 1976 1.101 1977 0.785 1978 0.814 1979 1.027 1980 0.919 1981 0.771 1982 0.854 1983 0.855