# northamerica_usa_nm552 - Osha 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/5089 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: northamerica_usa_nm552 - Osha 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: Osha Mountain # Location: # Country: United States # Northernmost_Latitude: 36.3 # Southernmost_Latitude: 36.3 # Easternmost_Longitude: -105.42 # Westernmost_Longitude: -105.42 # Elevation: 2896 m #-------------------- # Data_Collection # Collection_Name: northamerica_usa_nm552B # Earliest_Year: 1706 # Most_Recent_Year: 1981 # 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":"4.2223964021","T2":"15.3606970246","M1":"0.0229450871438","M2":"0.51386834575"}} #-------------------- # 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 1706 1.04 1707 0.788 1708 0.996 1709 0.935 1710 1.036 1711 0.961 1712 0.886 1713 0.951 1714 0.9 1715 0.869 1716 0.91 1717 1.209 1718 1.33 1719 0.957 1720 1.294 1721 1.07 1722 0.968 1723 1.032 1724 1.214 1725 1.097 1726 1.141 1727 0.851 1728 0.851 1729 0.483 1730 0.816 1731 0.914 1732 0.938 1733 0.745 1734 1.024 1735 0.782 1736 0.921 1737 0.559 1738 0.835 1739 0.853 1740 0.919 1741 0.821 1742 1.072 1743 1.044 1744 0.925 1745 1.035 1746 1.236 1747 1.084 1748 0.557 1749 0.979 1750 0.777 1751 0.96 1752 0.259 1753 0.501 1754 0.778 1755 0.996 1756 1.036 1757 1.285 1758 1.344 1759 1.333 1760 1.201 1761 1.371 1762 1.268 1763 1.184 1764 1.212 1765 1.172 1766 1.394 1767 1.349 1768 1.237 1769 1.064 1770 1.025 1771 1.115 1772 1.042 1773 0.656 1774 0.915 1775 0.873 1776 0.805 1777 0.815 1778 0.893 1779 1.015 1780 0.771 1781 0.664 1782 1.055 1783 1.069 1784 1.175 1785 1.151 1786 1.132 1787 1.149 1788 1.236 1789 0.954 1790 0.863 1791 1.075 1792 1.112 1793 1.172 1794 1.004 1795 0.8 1796 0.944 1797 0.8 1798 0.648 1799 0.862 1800 0.873 1801 0.231 1802 0.589 1803 0.734 1804 1.065 1805 1.102 1806 1.381 1807 1.529 1808 1.548 1809 1.205 1810 1.356 1811 1.221 1812 1.277 1813 1.394 1814 1.373 1815 1.108 1816 1.05 1817 0.883 1818 0.68 1819 0.815 1820 1.023 1821 1.04 1822 0.964 1823 1.083 1824 0.933 1825 1.221 1826 1.204 1827 1.25 1828 1.283 1829 1.255 1830 1.113 1831 1.063 1832 1.121 1833 1.164 1834 1.256 1835 1.104 1836 0.771 1837 0.909 1838 0.892 1839 0.72 1840 0.886 1841 0.874 1842 0.483 1843 0.668 1844 0.676 1845 0.534 1846 0.403 1847 0.406 1848 0.387 1849 0.464 1850 0.485 1851 0.145 1852 0.51 1853 0.957 1854 1.266 1855 1.249 1856 1.098 1857 1.328 1858 1.182 1859 0.845 1860 1.066 1861 0.967 1862 1.113 1863 1.1 1864 1.029 1865 0.799 1866 0.955 1867 0.986 1868 0.885 1869 0.921 1870 0.899 1871 0.708 1872 0.936 1873 0.82 1874 0.799 1875 0.85 1876 1.051 1877 0.94 1878 0.637 1879 0.717 1880 0.284 1881 0.437 1882 0.64 1883 0.709 1884 0.79 1885 0.943 1886 1.0 1887 1.174 1888 1.127 1889 1.105 1890 0.966 1891 1.109 1892 0.978 1893 0.829 1894 0.721 1895 1.103 1896 0.858 1897 1.011 1898 1.356 1899 1.106 1900 1.265 1901 1.276 1902 1.239 1903 1.305 1904 1.006 1905 1.061 1906 1.251 1907 1.621 1908 1.349 1909 1.247 1910 1.037 1911 1.233 1912 1.235 1913 1.22 1914 1.371 1915 1.142 1916 1.222 1917 0.768 1918 1.078 1919 1.124 1920 1.14 1921 1.246 1922 0.954 1923 1.151 1924 1.108 1925 0.752 1926 1.157 1927 0.995 1928 1.068 1929 1.129 1930 0.898 1931 0.884 1932 0.835 1933 0.93 1934 0.606 1935 0.96 1936 0.753 1937 0.932 1938 0.931 1939 0.819 1940 0.961 1941 1.108 1942 1.186 1943 1.286 1944 1.15 1945 1.145 1946 0.627 1947 0.836 1948 0.973 1949 1.08 1950 0.859 1951 0.772 1952 0.894 1953 0.815 1954 0.583 1955 0.835 1956 0.253 1957 0.523 1958 0.726 1959 0.724 1960 0.945 1961 0.91 1962 1.081 1963 0.817 1964 0.685 1965 1.127 1966 1.449 1967 1.503 1968 1.388 1969 1.654 1970 1.095 1971 0.385 1972 0.629 1973 0.824 1974 0.885 1975 1.029 1976 0.783 1977 0.779 1978 0.89 1979 0.879 1980 0.909 1981 0.631