# asia_russ096w - Murmashi - 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/4546 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_russ096w - Murmashi - 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: Murmashi # Location: # Country: Russia # Northernmost_Latitude: 68.77 # Southernmost_Latitude: 68.77 # Easternmost_Longitude: 32.8 # Westernmost_Longitude: 32.8 # Elevation: 140 m #-------------------- # Data_Collection # Collection_Name: asia_russ096wB # Earliest_Year: 1711 # Most_Recent_Year: 1992 # 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":"6.72434482968","T2":"19.315286354","M1":"0.0226192617202","M2":"0.260772789674"}} #-------------------- # Species # Species_Name: Norway spruce # Species_Code: PCAB #-------------------- # 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 1711 1.261 1712 0.576 1713 0.975 1714 0.713 1715 1.175 1716 1.477 1717 1.314 1718 1.324 1719 1.083 1720 1.167 1721 1.016 1722 1.011 1723 1.07 1724 1.029 1725 1.096 1726 0.932 1727 0.705 1728 0.688 1729 0.784 1730 0.754 1731 0.764 1732 0.899 1733 0.933 1734 0.524 1735 0.991 1736 0.71 1737 0.604 1738 0.785 1739 0.782 1740 0.802 1741 0.598 1742 0.753 1743 0.727 1744 0.841 1745 0.863 1746 0.91 1747 0.631 1748 0.671 1749 0.81 1750 0.846 1751 0.816 1752 0.867 1753 0.999 1754 1.455 1755 1.388 1756 1.439 1757 1.623 1758 1.49 1759 1.537 1760 1.22 1761 1.463 1762 1.338 1763 1.398 1764 1.102 1765 0.961 1766 0.819 1767 1.046 1768 1.049 1769 0.91 1770 1.019 1771 1.161 1772 0.949 1773 1.153 1774 1.042 1775 1.025 1776 0.861 1777 1.177 1778 0.929 1779 1.058 1780 1.275 1781 0.994 1782 1.476 1783 1.321 1784 1.003 1785 1.126 1786 0.911 1787 0.729 1788 0.902 1789 0.739 1790 0.395 1791 0.805 1792 0.816 1793 1.05 1794 0.724 1795 0.473 1796 0.289 1797 0.329 1798 0.497 1799 0.761 1800 0.935 1801 0.937 1802 1.039 1803 0.691 1804 0.927 1805 0.955 1806 0.525 1807 0.999 1808 0.939 1809 1.209 1810 0.713 1811 1.129 1812 0.845 1813 0.637 1814 0.579 1815 0.539 1816 0.65 1817 0.464 1818 1.006 1819 1.226 1820 0.858 1821 0.819 1822 0.885 1823 1.424 1824 1.259 1825 1.499 1826 2.146 1827 1.936 1828 1.651 1829 2.094 1830 1.767 1831 1.905 1832 1.198 1833 1.557 1834 1.06 1835 1.363 1836 0.679 1837 0.687 1838 0.882 1839 0.732 1840 0.619 1841 0.639 1842 0.618 1843 0.583 1844 0.706 1845 1.16 1846 0.873 1847 0.927 1848 0.585 1849 0.923 1850 0.827 1851 1.196 1852 1.114 1853 1.39 1854 1.019 1855 0.909 1856 1.241 1857 0.753 1858 1.181 1859 1.018 1860 1.005 1861 1.225 1862 0.773 1863 0.964 1864 0.853 1865 0.619 1866 0.666 1867 0.579 1868 0.48 1869 0.594 1870 0.623 1871 0.296 1872 0.437 1873 0.518 1874 0.237 1875 0.742 1876 0.858 1877 0.94 1878 0.84 1879 0.481 1880 0.783 1881 1.009 1882 0.585 1883 1.142 1884 0.983 1885 0.953 1886 0.959 1887 0.803 1888 0.964 1889 1.632 1890 1.795 1891 1.581 1892 1.06 1893 1.336 1894 1.04 1895 1.464 1896 1.772 1897 1.126 1898 1.222 1899 0.957 1900 0.653 1901 1.063 1902 0.755 1903 0.784 1904 1.064 1905 0.991 1906 0.863 1907 1.183 1908 0.76 1909 0.605 1910 0.206 1911 0.58 1912 0.332 1913 0.516 1914 0.768 1915 0.714 1916 0.827 1917 0.775 1918 0.64 1919 0.907 1920 0.484 1921 0.855 1922 1.129 1923 0.915 1924 0.881 1925 1.037 1926 0.889 1927 1.486 1928 0.782 1929 1.018 1930 1.177 1931 0.797 1932 1.043 1933 1.232 1934 0.689 1935 0.838 1936 1.412 1937 1.244 1938 1.254 1939 1.304 1940 1.211 1941 1.324 1942 1.181 1943 0.851 1944 0.782 1945 0.927 1946 0.904 1947 1.397 1948 0.92 1949 0.584 1950 0.923 1951 0.758 1952 1.286 1953 1.156 1954 1.053 1955 0.767 1956 1.149 1957 0.741 1958 0.941 1959 0.609 1960 0.782 1961 1.007 1962 0.683 1963 0.844 1964 1.13 1965 1.066 1966 1.033 1967 0.778 1968 0.875 1969 0.908 1970 1.216 1971 0.767 1972 1.182 1973 0.831 1974 0.751 1975 0.32 1976 0.788 1977 0.97 1978 1.057 1979 1.324 1980 1.22 1981 1.288 1982 0.238 1983 1.048 1984 1.475 1985 1.324 1986 1.393 1987 1.263 1988 1.688 1989 1.108 1990 0.967 1991 1.6 1992 1.5