# europe_swed328 - Tyresta - 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/6142 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_swed328 - Tyresta - 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: Tyresta # Location: # Country: Sweden # Northernmost_Latitude: 59.18 # Southernmost_Latitude: 59.18 # Easternmost_Longitude: 18.27 # Westernmost_Longitude: 18.27 # Elevation: 60 m #-------------------- # Data_Collection # Collection_Name: europe_swed328B # Earliest_Year: 1765 # Most_Recent_Year: 2000 # 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":"3.9931200422","T2":"14.9609992853","M1":"0.0228652571955","M2":"0.524732373725"}} #-------------------- # 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 1765 0.933 1766 1.228 1767 1.342 1768 1.024 1769 1.445 1770 0.973 1771 0.733 1772 1.238 1773 1.172 1774 1.006 1775 0.864 1776 1.108 1777 1.118 1778 1.346 1779 1.792 1780 1.286 1781 0.674 1782 1.161 1783 0.774 1784 1.007 1785 0.798 1786 0.808 1787 1.155 1788 0.736 1789 0.864 1790 1.145 1791 1.378 1792 1.082 1793 1.233 1794 1.499 1795 1.015 1796 1.275 1797 1.46 1798 0.762 1799 1.116 1800 1.081 1801 0.618 1802 0.934 1803 0.737 1804 0.7 1805 1.088 1806 1.111 1807 0.927 1808 0.771 1809 0.935 1810 0.795 1811 0.761 1812 0.61 1813 0.594 1814 0.589 1815 0.749 1816 0.555 1817 0.814 1818 0.422 1819 0.606 1820 0.618 1821 0.608 1822 0.315 1823 0.469 1824 0.62 1825 0.695 1826 0.478 1827 0.552 1828 0.517 1829 0.366 1830 0.6 1831 0.67 1832 0.995 1833 0.773 1834 1.51 1835 1.114 1836 0.941 1837 1.061 1838 0.823 1839 1.081 1840 1.538 1841 1.411 1842 1.492 1843 1.387 1844 1.856 1845 1.085 1846 0.983 1847 0.999 1848 1.207 1849 1.319 1850 0.958 1851 1.049 1852 0.78 1853 0.445 1854 0.655 1855 0.699 1856 1.289 1857 0.975 1858 0.935 1859 0.806 1860 1.078 1861 0.657 1862 1.166 1863 1.127 1864 1.224 1865 1.216 1866 1.221 1867 1.118 1868 1.01 1869 0.973 1870 0.993 1871 1.142 1872 1.296 1873 1.169 1874 1.157 1875 1.248 1876 0.91 1877 1.15 1878 1.15 1879 0.978 1880 1.345 1881 1.064 1882 1.553 1883 0.786 1884 1.194 1885 0.956 1886 1.216 1887 0.984 1888 0.888 1889 0.792 1890 1.084 1891 0.835 1892 1.231 1893 0.96 1894 1.636 1895 0.736 1896 0.816 1897 1.116 1898 1.232 1899 0.929 1900 0.945 1901 0.528 1902 0.46 1903 0.645 1904 0.543 1905 0.425 1906 0.575 1907 0.764 1908 0.842 1909 1.026 1910 1.249 1911 1.011 1912 1.08 1913 0.815 1914 0.701 1915 0.856 1916 0.726 1917 0.413 1918 0.586 1919 0.648 1920 0.761 1921 0.798 1922 1.113 1923 1.328 1924 1.351 1925 1.072 1926 0.966 1927 1.318 1928 1.034 1929 1.15 1930 1.029 1931 1.085 1932 1.173 1933 0.982 1934 1.087 1935 0.978 1936 1.155 1937 1.057 1938 1.148 1939 0.87 1940 0.443 1941 0.823 1942 0.875 1943 0.696 1944 0.686 1945 1.158 1946 1.281 1947 0.925 1948 1.193 1949 1.09 1950 0.784 1951 0.875 1952 1.24 1953 1.314 1954 1.296 1955 1.105 1956 1.107 1957 1.35 1958 1.252 1959 0.512 1960 0.786 1961 0.888 1962 1.001 1963 0.956 1964 1.079 1965 1.015 1966 0.649 1967 0.912 1968 0.796 1969 0.396 1970 0.617 1971 0.565 1972 1.001 1973 1.063 1974 0.956 1975 0.905 1976 1.049 1977 1.182 1978 0.857 1979 1.374 1980 1.373 1981 1.288 1982 0.842 1983 1.161 1984 1.274 1985 0.8 1986 1.088 1987 1.204 1988 1.266 1989 1.042 1990 1.19 1991 1.29 1992 0.738 1993 0.856 1994 0.806 1995 1.089 1996 0.96 1997 1.104 1998 1.027 1999 0.769 2000 1.06