# asia_russ169w - Kodarpass (Baikal) - 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/4471 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_russ169w - Kodarpass (Baikal) - 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: Kodarpass (Baikal) # Location: # Country: Russia # Northernmost_Latitude: 56.5 # Southernmost_Latitude: 56.5 # Easternmost_Longitude: 117.25 # Westernmost_Longitude: 117.25 # Elevation: 1000 m #-------------------- # Data_Collection # Collection_Name: asia_russ169wB # Earliest_Year: 1725 # Most_Recent_Year: 1996 # 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":"4.99177141597","T2":"16.0767537101","M1":"0.0227142700263","M2":"0.416411040358"}} #-------------------- # 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 1725 1.192 1726 1.014 1727 1.075 1728 1.17 1729 1.045 1730 0.911 1731 0.762 1732 0.815 1733 0.788 1734 0.842 1735 0.762 1736 0.933 1737 0.956 1738 1.008 1739 1.122 1740 0.914 1741 0.964 1742 1.067 1743 0.851 1744 0.879 1745 0.914 1746 0.64 1747 0.96 1748 0.577 1749 0.69 1750 0.635 1751 0.794 1752 0.998 1753 1.02 1754 0.66 1755 0.868 1756 0.933 1757 1.06 1758 1.114 1759 1.074 1760 1.203 1761 1.555 1762 1.645 1763 1.676 1764 1.814 1765 1.626 1766 1.252 1767 1.272 1768 1.221 1769 1.041 1770 0.917 1771 1.011 1772 0.901 1773 0.867 1774 0.726 1775 0.679 1776 0.887 1777 0.734 1778 0.776 1779 1.018 1780 1.069 1781 1.086 1782 1.006 1783 1.014 1784 0.862 1785 0.751 1786 1.051 1787 0.733 1788 0.849 1789 0.863 1790 0.833 1791 0.97 1792 0.959 1793 0.99 1794 0.794 1795 0.888 1796 0.741 1797 0.855 1798 0.696 1799 0.969 1800 0.703 1801 0.787 1802 1.062 1803 1.073 1804 1.033 1805 1.128 1806 1.264 1807 1.11 1808 1.299 1809 1.196 1810 1.12 1811 0.883 1812 0.719 1813 0.767 1814 0.602 1815 0.677 1816 0.873 1817 0.714 1818 0.95 1819 0.765 1820 0.832 1821 0.755 1822 0.698 1823 0.938 1824 0.933 1825 1.205 1826 0.965 1827 1.372 1828 1.42 1829 1.267 1830 1.399 1831 1.32 1832 1.032 1833 1.542 1834 0.8 1835 0.907 1836 0.9 1837 0.877 1838 0.769 1839 0.784 1840 1.031 1841 1.199 1842 0.98 1843 1.263 1844 1.054 1845 1.211 1846 1.349 1847 1.074 1848 1.382 1849 1.097 1850 1.097 1851 0.794 1852 0.576 1853 0.768 1854 0.698 1855 1.084 1856 0.934 1857 0.935 1858 1.295 1859 1.135 1860 0.653 1861 1.025 1862 1.055 1863 1.055 1864 0.929 1865 1.26 1866 1.026 1867 1.129 1868 1.264 1869 1.156 1870 1.396 1871 1.212 1872 1.349 1873 1.323 1874 1.44 1875 1.292 1876 1.193 1877 1.205 1878 1.071 1879 1.056 1880 1.062 1881 1.126 1882 1.185 1883 1.113 1884 1.107 1885 1.186 1886 1.039 1887 0.982 1888 0.851 1889 1.072 1890 0.717 1891 1.061 1892 0.718 1893 0.896 1894 0.835 1895 0.904 1896 0.901 1897 0.769 1898 0.756 1899 1.096 1900 1.048 1901 0.806 1902 0.636 1903 1.067 1904 0.784 1905 1.118 1906 0.923 1907 0.675 1908 0.999 1909 1.039 1910 0.749 1911 0.493 1912 0.93 1913 0.862 1914 1.012 1915 0.552 1916 0.949 1917 0.841 1918 0.952 1919 0.768 1920 0.704 1921 0.862 1922 0.69 1923 0.647 1924 0.555 1925 0.827 1926 0.797 1927 0.769 1928 1.015 1929 0.773 1930 0.818 1931 0.891 1932 0.672 1933 0.801 1934 0.791 1935 1.067 1936 0.761 1937 1.016 1938 0.929 1939 1.014 1940 0.955 1941 0.941 1942 0.847 1943 0.75 1944 0.868 1945 0.708 1946 0.881 1947 0.628 1948 0.852 1949 0.698 1950 1.094 1951 0.638 1952 1.119 1953 1.034 1954 1.112 1955 1.007 1956 0.952 1957 0.833 1958 0.976 1959 1.358 1960 1.235 1961 1.032 1962 1.288 1963 1.168 1964 1.114 1965 1.103 1966 1.53 1967 1.628 1968 1.599 1969 1.007 1970 1.301 1971 1.339 1972 1.224 1973 1.249 1974 1.273 1975 1.071 1976 1.356 1977 1.375 1978 1.134 1979 1.172 1980 1.141 1981 0.49 1982 1.163 1983 0.856 1984 0.952 1985 0.748 1986 0.729 1987 0.505 1988 0.806 1989 0.555 1990 0.83 1991 0.843 1992 0.788 1993 0.986 1994 0.956 1995 1.003 1996 0.721