# northamerica_usa_or033 - Bally 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/5229 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: northamerica_usa_or033 - Bally 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: Bally Mountain # Location: # Country: United States # Northernmost_Latitude: 45.28 # Southernmost_Latitude: 45.28 # Easternmost_Longitude: -118.57 # Westernmost_Longitude: -118.57 # Elevation: 0 m #-------------------- # Data_Collection # Collection_Name: northamerica_usa_or033B # Earliest_Year: 1699 # Most_Recent_Year: 1990 # 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":"3.71602604878","T2":"15.5264048193","M1":"0.0228392146128","M2":"0.516040336623"}} #-------------------- # Species # Species_Name: ponderosa pine # Species_Code: PIPO #-------------------- # 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 1699 1.176 1700 0.794 1701 0.755 1702 1.323 1703 1.17 1704 1.153 1705 0.806 1706 1.012 1707 1.14 1708 1.009 1709 0.71 1710 1.17 1711 1.193 1712 1.235 1713 1.012 1714 1.273 1715 1.522 1716 1.59 1717 0.738 1718 0.746 1719 1.043 1720 1.207 1721 1.077 1722 1.008 1723 1.176 1724 0.941 1725 0.88 1726 0.908 1727 1.367 1728 1.046 1729 1.001 1730 0.978 1731 0.902 1732 1.426 1733 1.143 1734 1.081 1735 0.904 1736 0.587 1737 0.818 1738 1.057 1739 0.812 1740 0.481 1741 0.405 1742 0.592 1743 0.73 1744 0.445 1745 0.745 1746 0.841 1747 1.045 1748 0.944 1749 0.932 1750 1.737 1751 1.282 1752 0.496 1753 0.478 1754 0.389 1755 0.937 1756 0.598 1757 0.624 1758 0.654 1759 0.63 1760 0.806 1761 1.209 1762 1.154 1763 1.222 1764 0.721 1765 0.949 1766 1.12 1767 1.136 1768 1.167 1769 1.181 1770 1.61 1771 1.399 1772 1.113 1773 1.673 1774 1.348 1775 1.062 1776 0.709 1777 0.652 1778 0.863 1779 0.851 1780 0.559 1781 0.848 1782 0.799 1783 0.65 1784 0.757 1785 0.744 1786 0.852 1787 0.587 1788 0.718 1789 0.914 1790 0.73 1791 1.28 1792 0.907 1793 1.025 1794 0.773 1795 0.695 1796 0.743 1797 0.509 1798 0.728 1799 0.824 1800 0.572 1801 0.907 1802 1.174 1803 1.026 1804 0.732 1805 1.037 1806 0.92 1807 0.796 1808 0.787 1809 0.812 1810 0.847 1811 1.125 1812 1.213 1813 0.965 1814 0.875 1815 0.938 1816 1.217 1817 0.879 1818 1.086 1819 1.24 1820 0.718 1821 0.866 1822 1.334 1823 0.838 1824 1.106 1825 1.483 1826 1.281 1827 0.721 1828 0.987 1829 0.972 1830 0.79 1831 0.381 1832 0.816 1833 0.804 1834 0.92 1835 0.418 1836 0.706 1837 0.726 1838 1.104 1839 1.1 1840 0.609 1841 0.653 1842 0.739 1843 0.856 1844 0.841 1845 0.974 1846 0.581 1847 0.275 1848 0.529 1849 0.403 1850 0.366 1851 0.666 1852 0.696 1853 0.877 1854 0.865 1855 1.312 1856 1.133 1857 1.343 1858 1.135 1859 0.872 1860 0.817 1861 1.013 1862 1.159 1863 1.104 1864 0.988 1865 0.81 1866 0.945 1867 0.848 1868 1.081 1869 0.821 1870 0.84 1871 0.65 1872 0.549 1873 0.715 1874 0.696 1875 0.811 1876 0.868 1877 1.347 1878 1.326 1879 1.241 1880 0.97 1881 1.054 1882 0.821 1883 0.561 1884 1.0 1885 1.269 1886 0.547 1887 0.555 1888 0.651 1889 0.565 1890 0.337 1891 1.098 1892 1.029 1893 0.978 1894 1.462 1895 1.219 1896 1.157 1897 1.366 1898 1.521 1899 0.849 1900 2.015 1901 1.766 1902 1.241 1903 1.75 1904 2.235 1905 1.421 1906 1.492 1907 1.953 1908 1.919 1909 1.325 1910 1.22 1911 1.146 1912 1.173 1913 1.581 1914 1.582 1915 1.53 1916 1.346 1917 1.018 1918 0.953 1919 1.186 1920 0.683 1921 1.18 1922 0.951 1923 0.997 1924 0.99 1925 0.662 1926 0.682 1927 1.031 1928 0.894 1929 0.642 1930 0.36 1931 0.61 1932 0.568 1933 0.506 1934 0.973 1935 0.449 1936 0.384 1937 0.674 1938 0.996 1939 0.963 1940 0.947 1941 1.526 1942 2.128 1943 1.353 1944 1.074 1945 0.93 1946 1.346 1947 1.605 1948 1.297 1949 1.051 1950 1.007 1951 0.964 1952 0.989 1953 0.926 1954 1.043 1955 1.089 1956 1.007 1957 0.985 1958 1.145 1959 0.812 1960 1.023 1961 0.873 1962 0.726 1963 0.709 1964 0.699 1965 0.765 1966 0.871 1967 0.624 1968 0.507 1969 1.106 1970 0.611 1971 0.859 1972 0.682 1973 0.339 1974 0.544 1975 0.624 1976 0.816 1977 0.833 1978 0.85 1979 0.799 1980 0.945 1981 1.152 1982 1.261 1983 1.446 1984 1.074 1985 0.976 1986 1.072 1987 1.005 1988 0.717 1989 0.674 1990 1.358