# asia_russ098w - Pinega, Belomop-kuloi pla - 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/4593 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_russ098w - Pinega, Belomop-kuloi pla - 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: Pinega, Belomop-kuloi pla # Location: # Country: Russia # Northernmost_Latitude: 64.92 # Southernmost_Latitude: 64.92 # Easternmost_Longitude: 42.5 # Westernmost_Longitude: 42.5 # Elevation: 230 m #-------------------- # Data_Collection # Collection_Name: asia_russ098wB # Earliest_Year: 1695 # Most_Recent_Year: 1990 # Time_Unit: y_ad # Core_Length: # Notes: {"database":{"database1":"LMR","database2":"Breits"}} {"climateInterpretation":{"basis":"", "climateVariable":"M", "climateVariableDetail":"air", "interpDirection":"positive", "seasonality":"[6, 7, 8]"}}{"VSLite_parameters":{"T1":"6.40562577232","T2":"16.3682510759","M1":"0.0228590631053","M2":"0.521716946438"}} #-------------------- # 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 1695 0.938 1696 1.095 1697 1.257 1698 1.019 1699 0.811 1700 0.662 1701 0.803 1702 0.701 1703 0.798 1704 0.868 1705 1.098 1706 0.64 1707 1.377 1708 1.189 1709 1.08 1710 1.055 1711 0.967 1712 0.31 1713 1.052 1714 1.123 1715 1.205 1716 1.413 1717 0.566 1718 1.081 1719 0.415 1720 0.36 1721 0.692 1722 0.816 1723 0.909 1724 1.15 1725 1.2 1726 1.307 1727 1.519 1728 1.331 1729 1.268 1730 0.938 1731 1.548 1732 1.195 1733 1.369 1734 1.23 1735 1.229 1736 1.787 1737 1.71 1738 1.638 1739 1.75 1740 1.367 1741 1.014 1742 1.022 1743 0.85 1744 0.933 1745 1.348 1746 1.283 1747 1.397 1748 0.926 1749 1.051 1750 0.484 1751 0.862 1752 1.334 1753 1.001 1754 1.328 1755 1.605 1756 1.09 1757 0.869 1758 1.41 1759 0.917 1760 0.964 1761 0.776 1762 1.248 1763 1.265 1764 0.943 1765 0.973 1766 0.704 1767 1.443 1768 1.216 1769 0.9 1770 0.613 1771 0.82 1772 0.268 1773 0.637 1774 1.425 1775 1.491 1776 0.296 1777 0.102 1778 0.211 1779 0.665 1780 0.54 1781 0.544 1782 0.906 1783 0.809 1784 0.616 1785 0.717 1786 0.324 1787 0.529 1788 0.714 1789 0.719 1790 0.988 1791 0.584 1792 0.479 1793 0.562 1794 0.94 1795 1.238 1796 1.372 1797 1.537 1798 1.207 1799 1.5 1800 1.373 1801 1.052 1802 1.247 1803 1.037 1804 0.578 1805 0.013 1806 0.25 1807 0.475 1808 0.43 1809 0.688 1810 0.133 1811 0.526 1812 0.495 1813 0.135 1814 0.245 1815 0.056 1816 0.317 1817 0.345 1818 0.477 1819 0.948 1820 0.972 1821 0.567 1822 0.562 1823 1.79 1824 1.643 1825 2.225 1826 2.791 1827 2.604 1828 2.661 1829 1.777 1830 1.766 1831 1.231 1832 1.017 1833 1.305 1834 0.643 1835 0.75 1836 -0.024 1837 0.557 1838 0.301 1839 0.404 1840 0.89 1841 1.058 1842 1.492 1843 1.424 1844 1.328 1845 0.66 1846 0.289 1847 1.063 1848 1.132 1849 1.295 1850 1.516 1851 1.463 1852 1.347 1853 1.353 1854 0.276 1855 0.387 1856 0.894 1857 0.692 1858 0.543 1859 0.913 1860 1.235 1861 1.456 1862 0.749 1863 0.687 1864 1.462 1865 1.246 1866 1.017 1867 0.625 1868 0.215 1869 0.773 1870 0.874 1871 0.488 1872 0.354 1873 0.306 1874 0.211 1875 0.696 1876 0.969 1877 1.346 1878 1.557 1879 0.863 1880 1.253 1881 1.198 1882 0.629 1883 1.225 1884 1.386 1885 1.344 1886 1.16 1887 1.444 1888 1.261 1889 1.125 1890 1.657 1891 1.305 1892 0.759 1893 0.594 1894 0.487 1895 0.792 1896 0.987 1897 1.319 1898 2.026 1899 1.533 1900 1.604 1901 1.736 1902 1.552 1903 0.979 1904 0.916 1905 0.179 1906 0.446 1907 0.608 1908 0.355 1909 0.385 1910 0.192 1911 0.596 1912 0.539 1913 0.318 1914 0.666 1915 0.568 1916 0.907 1917 0.85 1918 0.888 1919 0.856 1920 0.875 1921 1.625 1922 1.345 1923 1.375 1924 0.437 1925 0.74 1926 0.735 1927 0.806 1928 0.607 1929 0.637 1930 0.388 1931 0.545 1932 0.538 1933 0.954 1934 0.885 1935 0.699 1936 0.732 1937 0.852 1938 0.99 1939 1.388 1940 1.232 1941 1.052 1942 0.968 1943 1.229 1944 1.075 1945 1.105 1946 1.086 1947 1.055 1948 1.358 1949 1.742 1950 1.366 1951 1.238 1952 1.463 1953 1.4 1954 1.525 1955 1.108 1956 1.431 1957 1.333 1958 1.264 1959 1.261 1960 1.238 1961 1.129 1962 0.716 1963 0.844 1964 1.21 1965 0.956 1966 0.895 1967 0.425 1968 0.767 1969 0.275 1970 0.679 1971 0.528 1972 0.53 1973 0.701 1974 1.109 1975 0.758 1976 1.033 1977 1.165 1978 0.95 1979 0.851 1980 0.85 1981 1.112 1982 0.513 1983 0.705 1984 1.369 1985 0.975 1986 0.813 1987 1.014 1988 1.057 1989 0.865 1990 0.911