# northamerica_usa_or030 - Grizzly Bear - 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/5080 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: northamerica_usa_or030 - Grizzly Bear - 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: Grizzly Bear # Location: # Country: United States # Northernmost_Latitude: 45.97 # Southernmost_Latitude: 45.97 # Easternmost_Longitude: -117.72 # Westernmost_Longitude: -117.72 # Elevation: 1231 m #-------------------- # Data_Collection # Collection_Name: northamerica_usa_or030B # Earliest_Year: 1612 # Most_Recent_Year: 1991 # 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":"4.61977646879","T2":"15.0149334823","M1":"0.0230594164185","M2":"0.514891209705"}} #-------------------- # 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 1612 1.224 1613 1.255 1614 1.009 1615 1.06 1616 1.103 1617 1.239 1618 1.152 1619 0.789 1620 0.845 1621 0.916 1622 0.878 1623 0.535 1624 0.761 1625 0.877 1626 0.652 1627 0.83 1628 0.618 1629 0.58 1630 0.68 1631 0.778 1632 0.718 1633 0.876 1634 0.47 1635 0.611 1636 0.693 1637 0.742 1638 0.717 1639 0.71 1640 0.804 1641 1.064 1642 1.011 1643 0.851 1644 0.993 1645 1.024 1646 0.872 1647 0.56 1648 0.979 1649 0.72 1650 0.757 1651 0.462 1652 0.528 1653 0.769 1654 0.879 1655 0.726 1656 1.041 1657 0.628 1658 1.162 1659 1.044 1660 0.999 1661 0.926 1662 0.945 1663 0.944 1664 0.888 1665 0.706 1666 1.034 1667 1.123 1668 0.895 1669 1.217 1670 1.26 1671 1.006 1672 1.052 1673 1.054 1674 0.929 1675 0.951 1676 0.817 1677 0.732 1678 0.919 1679 1.048 1680 0.946 1681 1.207 1682 0.96 1683 0.897 1684 1.04 1685 1.166 1686 1.049 1687 1.191 1688 1.235 1689 1.183 1690 1.156 1691 1.249 1692 1.331 1693 1.226 1694 1.264 1695 1.025 1696 1.105 1697 1.278 1698 1.061 1699 1.19 1700 1.23 1701 1.074 1702 1.328 1703 1.418 1704 1.175 1705 1.197 1706 1.241 1707 1.455 1708 0.887 1709 0.999 1710 1.004 1711 1.179 1712 1.172 1713 1.226 1714 0.992 1715 1.427 1716 1.348 1717 0.79 1718 0.772 1719 0.958 1720 0.931 1721 0.436 1722 0.896 1723 0.914 1724 0.956 1725 0.966 1726 1.115 1727 1.287 1728 0.895 1729 0.802 1730 1.071 1731 1.074 1732 1.026 1733 1.329 1734 1.141 1735 0.99 1736 0.868 1737 0.874 1738 1.05 1739 0.663 1740 0.602 1741 0.74 1742 0.99 1743 0.948 1744 0.88 1745 1.094 1746 1.111 1747 0.937 1748 0.799 1749 0.918 1750 1.301 1751 1.136 1752 0.963 1753 0.837 1754 0.728 1755 1.0 1756 0.597 1757 0.518 1758 0.726 1759 0.699 1760 0.656 1761 1.226 1762 1.174 1763 0.991 1764 0.813 1765 1.061 1766 1.041 1767 1.051 1768 0.99 1769 1.002 1770 1.128 1771 1.047 1772 0.994 1773 1.206 1774 1.076 1775 1.171 1776 0.975 1777 0.902 1778 1.077 1779 1.146 1780 1.087 1781 1.03 1782 1.081 1783 0.726 1784 0.711 1785 0.908 1786 0.976 1787 0.706 1788 1.038 1789 1.175 1790 0.978 1791 0.983 1792 1.134 1793 1.056 1794 0.946 1795 1.121 1796 1.09 1797 0.514 1798 0.567 1799 0.982 1800 0.702 1801 0.909 1802 1.128 1803 1.03 1804 0.845 1805 0.992 1806 1.091 1807 0.801 1808 0.901 1809 1.104 1810 1.047 1811 1.031 1812 1.354 1813 1.104 1814 1.346 1815 1.113 1816 1.09 1817 0.983 1818 1.163 1819 1.252 1820 1.044 1821 1.001 1822 1.159 1823 0.674 1824 0.974 1825 1.004 1826 0.914 1827 1.075 1828 1.052 1829 1.172 1830 0.947 1831 0.943 1832 1.277 1833 1.351 1834 1.003 1835 0.893 1836 1.078 1837 1.033 1838 1.138 1839 0.476 1840 0.608 1841 0.898 1842 0.871 1843 0.911 1844 0.826 1845 1.131 1846 0.902 1847 0.814 1848 0.811 1849 0.661 1850 0.842 1851 0.849 1852 0.765 1853 1.014 1854 0.966 1855 1.11 1856 1.031 1857 1.147 1858 1.215 1859 0.989 1860 1.166 1861 1.385 1862 1.189 1863 1.129 1864 1.209 1865 1.061 1866 1.334 1867 1.098 1868 0.903 1869 0.814 1870 0.991 1871 1.005 1872 0.877 1873 1.115 1874 0.986 1875 1.07 1876 1.275 1877 1.684 1878 1.415 1879 1.318 1880 1.162 1881 1.496 1882 1.21 1883 0.931 1884 1.036 1885 1.312 1886 0.84 1887 0.969 1888 1.096 1889 0.745 1890 0.61 1891 0.835 1892 0.821 1893 0.69 1894 1.104 1895 1.051 1896 0.796 1897 0.954 1898 0.815 1899 0.615 1900 1.11 1901 1.152 1902 0.899 1903 0.923 1904 1.245 1905 0.652 1906 0.748 1907 1.105 1908 1.122 1909 0.903 1910 0.978 1911 0.838 1912 0.934 1913 1.519 1914 1.32 1915 1.014 1916 1.235 1917 1.051 1918 0.83 1919 1.085 1920 0.932 1921 1.258 1922 1.008 1923 0.831 1924 0.899 1925 0.838 1926 0.807 1927 0.991 1928 1.225 1929 0.744 1930 0.652 1931 0.75 1932 0.758 1933 0.61 1934 0.899 1935 0.705 1936 0.587 1937 0.824 1938 0.967 1939 0.898 1940 0.731 1941 0.893 1942 1.618 1943 1.217 1944 0.693 1945 0.896 1946 1.231 1947 1.268 1948 0.765 1949 0.821 1950 1.01 1951 1.073 1952 1.113 1953 0.864 1954 1.016 1955 1.14 1956 1.23 1957 1.299 1958 0.907 1959 1.171 1960 1.515 1961 1.155 1962 1.136 1963 1.052 1964 0.767 1965 0.954 1966 0.923 1967 0.633 1968 0.643 1969 1.023 1970 0.76 1971 0.756 1972 0.872 1973 0.643 1974 0.656 1975 0.934 1976 1.306 1977 0.502 1978 1.087 1979 1.119 1980 1.178 1981 1.292 1982 1.129 1983 1.396 1984 1.202 1985 0.846 1986 1.191 1987 0.965 1988 0.674 1989 0.539 1990 1.19 1991 0.901