# europe_finl047 - Kessi Inari - 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/3994 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_finl047 - Kessi Inari - 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: Kessi Inari # Location: # Country: Finland # Northernmost_Latitude: 68.92 # Southernmost_Latitude: 68.92 # Easternmost_Longitude: 28.48 # Westernmost_Longitude: 28.48 # Elevation: nan m #-------------------- # Data_Collection # Collection_Name: europe_finl047B # Earliest_Year: 1754 # 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":"6.45585676164","T2":"20.0734307415","M1":"0.021904173936","M2":"0.201335143837"}} #-------------------- # 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 1754 1.381 1755 1.641 1756 1.697 1757 1.528 1758 1.37 1759 1.222 1760 1.362 1761 1.442 1762 1.196 1763 1.214 1764 1.212 1765 1.258 1766 1.341 1767 1.036 1768 1.091 1769 0.839 1770 0.817 1771 0.766 1772 0.694 1773 0.718 1774 0.878 1775 0.948 1776 0.967 1777 1.021 1778 0.897 1779 0.933 1780 1.067 1781 0.966 1782 0.937 1783 0.838 1784 0.907 1785 1.08 1786 0.878 1787 0.9 1788 1.116 1789 0.982 1790 0.641 1791 0.607 1792 0.7 1793 0.648 1794 0.54 1795 0.423 1796 0.52 1797 0.746 1798 0.836 1799 1.016 1800 0.787 1801 0.686 1802 0.833 1803 0.867 1804 0.97 1805 1.033 1806 0.323 1807 0.837 1808 0.954 1809 1.095 1810 0.981 1811 0.785 1812 0.615 1813 0.398 1814 0.411 1815 0.427 1816 0.361 1817 0.476 1818 0.58 1819 0.547 1820 0.541 1821 0.59 1822 0.774 1823 1.039 1824 1.122 1825 1.064 1826 1.915 1827 1.354 1828 1.114 1829 1.577 1830 1.297 1831 1.259 1832 1.111 1833 0.92 1834 0.887 1835 0.695 1836 0.714 1837 0.331 1838 0.665 1839 0.455 1840 0.794 1841 0.631 1842 0.631 1843 0.685 1844 0.963 1845 0.902 1846 0.855 1847 0.783 1848 0.932 1849 1.037 1850 0.994 1851 1.153 1852 1.21 1853 1.175 1854 1.512 1855 1.348 1856 1.286 1857 1.235 1858 1.295 1859 1.08 1860 1.187 1861 1.101 1862 0.955 1863 1.086 1864 1.33 1865 1.142 1866 0.836 1867 0.834 1868 0.929 1869 1.147 1870 1.232 1871 1.007 1872 1.089 1873 1.332 1874 0.937 1875 1.001 1876 1.285 1877 1.212 1878 0.946 1879 0.855 1880 0.717 1881 0.749 1882 1.011 1883 1.078 1884 0.85 1885 1.038 1886 1.215 1887 1.108 1888 0.86 1889 1.207 1890 1.438 1891 1.116 1892 0.728 1893 0.746 1894 0.939 1895 0.86 1896 0.927 1897 0.943 1898 1.456 1899 1.026 1900 0.653 1901 0.954 1902 0.667 1903 0.396 1904 0.654 1905 0.623 1906 0.714 1907 0.654 1908 0.897 1909 0.765 1910 0.518 1911 0.709 1912 0.987 1913 0.952 1914 1.19 1915 1.252 1916 1.172 1917 1.047 1918 1.065 1919 1.046 1920 1.195 1921 1.503 1922 1.722 1923 1.782 1924 1.738 1925 1.805 1926 1.144 1927 1.568 1928 0.959 1929 0.786 1930 1.674 1931 1.541 1932 1.526 1933 1.555 1934 1.879 1935 1.462 1936 1.165 1937 1.731 1938 1.215 1939 1.259 1940 0.955 1941 1.354 1942 1.217 1943 0.982 1944 1.063 1945 1.04 1946 0.683 1947 0.765 1948 0.944 1949 0.973 1950 1.07 1951 0.813 1952 0.872 1953 1.147 1954 1.266 1955 1.091 1956 1.143 1957 1.405 1958 1.062 1959 1.129 1960 1.411 1961 0.856 1962 0.959 1963 0.736 1964 1.315 1965 0.79 1966 0.782 1967 0.884 1968 0.79 1969 0.641 1970 0.856 1971 0.698 1972 0.74 1973 0.914 1974 0.651 1975 0.729 1976 0.838 1977 0.724 1978 0.659 1979 0.83 1980 0.734 1981 0.592 1982 0.672 1983 0.772 1984 0.667 1985 0.807 1986 0.663 1987 0.59 1988 0.765 1989 0.784 1990 0.803 1991 0.832 1992 0.907 1993 1.016 1994 0.921 1995 0.809 1996 0.773 1997 0.91 1998 0.871 1999 0.824 2000 0.94 2001 0.943