# asia_russ027w - Indikyakha-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/4438 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_russ027w - Indikyakha-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: Indikyakha-River # Location: # Country: Russia # Northernmost_Latitude: 68.25 # Southernmost_Latitude: 68.25 # Easternmost_Longitude: 80.18 # Westernmost_Longitude: 80.18 # Elevation: 60 m #-------------------- # Data_Collection # Collection_Name: asia_russ027wB # Earliest_Year: 1705 # 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":"7.60191730896","T2":"18.6875680756","M1":"0.0223466975859","M2":"0.350318973815"}} #-------------------- # 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 1705 1.15 1706 0.78 1707 1.73 1708 1.345 1709 1.846 1710 1.397 1711 1.097 1712 1.189 1713 0.997 1714 0.368 1715 1.401 1716 1.128 1717 0.711 1718 0.554 1719 1.143 1720 0.96 1721 1.029 1722 1.111 1723 1.093 1724 1.687 1725 0.782 1726 1.256 1727 1.191 1728 0.741 1729 1.02 1730 0.764 1731 1.046 1732 0.265 1733 1.21 1734 0.66 1735 1.115 1736 0.465 1737 0.827 1738 0.634 1739 0.604 1740 0.833 1741 0.717 1742 0.227 1743 1.05 1744 0.957 1745 0.692 1746 0.906 1747 0.654 1748 0.555 1749 0.516 1750 0.659 1751 1.06 1752 0.712 1753 0.812 1754 1.276 1755 0.927 1756 1.157 1757 1.424 1758 0.738 1759 0.509 1760 1.32 1761 1.573 1762 1.731 1763 1.587 1764 1.123 1765 1.144 1766 1.208 1767 1.452 1768 0.693 1769 0.962 1770 0.619 1771 1.041 1772 0.381 1773 0.657 1774 0.512 1775 1.495 1776 0.595 1777 1.096 1778 1.647 1779 1.429 1780 1.188 1781 1.056 1782 1.348 1783 0.171 1784 1.278 1785 1.206 1786 1.069 1787 1.242 1788 0.588 1789 0.833 1790 1.308 1791 1.145 1792 1.176 1793 2.237 1794 2.015 1795 1.39 1796 1.57 1797 1.131 1798 1.193 1799 1.021 1800 0.742 1801 1.252 1802 0.881 1803 0.935 1804 0.819 1805 1.435 1806 1.085 1807 0.877 1808 1.318 1809 1.381 1810 1.046 1811 1.089 1812 0.416 1813 0.81 1814 0.908 1815 0.538 1816 0.526 1817 0.864 1818 0.849 1819 0.363 1820 0.49 1821 0.777 1822 1.055 1823 0.833 1824 0.696 1825 0.204 1826 0.717 1827 0.971 1828 0.581 1829 1.138 1830 0.629 1831 0.587 1832 1.07 1833 0.116 1834 0.383 1835 0.558 1836 0.499 1837 0.455 1838 0.734 1839 1.009 1840 0.829 1841 0.326 1842 0.943 1843 0.59 1844 1.327 1845 1.696 1846 1.535 1847 1.204 1848 1.139 1849 1.011 1850 1.109 1851 1.184 1852 1.2 1853 1.36 1854 1.109 1855 0.636 1856 1.427 1857 1.279 1858 0.996 1859 1.216 1860 0.832 1861 1.468 1862 0.907 1863 0.739 1864 0.558 1865 0.75 1866 0.853 1867 0.109 1868 1.06 1869 0.56 1870 1.416 1871 0.905 1872 1.23 1873 0.765 1874 0.626 1875 0.866 1876 1.076 1877 1.341 1878 1.719 1879 1.543 1880 0.761 1881 0.5 1882 0.227 1883 0.83 1884 0.231 1885 0.221 1886 0.903 1887 0.893 1888 0.764 1889 0.28 1890 0.858 1891 0.364 1892 0.965 1893 0.486 1894 0.954 1895 0.992 1896 0.621 1897 1.325 1898 1.756 1899 0.347 1900 1.236 1901 0.51 1902 1.069 1903 0.711 1904 1.061 1905 1.173 1906 1.085 1907 0.439 1908 1.259 1909 1.427 1910 1.467 1911 1.184 1912 0.713 1913 0.648 1914 0.41 1915 1.076 1916 0.366 1917 0.757 1918 1.517 1919 0.985 1920 0.938 1921 1.075 1922 1.35 1923 1.753 1924 1.546 1925 1.058 1926 1.236 1927 0.799 1928 0.973 1929 1.302 1930 1.346 1931 0.838 1932 1.356 1933 1.418 1934 0.397 1935 0.7 1936 0.606 1937 0.767 1938 0.996 1939 0.945 1940 0.832 1941 0.839 1942 1.843 1943 1.652 1944 2.014 1945 2.283 1946 1.56 1947 0.625 1948 1.852 1949 0.893 1950 1.191 1951 1.254 1952 0.935 1953 1.289 1954 0.803 1955 1.645 1956 1.621 1957 1.202 1958 1.411 1959 1.599 1960 0.994 1961 1.304 1962 1.094 1963 1.144 1964 1.474 1965 1.425 1966 0.763 1967 1.243 1968 0.66 1969 1.257 1970 0.783 1971 0.409 1972 0.684 1973 0.352 1974 0.685 1975 0.448 1976 0.849 1977 0.652 1978 1.033 1979 1.111 1980 0.557 1981 0.812 1982 0.995 1983 0.905 1984 1.201 1985 0.96 1986 1.225 1987 1.199 1988 0.861 1989 0.816 1990 0.901