# asia_russ174w - White River, P.Tung. - 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/4734 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_russ174w - White River, P.Tung. - 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: White River, P.Tung. # Location: # Country: Russia # Northernmost_Latitude: 61.85 # Southernmost_Latitude: 61.85 # Easternmost_Longitude: 93.4 # Westernmost_Longitude: 93.4 # Elevation: 120 m #-------------------- # Data_Collection # Collection_Name: asia_russ174wB # Earliest_Year: 1793 # Most_Recent_Year: 1994 # 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":"4.85394069435","T2":"17.0381058735","M1":"0.0222495047384","M2":"0.499239786413"}} #-------------------- # Species # Species_Name: Siberian spruce # Species_Code: PCOB #-------------------- # 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 1793 0.754 1794 0.869 1795 0.75 1796 0.696 1797 0.448 1798 0.438 1799 0.664 1800 0.567 1801 0.515 1802 0.597 1803 0.71 1804 0.614 1805 0.67 1806 0.887 1807 0.843 1808 0.868 1809 0.823 1810 0.884 1811 1.254 1812 0.582 1813 0.82 1814 0.815 1815 0.656 1816 0.641 1817 0.62 1818 0.697 1819 0.777 1820 0.631 1821 0.698 1822 0.564 1823 0.138 1824 0.285 1825 0.357 1826 0.366 1827 0.445 1828 0.536 1829 0.646 1830 0.693 1831 0.804 1832 0.824 1833 1.106 1834 1.186 1835 1.315 1836 1.244 1837 1.344 1838 1.643 1839 1.41 1840 1.441 1841 1.323 1842 1.539 1843 1.215 1844 1.364 1845 1.335 1846 1.313 1847 1.359 1848 1.462 1849 1.372 1850 1.404 1851 1.112 1852 1.207 1853 1.37 1854 0.772 1855 1.476 1856 1.637 1857 1.385 1858 1.236 1859 1.219 1860 1.465 1861 1.568 1862 1.296 1863 1.481 1864 1.322 1865 1.518 1866 1.491 1867 1.042 1868 1.279 1869 1.007 1870 1.093 1871 0.996 1872 1.199 1873 1.114 1874 1.106 1875 1.143 1876 1.256 1877 1.212 1878 1.645 1879 1.161 1880 1.172 1881 0.75 1882 1.104 1883 0.791 1884 0.94 1885 0.888 1886 0.86 1887 0.816 1888 0.711 1889 0.571 1890 0.608 1891 0.858 1892 0.895 1893 1.07 1894 0.98 1895 0.714 1896 0.845 1897 0.732 1898 0.861 1899 0.725 1900 0.998 1901 0.673 1902 0.696 1903 0.957 1904 0.963 1905 0.905 1906 1.146 1907 0.675 1908 1.201 1909 0.467 1910 0.947 1911 0.791 1912 1.045 1913 0.899 1914 0.908 1915 0.76 1916 0.859 1917 0.692 1918 0.941 1919 0.544 1920 1.12 1921 0.676 1922 0.72 1923 0.725 1924 0.587 1925 0.729 1926 0.763 1927 1.032 1928 1.127 1929 0.674 1930 1.01 1931 0.953 1932 0.814 1933 0.759 1934 0.787 1935 0.848 1936 0.887 1937 0.801 1938 0.903 1939 0.994 1940 1.044 1941 0.945 1942 1.125 1943 1.007 1944 1.031 1945 1.044 1946 1.255 1947 1.209 1948 1.33 1949 0.95 1950 1.215 1951 0.913 1952 1.095 1953 1.126 1954 1.126 1955 0.918 1956 0.959 1957 1.023 1958 0.914 1959 0.892 1960 0.824 1961 0.735 1962 1.08 1963 0.805 1964 0.996 1965 0.883 1966 0.88 1967 0.924 1968 1.025 1969 0.968 1970 0.714 1971 0.952 1972 1.013 1973 0.923 1974 0.898 1975 1.039 1976 1.113 1977 1.16 1978 1.032 1979 1.293 1980 0.978 1981 1.037 1982 0.986 1983 1.094 1984 1.026 1985 1.196 1986 1.057 1987 0.775 1988 0.996 1989 1.034 1990 1.201 1991 1.242 1992 1.134 1993 1.343 1994 1.216