# northamerica_usa_me022 - Sag Pond - 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/3024 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: northamerica_usa_me022 - Sag Pond - 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: Sag Pond # Location: # Country: United States # Northernmost_Latitude: 46.77 # Southernmost_Latitude: 46.77 # Easternmost_Longitude: -69.17 # Westernmost_Longitude: -69.17 # Elevation: 500 m #-------------------- # Data_Collection # Collection_Name: northamerica_usa_me022B # Earliest_Year: 1705 # Most_Recent_Year: 1986 # 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":"5.13575700107","T2":"17.5028970395","M1":"0.0227120793795","M2":"0.411823373984"}} #-------------------- # Species # Species_Name: northern white cedar # Species_Code: THOC #-------------------- # 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 1705 0.909 1706 0.951 1707 1.038 1708 1.068 1709 1.059 1710 0.986 1711 0.801 1712 0.997 1713 0.813 1714 1.031 1715 0.936 1716 0.795 1717 0.792 1718 0.872 1719 0.825 1720 0.694 1721 0.681 1722 0.846 1723 0.894 1724 0.977 1725 0.963 1726 0.78 1727 0.982 1728 0.918 1729 1.026 1730 0.769 1731 0.891 1732 1.108 1733 0.863 1734 0.806 1735 0.719 1736 0.675 1737 0.782 1738 1.018 1739 0.884 1740 0.875 1741 0.825 1742 1.006 1743 0.982 1744 0.803 1745 0.883 1746 0.828 1747 0.956 1748 0.842 1749 0.915 1750 0.952 1751 0.791 1752 0.86 1753 0.792 1754 1.114 1755 1.146 1756 0.973 1757 0.852 1758 0.741 1759 1.033 1760 0.905 1761 1.273 1762 1.303 1763 1.204 1764 1.107 1765 1.242 1766 1.246 1767 1.408 1768 1.244 1769 0.933 1770 1.009 1771 1.153 1772 1.072 1773 1.052 1774 0.934 1775 1.268 1776 1.036 1777 0.964 1778 1.054 1779 0.971 1780 1.233 1781 1.131 1782 1.221 1783 0.962 1784 1.095 1785 1.236 1786 1.208 1787 1.561 1788 0.992 1789 1.035 1790 1.053 1791 0.98 1792 0.841 1793 1.183 1794 1.021 1795 0.882 1796 0.839 1797 0.906 1798 1.001 1799 1.081 1800 1.103 1801 1.074 1802 1.102 1803 1.1 1804 1.126 1805 1.155 1806 1.134 1807 1.366 1808 0.99 1809 1.066 1810 0.989 1811 1.19 1812 1.03 1813 1.218 1814 1.262 1815 1.334 1816 1.03 1817 0.938 1818 0.777 1819 1.018 1820 0.866 1821 0.741 1822 0.827 1823 0.962 1824 0.887 1825 1.06 1826 0.836 1827 0.944 1828 0.884 1829 0.89 1830 1.019 1831 0.76 1832 0.992 1833 1.087 1834 0.932 1835 0.745 1836 0.878 1837 0.891 1838 0.562 1839 0.772 1840 0.769 1841 0.729 1842 0.894 1843 0.876 1844 0.902 1845 1.148 1846 0.943 1847 0.99 1848 1.14 1849 0.935 1850 0.791 1851 1.014 1852 1.198 1853 0.866 1854 1.074 1855 0.973 1856 0.917 1857 0.982 1858 1.047 1859 1.063 1860 0.783 1861 0.944 1862 1.027 1863 0.839 1864 0.727 1865 0.793 1866 0.881 1867 0.802 1868 0.797 1869 0.959 1870 0.952 1871 1.064 1872 0.894 1873 0.868 1874 0.984 1875 0.916 1876 0.594 1877 0.731 1878 0.973 1879 1.087 1880 0.976 1881 0.946 1882 0.829 1883 0.835 1884 0.899 1885 0.983 1886 1.183 1887 1.101 1888 0.864 1889 1.093 1890 1.019 1891 0.806 1892 1.056 1893 0.977 1894 1.096 1895 1.008 1896 1.154 1897 1.023 1898 1.093 1899 1.048 1900 0.869 1901 0.965 1902 0.948 1903 1.079 1904 1.123 1905 0.86 1906 0.868 1907 0.741 1908 0.735 1909 0.647 1910 0.893 1911 0.853 1912 0.671 1913 0.78 1914 0.759 1915 0.797 1916 0.963 1917 0.806 1918 0.96 1919 0.79 1920 0.932 1921 1.036 1922 0.958 1923 1.069 1924 0.963 1925 1.141 1926 1.011 1927 0.949 1928 0.989 1929 0.855 1930 0.754 1931 1.05 1932 1.128 1933 0.985 1934 0.953 1935 1.034 1936 0.91 1937 1.03 1938 0.906 1939 1.167 1940 1.122 1941 0.866 1942 0.916 1943 1.16 1944 1.04 1945 1.09 1946 1.007 1947 0.905 1948 1.076 1949 0.937 1950 0.861 1951 0.74 1952 0.991 1953 0.909 1954 0.996 1955 1.077 1956 0.688 1957 0.933 1958 1.37 1959 1.217 1960 1.084 1961 1.144 1962 1.136 1963 1.051 1964 1.006 1965 1.385 1966 1.08 1967 0.886 1968 1.175 1969 1.215 1970 1.158 1971 1.255 1972 1.066 1973 1.22 1974 1.118 1975 1.35 1976 0.778 1977 1.33 1978 1.243 1979 1.125 1980 1.481 1981 1.208 1982 0.93 1983 1.02 1984 1.213 1985 0.711 1986 0.789