# asia_russ047w - Kedvaran - 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/4459 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_russ047w - Kedvaran - 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: Kedvaran # Location: # Country: Russia # Northernmost_Latitude: 64.25 # Southernmost_Latitude: 64.25 # Easternmost_Longitude: 53.57 # Westernmost_Longitude: 53.57 # Elevation: 70 m #-------------------- # Data_Collection # Collection_Name: asia_russ047wB # Earliest_Year: 1730 # 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":"7.30420684432","T2":"17.5280812502","M1":"0.0222197579627","M2":"0.240817007919"}} #-------------------- # 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 1730 1.14 1731 1.203 1732 1.17 1733 1.25 1734 1.171 1735 0.791 1736 1.109 1737 1.21 1738 1.202 1739 1.454 1740 1.252 1741 1.211 1742 1.007 1743 0.855 1744 0.941 1745 1.131 1746 1.279 1747 1.289 1748 0.915 1749 0.966 1750 0.73 1751 0.928 1752 0.808 1753 1.159 1754 0.976 1755 1.128 1756 1.132 1757 0.703 1758 0.716 1759 0.746 1760 0.686 1761 1.035 1762 1.057 1763 0.771 1764 0.903 1765 0.814 1766 0.762 1767 1.079 1768 0.993 1769 0.972 1770 0.678 1771 0.895 1772 0.467 1773 0.592 1774 1.049 1775 0.658 1776 0.735 1777 0.881 1778 0.462 1779 0.491 1780 0.567 1781 0.827 1782 0.756 1783 0.701 1784 0.649 1785 0.8 1786 0.647 1787 0.718 1788 0.916 1789 0.837 1790 1.025 1791 1.05 1792 0.882 1793 0.987 1794 1.158 1795 1.148 1796 1.35 1797 1.197 1798 1.542 1799 1.223 1800 1.53 1801 1.389 1802 0.843 1803 0.757 1804 1.019 1805 1.417 1806 0.901 1807 1.037 1808 1.062 1809 0.949 1810 0.654 1811 0.802 1812 0.64 1813 0.808 1814 0.731 1815 0.8 1816 0.523 1817 0.095 1818 0.249 1819 0.137 1820 0.116 1821 0.214 1822 0.283 1823 0.427 1824 0.445 1825 0.726 1826 0.603 1827 1.085 1828 1.528 1829 1.898 1830 1.682 1831 1.341 1832 1.126 1833 1.431 1834 1.164 1835 0.987 1836 0.722 1837 1.026 1838 0.718 1839 1.24 1840 0.924 1841 0.665 1842 0.887 1843 0.931 1844 1.217 1845 1.173 1846 1.327 1847 1.286 1848 0.954 1849 1.14 1850 0.97 1851 0.918 1852 0.688 1853 0.737 1854 0.906 1855 1.065 1856 1.403 1857 1.258 1858 0.88 1859 1.149 1860 0.845 1861 0.87 1862 0.77 1863 0.658 1864 0.888 1865 0.59 1866 0.746 1867 0.762 1868 0.691 1869 0.751 1870 0.756 1871 0.625 1872 0.914 1873 1.068 1874 0.708 1875 0.804 1876 0.688 1877 0.864 1878 1.233 1879 1.003 1880 1.087 1881 0.775 1882 0.825 1883 1.017 1884 1.026 1885 1.147 1886 0.906 1887 1.219 1888 1.074 1889 1.361 1890 1.344 1891 1.201 1892 1.269 1893 0.977 1894 0.98 1895 0.9 1896 0.917 1897 0.743 1898 0.954 1899 0.747 1900 1.099 1901 1.068 1902 1.015 1903 0.506 1904 0.549 1905 0.622 1906 0.868 1907 1.127 1908 1.096 1909 1.117 1910 0.687 1911 1.272 1912 1.045 1913 1.227 1914 0.98 1915 1.214 1916 1.162 1917 1.42 1918 1.447 1919 1.18 1920 0.889 1921 1.098 1922 1.608 1923 1.491 1924 1.49 1925 1.831 1926 1.708 1927 1.69 1928 1.314 1929 1.297 1930 0.948 1931 1.16 1932 0.897 1933 0.927 1934 0.96 1935 1.036 1936 1.265 1937 1.328 1938 1.507 1939 1.401 1940 1.419 1941 0.947 1942 1.021 1943 0.734 1944 0.877 1945 1.123 1946 1.043 1947 1.069 1948 1.236 1949 1.031 1950 0.892 1951 1.118 1952 1.329 1953 1.116 1954 0.97 1955 0.887 1956 1.128 1957 0.915 1958 0.885 1959 1.133 1960 0.982 1961 0.937 1962 0.551 1963 0.724 1964 0.997 1965 0.949 1966 0.89 1967 0.398 1968 0.829 1969 0.669 1970 0.852 1971 0.682 1972 0.597 1973 0.627 1974 0.641 1975 0.393 1976 0.721 1977 0.853 1978 0.752 1979 1.027 1980 0.923 1981 1.161 1982 0.771 1983 0.989 1984 1.097 1985 0.749 1986 0.749 1987 0.842 1988 0.799 1989 0.616 1990 0.595