# asia_russ124w - Balschaya Kamenka 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/4330 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_russ124w - Balschaya Kamenka 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: Balschaya Kamenka River # Location: # Country: Russia # Northernmost_Latitude: 71.33 # Southernmost_Latitude: 71.33 # Easternmost_Longitude: 93.83 # Westernmost_Longitude: 93.83 # Elevation: 60 m #-------------------- # Data_Collection # Collection_Name: asia_russ124wB # Earliest_Year: 1694 # 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":"5.6387539313","T2":"19.6891970571","M1":"0.0225196579927","M2":"0.249416015779"}} #-------------------- # Species # Species_Name: Dahurian larch # Species_Code: LAGM #-------------------- # 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 1694 1.661 1695 3.029 1696 0.827 1697 1.192 1698 0.423 1699 0.334 1700 0.564 1701 0.697 1702 0.14 1703 0.332 1704 0.761 1705 0.923 1706 0.807 1707 1.233 1708 1.121 1709 1.415 1710 0.717 1711 1.154 1712 0.869 1713 1.042 1714 0.605 1715 1.498 1716 1.224 1717 0.505 1718 0.11 1719 0.932 1720 0.745 1721 0.916 1722 0.828 1723 0.697 1724 0.8 1725 0.708 1726 1.021 1727 1.611 1728 0.808 1729 1.867 1730 1.571 1731 1.483 1732 0.46 1733 0.79 1734 0.793 1735 0.801 1736 0.701 1737 0.947 1738 0.618 1739 1.236 1740 1.115 1741 1.318 1742 0.231 1743 1.222 1744 1.731 1745 0.588 1746 1.261 1747 1.967 1748 2.088 1749 1.598 1750 0.801 1751 0.997 1752 1.132 1753 0.813 1754 1.045 1755 0.83 1756 1.046 1757 1.581 1758 1.339 1759 1.082 1760 0.576 1761 1.146 1762 1.12 1763 1.628 1764 1.462 1765 1.532 1766 1.686 1767 2.203 1768 1.327 1769 2.07 1770 1.576 1771 1.182 1772 0.8 1773 0.486 1774 0.766 1775 1.463 1776 1.104 1777 1.381 1778 1.264 1779 1.151 1780 0.921 1781 0.503 1782 1.329 1783 0.583 1784 1.353 1785 1.304 1786 1.017 1787 1.479 1788 0.709 1789 1.356 1790 0.566 1791 0.996 1792 1.026 1793 1.331 1794 1.888 1795 1.055 1796 1.218 1797 1.06 1798 0.513 1799 0.658 1800 0.741 1801 1.561 1802 1.061 1803 1.101 1804 1.11 1805 1.365 1806 1.592 1807 0.387 1808 1.72 1809 1.525 1810 1.145 1811 0.932 1812 0.245 1813 0.653 1814 0.734 1815 0.417 1816 0.41 1817 0.879 1818 0.655 1819 0.288 1820 0.22 1821 0.582 1822 0.699 1823 0.534 1824 0.609 1825 0.147 1826 0.284 1827 0.517 1828 0.862 1829 0.598 1830 0.21 1831 0.528 1832 0.531 1833 0.136 1834 0.536 1835 0.595 1836 0.574 1837 0.229 1838 0.76 1839 0.422 1840 0.609 1841 0.588 1842 0.869 1843 0.52 1844 0.874 1845 0.893 1846 0.838 1847 0.345 1848 0.82 1849 1.099 1850 0.943 1851 0.679 1852 1.263 1853 1.191 1854 1.219 1855 0.84 1856 0.966 1857 1.281 1858 1.123 1859 1.476 1860 1.375 1861 1.474 1862 1.006 1863 1.014 1864 0.977 1865 1.173 1866 0.516 1867 0.396 1868 1.13 1869 0.299 1870 0.495 1871 0.636 1872 0.982 1873 0.5 1874 0.308 1875 0.906 1876 0.722 1877 1.455 1878 1.646 1879 0.984 1880 0.968 1881 0.874 1882 0.716 1883 1.138 1884 0.213 1885 0.213 1886 0.72 1887 1.03 1888 0.85 1889 0.36 1890 0.488 1891 0.792 1892 1.154 1893 0.85 1894 1.463 1895 0.522 1896 1.464 1897 1.845 1898 1.171 1899 0.479 1900 0.768 1901 0.656 1902 0.596 1903 1.006 1904 0.685 1905 0.594 1906 0.631 1907 0.347 1908 2.102 1909 1.214 1910 0.606 1911 0.464 1912 0.44 1913 0.357 1914 0.569 1915 0.699 1916 0.651 1917 0.723 1918 1.113 1919 0.786 1920 1.0 1921 1.029 1922 0.837 1923 1.186 1924 1.382 1925 0.634 1926 1.436 1927 0.715 1928 1.818 1929 1.651 1930 1.165 1931 0.831 1932 1.222 1933 0.94 1934 0.892 1935 0.683 1936 1.187 1937 0.93 1938 0.895 1939 1.131 1940 1.212 1941 1.53 1942 1.75 1943 1.888 1944 1.559 1945 1.969 1946 1.771 1947 0.846 1948 1.397 1949 0.606 1950 1.037 1951 0.967 1952 0.745 1953 1.528 1954 0.777 1955 1.48 1956 1.224 1957 1.203 1958 1.056 1959 0.97 1960 0.768 1961 1.195 1962 1.042 1963 0.845 1964 1.135 1965 0.861 1966 0.556 1967 1.023 1968 0.559 1969 0.757 1970 0.606 1971 0.42 1972 0.603 1973 0.691 1974 0.292 1975 0.52 1976 1.131 1977 0.796 1978 1.16 1979 1.488 1980 1.009 1981 1.219 1982 1.413 1983 1.326 1984 2.078 1985 0.652 1986 1.419 1987 1.338 1988 1.07 1989 0.671 1990 0.767