# asia_russ022w - Polar Ural (rezent) - 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/4598 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_russ022w - Polar Ural (rezent) - 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: Polar Ural (rezent) # Location: # Country: Russia # Northernmost_Latitude: 66.87 # Southernmost_Latitude: 66.87 # Easternmost_Longitude: 65.63 # Westernmost_Longitude: 65.63 # Elevation: 250 m #-------------------- # Data_Collection # Collection_Name: asia_russ022wB # Earliest_Year: 1739 # 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":"4.69416613249","T2":"15.4568513512","M1":"0.0229815075847","M2":"0.492946975521"}} #-------------------- # Species # Species_Name: Siberian spruce # Species_Code: PCOB #-------------------- # 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 1739 0.783 1740 1.019 1741 0.946 1742 0.951 1743 0.897 1744 1.11 1745 1.026 1746 1.323 1747 1.338 1748 1.19 1749 1.037 1750 0.991 1751 1.061 1752 0.766 1753 0.958 1754 1.099 1755 0.962 1756 1.408 1757 1.624 1758 1.988 1759 1.536 1760 1.223 1761 1.408 1762 1.403 1763 1.484 1764 1.333 1765 1.358 1766 1.117 1767 1.213 1768 1.263 1769 1.202 1770 1.114 1771 1.2 1772 0.769 1773 0.998 1774 1.014 1775 1.458 1776 1.233 1777 1.154 1778 1.211 1779 1.154 1780 1.285 1781 1.431 1782 1.582 1783 0.825 1784 1.312 1785 0.936 1786 0.977 1787 0.861 1788 0.525 1789 0.678 1790 0.866 1791 0.872 1792 0.804 1793 0.912 1794 0.843 1795 1.101 1796 0.801 1797 0.659 1798 1.044 1799 0.884 1800 1.027 1801 0.881 1802 0.962 1803 1.045 1804 0.885 1805 1.196 1806 1.033 1807 1.402 1808 1.448 1809 1.35 1810 1.107 1811 0.979 1812 1.052 1813 1.187 1814 0.889 1815 0.729 1816 0.71 1817 0.646 1818 0.616 1819 0.794 1820 0.626 1821 0.647 1822 0.681 1823 0.848 1824 0.805 1825 0.876 1826 0.841 1827 1.047 1828 0.728 1829 1.617 1830 1.267 1831 1.075 1832 1.629 1833 1.347 1834 1.026 1835 1.358 1836 1.151 1837 1.034 1838 0.72 1839 1.062 1840 1.025 1841 0.656 1842 0.625 1843 0.65 1844 0.774 1845 0.878 1846 0.883 1847 0.813 1848 0.792 1849 0.958 1850 0.951 1851 1.213 1852 1.304 1853 1.202 1854 1.114 1855 0.623 1856 1.33 1857 1.14 1858 1.574 1859 1.288 1860 0.958 1861 1.459 1862 1.065 1863 1.268 1864 0.817 1865 1.0 1866 0.772 1867 0.563 1868 0.716 1869 0.707 1870 0.954 1871 0.946 1872 1.153 1873 1.437 1874 1.155 1875 0.973 1876 0.974 1877 1.008 1878 1.046 1879 0.795 1880 1.068 1881 1.042 1882 0.942 1883 0.69 1884 0.58 1885 0.484 1886 0.49 1887 0.422 1888 0.404 1889 0.372 1890 0.706 1891 0.441 1892 0.649 1893 0.491 1894 0.524 1895 0.662 1896 0.588 1897 0.705 1898 0.71 1899 0.484 1900 0.806 1901 0.644 1902 0.865 1903 0.236 1904 0.61 1905 0.661 1906 0.714 1907 0.609 1908 0.646 1909 0.888 1910 0.628 1911 0.771 1912 0.566 1913 0.795 1914 0.483 1915 0.818 1916 0.482 1917 0.876 1918 0.965 1919 0.703 1920 0.804 1921 0.889 1922 0.901 1923 1.009 1924 0.897 1925 0.815 1926 0.895 1927 0.86 1928 0.825 1929 0.783 1930 0.708 1931 0.875 1932 0.719 1933 0.998 1934 0.968 1935 1.102 1936 0.952 1937 1.038 1938 1.252 1939 1.192 1940 1.173 1941 0.822 1942 1.49 1943 1.265 1944 0.984 1945 1.257 1946 0.979 1947 0.9 1948 1.177 1949 0.773 1950 1.264 1951 0.875 1952 1.226 1953 1.24 1954 1.206 1955 1.118 1956 1.275 1957 1.139 1958 1.297 1959 1.69 1960 0.798 1961 1.091 1962 0.964 1963 0.945 1964 1.191 1965 1.26 1966 0.826 1967 1.213 1968 0.851 1969 1.412 1970 1.095 1971 1.022 1972 1.037 1973 0.902 1974 1.0 1975 0.741 1976 1.261 1977 1.16 1978 1.148 1979 1.326 1980 0.826 1981 1.093 1982 1.071 1983 1.121 1984 1.127 1985 0.884 1986 0.903 1987 1.07 1988 1.058 1989 1.253 1990 1.122