# asia_russ028w - Kulyumbe 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/4486 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_russ028w - Kulyumbe 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: Kulyumbe River # Location: # Country: Russia # Northernmost_Latitude: 67.97 # Southernmost_Latitude: 67.97 # Easternmost_Longitude: 88.92 # Westernmost_Longitude: 88.92 # Elevation: 160 m #-------------------- # Data_Collection # Collection_Name: asia_russ028wB # Earliest_Year: 1681 # 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":"5.68266776584","T2":"19.6274748381","M1":"0.0223663750867","M2":"0.316960094272"}} #-------------------- # 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 1681 0.404 1682 0.683 1683 0.601 1684 0.713 1685 0.968 1686 0.906 1687 1.191 1688 1.483 1689 1.038 1690 1.021 1691 0.862 1692 0.707 1693 1.151 1694 0.278 1695 1.293 1696 0.626 1697 0.608 1698 0.776 1699 0.408 1700 1.06 1701 0.972 1702 0.667 1703 0.602 1704 0.543 1705 0.593 1706 0.503 1707 0.915 1708 0.601 1709 1.01 1710 0.72 1711 0.706 1712 0.735 1713 0.662 1714 0.549 1715 1.067 1716 0.898 1717 1.301 1718 0.667 1719 0.752 1720 0.715 1721 0.993 1722 0.88 1723 0.869 1724 1.212 1725 0.939 1726 0.823 1727 1.222 1728 0.95 1729 1.284 1730 1.353 1731 1.421 1732 0.481 1733 1.093 1734 0.863 1735 1.054 1736 0.909 1737 0.777 1738 0.424 1739 0.911 1740 1.267 1741 0.91 1742 0.283 1743 1.809 1744 1.583 1745 0.993 1746 0.993 1747 1.699 1748 1.411 1749 0.738 1750 0.642 1751 0.909 1752 0.415 1753 0.66 1754 0.905 1755 0.744 1756 1.131 1757 1.19 1758 1.476 1759 0.594 1760 0.772 1761 1.091 1762 1.499 1763 1.073 1764 1.44 1765 1.505 1766 1.693 1767 1.807 1768 0.85 1769 1.429 1770 0.762 1771 1.21 1772 0.817 1773 0.435 1774 0.833 1775 1.55 1776 1.008 1777 1.406 1778 1.136 1779 0.969 1780 0.944 1781 1.182 1782 1.56 1783 0.69 1784 1.202 1785 1.018 1786 1.005 1787 1.021 1788 0.651 1789 1.087 1790 1.292 1791 1.127 1792 1.014 1793 2.135 1794 1.878 1795 1.219 1796 1.248 1797 0.653 1798 0.835 1799 1.213 1800 0.896 1801 1.217 1802 0.991 1803 1.019 1804 1.293 1805 1.506 1806 1.665 1807 0.6 1808 0.982 1809 1.425 1810 1.253 1811 1.198 1812 0.685 1813 1.065 1814 1.331 1815 1.064 1816 0.786 1817 1.395 1818 0.813 1819 0.309 1820 0.862 1821 0.937 1822 1.008 1823 0.785 1824 0.641 1825 0.379 1826 0.583 1827 1.105 1828 0.369 1829 1.159 1830 0.28 1831 0.878 1832 0.454 1833 0.196 1834 0.586 1835 0.434 1836 0.328 1837 0.477 1838 0.551 1839 0.929 1840 1.069 1841 0.889 1842 1.194 1843 0.451 1844 1.131 1845 0.631 1846 0.621 1847 1.005 1848 0.863 1849 0.976 1850 1.184 1851 1.332 1852 1.074 1853 1.289 1854 1.154 1855 0.996 1856 0.82 1857 0.52 1858 0.582 1859 0.776 1860 0.912 1861 1.084 1862 0.822 1863 1.147 1864 1.109 1865 1.051 1866 0.675 1867 0.081 1868 1.132 1869 0.319 1870 1.148 1871 0.949 1872 0.947 1873 0.736 1874 0.427 1875 0.939 1876 0.849 1877 1.16 1878 1.019 1879 1.606 1880 1.29 1881 0.926 1882 0.69 1883 0.925 1884 0.66 1885 0.283 1886 0.998 1887 0.865 1888 0.829 1889 0.536 1890 0.722 1891 0.973 1892 1.077 1893 0.912 1894 1.105 1895 0.49 1896 1.532 1897 1.583 1898 1.323 1899 0.608 1900 0.735 1901 0.524 1902 0.836 1903 1.017 1904 0.94 1905 0.715 1906 0.776 1907 0.43 1908 1.497 1909 0.89 1910 0.693 1911 0.607 1912 1.037 1913 0.726 1914 0.871 1915 1.354 1916 0.765 1917 1.166 1918 1.253 1919 1.097 1920 1.18 1921 0.885 1922 1.302 1923 1.631 1924 1.638 1925 0.877 1926 1.228 1927 1.045 1928 1.375 1929 0.974 1930 1.42 1931 0.935 1932 1.045 1933 1.076 1934 1.208 1935 1.012 1936 1.247 1937 0.958 1938 1.078 1939 1.026 1940 0.943 1941 0.919 1942 1.34 1943 1.517 1944 1.508 1945 1.548 1946 1.228 1947 0.721 1948 1.046 1949 0.198 1950 0.879 1951 0.405 1952 0.894 1953 1.143 1954 1.057 1955 1.581 1956 1.264 1957 1.375 1958 1.349 1959 1.557 1960 1.275 1961 1.191 1962 1.411 1963 1.294 1964 1.301 1965 1.193 1966 0.888 1967 1.275 1968 0.657 1969 0.794 1970 0.863 1971 0.598 1972 1.064 1973 0.47 1974 0.468 1975 0.794 1976 1.127 1977 0.941 1978 0.877 1979 1.117 1980 0.815 1981 0.825 1982 0.765 1983 1.101 1984 1.476 1985 1.405 1986 1.562 1987 1.279 1988 1.178 1989 0.746 1990 1.121