# northamerica_usa_mt109 - Grass Mountain #2 - 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/3314 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: northamerica_usa_mt109 - Grass Mountain #2 - 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: Grass Mountain #2 # Location: # Country: United States # Northernmost_Latitude: 45.17 # Southernmost_Latitude: 45.17 # Easternmost_Longitude: -109.52 # Westernmost_Longitude: -109.52 # Elevation: 3208 m #-------------------- # Data_Collection # Collection_Name: northamerica_usa_mt109B # Earliest_Year: 1723 # Most_Recent_Year: 1999 # 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":"6.25224137616","T2":"19.6661300749","M1":"0.022153654093","M2":"0.295109489267"}} #-------------------- # Species # Species_Name: Engelmann spruce # Species_Code: PCEN #-------------------- # 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 1723 0.878 1724 1.097 1725 0.925 1726 1.011 1727 1.143 1728 1.266 1729 1.277 1730 1.41 1731 1.126 1732 1.017 1733 1.068 1734 1.062 1735 0.944 1736 0.953 1737 0.806 1738 0.901 1739 1.119 1740 0.844 1741 0.821 1742 1.118 1743 1.021 1744 0.896 1745 0.839 1746 0.649 1747 0.818 1748 0.934 1749 0.832 1750 0.971 1751 1.283 1752 0.889 1753 0.849 1754 0.803 1755 1.012 1756 1.281 1757 1.195 1758 0.812 1759 1.119 1760 0.945 1761 0.801 1762 1.185 1763 1.133 1764 1.067 1765 0.95 1766 0.8 1767 0.788 1768 0.982 1769 0.837 1770 0.776 1771 0.963 1772 1.099 1773 1.245 1774 1.207 1775 1.022 1776 1.1 1777 1.061 1778 1.072 1779 0.759 1780 0.946 1781 1.078 1782 0.848 1783 1.109 1784 1.188 1785 0.953 1786 1.12 1787 0.804 1788 0.945 1789 0.751 1790 0.813 1791 0.668 1792 0.728 1793 0.739 1794 0.995 1795 1.039 1796 1.016 1797 0.948 1798 1.177 1799 0.958 1800 0.932 1801 0.972 1802 1.107 1803 0.842 1804 1.068 1805 0.941 1806 0.831 1807 0.968 1808 1.162 1809 0.774 1810 0.95 1811 1.302 1812 1.332 1813 1.127 1814 0.88 1815 1.022 1816 0.948 1817 1.02 1818 1.123 1819 1.29 1820 1.016 1821 1.045 1822 0.921 1823 0.89 1824 0.916 1825 1.0 1826 1.021 1827 0.938 1828 1.095 1829 1.316 1830 1.073 1831 1.034 1832 0.763 1833 1.138 1834 0.887 1835 0.945 1836 0.844 1837 1.069 1838 0.716 1839 0.887 1840 0.956 1841 1.142 1842 0.999 1843 1.17 1844 1.078 1845 0.943 1846 1.233 1847 1.086 1848 1.143 1849 1.086 1850 1.279 1851 1.049 1852 0.908 1853 0.826 1854 1.062 1855 0.913 1856 0.973 1857 1.005 1858 0.926 1859 1.178 1860 0.952 1861 1.084 1862 0.899 1863 1.107 1864 0.945 1865 0.871 1866 0.962 1867 0.973 1868 0.912 1869 0.862 1870 0.957 1871 1.097 1872 0.58 1873 1.263 1874 1.194 1875 0.88 1876 0.909 1877 0.865 1878 1.034 1879 0.411 1880 0.423 1881 0.577 1882 0.473 1883 0.326 1884 0.57 1885 0.748 1886 0.898 1887 0.758 1888 1.042 1889 0.949 1890 0.945 1891 0.805 1892 0.965 1893 1.086 1894 0.845 1895 0.711 1896 1.072 1897 0.914 1898 1.017 1899 0.623 1900 1.043 1901 0.922 1902 0.676 1903 0.883 1904 0.836 1905 0.817 1906 0.782 1907 0.809 1908 1.082 1909 1.097 1910 1.042 1911 0.907 1912 1.086 1913 1.103 1914 1.335 1915 0.768 1916 1.2 1917 1.025 1918 1.092 1919 1.093 1920 1.083 1921 1.209 1922 1.045 1923 0.973 1924 0.695 1925 1.282 1926 1.009 1927 1.137 1928 1.054 1929 1.45 1930 1.272 1931 1.348 1932 1.433 1933 1.314 1934 0.758 1935 0.938 1936 0.899 1937 0.78 1938 0.804 1939 1.009 1940 1.21 1941 1.058 1942 0.972 1943 1.094 1944 1.064 1945 1.219 1946 1.171 1947 1.089 1948 1.056 1949 1.118 1950 0.945 1951 1.158 1952 1.018 1953 1.345 1954 1.139 1955 1.019 1956 0.832 1957 1.019 1958 0.664 1959 1.068 1960 0.793 1961 0.83 1962 0.73 1963 1.099 1964 1.27 1965 1.088 1966 1.243 1967 1.124 1968 1.056 1969 0.804 1970 1.177 1971 0.92 1972 0.842 1973 1.201 1974 1.089 1975 0.973 1976 1.181 1977 0.992 1978 0.963 1979 1.105 1980 1.009 1981 0.892 1982 0.839 1983 0.985 1984 1.164 1985 0.91 1986 0.921 1987 0.885 1988 1.505 1989 1.21 1990 1.067 1991 1.026 1992 0.614 1993 0.515 1994 1.039 1995 0.99 1996 0.913 1997 0.845 1998 0.924 1999 0.943