# asia_russ181 - Venehjärvi - 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/4019 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_russ181 - Venehjärvi - 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: Venehjärvi # Location: # Country: Russia # Northernmost_Latitude: 64.95 # Southernmost_Latitude: 64.95 # Easternmost_Longitude: 30.2 # Westernmost_Longitude: 30.2 # Elevation: nan m #-------------------- # Data_Collection # Collection_Name: asia_russ181B # Earliest_Year: 1775 # Most_Recent_Year: 2001 # 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":"3.46047095728","T2":"14.0575475003","M1":"0.0230010415075","M2":"0.530875130572"}} #-------------------- # 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 1775 0.945 1776 0.634 1777 0.576 1778 0.952 1779 0.869 1780 0.776 1781 0.693 1782 0.743 1783 0.675 1784 0.793 1785 0.707 1786 0.646 1787 0.55 1788 0.561 1789 0.537 1790 0.493 1791 0.749 1792 0.879 1793 1.102 1794 0.966 1795 0.842 1796 0.783 1797 0.794 1798 0.833 1799 0.803 1800 0.75 1801 0.893 1802 0.928 1803 0.784 1804 0.894 1805 0.98 1806 0.684 1807 0.788 1808 0.818 1809 0.982 1810 0.821 1811 0.829 1812 0.92 1813 0.842 1814 0.639 1815 0.764 1816 0.78 1817 0.953 1818 1.009 1819 1.16 1820 0.634 1821 0.826 1822 1.088 1823 1.141 1824 1.157 1825 1.24 1826 1.49 1827 1.327 1828 1.062 1829 1.206 1830 1.107 1831 1.176 1832 0.962 1833 0.964 1834 1.052 1835 0.823 1836 0.839 1837 0.844 1838 0.785 1839 0.724 1840 1.07 1841 1.196 1842 1.332 1843 0.973 1844 0.902 1845 1.085 1846 1.202 1847 1.025 1848 1.16 1849 1.345 1850 1.266 1851 1.245 1852 1.094 1853 1.006 1854 1.125 1855 0.98 1856 0.899 1857 0.922 1858 0.933 1859 0.804 1860 0.876 1861 0.989 1862 0.639 1863 0.792 1864 0.905 1865 0.997 1866 0.836 1867 0.593 1868 0.863 1869 0.891 1870 1.132 1871 0.896 1872 0.973 1873 0.936 1874 1.141 1875 1.287 1876 1.093 1877 1.224 1878 1.012 1879 0.936 1880 0.874 1881 0.735 1882 1.208 1883 0.772 1884 0.864 1885 1.004 1886 0.957 1887 1.178 1888 1.132 1889 1.145 1890 1.453 1891 1.262 1892 1.172 1893 1.26 1894 1.075 1895 0.778 1896 0.912 1897 0.917 1898 1.096 1899 0.86 1900 1.01 1901 1.178 1902 0.828 1903 0.769 1904 1.024 1905 0.863 1906 1.04 1907 0.839 1908 0.932 1909 0.834 1910 0.912 1911 1.125 1912 1.136 1913 0.946 1914 0.914 1915 1.081 1916 0.98 1917 0.917 1918 0.878 1919 0.961 1920 1.107 1921 1.101 1922 1.309 1923 1.249 1924 1.358 1925 1.334 1926 0.932 1927 1.042 1928 0.931 1929 1.085 1930 1.216 1931 1.063 1932 1.032 1933 0.748 1934 1.179 1935 0.891 1936 1.081 1937 0.981 1938 0.677 1939 0.763 1940 0.77 1941 0.659 1942 0.562 1943 0.69 1944 0.67 1945 0.688 1946 0.645 1947 0.641 1948 0.755 1949 0.888 1950 1.171 1951 0.98 1952 0.824 1953 1.128 1954 1.398 1955 1.085 1956 0.861 1957 1.286 1958 1.005 1959 1.144 1960 0.902 1961 0.715 1962 0.777 1963 0.923 1964 1.255 1965 0.762 1966 0.722 1967 1.203 1968 0.969 1969 0.887 1970 0.801 1971 0.795 1972 0.889 1973 1.058 1974 0.923 1975 1.267 1976 1.336 1977 1.075 1978 1.127 1979 1.396 1980 1.018 1981 1.043 1982 0.965 1983 1.139 1984 1.235 1985 1.038 1986 1.067 1987 1.045 1988 1.189 1989 1.19 1990 1.155 1991 0.971 1992 0.898 1993 0.98 1994 0.79 1995 0.878 1996 0.894 1997 0.863 1998 0.796 1999 0.777 2000 1.024 2001 1.002