# asia_russ014 - Esso Village Kamchatka - 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/4757 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_russ014 - Esso Village Kamchatka - 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: Esso Village Kamchatka # Location: # Country: Russia # Northernmost_Latitude: 55.9 # Southernmost_Latitude: 55.9 # Easternmost_Longitude: 158.8 # Westernmost_Longitude: 158.8 # Elevation: 900 m #-------------------- # Data_Collection # Collection_Name: asia_russ014B # Earliest_Year: 1720 # Most_Recent_Year: 1984 # 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":"2.52511992326","T2":"17.0345086234","M1":"0.0230115266919","M2":"0.394689562123"}} #-------------------- # 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 1720 0.627 1721 1.107 1722 1.181 1723 0.892 1724 0.48 1725 0.877 1726 0.687 1727 0.873 1728 0.923 1729 1.091 1730 0.843 1731 0.848 1732 1.08 1733 1.142 1734 1.287 1735 1.563 1736 1.429 1737 1.327 1738 1.267 1739 1.132 1740 0.553 1741 1.062 1742 1.865 1743 0.324 1744 1.063 1745 1.418 1746 1.558 1747 1.121 1748 1.184 1749 1.704 1750 1.332 1751 1.179 1752 1.009 1753 1.225 1754 1.335 1755 0.984 1756 0.872 1757 1.22 1758 0.89 1759 0.738 1760 0.854 1761 0.608 1762 1.029 1763 0.688 1764 1.001 1765 0.735 1766 1.06 1767 1.035 1768 0.738 1769 1.232 1770 0.473 1771 0.945 1772 0.874 1773 1.388 1774 1.0 1775 1.073 1776 1.656 1777 0.902 1778 0.196 1779 0.637 1780 0.879 1781 0.955 1782 1.122 1783 1.037 1784 0.617 1785 0.72 1786 0.751 1787 0.455 1788 0.859 1789 0.843 1790 1.063 1791 0.959 1792 1.285 1793 1.507 1794 0.765 1795 1.017 1796 1.194 1797 0.617 1798 1.247 1799 1.585 1800 1.491 1801 1.389 1802 1.225 1803 1.267 1804 1.069 1805 0.954 1806 1.337 1807 1.312 1808 1.321 1809 1.525 1810 1.127 1811 0.469 1812 0.706 1813 0.323 1814 0.834 1815 0.874 1816 1.253 1817 0.451 1818 0.684 1819 0.559 1820 0.621 1821 0.849 1822 0.95 1823 0.72 1824 0.745 1825 1.069 1826 1.14 1827 0.833 1828 0.99 1829 1.259 1830 1.116 1831 1.014 1832 1.001 1833 0.863 1834 1.264 1835 1.118 1836 0.974 1837 0.661 1838 0.819 1839 0.853 1840 1.095 1841 1.582 1842 0.99 1843 1.182 1844 1.262 1845 1.174 1846 1.239 1847 1.228 1848 0.798 1849 1.059 1850 1.18 1851 1.43 1852 0.859 1853 0.978 1854 1.017 1855 1.077 1856 0.634 1857 0.357 1858 0.968 1859 1.241 1860 0.838 1861 0.889 1862 1.118 1863 1.05 1864 0.233 1865 0.38 1866 0.696 1867 0.103 1868 0.634 1869 0.841 1870 0.731 1871 0.983 1872 1.052 1873 0.89 1874 1.108 1875 1.033 1876 0.702 1877 0.38 1878 0.688 1879 0.716 1880 0.956 1881 0.754 1882 0.9 1883 0.872 1884 0.936 1885 0.624 1886 0.995 1887 0.354 1888 0.597 1889 0.989 1890 1.062 1891 0.881 1892 1.137 1893 0.923 1894 1.139 1895 1.085 1896 1.104 1897 1.147 1898 1.166 1899 1.289 1900 1.544 1901 1.051 1902 0.995 1903 1.11 1904 0.507 1905 0.619 1906 0.759 1907 0.837 1908 0.868 1909 1.083 1910 1.132 1911 0.923 1912 0.63 1913 0.691 1914 1.028 1915 1.129 1916 1.131 1917 0.804 1918 0.597 1919 0.699 1920 1.143 1921 1.003 1922 0.799 1923 1.026 1924 1.132 1925 1.173 1926 0.512 1927 0.331 1928 0.972 1929 1.157 1930 1.124 1931 1.011 1932 0.978 1933 1.234 1934 1.265 1935 1.334 1936 1.535 1937 1.05 1938 1.274 1939 1.321 1940 1.01 1941 1.177 1942 1.197 1943 1.298 1944 1.289 1945 0.992 1946 1.058 1947 0.27 1948 1.397 1949 1.137 1950 0.736 1951 0.792 1952 0.866 1953 0.816 1954 1.199 1955 1.06 1956 1.172 1957 0.941 1958 1.152 1959 1.146 1960 0.838 1961 0.926 1962 0.826 1963 1.091 1964 1.306 1965 0.896 1966 1.476 1967 1.316 1968 0.931 1969 1.107 1970 1.131 1971 1.031 1972 0.899 1973 0.985 1974 1.149 1975 1.108 1976 0.718 1977 1.116 1978 0.956 1979 1.012 1980 1.276 1981 1.38 1982 0.565 1983 1.45 1984 0.455