# europe_swed323 - Norberg - 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/6137 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_swed323 - Norberg - 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: Norberg # Location: # Country: Sweden # Northernmost_Latitude: 60.13 # Southernmost_Latitude: 60.13 # Easternmost_Longitude: 16.08 # Westernmost_Longitude: 16.08 # Elevation: 150 m #-------------------- # Data_Collection # Collection_Name: europe_swed323B # Earliest_Year: 1755 # Most_Recent_Year: 1997 # 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":"2.45420465427","T2":"12.7079304761","M1":"0.0230020274713","M2":"0.594773751043"}} #-------------------- # 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 1755 1.173 1756 1.039 1757 0.657 1758 0.751 1759 1.132 1760 1.159 1761 1.199 1762 1.086 1763 0.911 1764 0.696 1765 0.664 1766 0.651 1767 0.715 1768 0.553 1769 0.594 1770 0.682 1771 0.579 1772 0.877 1773 0.702 1774 0.541 1775 0.958 1776 1.754 1777 1.327 1778 0.924 1779 1.316 1780 1.106 1781 0.939 1782 1.696 1783 1.499 1784 1.872 1785 1.51 1786 0.981 1787 1.021 1788 0.761 1789 0.725 1790 1.574 1791 1.775 1792 1.268 1793 1.13 1794 1.396 1795 0.939 1796 1.023 1797 1.179 1798 0.745 1799 0.804 1800 0.833 1801 0.682 1802 0.737 1803 0.752 1804 0.778 1805 1.101 1806 0.769 1807 0.675 1808 0.774 1809 1.076 1810 1.166 1811 0.851 1812 0.911 1813 1.323 1814 1.094 1815 1.199 1816 0.83 1817 1.347 1818 0.87 1819 0.846 1820 0.847 1821 1.009 1822 0.773 1823 0.827 1824 0.955 1825 0.764 1826 0.802 1827 0.953 1828 1.053 1829 0.596 1830 1.057 1831 1.008 1832 0.833 1833 0.828 1834 1.448 1835 0.939 1836 1.151 1837 1.13 1838 1.105 1839 1.156 1840 1.076 1841 0.834 1842 1.06 1843 0.679 1844 1.013 1845 0.612 1846 0.814 1847 0.542 1848 0.952 1849 0.745 1850 0.835 1851 0.85 1852 0.624 1853 0.419 1854 0.626 1855 0.887 1856 0.943 1857 1.012 1858 0.81 1859 0.786 1860 0.953 1861 0.748 1862 1.103 1863 1.059 1864 1.099 1865 1.143 1866 1.103 1867 0.974 1868 0.728 1869 1.135 1870 1.084 1871 0.97 1872 0.984 1873 0.952 1874 0.533 1875 0.883 1876 0.891 1877 0.992 1878 1.247 1879 0.899 1880 0.905 1881 0.662 1882 1.12 1883 0.813 1884 0.96 1885 0.898 1886 0.917 1887 0.742 1888 0.721 1889 0.645 1890 0.812 1891 0.533 1892 0.844 1893 0.789 1894 1.297 1895 0.652 1896 0.898 1897 0.81 1898 0.983 1899 0.937 1900 0.854 1901 0.636 1902 0.732 1903 0.993 1904 0.767 1905 0.714 1906 0.751 1907 0.936 1908 0.753 1909 0.746 1910 0.867 1911 0.489 1912 0.842 1913 0.699 1914 0.87 1915 0.916 1916 0.998 1917 0.591 1918 0.751 1919 0.821 1920 0.927 1921 1.005 1922 1.134 1923 1.239 1924 1.236 1925 0.912 1926 1.139 1927 1.282 1928 1.156 1929 1.288 1930 1.048 1931 0.812 1932 0.833 1933 0.744 1934 0.755 1935 0.736 1936 0.734 1937 0.689 1938 0.927 1939 0.877 1940 0.514 1941 0.845 1942 1.177 1943 1.123 1944 1.156 1945 1.442 1946 1.694 1947 1.492 1948 1.345 1949 1.189 1950 1.387 1951 1.408 1952 1.498 1953 1.833 1954 1.557 1955 1.253 1956 1.163 1957 1.588 1958 1.395 1959 1.0 1960 0.665 1961 0.897 1962 1.0 1963 1.175 1964 1.326 1965 1.266 1966 0.814 1967 1.209 1968 0.956 1969 0.765 1970 0.825 1971 0.836 1972 1.128 1973 1.278 1974 1.14 1975 1.087 1976 0.982 1977 1.172 1978 0.922 1979 1.103 1980 1.307 1981 1.316 1982 1.022 1983 1.305 1984 1.244 1985 0.919 1986 0.936 1987 0.996 1988 0.946 1989 0.968 1990 0.8 1991 1.116 1992 1.006 1993 1.083 1994 1.014 1995 1.114 1996 1.028 1997 0.292