# europe_finl045 - Vuotso GSF - 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/4021 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_finl045 - Vuotso GSF - 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: Vuotso GSF # Location: # Country: Finland # Northernmost_Latitude: 68.07 # Southernmost_Latitude: 68.07 # Easternmost_Longitude: 27.2 # Westernmost_Longitude: 27.2 # Elevation: nan m #-------------------- # Data_Collection # Collection_Name: europe_finl045B # Earliest_Year: 1777 # Most_Recent_Year: 2001 # 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":"3.97077231456","T2":"19.5872578996","M1":"0.0221869205047","M2":"0.252225765228"}} #-------------------- # 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 1777 1.067 1778 0.905 1779 1.044 1780 1.337 1781 1.181 1782 1.08 1783 0.984 1784 0.862 1785 1.143 1786 0.932 1787 1.206 1788 1.254 1789 1.218 1790 0.541 1791 0.59 1792 0.609 1793 0.679 1794 0.837 1795 0.738 1796 0.756 1797 0.788 1798 0.929 1799 1.142 1800 0.907 1801 0.95 1802 0.981 1803 0.999 1804 1.348 1805 1.357 1806 0.793 1807 1.449 1808 1.344 1809 1.436 1810 1.211 1811 1.102 1812 0.913 1813 0.622 1814 1.09 1815 1.001 1816 1.116 1817 1.342 1818 1.577 1819 1.294 1820 1.339 1821 1.241 1822 1.295 1823 1.59 1824 1.391 1825 1.204 1826 1.601 1827 1.386 1828 1.306 1829 1.642 1830 1.291 1831 1.318 1832 0.945 1833 0.863 1834 0.782 1835 0.683 1836 0.728 1837 0.263 1838 0.541 1839 0.545 1840 0.74 1841 0.601 1842 0.569 1843 0.648 1844 0.763 1845 0.921 1846 0.815 1847 0.853 1848 0.746 1849 0.96 1850 0.971 1851 1.173 1852 1.236 1853 1.005 1854 1.316 1855 1.254 1856 1.1 1857 1.023 1858 1.191 1859 1.005 1860 0.982 1861 0.938 1862 0.774 1863 0.754 1864 0.798 1865 0.847 1866 0.671 1867 0.683 1868 0.686 1869 0.643 1870 0.607 1871 0.528 1872 0.53 1873 0.617 1874 0.47 1875 0.456 1876 0.776 1877 0.562 1878 0.475 1879 0.399 1880 0.342 1881 0.48 1882 0.486 1883 0.59 1884 0.614 1885 0.732 1886 0.867 1887 0.728 1888 0.557 1889 0.861 1890 0.877 1891 0.851 1892 0.687 1893 0.639 1894 0.635 1895 0.846 1896 0.858 1897 0.913 1898 1.159 1899 0.92 1900 0.754 1901 1.045 1902 0.716 1903 0.409 1904 0.517 1905 0.613 1906 0.537 1907 0.455 1908 0.709 1909 0.773 1910 0.651 1911 0.672 1912 0.767 1913 0.867 1914 1.027 1915 0.854 1916 0.964 1917 0.801 1918 0.914 1919 1.048 1920 1.182 1921 1.467 1922 1.65 1923 1.529 1924 1.296 1925 1.422 1926 1.069 1927 1.153 1928 1.084 1929 0.937 1930 1.506 1931 1.146 1932 0.976 1933 0.975 1934 1.436 1935 1.436 1936 1.14 1937 1.626 1938 1.186 1939 1.255 1940 1.075 1941 1.463 1942 1.273 1943 1.016 1944 0.96 1945 0.833 1946 0.783 1947 1.07 1948 1.133 1949 1.093 1950 1.157 1951 0.965 1952 1.187 1953 1.602 1954 1.471 1955 1.231 1956 1.392 1957 1.656 1958 1.275 1959 1.394 1960 1.661 1961 1.032 1962 1.137 1963 0.796 1964 1.032 1965 0.631 1966 0.831 1967 0.89 1968 0.989 1969 0.769 1970 0.96 1971 0.907 1972 0.982 1973 1.259 1974 0.833 1975 0.993 1976 1.251 1977 1.171 1978 1.099 1979 1.355 1980 1.001 1981 0.882 1982 1.147 1983 1.209 1984 1.154 1985 1.286 1986 1.179 1987 0.959 1988 1.104 1989 1.234 1990 1.245 1991 1.27 1992 1.052 1993 1.12 1994 1.143 1995 1.068 1996 1.102 1997 1.093 1998 1.127 1999 1.107 2000 1.27 2001 1.135