# asia_russ092w - Khadutte River - 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/4461 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_russ092w - Khadutte River - 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: Khadutte River # Location: # Country: Russia # Northernmost_Latitude: 67.47 # Southernmost_Latitude: 67.47 # Easternmost_Longitude: 76.77 # Westernmost_Longitude: 76.77 # Elevation: 20 m #-------------------- # Data_Collection # Collection_Name: asia_russ092wB # Earliest_Year: 1685 # Most_Recent_Year: 1990 # 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":"7.9986065323","T2":"20.2378248125","M1":"0.0220711873651","M2":"0.258856485436"}} #-------------------- # Species # Species_Name: Siberian larch # Species_Code: LASI #-------------------- # 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 1685 0.881 1686 0.976 1687 0.722 1688 0.396 1689 0.565 1690 1.099 1691 0.882 1692 0.781 1693 0.926 1694 0.555 1695 1.488 1696 1.012 1697 0.927 1698 0.762 1699 0.284 1700 0.709 1701 0.618 1702 0.604 1703 0.809 1704 0.914 1705 1.015 1706 0.929 1707 1.44 1708 1.514 1709 1.241 1710 1.008 1711 1.09 1712 1.109 1713 1.183 1714 0.566 1715 1.051 1716 1.054 1717 0.571 1718 0.695 1719 1.402 1720 1.258 1721 1.356 1722 0.898 1723 0.584 1724 0.948 1725 0.52 1726 0.967 1727 1.166 1728 0.878 1729 1.45 1730 0.825 1731 1.301 1732 0.406 1733 1.588 1734 1.14 1735 1.628 1736 0.953 1737 1.081 1738 0.739 1739 0.975 1740 1.308 1741 1.145 1742 0.173 1743 1.067 1744 1.054 1745 0.941 1746 0.723 1747 0.764 1748 0.71 1749 0.761 1750 0.969 1751 1.375 1752 0.99 1753 1.322 1754 1.624 1755 1.161 1756 1.901 1757 1.899 1758 1.132 1759 0.8 1760 1.277 1761 1.391 1762 1.347 1763 1.185 1764 1.253 1765 1.219 1766 1.447 1767 1.782 1768 1.092 1769 1.493 1770 0.854 1771 1.337 1772 0.368 1773 0.764 1774 0.814 1775 1.454 1776 0.814 1777 1.304 1778 1.517 1779 1.474 1780 1.416 1781 1.293 1782 1.493 1783 0.206 1784 1.714 1785 1.646 1786 1.291 1787 1.192 1788 0.685 1789 1.087 1790 1.617 1791 1.251 1792 1.134 1793 2.044 1794 1.297 1795 1.47 1796 1.534 1797 1.076 1798 1.517 1799 1.121 1800 0.731 1801 1.143 1802 0.769 1803 0.776 1804 0.536 1805 1.148 1806 0.806 1807 0.87 1808 1.158 1809 1.078 1810 0.894 1811 0.851 1812 0.402 1813 0.776 1814 1.138 1815 0.566 1816 0.346 1817 0.841 1818 0.71 1819 0.165 1820 0.557 1821 0.712 1822 1.059 1823 1.263 1824 0.802 1825 0.285 1826 0.873 1827 1.042 1828 0.33 1829 0.998 1830 0.498 1831 0.371 1832 0.64 1833 0.083 1834 0.335 1835 0.577 1836 0.276 1837 0.36 1838 0.543 1839 0.697 1840 0.75 1841 0.44 1842 0.886 1843 0.563 1844 1.19 1845 1.232 1846 1.101 1847 1.086 1848 0.662 1849 0.696 1850 0.831 1851 0.948 1852 0.842 1853 0.991 1854 0.768 1855 0.416 1856 1.252 1857 0.978 1858 0.973 1859 0.926 1860 0.592 1861 1.268 1862 0.657 1863 0.772 1864 0.469 1865 0.673 1866 0.728 1867 0.076 1868 0.983 1869 0.522 1870 1.308 1871 0.999 1872 1.072 1873 0.588 1874 0.697 1875 0.951 1876 1.12 1877 1.397 1878 1.627 1879 1.773 1880 1.008 1881 0.762 1882 0.191 1883 0.999 1884 0.265 1885 0.346 1886 0.851 1887 0.874 1888 0.547 1889 0.243 1890 0.883 1891 0.341 1892 1.126 1893 0.768 1894 0.947 1895 1.036 1896 0.437 1897 1.072 1898 1.202 1899 0.343 1900 1.112 1901 0.723 1902 1.354 1903 0.913 1904 1.219 1905 1.047 1906 1.133 1907 0.545 1908 0.857 1909 1.19 1910 1.113 1911 0.941 1912 0.494 1913 0.531 1914 0.335 1915 1.052 1916 0.294 1917 0.98 1918 1.279 1919 1.033 1920 1.277 1921 1.692 1922 1.395 1923 2.061 1924 2.031 1925 1.428 1926 1.741 1927 1.151 1928 1.582 1929 1.76 1930 0.849 1931 0.591 1932 1.025 1933 1.091 1934 0.424 1935 0.701 1936 0.431 1937 0.841 1938 1.1 1939 1.21 1940 0.898 1941 0.862 1942 2.21 1943 1.643 1944 1.749 1945 2.278 1946 1.551 1947 0.707 1948 1.351 1949 0.524 1950 0.675 1951 0.677 1952 0.894 1953 0.925 1954 0.664 1955 1.234 1956 1.657 1957 1.199 1958 1.227 1959 1.259 1960 0.923 1961 1.063 1962 1.014 1963 1.221 1964 1.538 1965 1.609 1966 0.937 1967 1.455 1968 0.811 1969 1.44 1970 0.78 1971 0.505 1972 0.783 1973 0.473 1974 0.63 1975 0.491 1976 0.634 1977 0.823 1978 0.99 1979 1.317 1980 0.647 1981 0.826 1982 0.883 1983 0.857 1984 1.172 1985 1.088 1986 1.161 1987 0.872 1988 0.824 1989 1.157 1990 1.027