# asia_russ120w - Molebny Kamen Ridge - 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/4533 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_russ120w - Molebny Kamen Ridge - 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: Molebny Kamen Ridge # Location: # Country: Russia # Northernmost_Latitude: 61.27 # Southernmost_Latitude: 61.27 # Easternmost_Longitude: 59.33 # Westernmost_Longitude: 59.33 # Elevation: 670 m #-------------------- # Data_Collection # Collection_Name: asia_russ120wB # Earliest_Year: 1762 # Most_Recent_Year: 1993 # 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":"6.82668522504","T2":"15.7023530692","M1":"0.0224830857022","M2":"0.50575284056"}} #-------------------- # 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 1762 1.057 1763 0.876 1764 0.992 1765 0.973 1766 0.754 1767 0.975 1768 1.147 1769 1.366 1770 1.259 1771 1.397 1772 1.067 1773 0.659 1774 1.178 1775 0.933 1776 0.903 1777 1.008 1778 0.863 1779 0.896 1780 0.948 1781 1.132 1782 1.019 1783 0.915 1784 0.984 1785 1.113 1786 1.185 1787 1.32 1788 1.305 1789 0.882 1790 1.126 1791 1.04 1792 0.967 1793 0.983 1794 1.136 1795 1.189 1796 1.201 1797 1.123 1798 1.32 1799 1.015 1800 1.063 1801 1.237 1802 0.934 1803 0.791 1804 0.829 1805 1.005 1806 0.906 1807 1.101 1808 1.153 1809 1.259 1810 0.874 1811 0.94 1812 1.053 1813 1.069 1814 1.14 1815 0.92 1816 0.964 1817 0.887 1818 0.828 1819 0.74 1820 0.898 1821 1.03 1822 0.989 1823 1.058 1824 1.147 1825 1.083 1826 0.799 1827 1.0 1828 0.834 1829 1.089 1830 0.993 1831 0.848 1832 1.082 1833 0.91 1834 0.876 1835 0.937 1836 0.874 1837 1.031 1838 0.939 1839 1.36 1840 1.242 1841 1.092 1842 0.88 1843 0.997 1844 0.74 1845 0.669 1846 0.693 1847 0.785 1848 0.486 1849 0.692 1850 0.689 1851 0.581 1852 0.664 1853 0.716 1854 0.613 1855 0.53 1856 0.74 1857 0.769 1858 0.467 1859 0.75 1860 0.727 1861 0.884 1862 0.806 1863 0.863 1864 0.99 1865 0.948 1866 1.17 1867 1.028 1868 1.3 1869 1.239 1870 1.16 1871 1.174 1872 0.869 1873 0.872 1874 0.706 1875 0.978 1876 1.042 1877 0.962 1878 1.249 1879 0.949 1880 1.035 1881 0.715 1882 0.789 1883 0.932 1884 0.999 1885 1.075 1886 0.971 1887 0.882 1888 1.175 1889 1.452 1890 1.208 1891 1.522 1892 1.695 1893 1.244 1894 1.233 1895 1.441 1896 1.102 1897 1.316 1898 1.33 1899 1.018 1900 1.327 1901 1.225 1902 1.07 1903 0.919 1904 0.588 1905 0.944 1906 1.255 1907 1.327 1908 1.237 1909 1.572 1910 1.089 1911 1.122 1912 1.045 1913 1.026 1914 0.837 1915 1.267 1916 0.727 1917 1.244 1918 1.285 1919 1.004 1920 0.971 1921 0.813 1922 0.853 1923 0.835 1924 0.854 1925 1.055 1926 0.973 1927 1.563 1928 1.431 1929 1.674 1930 1.714 1931 1.652 1932 1.492 1933 1.283 1934 1.116 1935 0.964 1936 0.817 1937 0.576 1938 0.692 1939 0.703 1940 0.831 1941 0.511 1942 0.749 1943 0.6 1944 0.601 1945 0.647 1946 0.571 1947 0.464 1948 0.764 1949 0.704 1950 0.752 1951 0.584 1952 0.667 1953 0.713 1954 0.839 1955 0.758 1956 1.036 1957 0.854 1958 0.78 1959 1.046 1960 0.948 1961 1.018 1962 0.46 1963 0.782 1964 0.766 1965 0.927 1966 0.597 1967 0.443 1968 0.86 1969 0.782 1970 0.739 1971 0.738 1972 0.986 1973 1.09 1974 1.264 1975 0.919 1976 1.066 1977 0.855 1978 0.873 1979 0.934 1980 0.991 1981 1.234 1982 0.939 1983 1.141 1984 1.189 1985 1.019 1986 0.8 1987 1.046 1988 0.862 1989 1.154 1990 0.984 1991 1.135 1992 0.712 1993 1.156