# northamerica_usa_va016 - Watch Dog Massenhutten Mountain - 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/3037 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: northamerica_usa_va016 - Watch Dog Massenhutten Mountain - 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: Watch Dog Massenhutten Mountain # Location: # Country: United States # Northernmost_Latitude: 38.5 # Southernmost_Latitude: 38.5 # Easternmost_Longitude: -78.35 # Westernmost_Longitude: -78.35 # Elevation: 1000 m #-------------------- # Data_Collection # Collection_Name: northamerica_usa_va016B # Earliest_Year: 1700 # Most_Recent_Year: 1980 # 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":"3.91251781368","T2":"15.7277969759","M1":"0.0225772936314","M2":"0.540976944495"}} #-------------------- # Species # Species_Name: chestnut oak # Species_Code: QUPR #-------------------- # 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 1700 0.884 1701 0.964 1702 0.938 1703 0.754 1704 0.559 1705 0.742 1706 0.808 1707 0.891 1708 0.908 1709 0.809 1710 0.792 1711 0.957 1712 1.038 1713 0.895 1714 0.868 1715 0.817 1716 0.953 1717 0.917 1718 0.9 1719 0.95 1720 1.072 1721 0.882 1722 0.921 1723 0.815 1724 0.886 1725 0.9 1726 0.812 1727 0.801 1728 0.76 1729 1.0 1730 0.855 1731 1.203 1732 0.896 1733 0.764 1734 0.734 1735 1.08 1736 1.238 1737 1.028 1738 0.923 1739 1.203 1740 1.239 1741 0.81 1742 1.187 1743 0.968 1744 0.882 1745 1.028 1746 0.752 1747 0.974 1748 0.652 1749 0.888 1750 1.108 1751 1.104 1752 1.118 1753 1.143 1754 1.34 1755 0.855 1756 1.43 1757 0.979 1758 0.785 1759 0.897 1760 0.857 1761 1.234 1762 0.97 1763 1.312 1764 1.018 1765 1.001 1766 1.235 1767 1.007 1768 1.256 1769 0.979 1770 1.316 1771 1.199 1772 0.984 1773 1.145 1774 0.773 1775 0.822 1776 1.008 1777 1.032 1778 1.141 1779 0.875 1780 1.224 1781 1.315 1782 1.152 1783 1.105 1784 1.015 1785 1.068 1786 1.215 1787 1.169 1788 1.289 1789 0.942 1790 0.943 1791 0.796 1792 0.761 1793 1.067 1794 1.109 1795 1.192 1796 1.182 1797 0.958 1798 1.106 1799 1.204 1800 1.075 1801 1.237 1802 1.146 1803 1.048 1804 1.185 1805 1.054 1806 0.856 1807 0.957 1808 1.042 1809 1.092 1810 0.883 1811 1.018 1812 0.995 1813 0.994 1814 1.052 1815 1.049 1816 0.965 1817 1.022 1818 1.098 1819 1.049 1820 0.982 1821 1.091 1822 0.908 1823 0.889 1824 1.039 1825 0.952 1826 0.865 1827 1.097 1828 1.026 1829 0.913 1830 1.07 1831 0.989 1832 1.176 1833 1.103 1834 1.025 1835 0.933 1836 1.057 1837 0.911 1838 0.917 1839 0.816 1840 1.025 1841 0.942 1842 0.87 1843 0.791 1844 0.833 1845 0.777 1846 0.828 1847 0.769 1848 0.796 1849 0.865 1850 0.959 1851 0.84 1852 0.869 1853 0.809 1854 0.979 1855 0.944 1856 0.919 1857 0.928 1858 0.841 1859 0.752 1860 0.737 1861 0.776 1862 0.93 1863 0.832 1864 0.857 1865 0.832 1866 0.816 1867 0.756 1868 0.827 1869 0.949 1870 0.932 1871 0.74 1872 0.757 1873 0.816 1874 0.738 1875 0.866 1876 0.841 1877 0.782 1878 0.958 1879 0.837 1880 0.844 1881 0.968 1882 0.919 1883 0.858 1884 0.956 1885 0.81 1886 0.873 1887 0.878 1888 0.867 1889 1.048 1890 0.9 1891 0.815 1892 0.818 1893 0.856 1894 0.82 1895 0.866 1896 0.815 1897 0.811 1898 0.785 1899 0.86 1900 0.847 1901 1.048 1902 0.89 1903 1.094 1904 1.093 1905 0.997 1906 1.141 1907 1.119 1908 1.123 1909 1.166 1910 1.121 1911 0.796 1912 1.003 1913 1.108 1914 0.819 1915 0.973 1916 1.256 1917 1.175 1918 1.004 1919 1.213 1920 1.25 1921 1.137 1922 1.181 1923 0.999 1924 1.269 1925 0.907 1926 1.03 1927 1.24 1928 1.362 1929 1.174 1930 1.077 1931 1.071 1932 1.117 1933 0.96 1934 1.034 1935 0.978 1936 0.978 1937 1.175 1938 1.194 1939 1.173 1940 1.201 1941 1.0 1942 1.079 1943 1.102 1944 0.95 1945 0.92 1946 1.037 1947 0.866 1948 0.973 1949 1.211 1950 1.262 1951 1.332 1952 1.072 1953 1.174 1954 0.997 1955 0.877 1956 1.0 1957 1.098 1958 1.085 1959 1.046 1960 0.974 1961 1.11 1962 0.997 1963 0.839 1964 0.88 1965 0.884 1966 0.768 1967 0.85 1968 0.922 1969 0.893 1970 1.064 1971 1.135 1972 1.101 1973 0.997 1974 1.03 1975 1.065 1976 1.028 1977 0.859 1978 0.95 1979 0.917 1980 0.889