# europe_pola014 - Torun - 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/5222 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_pola014 - Torun - 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: Torun # Location: # Country: Poland # Northernmost_Latitude: 53.08 # Southernmost_Latitude: 53.08 # Easternmost_Longitude: 18.55 # Westernmost_Longitude: 18.55 # Elevation: 70 m #-------------------- # Data_Collection # Collection_Name: europe_pola014B # Earliest_Year: 1766 # Most_Recent_Year: 1986 # 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":"5.11122945883","T2":"16.8663192682","M1":"0.0223078714056","M2":"0.456620093398"}} #-------------------- # Species # Species_Name: English oak # Species_Code: QURO #-------------------- # 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 1766 1.378 1767 1.314 1768 1.092 1769 1.284 1770 1.536 1771 1.539 1772 1.61 1773 1.544 1774 1.326 1775 1.516 1776 1.312 1777 1.403 1778 1.475 1779 1.082 1780 0.862 1781 0.842 1782 0.8 1783 0.961 1784 0.886 1785 0.978 1786 0.913 1787 0.78 1788 0.708 1789 0.76 1790 0.808 1791 1.08 1792 0.952 1793 0.835 1794 0.889 1795 0.699 1796 1.053 1797 0.895 1798 1.189 1799 1.314 1800 1.092 1801 1.693 1802 1.232 1803 0.956 1804 0.732 1805 0.761 1806 0.617 1807 0.807 1808 0.708 1809 0.779 1810 0.766 1811 0.724 1812 0.878 1813 0.894 1814 0.957 1815 0.815 1816 1.006 1817 0.954 1818 0.707 1819 0.709 1820 0.798 1821 0.972 1822 1.123 1823 1.197 1824 1.082 1825 0.961 1826 0.965 1827 0.885 1828 1.132 1829 1.112 1830 1.106 1831 1.133 1832 0.897 1833 0.877 1834 1.159 1835 0.801 1836 0.884 1837 0.963 1838 0.783 1839 1.026 1840 0.754 1841 0.758 1842 0.962 1843 0.725 1844 0.873 1845 0.952 1846 1.2 1847 0.92 1848 0.864 1849 0.937 1850 1.11 1851 0.893 1852 0.94 1853 1.015 1854 0.673 1855 0.602 1856 0.6 1857 0.88 1858 0.714 1859 0.829 1860 0.82 1861 1.008 1862 0.913 1863 0.792 1864 0.803 1865 0.871 1866 0.78 1867 0.91 1868 0.995 1869 1.177 1870 1.143 1871 1.132 1872 1.15 1873 1.111 1874 1.037 1875 1.138 1876 1.004 1877 1.22 1878 1.088 1879 1.176 1880 1.217 1881 1.074 1882 1.033 1883 1.071 1884 1.137 1885 0.936 1886 1.214 1887 0.929 1888 0.926 1889 1.193 1890 1.271 1891 1.097 1892 1.013 1893 0.895 1894 0.98 1895 0.957 1896 1.079 1897 1.129 1898 1.001 1899 0.905 1900 0.825 1901 0.785 1902 0.927 1903 1.083 1904 1.167 1905 1.128 1906 1.209 1907 1.11 1908 1.141 1909 0.966 1910 1.25 1911 1.134 1912 0.973 1913 1.187 1914 0.827 1915 0.906 1916 1.194 1917 1.026 1918 1.085 1919 0.963 1920 1.023 1921 0.827 1922 1.115 1923 0.904 1924 1.168 1925 1.103 1926 0.989 1927 1.116 1928 1.061 1929 1.125 1930 0.747 1931 1.213 1932 1.152 1933 0.911 1934 1.017 1935 1.179 1936 1.057 1937 1.003 1938 1.044 1939 1.043 1940 0.912 1941 0.979 1942 0.681 1943 0.757 1944 0.831 1945 1.157 1946 1.111 1947 1.002 1948 1.028 1949 1.101 1950 0.951 1951 1.027 1952 0.856 1953 0.991 1954 0.919 1955 0.942 1956 0.82 1957 1.034 1958 1.059 1959 0.792 1960 0.774 1961 0.764 1962 1.001 1963 0.87 1964 1.029 1965 0.947 1966 0.972 1967 1.149 1968 0.982 1969 0.977 1970 0.959 1971 1.133 1972 1.107 1973 0.896 1974 0.94 1975 1.066 1976 0.914 1977 0.891 1978 0.871 1979 1.027 1980 0.756 1981 0.646 1982 0.849 1983 0.685 1984 1.13 1985 1.256 1986 1.258